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Estimation of evapotranspiration using continuous soil moisture measurement

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Title:
Estimation of evapotranspiration using continuous soil moisture measurement
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English
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Rahgozar, Mandana Seyed
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University of South Florida
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Tampa, Fla
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Subjects / Keywords:
West Central Florida
Vadose zone hydrology
Shallow water table
Potential ET
Groundwater ET
Dissertations, Academic -- Civil Engineering -- Doctoral -- USF   ( lcsh )
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bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )

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Abstract:
ABSTRACT: A new methodology is proposed for estimation of evapotranspiration (ET) flux at small spatial and temporal scales. The method involves simultaneous measurement of soil moisture (SM) profiles and water table heads along transects flow paths. The method has been applied in a shallow water table field site in West-Central Florida for data collected from January 2002 through June 2004. Capacitance shift type moisture sensors were used for this research, placed at variable depth intervals starting at approximately 4 in. (10 cm) below land surface and extending well below the seasonal low water table depth of 59 in. (1.5 m). Vegetation included grassland and wetland forested flatwoods. The approach includes the ability to resolve multiple ET components including shallow and deep vadose zone, surface interception capture and depression storage ET. Other components of the water budget including infiltration, total and saturation rainfall excess runoff, net runoff, changes in storage and lateral groundwater flows are also derived from the approach. One shortcoming of the method is the reliance on open pan or other potential ET estimation techniques when the water table is at or near land surface. Results are compared with values derived for the two vegetative covers from micrometeorological and Bowen ratio methods. Advantages of the SM method include resolving component ET.
Thesis:
Dissertation (Ph.D.)--University of South Florida, 2006.
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Includes bibliographical references.
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by Mandana Seyed Rahgozar.
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Document formatted into pages; contains 143 pages.
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Includes vita.

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oclc - 184720042
usfldc doi - E14-SFE0001812
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Estimation of Evapotranspiration Using Continuous Soil Moisture Measurement by Mandana Seyed Rahgozar A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Civil and Environmental Engineering College of Engineering University of South Florida Major Professor: Mark A. Ross, Ph.D. Jeff Geurink, Ph.D. Edward Mierzejewski, Ph.D. Mahmood Nachabe, Ph.D. Mark Stewart, Ph.D. David Sumner, Ph.D. Date of Approval: November 6, 2006 Keywords: West Central Florida, Vadose Zone Hydrology, Shallow Water Table, Potential ET, Groundwater ET Copyright 2006, Mandana Seyed Rahgozar

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DEDICATION This research is dedicated to my pa rents, Mahineh Tavakoli & Jallal Seyed Rahgozar, for the sacrifices they made and my beloved brother Albert whose exceptional strength, unwavering kindness and unique happy spirit were an inspiration to all who knew him. I love and miss you imme nsely. This is also dedicated to John and Lee Farrinacci, David and Virginia Close, Magnolia Burnett who became my extended family and Minoo and Havva my childhood friends. How I miss each one of you. A special thanks to my special friend Ron Norwood. This research is also dedicated to my major professor Dr. Mark A. Ross whom unw avering support and patience has been with me for many years and in his own right became a major contributor in my life. I also wish to include late Dr. Franques whom served on my master’s defense. Each one of you, in your own unique and gentle ways became an integral pa rt of my life to a point that I simply cannot imagine my life without you. I cherished your values, integrity, kindness, support and understanding. How I wished everyone could have been as lucky as I have been. Napoleon B onaparte once said “If throughout your life you have one true friend then you have had one more than your share.” I wish I knew what I have done to have deserved your friendships. I promise that I will cherish and uphold the legacy that you so instinctively a nd effortlessly demonstrated and demanded and simply could not help but to bestow upon those whom were in the enviable position of having your association. How honored I am that God permitted our path to not just

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cross but become a journey. Thank you again, all of you for everything. It simply would have been impossible without you.

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ACKNOWLEGMENTS The author hereby wishes to extend her sincere thanks to Dr. Mark Ross, P.E., Director of Center for M odeling Hydrologic and Aquatic System, for his unwavering support, extensive contribution and valuable input throughout this research. Also, Jeff Vomacka, P.E. for his field contribution and data collectio n efforts and Dr. Ahmed Said and Nirjhar Shah for contributi ng to Journal publications. A ppreciation is also extended to Tampa Bay Water (TBW), University of South Florida (USF) and Southwest Florida Water Management District (SWFWMD) for financial assistance that made this research possible.

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i TABLE OF CONTENTS LIST OF TABLES..............................................................................................................ii LIST OF FIGURES...........................................................................................................iv ABSTRACT.....................................................................................................................vi ii CHAPTER ONE BACKGROUND....................................................................................1 Introduction.............................................................................................................1 Available Models for Measuremen ts of ET and Their Potential Strengths and Weaknesses.................................................................................3 Available Techniques for Soil Moisture Measurements Used for ET Estimation and Their Potential Strengths and Weaknesses...............................6 Crop Coefficients.............................................................................................17 Objectives........................................................................................................20 CHAPTER TWO METHODOLOGY, HYPO THESIS & DEFINITIONS......................21 Methodology.........................................................................................................21 Hypothesis.............................................................................................................25 Definitions.............................................................................................................31 CHAPTER THREE FIELD DATA COLLECTION........................................................36 CHAPTER FOUR RESULTS..........................................................................................44 CHAPTER FIVE DISCUSSIONS OF RESULTS, SUMMARY AND CONCLUSIONS.................................................................................62 Results...................................................................................................................62 Summary...............................................................................................................71 Conclusions...........................................................................................................74 REFERENCES.................................................................................................................77

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i APPENDICES..................................................................................................................85 Appendix A: Soil Description at the Field Study Site..........................................86 Appendix B: Influence of Temporal Variability in Soil Moisture Averaging on ET Results................................................................88 Appendix C: Techniques for Estimation of Potential ET, Site Potential ET, Ground Potential ET and Adjusted SM...........................................90 Appendix D: Daily Variability in SM and DS ET with Landuse.........................93 Appendix E: Monthly Distribution of SM, DS and Ic ET and Quarterly Averaged DTWT.............................................................................95 Appendix F: Quarterly Water Budget Components..............................................99 3rd Quarter Water Budget Components...........................................................99 4th Quarter Water Budget Components.........................................................102 5th Quarter Water Budget Components.........................................................105 6th Quarter Water Budget Components.........................................................109 7th Quarter Water Budget Components.........................................................112 8th Quarter Water Budget Components.........................................................116 9th Quarter Water Budget Components.........................................................120 10th Quarter Water Budget Components.......................................................123 11th Quarter Water Budget Components.......................................................126 12th Quarter Water Budget Components.......................................................129 Appendix G: Comparison of Observed Hourly SM+DS ET with Site PET.......132 Appendix H: Sample of Observed Quarterly SM ET with Adjusted SM ET and GPET for Grass and Forested Land in 2003..........................141 ABOUT THE AUTHOR.......................................................................................End Page

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ii LIST OF TABLES Table 1. Annual water budget results for 2002………………………………………….63 Table 2. Annual water budget results for 2003………………………………………….64 Table 3. Semi-annual water budget results for 2004…………………………………….65 Table 4. ET results for grass and forest using various ET mo dels………………………72 Table 5. Quarterly values computed for PET, site PET and GPET..................................92 Table 6. Annual values computed for PET, site PET and GPET.....................................92 Table 7. Quarterly water budget results for winter 2002 for PS43-PS39.......................100 Table 8. Quarterly water budget results fo r winter 2002 for USF3 and USF1...............101 Table 9. Quarterly water budget results for spring of 2002 for PS43-PS39...................103 Table 10. Quarterly water budget results for spring 2002 for USF3 and USF1.............104 Table 11. Quarterly water budget resu lts for summer 2002 for PS43-PS39..................107 Table 12. Quarterly water budget results for summer 2002 for USF3 and USF1..........108 Table 13. Quarterly water budget resu lts for fall 2002 for PS43-PS39..........................110 Table 14. Quarterly water budget results for fall 2002 for USF3-USF1........................111 Table 15. Quarterly water budget results for winter 2003 for PS43-PS39.....................114 Table 16. Quarterly water budget results fo r winter 2003 for USF3 and USF1.............115 Table 17. Quarterly water budget resu lts for spring 2003 for PS43-PS39.....................118 Table 18. Quarterly water budget results for spring 2003 for USF3 and USF1.............119 Table 19. Quarterly water budget resu lts for summer 2003 for PS43-PS39..................121

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iii Table 20. Annual water budget results for summer 2003 for USF3 and USF1..............122 Table 21. Quarterly water budget resu lts for fall 2003 for PS43-PS39..........................124 Table 22. Annual water budget results fo r fall 2003 for USF3 and USF1.....................125 Table 23. Quarterly water budget results for winter 2004 for PS43-PS39.....................127 Table 24. Annual water budget results forn winter 2004 for USF3 and USF1..............128 Table 25. Quarterly water budget resu lts for spring 2004 for PS43-PS39.....................130 Table 26. Quarterly water budget results for spring 2004 for USF3 and USF1.............131

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iv LIST OF FIGURES Figure 1. Variable Sy model used dur ing brief periods of soil moisture measurement gaps............................................................................................23 Figure 2. Aerial view of the Alafia river watershed showing the boundary and sub-basins delineation for the research site......................................................38 Figure 3. Graphical display of the 1-D flow model for the transect wells, PS43PS39.................................................................................................................39 Figure 4. Graphical display of the 1-D fl ow model for the transect wells, USF3USF1................................................................................................................40 Figure 5. Direct push dri lling results near PS42..............................................................41 Figure 6. Enviro-smart Soil Moisture probe..................................................................43 Figure 7. Observed changes in total soil moisture corresponding to several precipitation events during spri ng of 2002 near station PS41.........................45 Figure 8. Observed 20-minute changes in total soil moisture during a high ET period for grassland cover (PS43)....................................................................45 Figure 9. Change in total soil moisture (PS43) in response to a precipitation event.................................................................................................................46 Figure 10. Decline in total soil moistu re and water table supporting ET demand for grassland (PS43)......................................................................................47 Figure 11. Steeper decline in water table a nd higher losses in total soil moisture for forested wetland neares t the stream (PS-40)............................................48 Figure 12. Increase in total soil moistu re and rise in water table during a 1.93 inches rainfall event for grassland (PS43).....................................................48 Figure 13. Observed losses in total soil moisture corresponding to fluctuations in solar radiation for grassland (PS43)..............................................................49

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v Figure 14. Change in total soil moisture and solar radiation during and after a rainfall event for grassland (PS43)................................................................50 Figure 15. Monthly precipitation record fr om research site vs. monthly avg. from NOAA............................................................................................................51 Figure 16. Monthly averaged ET cont ributions for grassland in 2002...........................52 Figure 17. Monthly averaged ET cont ributions for grassland in 2003...........................53 Figure 18. Monthly averaged ET cont ributions for grassland in 2004...........................53 Figure 19. Monthly averaged ET contribu tions for forested wetland in 2002................54 Figure 20. Monthly averaged ET contribu tions for forested wetland in 2003................54 Figure 21. Monthly averaged ET contribu tions for forested wetland in 2004................55 Figure 22. Monthly averaged plant coeffi cient for grass and forested wetland..............56 Figure 23. Quarterly total interceptions cap ture (Ic) ET for forest and grass from January 2002 through June 2004...................................................................57 Figure 24. Quarterly total soil moisture ET for forest and grass from January 2002 through June 2004.................................................................................57 Figure 25. Quarterly total ET for fore st and grass from January 2002 through June 2004.......................................................................................................58 Figure 26. Quarterly infiltration for fo rest and grass from January 2002 through June 2004.......................................................................................................58 Figure 27. Quarterly total rainfall excess runoff for grass and forest from January 2002 through June 2004.................................................................................59 Figure 28. Quarterly saturation excess runo ff for grass and forest from January 2002 through June 2004.................................................................................59 Figure 29. Quarterly net runoff for gra ss and forest from January 2002 through June 2004.......................................................................................................60 Figure 30. Quarterly averaged depth to water table for grass and forest from January 2002 through June 2004...................................................................60

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vi Figure 31. Estimated ET using various methods for grassland and forested wetland….......................................................................................................73 Figure 32. Estimated potential ET using va rious methods for open water vs. site PET................................................................................................................74 Figure 33. Direct push dril ling results near USF3..........................................................87 Figure 34. Temporal variability in soil moisture for grassland cover (Station PS43)..............................................................................................................89 Figure 35. Temporal variability in soil mo isture for forest cover (Station PS40)..........89 Figure 36. Quarterly values of poten tial ET, site potential ET and ground potential ET (GPET)......................................................................................91 Figure 37. Daily fluctuations in soil mo isture and depression storage ET for grassland (PS-43) in 2003..............................................................................93 Figure 38. Daily soil moisture and de pression storage ET for forested wetland (PS-40) in 2003..............................................................................................94 Figure 39. Monthly total soil moisture depression storag e and interception capture ET distribution for grassl and cover (PS43, USF3 and USF1) in 2002...........................................................................................................96 Figure 40. Monthly total soil moisture depression storag e and interception capture ET distribution for grassl and cover (PS43, USF3 and USF1) in 2003...........................................................................................................96 Figure 41. Monthly total soil moisture depression storag e and interception capture ET distribution for forest covers (PS42, PS41 and PS40) in 2002...............................................................................................................97 Figure 42. Monthly total soil moisture depression storag e and interception capture ET distribution for forest covers (PS42, PS41 and PS40) in 2003...............................................................................................................97 Figure 43. Quarterly averaged depth to wa ter table for grassland stations (PS43, USF3 and USF1)............................................................................................98 Figure 44. Quarterly averaged depth to wa ter table for forested wetland stations (PS42, PS41 and PS40)..................................................................................98

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vii Figure 45. Hourly site potenti al ET vs. observed and adjusted total soil moisture and depression storage ET for grassland covers (PS43) in 2002.................133 Figure 46. Monthly site potential ET vs. observed and adjusted total soil moisture and depression storage ET for grassland (PS43) in 2002.............133 Figure 47. Quarterly site potential ET vs. observed and adjusted total soil moisture and depression storage ET for grassland (PS43) in 2002.............134 Figure 48. Hourly site potenti al ET vs. observed and adjusted total soil moisture and depression storage ET for forest wetland (PS40) in 2002....................135 Figure 49. Monthly site potential ET vs. observed and adjusted total soil moisture and depression storage ET for forest (PS40) in 2002...................135 Figure 50. Quarterly site potential ET vs. observed and adjusted total soil moisture and depression storage ET for forest (PS40) in 2002...................136 Figure 51. Hourly site potenti al ET vs. observed and adjusted total soil moisture and depression storage ET for grassland (PS-43) in 2003...........................137 Figure 52. Monthly site potential ET vs. observed and adjusted total soil moisture and depression storage ET for grassland (PS43) in 2003.............138 Figure 53. Quarterly site potential ET vs. observed and adjusted total soil moisture and depression storage ET for grassland (PS43) in 2003.............138 Figure 54. Hourly site potenti al ET vs. observed and adjusted total soil moisture and depression storage ET for forested wetland (PS-40) in 2003...............139 Figure 55. Monthly site potential ET vs. observed and adjusted total soil moisture and depression storage ET for forested wetland (PS40) in 2003.............................................................................................................140 Figure 56. Quarterly site potential ET vs. observed and adjusted total soil moisture and depression storage ET for forested wetland (PS40) in 2003.............................................................................................................140 Figure 57. Quarterly ground potential ET (G PET) with observed and adjusted soil moisture and depression storag e ET for grassland (PS43) summer 2003.............................................................................................................142 Figure 58. Quarterly ground potential ET (GP ET) vs. observed and adjusted total soil moisture and depression stor age ET for forested (PS42) in summer 2003..........................................................................................….143

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viii ESTIMATION OF EVAPOTRANSPIRATION USING CONTINOUS SOIL MOISTURE MEASUREMENT Mandana Seyed Rahgozar ABSTRACT A new methodology is proposed for estimati on of evapotranspira tion (ET) flux at small spatial and temporal scales. The met hod involves simultaneous measurement of soil moisture (SM) profiles and water table head s along transects flow paths. The method has been applied in a shallow water table field site in West-Central Florida for data collected from January 2002 through June 2004. Capacitance shift type moisture sensors were used for this research, placed at va riable depth intervals starting at approximately 4 in. (10 cm) below land surface and extending well below the seasonal low water table depth of 59 in. (1.5 m). Vegetation included grassland and wetland forested flatwoods. The approach includes the ability to resolve multiple ET components including shallow and deep vadose zone, surface interception capture and depression storage ET. Other components of the water budget including infiltration, total and saturation rainfall excess runoff, net runoff, changes in storage and lateral groun dwater flows are also derived from the approach. One shortcoming of the method is the reliance on open pa n or other potential ET estimation techniques when the water table is at or near land surface. Results are compared with values derived for the two ve getative covers from micrometeorological and Bowen ratio methods. Advantages of the SM method include resolving component ET.

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1 CHAPTER ONE BACKGROUND Introduction Measurement of the temporal and spatial distribution of evapotranspiration (ET) is a challenge facing the engineering and scie ntific community. ET estimation is required to calibrate hydrologic models and to asse ss hydrologic budgets. Basinwide studies have demonstrated that ET is second only to pr ecipitation in magnitude in terrestrial hydrologic budgets of Florida (J ones et al. 1984). ET in shallow water ta ble environments is governed by vegetation cover, soil hydrolog ic processes and depth to water table (DTWT). Atmospheric potential ET (PET) is a physical and modeling concept controlled by meteorological stresses including solar radiation, relative humidity, wind speed and temperature. The actual ET (A ET) from vegetative cover is controlled by PET, available moisture and plant physiology. Hydrologic models have varying techniques to represent the role of soil moisture in limiting direct soil evaporation and plant transpiration, commonly treated together as evapotranspiration (ET). Evaporation from the soil surface decreases as the shallow soil dries, and this interaction between soil water storage and evaporative loss can be an important aspect of unsaturated zone hydrol ogy (Hillel, 1982). The in teraction is more complex when vegetated surfaces are invol ved because plant-mediated water fluxes depend significantly on physiological and mor phological responses of plants to drought, root zone depths, moisture distri bution among many other factors.

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2 Despite the importance of ET in hydr ologic studies, seasonal and diurnal distributions of particular plant communities, including spatial field-scale and short timescale variability, remain relatively poorly qua ntified, and thus a topic deserving further investigation. In areas with pronounced wet and dry seasons and sandy soil, such as westcentral Florida, a highly variable and seasona lly shallow water table, combined with a wet vadose zone that transitions from very dry to very wet, controls the extent to which plants attain potential ET during the year Knowledge of seasona l or monthly plant uptake is needed to refine and parameteri ze hydrologic models us ed for water supply investigation. A more reliable technique for measuring soil water-balance components, including ET and water table recharge, could le ad to more reliable targets for simulation of the water table and thus r unoff and groundwater processes. Soil moisture (SM) is the critical variab le that dynamically links plants to the overall water balance, thereby influencing f eedbacks to the atmosphere. Below the land surface, plants utilize soil moisture by osmo tic uptake. This interaction between soil water storage and evaporative loss is an important component of unsaturated zone hydrology (Hillel, 1982). Knowledge and measurem ent capabilities of SM within the root zone would be quite useful for estimation of hydrologic fluxes. During the last decade an increasing nu mber of studies have been focused on dynamic measurement of SM, c onsidering to various degrees explicitly the spatiotemporal variations of this pr operty (Crave an d Gascuel-Odoux, 1977 ; Grayson and Western, 1998; Famiglietti et al., 1999). Many studies limit investig ation of SM to the near surface (0-5 cm), and have been c onducted at different sp atial scales (1 m2 to a few km2), and temporal scales from days to years (Wilson, et al., 2003; Ladekart, 1998).

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3 Many measurement techniques exist: gravimetri c analysis of physical samples, dynamic in situ measured with Time Domain Refl ectometry (TDR), Frequency Time Domain (FDR), Neutron Probes; and remote sensing (e .g., satellite approach) over a wide range of hydrologic and climatic conditi ons. Results from theses st udies, have provided more insight into the spatio-temporal dynamics of SM in vegetative environments. Spatiotemporal variability is also influenced by t opographic features such as soil surface slope angle (Hills and Reynolds, 1969 ; Moore et al., 1988 ; Nyberg, 1996) and slope orientation (Reid, 1973; Western et al., 1999a ), soil (hydrodynamics) prope rties (Henninger et al,. 1976; Crave and Gascuel-Odoux, 1997), vegeta tion distribution (Bouten et al,. 1992; Mohanty et al., 2000a), landuse and in particular the agricultur al practices (Famiglietti et al., 1999), and finally, by climatic variability ( Hawley et al., 1983 ). Available Models for Measurements of ET a nd Their Potential Strengths and Weaknesses The simple fact is no prolonged direct and undisruptive measurement of ET at the field scale can be made. However indirect me thods exist. All methods can be grouped in to the following distinct categories: 1) At mospheric flux estimation 2) Energy balance approaches 3) Soil moisture monitoring (including weighing lysimeter studies) 4) Pan evaporation measurement 5) Water budget es timation and 6) Combined methods. Well known methods include Eddy correlation meth od (ECM); Energy Balance Bowen Ratio (EBBR); Energy-Balance Wind and Scalar Profile (EBWSP); Eddy Correlation EnergyBalance Residual (ECEBR); Penman (1948), Penman-Monteith (1965) and Modified Priestly-Taylor one-dimensiona l model (1972). A brief revi ew of previously employed

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4 models and their potential weaknesses and strengths, pointed out by researchers employing the models, are presented here for comparison purposes: Estimating ET by the EBBR, EBWSP and ECM are subject to many potential sources of error. Evaluating those sour ces and quantifying ET error are extremely difficult. First, applicability of the three meteor ological techniques for a given site depends on the assumption of a steady-state atmospheric-bounda ry layer with negligible horizontal gradients of vertical fluxes. In some studies no attempt may be made to examine the assumption of a steady-state bound ary layer; instead, the boundary layer is assumed to be at steady state for the relativel y short averaging period s that are used for micrometeorological measurements (20 minutes). Also, attempts may not be made to test for horizontal gradients. The assumption of ne gligible horizontal gr adients may be based on instrument height and fetch guidelines. Second, if atmospheric boundary–layer conditions are met, the problem remains that determining the appropriate time-averaged and space averaged values for the time-series variables needed to compute ET. Measured values of the time-series variables, such as net radiation, subsur face heat flux, vapor pressure difference, and covariance of verti cal wind speed and vapor density, are subject both to random and systematic error. Rando m error can be random measurement error or the result of inadequate spatial or temporal sampling of the time-series variables. Systematic error, or bias, can be a serious source of error for many field measurements (Bidlake, et al., 1996). Errors in estimating ET by the EBBR and ECM methods can occur if the nature of turbulent transport in th e surface sub-layer where the measurements are made departs from the ideal conditions on which the methods are based. For example, assumptions on

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5 which the two methods are based are not valid if there are substantia l horizontal gradients in vertical fluxes of momentum, heat, or water vapor (Bidla ke et al., 1996). Errors in estimating ET also can arise due to errors in measuring or estimating the variables that are necessary fo r the application of the EBBR or ECM. ECM is used to measure two components of the energy budget of the plant canopy; la tent and sensible heat fluxes. A recurring pr oblem with the ECM is a common discrepancy of the measured latent heat and sensible heat fluxes with energy budget equation. Both fluxes are transported by turbulent eddies in the ai r generated by a combina tion of frictional and convective forces. Researchers have show n ECM performs best in windy conditions (relatively high friction velocity). Measurement of the soil heat flux and storage terms of the available energy can be problematic, gi ven the difficulty in making representative measurements of these terms. Assumptions can include the accuracy of measured available energy and that any error in the ener gy-budget closure is associated with errors in measurements of turbulent fluxes (Sumner 2001). Measured time-series variables, such as net radiation, subsurface heat flux, vaporpressure difference and covariance of vertical wind speed and vapor de nsity are subject to random and systematic error. Random erro r can be random measurement error or the result of inadequate spatial or temporal samp ling of the time-series variables (Bidlake and Boetcher 1996). Daily estimates of ET us ing EBBR, EBWSP and ECM have shown to have strong seasonal variability for each vegetation type. Maximum ET using these methods occurred during May-July for each vegetation type and minimum ET occurred during November-March, strongly driven by av ailable energy and moisture. (Bidlake et al. 1996).

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6 The Penman and Priestley-Taylor methods require less mete orological data and are less computationally de manding than the Penman-Monteith method. The Penman model ET has the potential to be a poor predictor of meas ured ET with little relation evident between Penman simulated ET and measured ET at a site (Sumner 1996). The discrepancy between model and measured values can be most extreme when canopy coverage and soil moisture ar e relatively low. However, daily ET rates, simulated by nontraditional Penman-Monteith and Priestley-Taylor models calibrated to a Bowen Ratio variant of the ECM demonstrated st rong seasonal variability (Sumner 1996) Upon calibration, ET models provided estimates of ET that were about 10% lower and higher depending upon the selected va riant of the eddy correlation method (Sumner 1996). Within the framework of the Priestley-Tayl or model, variations in daily ET were primarily the result of variati ons in surface cover, net radi ation, photosynthetically active radiation (PAR), air temperature and water table depth (Sumner 2001). Available Techniques for Soil Moisture Meas urements Used for ET Estimation and Their Potential Strengths and Weaknesses Direct and indirect methods are available for measuring SM in situ. As yet, there is no universally recognized standard method of measurement and no uniform way to compute and present the result of SM measurements. Investigators have described various problems with previous ly employed technique s. All methods can be grouped in to the following distinct categories for: So il Profile Water Content Measurement Method using 1) Neutron Scattering (NS) 2) Gamma-ray Absorption 3) Double-probe Gammaray 4) Tensiometer 5) Remotely Sensed SM Monitoring 6) Lysimeter, 7) Time Domain

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7 Reflectometers (TDR) and 8) Frequency Doma in Reflectometers (FDR). The advantages and disadvantages of some of the wi dely used techniques are presented. Neutron Scattering (NS) First develope d in the 1950s, the NS method has gained widespread acceptance as an efficient and re liable technique for monitoring SM in the field. The principal advantages of the NS ar e technical basis, non-destructive, robust rapid and simple installation. This method is practically independent of temperature and pressure. Its main disadvantages, however, are the high initial cost of instrument, low degree of spatial resolution, difficulty in measuring SM near the surface zone and the health hazard associated with exposure to neutron and gamm a radiation. The NS method, no matter how well calibrated, does not give accurate measurement near land surface where most storage change occurs (Evett et al. 1993). Gamma-ray Absorption The gamma-ray absorption method is used mostly in the laboratory, where the dimensions and density of the soil samp le, as well as the ambient temperature, can be precisely controlled. A high degree of spatial resolution (~2 mm) can be accomplished by collimation of the radi ation. Because the abso rption of radiation depends on the intervening mass between the so urce and the detector, the readings can be only related uniquely to SM if bulk density is constant or if its change is monitored simultaneously (Hillel, 1998). Double-probe Gamma-ray -The double-probe gamma-ray method has also been adapted to field use and is manufactured commercially. In principal, this technique offers several advantages over the Neutron moisture meter in that it allows much better depth resolution

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8 when measuring the distribution of SM th roughout the profile. A depth resolution of about 0.4 in. (1 cm) reportedly can be achieved. This resolution is sufficient to detect discontinuities between prof ile layers as well as movement of wetting fronts and conditions prevailing near the soil surf ace (Hillel, 1998). However, in some soils, difficulties are encountered in the accurate installation and alignment of two access tubes that must be strictly parallel, and the met hod requires the accurate determination of soil bulk density, providing problems as bulk de nsity can vary in depth and time. Problems of temperature sensitivity of th e electronic device, which plagued early designs, can apparently be so lved, but field calibration wi th the high degree of depth resolution required remains a difficulty (van Bavel et al., 1985). The health hazard associated with use of gamma-ray equipment is similar in principal to that of Neutron moisture meter. The equipment is considered safe only if strict attention is paid to all precautionary rules. Tensiometer The tensiometer is an instrument designed to provide a continuous indication of the soil’s matric suction (s oil-moisture tension) in situ. Suction measurements by tensiometry are generally limit ed to matric suction values below 1 atm (about 1 bar, or 100 kPa), mainly due to th e fact that vacuum gauges or manometer measurements are limited to partial vacuum relative to the external atmospheric pressure. Soil suction and moisture variation are a uni que soil property varyi ng considerably with soil type and vertical layer. Using suction for soil moisture measurements require calibration curves for each soil type and horizon. Furthermore, because the ceramic material used in a tensiometer is generally made of permeable and porous material in the

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9 interest of promoting rapid equilibrium with SM, higher suction may cause the entry of air from the soil into the cup (Hillel, 1998) Such air entry equa lizes the internal tensiometric pressure to the atmospheri c pressure. Consequently, soil suction may continue to increase even though the tensiomete r fails to show it. In practice, the useful limit of most tensiometers is a maxima l tension of about 0.8 atm (80 kPa). Remote Sensing This is the collection of information regarding an object of interest, conducted from some distance without actual contact with that ob ject. It is usually accomplished by detecting and measuring various portions (or bands) of the electromagnetic spectrum, usi ng airborne or satellite-bor n electronic scanning devices. Remote sensing of the earth’s surface includes aerial photography, multi-spectral imagery, infrared imagery, radar, and micr owave scanning. These techniques may be passive or active. Passive techniques measure signals emitted or reflected from the ground. Active sensing techniques consist of generating a signal that is sent to the ground, and of measuring its response (Hillel, 1998). Research conducted in the last three d ecades on remote sensing technology has shown that SM may be assessed by a variet y of methods using specific segments of electromagnetic spectrum, including gamma ra diation, visible and infrared radiation, as well as radar and microwaves (Schmugge 1990; Engman, 1991). Of the various techniques suggested for measuring SM, microwave technology appears to be the most promising at present. It can be used from a space platform (as well as from air-craft and truck mounted devices) and can provide quantitative data of SM in the soil’s top layer (approximately the top 5 cm) under a variety of topographic and

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10 vegetative conditions (Lin et al., 1994). Th e aerial resolution of microwave remote sensing of SM is rather coarse. The passi ve systems currently used only can provide spatial resolutions down to several to tens of kilometers (Engman and Chauhan, 1995). This may be satisfactory for regional-sc ale and global-scale monitoring of the interactions of climate and terrain (includi ng regional effects of climatic changes or fluctuations, and the assessment of expect able crop yields over large areas), but inadequate for landuse based resolution of urbanizing landscape and local water resources studies. Active sensors have the capability to provi de more detailed data, with a resolution of 66 to 98 ft (20-30 m) over a swath width of 100 km, but their sensit ivity to SM is more strongly influenced by surface roughness, topog raphic features, and vegetation than the passive systems. Research in remote sensi ng of SM is fast progressing, and may well result in the development of improve d techniques in the coming years. Lysimeter The most direct method for meas uring the field water balance is by use of Lysimeters (van Bavel and Myers, 1962; Hanks and Shawcroft, 1965; Harrold, 1966; Phene et al., 1989). These are generally large containers of soil, set in the field to represent the prevailing soil, vegetation, and climatic conditions and allowing more accurate measurement of physical processes th an can be carried out in the open field, Some lysimeters are equipped with a wei ghting device and a drainage system, which together permit continuous measurement of both ET and rainfall additions. Lysimeters may not provide a reliable measurement of the field water balance, when the soil or above ground conditions of the Lysimeter differ markedly from those of the field itself.

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11 This method is destructive, presents conc erns for representation analysis, and is not practical for large or well established vegetation such as natural vegetation landscape (Hillel, 1998). Time Domain Reflectometers (TDR) – This is a relatively new me thod for measuring SM wetness, based on the unusually high dielectric c onstant of water. A dielectric, in general, is a nonconductor of electricity, that is, a substance that, when placed between two charged surfaces (a capacitor), allows no net flow of electri c charge but only a displacement of charge. The dielectric consta nt is also called relative permittivity (or specific inductive capacity). At radio frequencies, the dielectr ic constant of pure water at 20 C and atmospheric pressure is relatively high, normally about 81, that of soil solids varies between 4 to 8 and that of air equals to 1 (Jackson and Schmugge, 1989). Therefore, the value of relative permittivity for a composite of soil body (consisting of the three phases in varying proportions) is largely determined by the fractional volume of water present. As more water becomes present in the soil, the dielectric constant of the mixture increases. The TDR method measures the velocity of propagation of a highfrequency signal reflected back from the end of a transmission line or wave guides in the soil. Wave guides (with two, three or more rods) may be installed in the soil profile vertically or horizontally. Previous researches revealed TDR arrays showed markedly different soil wetness even when separated only by a 15.74 in. (40 cm) horizontal distance Also, TDR overestimated ET following precipitation due to drainage flux out of the bottom of the 0 to 15.74 in. (0-40 cm) layer and underestimate d ET during drying periods due to upward

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12 soil water flux into the same layer. TDR es timated changes in daily ET during drying periods showed that an average of 88% of daily total soil profile changes in storage occurred in the top approximately 12 in (30 cm) of soil (Evett et al. 1993). The TDR method has been well documented by Topp et al. (1980) & Topp (1993). From laboratory experiments at freq uencies from 1 MHz to 1 GHz, Topp et al., (1980) determined an empirical relationship between the dielectric constant and soil volume wetness with a standard error of es timate of about 1.3% for all mineral soils. Their data agree very well with results of other researchers working in frequency ranges of 20 MHz to 1 GHz using a wide range of so ils and electrical techniques. Nevertheless, soils with high organic content and high clay content (75%) may require site specific calibrations (Herkelrath et al., 1991; Zegelin et al., 1992 ; Bridg et al., 1996) and TDR may not perform well. Various investigators cl aimed that the volume wetness of soils can be determined with an accuracy of 2% and a precision (or repeatability) of 1% Topp and Davis (1985) deemed this accuracy to be sufficient for using the TDR technique for irrigation applications without having to carry out calibration for each soil or field. They recommended that the transmission rods, the typical in situ device, be spaced 2 in. (5 cm) apart. A potential source of error in TDR measurements may arise from air gaps around each rod or across the pair of rods in the soil. Such gaps may occur during installation or subsequently as the soil tends to shrink upon dr ying. Installing the rods at an angle (rather than vertically) may help to minimize the fo rmation of cylindrical gaps around the rods. Possible errors due to the temperature ch anges have been stud ied (Hillel, 1998).

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13 TDR instrumentation tends to be quite expensive because they must produce a series of precisely-timed elec trical pulses, and return volta ges at interval s down to around 100 picoseconds. Measurements are typically made on a series of pulses, with the digitized delayed for a set interval on each succeeding pulse, so a complete reflectance trace is built up over perhaps 250 pulses. Because the speed of light in air is around 1 ft/sec (30 cm /sec) and probe lengths range from under approxi mately 4 to 12 in. (10 cm to perhaps 30 cm), precise electronics are re quired to resolve apparent probe length with reasonable accuracy. Therefore, the obvious di sadvantage of this measurement technique is the expense of the equipment and the nu merical challenges of properly analyzing each trace. The advantage, claimed by the manufact urer is that measurements are relatively insensitive to salinity, as l ong the salinity does not complete ly attenuate the reflected signal, and temperature. Alt hough the velocity of propagati on of the TDR pulse as it travels in the soil is eviden tly unaffected by the soil soluti on’s electrical conductive, the intensity of the transmitted signal is aff ected. The attenuation of the signal amplitude (i.e., the reduced voltages) can th erefore serve to indicate the soil’s salinity (Dalton et al., 1984). Frequency Domain Reflectomet ers (FDR) or Capacitance Sensors – Like TDR, FDR utilize the dielectric constant of the soil su rrounding the sensors in order to measure the volumetric water content, which is an intrinsic ch aracteristic of the soil-water-air mixture. The dielectric constant of soils can be m easured by capacitance. Measurement of the capacitance gives the dielectric c onstant, hence the water content of the soil. In a straight forward method for measuring cap acitance, the capacitor is arra nged to be part of an

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14 oscillator circuit so that frequency of osc illation is a direct measure of the capacitance (Gardner et al., 1991). During the last four decades, only a fe w capacitance probes have been designed and manufactured. Enviro-smart is a new system that has been developed in South Australia, using semi-permanent multi-senso r capacitance probes. The probes have been widely implemented in the irrigated agricu ltural industry of Aust ralia since 1991 (Buss, 1993) and have been introduced in the U.S. for over a decade. A water and salinity measurement version of this equipment is under U.S. patent (Watson et. al., 1995). The Enviro-smart multisensor capacitance probe consists of a plastic extrusion approximately 2 to 59 in. (5 cm 150 cm or ore), datum setting ha ndle, printed circuit board, and a 20-way ribbon cable with conn ectors for capacitance sensors placed approximately every 4 in. (10 cm) along its length. Each capa citance sensor consists of two brass rings approximately 2 to 1 i n. (50.5 mm O.D. and 25 mm high) mounted on a plastic sensor body separated by a 0.47 in ( 12 mm) plastic ring. Plastic spring guides located on each end of the sensor keep it in the center of the PVC pipe. The conductive rings of the center form the plates of the cap acitor. This capacitor is connected to an LC oscillator, consisting of an i nductor (L) and a capacitor (C) connected to circuitry that oscillates at a frequency depending on the va lues of L and C. As the inductor is fixed (seven turns of 0.02 in. (0.5-mm) wire), the fr equency of oscillation varies depending on variations of capacitance. The oscillating capacitance field genera ted between the two rings of the sensor extends beyond the PVC access pipe into the surrounding medium-soil (dielectric). The resonant frequency (F) can be measured using a general formula:

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15 (1) Where L is the circuit inductance and C is th e total capacitance, wh ich includes the soil components together with some constant s (Dean et al., 1987; Gardner et al., 1991; Whalley et al, 1992; Evett and Steiner 1995). Since the area of the plates-rings and the distance between the plates rings are fixed on the sensor, the capacitanc e varies only with varying complex dielectric constant of the material surrounding the plates-rings Theses sensors have been designed to oscillate in excess of 100 MHz (inside access tube in free air) so as to be essentially immune to conductivity (salinity and fertilizer effects) at levels typically found in agricultural soils. The frequency of oscillation of the Enviro-smart sensor is divided by a factor of 2048, providing an output freque ncy proportional to the frequency of oscillation. The data logger pow ers the sensor up for 0.5 s, then records the pulses during another 0.5 s to provide a count equal to half the out put. For example, if the sensor is oscillating at 150 MHz, th e output of the sensors would be 73.242 kHz (1.5 x 108/2048), so the logger would record a count of 36621 (73242/2). Th e data logger records the output of the sensor by count ing the pulses during a fixed time (0.5 s), therefore the counts are proportional to the frequency of oscillation of the sensors. The output (frequency) from the sensors pr imarily varies with variations in the air/water ratio and is measur ed by the data logger at us er-input sampling intervals to obtain a frequency of the soil. Frequency read ings of each sensor inside the PVC pipe, exposed to air and water (at room temperature, ~ 22 C), are registered separately before 12 LC F

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16 installing the probe in the soil. The frequencie s in air, water, and soil are passed through a normalization equation to determine a normaliz ed or scale frequency (SF), defined as: (2) Where Fa is the frequency reading in the PVC access pipe while suspended in air; FS is the reading in the PVC access pipe in soil; and FW is the reading in the PVC access pipe in the water bath. The SF has also been called a universal frequency Until a standard procedure is established and commonly recognized, SF is used. The data logger is capable of reading and storing data from multiple sensors ( 32 sensors in two to eight probes) and two analog channels at pre-selected sampling intervals ranging from 1 to 9999 min. During th e process of downloading data from the data logger, the SF is converted to v percentage using either a default or user-specified calibration equation. The Envirosmart software can then display the information as total water content in a profile (in millimeters) or at specified depths as a percentage (for this research we are using the latte r). The downloaded data may also be converted to standard spreadsheet format for further analysis. Due to reported accuracies of soil wate r measurements (Paltineanu et al. 1997), continuous monitoring cap abilities, virtually no health related hazard associated with use of the equipment, the ability to set multiple se nsors at varying depths from near surface to the zone of saturation, and the relatively affordable initial costs allowing purchase of multiple units, the FDR technique was the equipment of choice for this particular research. 1 W a S aF F F F SF

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17 Crop Coefficients Due to the fact that there are so many factors affecting ET, simplified formulations are often based on limiting the number of parameters and making reference to a potential ET value, to formulate an e quation that can produce estimates of ET for different sets of conditions. The idea of reference crop ET (ETref) was developed by researches interested in cr op variability (Doorenbos et al ., 1977 and Hargreaves et al., 1985). Reference crops are either grass or alfalfa surfaces whose biophysical characteristics have been studied extensivel y. Reference ET for a short crop having an approximate height of 0.12 m, e.g., from a standardized grass su rface, is commonly denoted as ETo whereas reference ET for a ta ll crop having an approximate height of 1.64 ft (0.5m), e.g., from a standardized alfalfa surface, is denoted as ETr. Many theoretical and empirical equations ar e used to estimate ETo. The choice of any one method depends on the accuracy of the equation under a given condition and the availability of required data. For referen ce surfaces with known biophysical properties, the main factors affecting ETo include solar radiation, relative humidity/vapor pressure, air temperature, and wind speed. For estimating ETref a modified version of the PenmanMonteith equation (Allen et al., 1999) with some fixed parameters has been recommended (Walter et al., 2000 and Itenfi su et al., 2000). The equation is: ETref = [0.408 (Rn – G) + (Cn / T+273)U2 (eS – ea ) ]/ + (1+Cd U2) (3) Where is the slope of the saturation vapor pressure at mean air temperature (kPa C-1), Rn and G are the net radiation and soil heat flux density in MJ m-2 d-1 for daily or MJ m-2 h-1 for hourly data, is the psychrometric constant (kPa C-1), T is the daily or hourly

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18 mean temperature ( C), U2 is the mean wind speed in m s-1, and eS – ea is the vapor pressure deficit (kPa). The coefficients in the numerator (Cn) and denominator (Cd) are given specific values depending on the calculation time step and the reference crop. The values for Cn vary because the aerodynamic resistance is different for the two reference crops and because of the conversion fr om energy to depth of water units. For the hourly calculations G is assumed equal to 10% of Rn when Rn 0 and G is assumed equal to 50% of Rn for Rn < 0 In addition, the surface (canopy) resistance is set equal to 50 s m-1 during daytime and to 200 s m-1 at night. This change accounts for nighttime stomatal closure and improves the daytime estimates as well. While ETref accounts for variations in weathe r and offers a measure of the “evaporative demand” of the atmosphere, cr op coefficients account for the difference between the crop ET (ETc) and ETo. The main factors affecting the difference between ETc and ETo are (1) light absorption by the canopy, (2) canopy roughness, which affects turbulence, (3) crop physiology, (4) leaf ag e, and (5) surface wetness. The ASCE committee on evapotransporation has recomme nded the use of Kco and Kcr for crop coefficients relative to ETos and ETrs, resp ectively, where “s” stands for standardized surface conditions. The logic of the reference ET is to set up weather stations on standardized reference surfaces where most of the biophysi cal properties used in the ET equations are known. Using these known parameters and meas ured weather parameters, ET from these surfaces can be estimated. Then, crop factor (Kr), or crop coefficients (Kc), can be used to calculate the actual ET (Etc) for a specific crop in the same microclimate as the weather station site.

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19 Crop coefficients (Kc) are used with ETo to estimate specific crop ET rates. The crop coefficient is a dimensionless number, usually between 0.1 and 1.2, that is multiplied by ETo value to arrive at a crop ET (ETc) estimates. The resulting ETc can be used for various purposes, including estimating ET demand and thus moisture availability. Crop coefficients vary by crops, stage of growth of the crop, and by some cultural practices. Citrus trees have smaller coefficien t than peach trees, when peach trees are at full cover. Coefficients for annual crops (row crops) will vary wi dely through the season, with a small coefficient in the early stages of the crop (when the crop is just a seed) to a large coefficient when the crop is at fu ll cover (the soil completely shaded). Smajstrla, 1990 obtained crops coefficien ts from the Agricultural Field Scale Irrigation Requirements Simulation (AFSIRS ) Model developed by the Agricultural Engineering Department at the University of Florida. Updated values for 1995 are also available. The value of Kc ranges from 0.4 to 1.2 for most agricu ltural crops. The lower Kc values result early in th e growing season when vegetativ e canopies are fragmented, or when other factors affect the normal maturity of healthy crop. The higher values occur during peak growth time and are characteristic of tall crops with cover that completely blankets the soil surface. The equation used for the measurement of pl ant “crop” coefficient in this research is: Plant coefficients = (Monthly averaged TSM ET+DS ET) / GPET (4)

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20 Where plant coefficients = crop coeffici ents [Non-dimentional] TSM = total soil moisture [L], DS ET = depression storage ET [L] and GPET = ground potential ET [L]. TSM ET, DS ET and GPET are discussed in greater details in the following chapters. It is noted that the influence of Interception cap ture is not included in the numerator and ground potential ET is used, not PET, as the denominator. Objectives The objective of this research was to investigate a new methodology for measuring hydrologic fluxes (rainfall excess, infiltration and plant uptake) and specifically ET at high spatial and temporal resolution for different landuse covers. This approach entails: 1) Installation of SM probes with multiple sensors at varying depths in close proximity to transe ct water table wells to derive SM storage changes through the unsaturated and saturated profile; 2) Coupling SM results from (1) & (2) with a one-dimensional (1D) transect flow model to solve for ve rtical and horizontal fluxes from the soil; 3) The resultant 1D trans ect model is solved to resolve vertical and horizontal fluxes (including ET) from differe nt horizons for two vegetative covers selected for monitoring; a bahia ungrazed pa sture grass and a slash pine flat woods forested wetland; 4) using the results to determine “plant” or crop coefficients for the two aforementioned landuse covers.

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21 CHAPTER TWO METHODOLOGY, HY POTHESIS & DEFINITIONS Methodology The approach is based on solving th e following basic water budget equation: I + q – ET – L = V/ t (5) where I = infiltration rate (L/T), q = net lateral flow(L/T), ET = Evapotranspiration(L/T), L = deep leakage (L/T), V = volume change in moisture (L/T), t = time step(T). Volume change ( V) at a point S(t)i is based on numerically integrating the observed soil moisture data. SM measurements are made at high ve rtical resolution (e.g., every 10 cm vertically) through the entire SM profile from near land surface to a depth below the seasonal deep water table elevati on 150 cm (59 inch). Observed SM changes are derived for each time step down below th e deepest expected water table condition (zone of saturation), Z0 From the discrete SM observati on, change in storage can be resolved as: (6) where S(t)i = Change in storage (L/T), = Volumetric water content integrated from near surface to the fixed control depth, z0, (L/T). dz z t z t Si i 0 0) ( ) (

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22 In the event of SM monitoring failures (data gaps), volume change ( S ) is based on a simple variable specific yield ( Sy ) model as: (7) where Sy = dimensionless variable corresponding to change in storage per unit area per unit drop in water table, and is change in water table elevation between current and previous time step (L). Following the approach of Ross et al. (2005 ) and findings of Sa id et al. (2004), a stepwise linear, but variable Sy model is us ed as follows and graphically depicted in Figure (1): For depth-to-water table, dWT (L), below the capillary fringe depth, CF, from land surface but above the soil capillary zone, CZ the specific yield is: (8) where the specific yield at any time, Syi, is a minimum value, Sy min or maximum value, Sy max depending on whether dWT < CF or dWT > CF, respectively (all Sy values are L/L), and linearly varying be tween the thresholds. Also, dWT er table (L), CF = capillary fringe (L), and CZ = total capillary zone (L) as de fined by Ross et al. (2005). For the lateral flows, a simple node-cente red Darcian computation is used. For each grid the averaged values of hydraulic conductivity j K (L/T), selected grid dimension (L), averaged aquifer flow thickness i (L), and observed head (L) will be specified. It is noted that terms with over bar represent spatially averaged values. Mass balance for grid ( i ) requires that inflow iQ from grid i (equation 9) minus the outflow / min) max ( minCF CZ CF WT id Sy Sy Sy Sy t i t t i y ih h S t S ) ( t i t t ih h t i t t ih h

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23 1 iQfrom grid (i-1) to grid (i+1) (equation 10), must equal the rate of change in storage tiV in grid ( i ) (equation 11). The flow equation al so incorporates the groundwater evapotranspiration rate. Figure 1. Variable Sy model used during br ief periods of soil moisture measurement gaps. Qi here from grid ( i1) is: i n i n i i i ih h K Q1 (9) where all terms were previously defined.

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24 Flow from grid (i) to grid 1 i is: 1 n 1 1 1 1 i n i i i i ih h K Q (10) where Q i +1 = L3 /T per unit width The rate of change of storage of water in grid ( i ) for the time interval ( t) is: / t t S Vn i i (11) where all terms were previously defined. Rearranging eqn. (5) with measured and esti mated flows placed on the LHS of the equation and derived fluxes on the RHS: The continuity for grid ( i ), including the groundwater evapotranspiration rate, is: I + L ET S Q Qi i i t 1 (12) t L ET I t Sn i n i n i n i ) ( ) Q (Q n 1 i n i (13) t L ET I IELn i n i n i n i ) ( (14) where IEL = combination of infiltration, evaporation and leakage (L), t = time step. All other terms previously defined. Referring to equation (12) there are three unknowns n iI, n iET and n iL that are combined into one term n iIEL which can be solved for each time step by substitution of equations (9), (10) and (11) and including infiltration (I).

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25 The behavior of n iIEL is as follows: positive changes in n iIELare primarily by infiltration in direct response to precipitati on and negative change s result from net ET loss from the soil coupled with deep vertical leakage. Equation 13 can thus be reduced to: t Q Q X S IELn i n i i n i n i ) (1 (15) where all terms were previously defined. Hypothesis Following the assumption of White et al. (1987) and Nachabe et al. (2005) that losses during the day are dominated by ET and those at night are primarily hill slope lateral and vertical leakage fluxes, some simp le assumptions are made. If integrated SM indicates that losses have occurred) 0 (1 n i n iIEL IEL, then the flux is assumed as a result of ET and L only. Conversely, if SM increases, then only I and L have occurred. Thus, it is assumed that ET is not occurring at the same time as rainfall (infiltration). Finally, to solve for ET, estimates for L must be made, using a simple e.g., a Darcian leakage method as: i n DA n il H h L) ( (16) where L is leakage [L], il is a vertical leakance estimated from a confinement thickness (L), ,and confinement vertical hydraulic conductivity vk as /v ik l, for a deep aquifer head, n DAH (L), compared to the water table head ] [ L hn i. The resultant data set is partitio ned for the following two scenarios: t L I IEL IELn i n i n i n i ) ( 0 or t L ET IEL IELn i n i n i n i ) ( 0 (17) where all terms were previously defined.

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26 Since all observed negative cell values are believed to be associated with evapaotranspiration (ET) or evaporative lo sses, all observed posi tive fluctuations are believed to be associated with infiltration and are therefore checked against precipitation flux. Observed positive cell values greate r than the precipitation are checked for occurrence of upslope runoff or delayed in filtration from local depression storage. When water table is at or near land surface, a common occurrence during the wet seasons, the soil moisture change does not refl ect all of the ET losses. Therefore, because the storage change is reflected in free surface storage change of water in surface depressions and plant uptake from the soil is readily replenished keeping the soil sensors at saturation. Since free surface conditions exist at the land surface an assumption is made that the ET rate then proceeds at potential ET (PET). Thus for this methodology to be applied to all periods it is essential to pos sess a good measure of on site PET. For these periods PET estimates can be deri ved by good local pan records or other meteorological methods. For this particular application good pa n measurements were not available and therefore another method was used. The PET va lues were estimated using the empirical equation of Jensen and Haise (1963). ) 08 0 ) 025 0 (( 2450 &ave S H JT R ETP (18) where ETPJ&H = monthly mean of daily potenti al evapotranspiration (L/T); Rs = monthly mean of daily global solar radiation (M/L2/T); Tave = monthly mean of daily air temperature (o C).

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27 Application of equation 18 was to estimat e PET using hourly so lar radiation and temperature. The solar radiation and temper ature data were obtai ned from the Florida Automated Weather Network (FAWN) web site ( http://fawn.ifas.ufl.edu/ ), stored in MINE data from the FAWN archived weather data. The data collected from the ONA site were utilized due to close proximity of th is site to the research site. Resolution consistency was essential for proper co mparison between J&H empirical model vs. research site SM ET. Although the J&H mode l does not incorporate the influence of relative humidity and wind speeds, but it does in clude the most influential parameters of solar radiation and temperature for PET, the re sults were considerably higher than typical PET range for the region which normally ra nges close to 50 to 52 in. (1270 to 1321 mm). The model results demonstrated daily a nd seasonal variability in PET. For this research, a correction pan factor of 0.7 is uniformly applied to the PET data to obtain estimates that average to know n values of mean annual open water (lake) evaporation. The APET records were further ad justed to account for temporal and spatial variability in rainfall for the research si te. This was achieved by comparing the APET records against the rainfall r ecords for the research site. For any observed positive rainfall record the APET record was set to zero for the same time-step otherwise the APET data were used. The new set of record was term ed Site PET. The S ite PET records were further adjusted to account for interception ca pture (Ic) and the new set of records were referenced ground potential ET (GPET). This was achieved by running a 24 hr sum of Site PET and rainfall records for the previous 24 hrs. For the sum of rainfall records for the previous 24 hrs greater than or equal to the sum of Site PET records for the previous 24 hrs for any given time-step, the GPET is set to zero otherwise the Site PET values

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28 were used. GPET records were then used in the model when the water table was very close to land surface (DTWT 1ft or 0.3 m) for estimation of shallow water table ET. ET estimated during these periods was referred to as depression storage ET. (DS ET) corresponding to the primary contributions when visible water is standing on the surface. The capacity of vegetated surfaces to inte rcept and store precipitation is of great practical importance for modeling. To hydr ologists the most important aspect of interception relates to its effect on site and catchment water balances. Rainfall interception or Interception Capture (Ic) and its subsequent evaporation constitute a net loss to the system which may assume cons iderable values under certain conditions (Shuttleworth and Calder, 1979; Schellekens et al., 2000). For this research, interception capture was estimated by plotting measured event precipitation ( P ) and corresponding estimated event infiltration ( I ) produced by the 1D transect model. These analyses were performed for each quarter and each station. Available quarterly data points were complie d, as the period of study was abnormally wet, there were several quarters where insu fficient data existed to formulate a basis quarterly Ic value. Therefore all quarterly data that were considered reliable were used to generate an annual interception capture ( Ic) value. Recommended values for interception capture in the literature vary between bigger than these ranges. The Ic values, derived by this analysis were very close to literature va lues of 0.05 to 0.10 in./day (1.3 to 2.5 mm ) (Viessman et al., 1977) corres ponding to grass and forested land cover, respectively. Thus, this methodology was shown to yield co mparable numbers to published values as well as the potential to resolve these thresh old values to quarterly values or more. Traditionally, results of interception studies have been expressed mostly in relation to

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29 gross rainfall, either as a percentage or th rough various types of regression equations (Zinke, 1967; Jackson, 1975). In tegrated soil moisture meas urement along flow transects yields actual event by event losses due to in terception capture for different land cover. Infiltration Estimation -Event infiltra tion estimation was pe rformed by summing observed positive changes in soil moistu re following a precipitation event until ET commenced (negative changes occurred). This was accomplished by writing a simple algorithm in the model. Observed positive values were then stored in a separate column corresponding to each station a nd identified as “event infilt ration”. Thus, each infiltration “event” included summing all observed positiv e cell values that occurred consecutively without interruption. Interesti ngly, on occasion and usually at night very small increases in soil moisture were observed in the abse nce of rainfall. They were mostly observed between the second and the third soil moisture sensors, for the grass land, but multiple sensors, excluding the top sensor s, for the forested wetland cover. No explanations are offered for these occurrences other than night time dew, vapor pressure gradient, or plant root “hydraulic lift” (Dawson 1995). In the following summaries, total sum of infiltration represents total observed infiltration events that correspond to precipitation events only. Observed positive values of infiltration are summed in the same manner as ET for weekly, monthly, quarterly and annual accumulation timescales. Total Rainfall Excess, Total Runoff, Sa turation Excess Runoff, Net Runoff and Hortonian Runoff Estimationvarious runoff mechanisms were examined with this method. First, estimated interception capture was removed for each precipitation event as the lesser of either the precipitation total or the IC estimate for the station land cover. If

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30 the precipitation event, after removing the in terception capture, was greater than the corresponding “event infiltrati on”, then total runoff is the difference between the precipitation event minus interception capture minus the “event infiltration”. For estimation of saturation excess runoff fr om total runoff a simple algorithm was developed considering depth to water table (DTWT). Basically, an assumption was made for the capillary fringe thickness and when th is thickness was close to 1 ft (0.3 m) below land surface or in tercepted land surface then all runoff was assumed to be from saturation excess. Following soil st udies on the site th e thickness was found to be 1 ft (0.3 m), approximately the dimension of the capillary fringe). For deeper water table conditions the runoff was categorized as Hort onian runoff. Many events resulted in both mechanisms of runoff. This process is perf ormed for each station and each quarter. The 1 ft (0.3 m) depth below land surface is used as the threshold in this research with the understanding that this is a simplistic a ssumption which may warrant future study. For estimation of net runoff, a simple al gorithm is included in the model for the difference between total rainfa ll excess and depression ET. In order to ensure that a pr oper balance is achieved for eac h rainfall event, a balance check is performed considering interception capture, infiltration and net runoff. SM ET, Adjusted ET, Deep water and sh allow water and Depression Storage ET EstimationPursuant to the described me thodology observed negative soil moisture changes and lateral flows were summed fo r SM ET estimation. Adjusted SM ET was estimated using the SM ET values while filtering the data such that observed SM ET

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31 values higher than the minimum GPET values with central moving in 24 hour period with a 1.1 multiplier will be substituted with GP ET value averaged over 3 hour period. The 1.1 multiplier was used to account for acceptance of slightly observed higher hourly values of SM ET. Shallow water ET estimation wa s made by the taking the highest negative values of either adj. SM ET or GPET when DTWT was shallow ( 1’ or o.3 m below land surface). For deep water table condition, > 1’ (0.3 m) below land surface, observed and adj. SM ET is used. Depression storage ET is then estimated by taking the difference between shallow water ET and adj. SM ET. Definitions The following definitions are offered to understand the results presented in the quarterly tables in th e following section; (1) Interception Storage, Ic /Event [L]: Obse rved interception capture values generated by regression analysis grouped by land cover; e. g., grass and forested wetlands. Each value represents the maximum interception captu re volume for any rainfall event for the specific vegetative cover. (2) Total Interception Capture, EIc [L]: Thes e values represent th e total surface capture for the given period (e.g., quarterly or annua l). This is a gross water budget accumulation. (3) Saturated Rainfall Excess, SRE [L]: SRE represents the observed volume of rainfall available for runoff along the transect wells when depth to water table was 1 ft (0.3 m) below land surface (soil saturation was presen t). This volume is available to satisfy depression storage ET and runoff.

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32 If DTWT 1 ft below Land Surface SRE = (P – Ic) – (I) (19) where SRE = saturation rainfall excess. (4) Total Rainfall Excess, TRE [L]: TRE represents the total observed volume of rainfall excess along the transect well s for any water table depth. This volume is available to satisfy depression storage ET and runoff. The following c onditional constraints were observed: If ( P – Ic) > I T R E = (P – Ic) – (I) (20) where P = Event Precipitation, Ic = Interception Capture, I = event infiltration and TRE = Total Rainfall Excess runoff. (5) Net Runoff, NR [L]: The difference between TRE runoff a nd ET from depression storage. (6) Infiltration, (I) [L]: I represent the total event inf iltration volume observed following particular precipitation events. (7) Total Precipitation, (P) [L]: P represen ts the total observed pr ecipitation volume for a given reporting peri od (e.g., quarter). (8) Total Lateral Flow, QGW [L]: QGW represents the net latera l flows along the transect wells that are summed quarterly.

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33 (9) Total Change in Lateral Flow, QGW [L]: Sum of Quarterly change in lateral flows along the transect wells. This is the change in flows between the down stream and the adjoining upstream well along the transect. (10) Total Observed Soil Moisture ET [L]: The observed quarterly evaporative losses, from the soil only, along the transect wells. (11) Adjusted SM ET [L]: The observed soil moisture ET adjusted with the GPET records. (12) Difference between Observed and Adj. SM ET [L]: The difference between the observed soil moisture ET values and adjusted soil moisture ET. (13) Deep Water SM ET (DTWT > 1 ft) [L]: The quarterly adjusted SM ET values when DTWT was greater than 1 ft (0.3 m)below land surface. (14) Shallow Water SM ET+ ET from DS (DTWT 1 ft or 0.3 m) [L]: The quarterly magnitude, using the smallest values of the SM ET or the GPET when DTWT is equal to or less than 1 ft (0.3 m) below land surface. (15) Depression Storage ET, DS ET [L]: The difference between the shallow water SM ET + ET from DS and total SM ET. (16) Shallow Water SM ETET from DS (DTWT 1 ft or 0.3 m) [L]: The difference between shallow water SM ET + ET from DS Depression Storage ET.

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34 (17) Total ET (Adj. SM ET, DS ET& Ic) [L ]: The total sum of adjusted SM ET, depression storage ET and interception capture ET. (18) Total Change in Storage, S [L]: S represents the total quarterly change in storage. (19) Upstream Runoff Infiltration (observed infiltration following a rainfall event up to several hours from the event) URI [L]: URI represents the total observed quarterly infiltration volumes in excess of the rainfall event minus the interception capture, during or within 24 hours of an event. On occasio n when the balance betw een event interception capture, infiltration and total r unoff did not balance event prec ipitation, excess infiltration was believed to be from up gradient runoff into the control section infiltrating in the vacuum of the stratum. (20) Depression Storage Infiltration (DS/I, ET) [L]: Total observed quarterly infiltration /ET two hours after a rainfall event up to 24 hrs or the next rainfall event whichever is shorter. (21) Soil Moisture Increase in the Absence of Rainfall Event (SMwoRain) [L]: Total observed quarterly infi ltration volumes in the absence of any observed rainfall events. The exact origin of this small water-budget item may be from dew (increases in SM in the top sensor in the early hours) or unrecorded rainfall events. (22) Soil Moisture Increase when Rainfall Event Not Recorded [L]: Observed quarterly infiltration volume in all stations wh en no rainfall event was recorded.

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35 (23) Balance: (I+ QWG+ET(SM)S+(19)+(21)+(22) [L]: Th ese values represent the total sum of the water budget balance equa tion based on the numerical model. The absence of closure, observed in some stati ons and some quarters, may be due to the substitution of the storage model and/or the ph ysical hill-slope leakage to deep aquifer storage. I, QWG, ET(SM), S, (19), (21) and (22): Te rms previously explained. (24) Avg. Depth to Water Ta ble (ADTWT) [L]: These valu es represent the quarterly averaged depth to water.

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36 CHAPTER THREE FIELD DATA COLLECTION The study site is located near the Alafia River Watershed in West-Central Florida. A small catchment area of 184.38 acres was selected for the study. A small perennial stream, Long Flat Creek, runs through the ca tchment. An aerial view of the watershed site showing the watershed boundary is depicted in Figure 2. Two sets of transect wells were installed west of Long Flat Creek. They are designa ted as PS43, PS42, PS41, PS40 and PS39 and USF3 and USF1. Figures 3 and 4 depicts the 1-D flow section and nest of transect wells used in the model. Vegetation in the upland area and near USF3 and USF1 was ungrazed Bahia grass. Vegetative communities close to and n ear the stream were dominated by alluvial mixed Slash Pine/hardwood forest ed trees typical of West-Central Florida. Green foliage density follows a seasonal pattern, reach ing maximum coverage during summer wet periods and minimum coverage during winter dry periods. Direct push drilling was pe rformed near PS43, PS42, PS41, USF3 and USF1 to characterize the stratigraphy of the soil and collect samples from which laboratory evaluation of saturated hydrau lic conductivity and porosity va lues could be derived. A sample of the result for station PS42 is grap hically shown in Figure 5. Result for station USF3 is graphically shown in Figure 33 in Appendix A. Falling head permeability test was used to determine hydraulic conductivity. Du e to the fact that hydraulic c onductivity tests are a non-invasive process these tests were performe d prior to texture analysis which

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37 is a rather invasive process. The hydrauli c conductivity used in the model ranged from 1.152 ft/day (0.35 m/day) for most of the upl and stations but for near the stream the hydraulic conductivity diminished by two order of magnitudes to about 0.014 ft/day (0.42 cm/day). The textural analysis revealed a combinat ion of sand and clay in the upland, PS43 and sand, sand/loamy sand and clay near PS41. Porosity tests were performed by measuring the mass of the soil sample before drying and after drying in the oven at 105 C for 24 hours. Porosity ranged from 0.24 to 0.43 in the upland, PS43, to about 0.34 to 0.58 near station PS41. The depth to clay layer (confinement) was also observed with direct push drilling measurement and ranged fr om 8.8 ft (2.68 m) below land surface near PS43 to 7.5 ft (2.29 m) near PS42. No signifi cant variation in dept h to clay layer was observed along the rest of the tr ansect wells to near the str eam region. The depth to clay layer for USF3 and USF1 were found near 5.4 ft and 4.375 ft (1.65 to 1.33m) respectively. Additional Details pertaining to th e site data collection are available in the final report, Ross et al. (2005) prepared for the funding agencies Tampa Bay Water and Southwest Florida Water Management District.

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38 Figure 2. Aerial view of the Alafia river watershed showing the boundary and sub-basins delineation for the research site.

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39 Figure 3. Graphical display of the 1-D flow model for the transect wells, PS43-PS39.

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40 Figure 4. Graphical display of the 1-D flow model for the transect wells, USF3-USF1.

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41 Figure 5. Direct push dri lling results near PS42. Figure 6 depicts the Enviro-Smart soil moisture equipment used for the study site. Sensor depth(s) were at -3.93, -7.87, -11.81, 15.74, -19.68, -27.55, -39.37 and -59 in. ( -10, -20, -30, -40, -50, -70, -100 a nd -150 cm) below land surface at each station. The termination depth at all wells was seen to be below the deepest water table elevation during the study. Each sensor was calibrated using factory calibration curves using the index for air and water and the results were within 1%. SM data were collected at 5-minute inte rvals and averaged over 20-minute or one hour intervals. Two samples of temporal varia tions in SM averaging are shown in Figures

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42 34 and 35 in Appendix B. In the absence of SM data, due to equipment malfunction, a variable specific yield (Sy) model is substituted. Transect wells data collection began in October 2001. Fluctuations in water table were continuously measured at 5-minute inte rvals and queried at 20-minutes resolution and averaged over a 6.5 hour period for smoothing. The averaging approach was implemented to account for removal of noise effect. For missing water table elevations, due to equipment malfunction, measured da ta for the adjacent wells were used to generate a regression equation. Stream gages were installed near upst ream, mid-stream and downstream of the Long Flat Creek. In the event of missing data, constant wate r surface elev ations were used. For precipitation measurements, two automatic tipping bucket rain gauges were installed to measure rainfall volume as well as temporal intensities. Two manual rainfall stations were also installed to verify th e accuracy of continuous rain gauges and to prevent loss of data in the event of equipment failure.

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43 Figure 6. Enviro-smart Soil Moisture probe.

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44 CHAPTER FOUR RESULTS Observed changes in soil moisture ar e shown with observed hydrological and meteorological data for selected presentation pe riods. Graphs depict th e near instantaneous response of measured changes in soil moistu re with meteorological stress, under both dry and wet conditions. Figure 7 shows observed cumula tive fluctuations in Total SM (the station is PS41 located near the stream) in response to peri odic rainfall episodes in spring of 2002. The measurement approach is responsive enough to show TSM changes in direct response to precipitations events observed. At shorter tim e scales observed decline in TSM is observed during the diurnal ET process. A typical daily pattern of fl uctuations in TSM, during periods of no rainfall are show n in Figure 8. Increases in TSM in response to an isolated rainfall episode on 4/14//02 in the upland region are shown in Figure 9. The rise in TSM is in immediate response to infiltration. Infiltra tion ceases as precipitation stops. For the next 24 hours succeeding this rainfall event, despit e available solar radiation, ET effects are masked (or are negligible) as redistribu tion dominates the process due to downward propagation of the wetting front immediately following the event.

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45 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 03/23/0204/12/0205/02/0205/22/0206/11/0207/01/02 HoursIntegrated Changes in Total Soil Moisture (ft)0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0Cumulative Rainfall (in) Integrated Changes in TSM-PS41-4Q (ft) Cumulative Rainfall (in) Figure 7. Observed changes in total soil moisture correspond ing to several precipitation events during spring of 2002 near station PS41. -0.0030 -0.0025 -0.0020 -0.0015 -0.0010 -0.0005 0.0000 0.0005 0.0010 3/31/02 7:12 PM 4/1/02 12:00 AM 4/1/02 4:48 AM 4/1/02 9:36 AM 4/1/02 2:24 PM 4/1/02 7:12 PM 4/2/02 12:00 AM 4/2/02 4:48 AM 4/2/02 9:36 AM HoursHourly Averaged Total Soil Moisture Storage Change (in) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0Incremental Precipitation (in) Hourly Avg. TSM ChangesPS43-4Q Incr. Precipitation Figure 8. Observed 20-minute changes in tota l soil moisture during a high ET period for grassland cover (PS43).

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46 -0.0020 -0.0010 0.0000 0.0010 0.0020 0.0030 0.0040 0.0050 0.0060 0.0070 0.0080 4/13/02 2:24 PM 4/13/02 7:12 PM 4/14/02 12:00 AM 4/14/02 4:48 AM 4/14/02 9:36 AM 4/14/02 2:24 PM 4/14/02 7:12 PM 4/15/02 12:00 AM 4/15/02 4:48 AM 4/15/02 9:36 AM 4/15/02 2:24 PM HoursHourly Averaged Total Soil Moisture Storage Change (in) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9Incremental Precipitation (in) Hourly Avg. TSM ChangesPS43-4Q Incr. Precipitation Figure 9. Change in total soil moisture (PS 43) in response to a precipitation event. Daily changes in TSM and water table fluc tuation for upland grassland (PS43) is shown in Figure 10. The principa l decline in water table coinciding with losses in TSM is in direct response to daily ET demands. Slight ri ses in water table, during very late evening or early morning hours, are from up-slope re -supply associated with the lateral flows. Figure 11 depicts daily losses in TSM and water table for forest cover (PS40) near the stream region for the same period of record. Steeper declines in water table and higher losses in TSM, for the same period of record are in direct response to higher ET demands of that landuse. Rise in water table near station PS40 in very la te evening and early morning hours are attributed to lateral flows. Losses in SM for the grassland and forested wetland regions continue well after solar radiat ions are diminished. Stomates shut down in the absence of solar radiations but in the presence of leaf water deficit the resultant suction/tension induces root water uptake, depl etion of soil moisture, and storage of water in the conveyance mechanisms such as roots, trunk, shoots and leaves. Changes in SM after 7 p.m. are four times greater at forest compared to grass. This is attributed to higher root

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47 water uptake potential in direct response to landuse change. Figure 12 depicts simultaneous increases in TSM and rise in water table in direct response to a precipitation event on 4/14/02 for the upland grass region (PS43) as in filtration dominates the flow. For this event the water table rises steadily (recharge) in response to observed precipitation. After precipitation ceases, water table elevation does not fluctuate rapidly for several hours. Decline in water table is somewhat delayed due to redistribution effects and continued downward migration of infiltrated volumes. Sli ght and gradual decline in water table is observed sometime after th e rainfall event ceases. -0.0030 -0.0025 -0.0020 -0.0015 -0.0010 -0.0005 0.0000 0.0005 0.0010 3/31/02 7:12 PM 4/1/02 12:00 AM 4/1/02 4:48 AM 4/1/02 9:36 AM 4/1/02 2:24 PM 4/1/02 7:12 PM 4/2/02 12:00 AM 4/2/02 4:48 AM 4/2/02 9:36 AM HoursHourly Averaged Total Soil Moisture Storage Change (in) 82.89 82.90 82.90 82.91 82.91 82.92 82.92 82.93Water Table Elevation (ft-NGVD) Hourly Avg. TSM Changes-PS43-4Q Fluctuations in WT Elev.-PS43, 4Q Figure 10. Decline in total soil moisture and water table supporting ET demand for grassland (PS43).

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48 -0.0035 -0.0030 -0.0025 -0.0020 -0.0015 -0.0010 -0.0005 0.0000 0.0005 0.0010 3/31/02 7:12 PM 4/1/02 12:00 AM 4/1/02 4:48 AM 4/1/02 9:36 AM 4/1/02 2:24 PM 4/1/02 7:12 PM 4/2/02 12:00 AM 4/2/02 4:48 AM 4/2/02 9:36 AM HoursHourly Averaged Total Soil Moisture Storage Change (in) 71.90 71.95 72.00 72.05 72.10 72.15Water Table Elevation (ft-NGVD) Hourly Avg. TSM Change-PS40-4Q Fluctuations in WT Elev.-PS40, 4Q Figure 11. Steeper decline in water table and higher losses in total soil moisture for forested wetland nearest the stream (PS-40). -0.0020 -0.0010 0.0000 0.0010 0.0020 0.0030 0.0040 0.0050 0.0060 0.0070 0.0080 4/13/02 2:24 PM 4/13/02 7:12 PM 4/14/02 12:00 AM 4/14/02 4:48 AM 4/14/02 9:36 AM 4/14/02 2:24 PM 4/14/02 7:12 PM 4/15/02 12:00 AM 4/15/02 4:48 AM 4/15/02 9:36 AM 4/15/02 2:24 PM HoursHourly Averaged Total Soil Moisture Storage Change (in) 84.6 84.8 85.0 85.2 85.4 85.6 85.8 86.0 86.2Water Table Elevation (ft-NGVD) Hourly Avg. TSM ChangesPS43-4Q Fluctuations in WT Elev.-PS43-4Q Figure 12. Increase in total soil moisture and rise in water table during a 1.93 inches rainfall event for grassland (PS43). Instantaneous daily decline in TSM in response to solar radiation for grassland cover (PS-43) in upland region is depicted in Figure 13. Higher ET coincides with observed higher values of solar radiation. ET drops in direct res ponse to observed lower

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49 solar radiation magnitudes. Figure 14 depicts changes in TSM corresponding to observed fluctuations in solar radiati on during a precipitation event for grassland (PS43). Often solar radiation does not diminish completely during precipitation events. Observed positive changes in TSM prior to the rainfall event ar e in response to a sepa rate precip itation event that was observed on April 12, 2002 from late in the afternoon to early morning on April 13, 2002. The total magnitude of this almost c ontinuous event was 2.95 inches (75 mm). -0.0030 -0.0025 -0.0020 -0.0015 -0.0010 -0.0005 0.0000 0.0005 0.0010 3/31/02 7:12 PM 4/1/02 12:00 AM 4/1/02 4:48 AM 4/1/02 9:36 AM 4/1/02 2:24 PM 4/1/02 7:12 PM 4/2/02 12:00 AM 4/2/02 4:48 AM 4/2/02 9:36 AM HoursHourly Averaged Total Soil Moisture Storage Change (in) 0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 800.0 900.0Incremental Solar Radiation (W/m2) Hourly Avg. TSM ChangesPS43-4Q Incr. Solar Radiation Figure 13. Observed losses in total soil mois ture corresponding to fl uctuations in solar radiation for grassland (PS43).

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50 -0.0020 -0.0010 0.0000 0.0010 0.0020 0.0030 0.0040 0.0050 0.0060 0.0070 0.0080 4/13/02 12:00 PM 4/14/02 12:00 AM 4/14/02 12:00 PM 4/15/02 12:00 AM 4/15/02 12:00 PM 4/16/02 12:00 AM 4/16/02 12:00 PM HoursHourly Averaged Total Soil Moisture Storage Change (in) 0.0 200.0 400.0 600.0 800.0 1000.0 1200.0Incremental Solar Radiation (W/m2) Hourly Avg. TSM ChangesPS43-4Q Incr. Solar Radiation Figure 14. Change in total soil moisture a nd solar radiation during and after a rainfall event for grassland (PS43). Monthly precipitation records for the 3 year s for this research site are plotted against monthly averaged preci pitation reported from NOAA ( http://www.noaa.gov ) for the region in Figure 15. Relatively rainfall magn itudes are comparable to average values observed except June, July and December in 2002 which were wetter than average and July of 2003 (dryer). Quarterly magnitudes for computed PET from the J&H model, site PET and GPET are shown in Figure 36 in Appendix-C. The quarterly and annu al results are also presented in Tables 4 and 5 re spectively in Appendix C. Samples of daily TSM and depression ET variability for grassland (PS43) and forested wetland (PS40) in 2003 are shown in Figures 37 and 38, respectively in Appendix D.

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51 0 5 10 15 20 JFMAMJJASONDMonthsPrecipitation (in) MPR-2002 MPR-2003 MPR-2004 Monthly Avg., NOAA Figure 15. Monthly precipitation record from research site vs. monthly avg. from NOAA. Monthly TSM, DS and Ic ET contributions were averaged for grassland covers (PS43, USF3 and USF1) and for Forested wetland (PS42, SP41 and PS40) in 2002, 2003 and 2004. Computed Site PET for each corre sponding month is included in the graphs. Figure 16, 17 and 18 depicts ET contributions averaged for gr assland covers and Figure 19, 20 and 21 depicts the ET contributi on averaged for forested wetland. For grassland cover, the highest TSM ET was observed in May 2002 contrasting with the highest total ET observed in Ju ly during 2002. Depression storage ET (DS ET) contributions were consistently higher during the wet periods. In 2003 and 2004 the highest TSM and total ET were observed in May. DS ET was obser ved more frequently in 2003 and 2004, in parts due to shallower DTWT for USF3 and USF1. For the forested wetland, the high est TSM ET was observed in May 2002 contrasting with the highest total ET observed in Apri l 2002. In 2003 and 2004 the highest TSM and total ET were observed in Ma y. DS ET contributions were less frequent

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52 and considerably lower in magnitude as ADT WT was rarely sustained near land surface for an extended period of time. Monthly total ET for each station, in 2002 and 2003, are shown in Figures 40 through 42 in Appendix E. The quarterly ADTWT for each station for the duration of the research are shown in Figures 43 through 44 also in Appendix E. Monthly averaged plant (crop) coefficien ts ratio (Kc) (defined by equation 4 in earlier section) for TSM+DS ET to GPET we re computed and averaged for grassland covers (PS43, USF3 and USF1) and for Fo rested wetland (PS42, SP41 and PS40) in 2002, 2003 and 2004. Computed mont hly plant coefficients for the two distinct landuse covers are presented in Figure 22. Excluding the winter of 2002, Kc is consistently higher for forested wetland than gr assland cover. This observe d behavior was intuitively anticipated. 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 JFMAMJJASONDMonthSite PET vs. ET (in) GRASS, SM ET GRASS, DS ET GRASS, Ic ET Balance of Site PET Figure 16. Monthly averaged ET cont ributions for grassland in 2002.

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53 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 JFMAMJJASOND MonthsSite PET vs. ET (in) GRASS, SM ET GRASS, DS ET GRASS,Ic ET Balance of Site PET Figure 17. Monthly averaged ET cont ributions for grassland in 2003. 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 JFMAMJ MonthsSite PET vs. ET (in) GRASS, SM ET GRASS, DS ET GRASS, Ic ET Balance of Site PET Figure 18. Monthly averaged ET cont ributions for grassland in 2004.

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54 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 JFMAMJJASONDMonthsSite PET vs. ET (in) FOREST, SM ET FOREST, DS ET FOREST, Ic ET Balance of Site PET Figure 19. Monthly averaged ET contributions for fo rested wetland in 2002. 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 JFMAMJJASOND MonthSite PET vs. ET (in) FOREST, SM ET FOREST, DS ET FOREST,Ic ET Balance of Site PET Figure 20. Monthly averaged ET contributions for fo rested wetland in 2003.

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55 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 JFMAMJMonthsSite PET vs. ET (in) FOREST, SM ET FOREST, DS ET FOREST, Ic ET Balance of Site PET Figure 21. Monthly averaged ET contributions for fo rested wetland in 2004. Monthly Kc ranged from 0.11 to 0.65 fo r grassland cover and 0.34 to 0.94 for forested wetland respectively. Lowest Kc ra tio for grassland covers were observed during the wet periods and highest values were obser ved in the spring and in the fall of 2003. For forested wetland the lowest Kc ratio we re observed in winter 2002, September 2002 and July 2003 while highest values were mos tly observed in the spring and fall periods. The maximum values of Kc, slightly in exce ss of 1.4 and 1.2, were observed in August followed by September of 2003 for the forested wetland. Kc value close to unity was also observed for the forested wetland in Augus t 2002. Higher Kc values are generally observed in the wet period and lower Kc valu es are observed in the dry period and Kc can vary considerably depending on the plan t species. It is not uncommon for a close growing crop to ET in excess of PET.

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56 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.61-Jan-02 1M ar02 1May -02 1-Jul-02 1Se p-02 1-Nov 02 1-Jan-03 1 -M ar03 1May -03 1-Jul 03 1 -Se p 03 1-Nov-03 1J an 04 1-M ar -04 1-May-04Month"Plant" Crop Coefficients FOREST GRASS Figure 22. Monthly averaged plant coefficient for gra ss and forested wetland. Quarterly observed water budget compone nts for Ic ET, TSM ET, total ET, including TSM ET plus DS ET and Ic ET, in filtration, TRE, SRE, NR and ADTWT was averaged for grassland cover, stations PS 43, USF-3 and USF1. Same components were also averaged for forested wetland covers, st ations PS42, PS41 and PS40, for the two and half consecutive years. Results are presented in Figures 23 through 30. Quarterly values for water budget components for each station are presented in Tabl es 6 through 25 in Appendix-F. Quarterly results for Ic ET, SM ET, total ET which includes TSM ET, plus DS ET and Ic ET, and infiltration are averaged for grassland cover (PS43, USF3 and USF1) and for forested wetland covers (PS42, PS41 and PS 40) for the two and half consecutive years of research period and are s hown in Figures 23 through 26 resp ectively. Quarterly observed TRE, SRE, NR and ADTWT averaged for gras sland and forested we tland covers and are shown in Figures 27 through 30.

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57 0 1 2 3 4 5 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04 SeasonsInterception Capture (in) Ic ET-Forest Ic ET-Grass Figure 23. Quarterly total interceptions capture (Ic) ET for forest and grass from January 2002 through June 2004. 0 5 10 15 20 25 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04 SeasonsTotal SM ET (in) TSM ET-Forest TSM ET-Grass Figure 24. Quarterly total so il moisture ET for forest and grass from January 2002 through June 2004.

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58 0 5 10 15 20 25 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04 SeasonsTotal ET (in) TET-Forest TET-Grass Figure 25. Quarterly total ET for forest a nd grass from January 2002 through June 2004. 0 5 10 15 20 25 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04 SeasonsInfiltration (in) Infiltration-Forest Infiltration-Grass Figure 26. Quarterly infiltra tion for forest and grass from January 2002 through June 2004.

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59 0 5 10 15 20 25 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04 SeasonsTotal Rainfall Exces (in) TRE-Grass TRE-Forest Figure 27. Quarterly total rain fall excess runoff for grass a nd forest from January 2002 through June 2004. 0 5 10 15 20 25 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04 SeasonsSaturation Rainfall Excess (in) SRE-Grass SRE-Forest Figure 28. Quarterly saturati on excess runoff for grass an d forest from January 2002 through June 2004.

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60 0 5 10 15 20 25 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04 SeasonsNet Runoff (in) NR-Grass NR-Forest Figure 29. Quarterly net runoff for grass and forest from January 2002 through June 2004. 0 1 2 3 4 5 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04ADTWT (ft) ADTWT-Grass ADTWT-Forest Figure 30. Quarterly averaged depth to water table for grass and forest from January 2002 through June 2004. Comparison of observed hour ly, monthly and quarter ly TSM ET+DS ET with simulated site PET in 2002 and 2003 for gra ssland station PS43 an d forested wetland station PS40 are graphically presented in Fi gures 45 through 50 and Figures 51 through 56 respectively in Appendix G. A sample of quarterly results for GPET, observed TSM ET

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61 and adjusted TSM ET for grassl and and forest in 2003 are s hown in Figures 57 and 58 in Appendix H.

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62 CHAPTER FIVE DISCUSSIONS OF RE SULTS, SUMMARY AND CONCLUSIONS Results Annual observed water budget components we re averaged for grassland cover, (PS43, USF3 and USF1) and forested wetl and covers (PS42, PS41 and PS40) in 2002, 2003 and January through end of June 2004. Results are presen ted in Tables 1, 2 and 3 respectively. Explanations for all the fields used in the tables are defined in chapter 2 under “definition” heading. Not surprisingly, lower ET magnitudes were consistently observed for the grassland than the forested wetland. Lowest total ET values were observed in the dry periods for the two landuse covers. Highest total ET values we re observed in the spring or summer time for forested wetland region. The highest ET de mands, coinciding with a high plant growth cycle, were typically observed in the spring and in particular in the month of May. In some cases this trend was also obser ved in summer season particularly near the stream region. The annual magnitude of inte rception capture, Ic (interception ET) in 2002 made up about 8% of the water budget for grassland and 11% for forest land cover. In 2003 the magnitude was observed near 9% and 13% co rresponding to the same landuse categories. For winter and spring in 2004 Ic ET was n ear 8% and 12% for the respective landuse regime.

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63 Landuse WellsRainfallLateral Flows InfiltrationADTWT in Storage Vertical Flows Dep. Storage Infiltration /ET CategoryLocation (in) (in) (in)(ft) (in) (in) (in) ID P IcNet ET from SM DS ET Total ET TRESREURINR Q IADTWT SVFDSI GrassUSF-375.345.7720.2513.5439.5648.4843.8111.1134.94 N /I21.091.46 8.350.00-1.05 GrassUSF-175.345.7720.3011.2837.3644.9943.739.2533.71 N /I24.581.36 8.780.000.51 GrassPS-4375.345.7720.517.6833.9648.6141.338.6740.930.8920.962.32 9.711.792.16 Mixed Zone PS-4275.344.7529.475.7139.9440.7135.7311.9334.990.5029.882.54 12.10-0.790.02 PS-4175.348.6928.416.7343.8341.5335.5911.8234.810.5325.122.31 9.310.061.15 PS-4075.347.7534.970.3143.0432.1415.0715.5831.830.3535.453.58 14.74-0.361.59 PS-3975.347.7535.180.6543.5832.2415.9215.7031.59-0.0635.353.0414.74-0.721.59 Runoff (in) TotalAnnualResults 2002 Period of Record ET (in)Annual 2002 Total for PS43-PS39 & USF3USF1Wetland Forest Table 1. Annual water budget results for 2002.

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64 Landuse WellsRainfallLateral Flows InfiltrationADTWT in Storage Vertical Flows Dep. Storage Infiltration /ET CategoryLocation (in) (in) (in)(ft) (in) (in) (in) ID P IcNet ET from SM DS ET Total ET TRESREURINR Q IADTWT SVFDSI GrassUSF-353.135.0416.1912.3633.6033.9231.092.5021.55N/I14.211.16 -0.220.02-0.91 GrassUSF-153.135.0418.0314.7137.7831.4730.806.5816.76N/I16.660.87 2.540.010.11 GrassPS-4353.135.0421.649.6836.3631 .5229.892.7221.841.0316.571.58 -2.972.17-0.22 Mixed Zone PS-4253.134.1735.293.4442.9023.7720.987.5020.330.5525.192.02 -4.16-0.631.07 PS-4153.137.5730.886.3044.7423.3120.924.0917.020.7422.251.85 -5.560.55-2.04 PS-4053.136.7441.030.2648.0317.218.636.0316.95-0.4329.183.51 -6.87-2.322.06 PS-3953.136.7439.990.4047.1317.179.836.2716.78-0.1829.222.79-6.880.522.04 Runoff (in)Period of Record TotalAnnualResults 2003 Wetland Forest ET (in)Annual 2003 Total for PS43-PS39 & USF3USF1 Table 2. Annual water budget results for 2003.

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65 Landuse WellsRainfallLateral Flows InfiltrationADTWT in Storage Vertical Flows Dep. Storage Infiltration /ET CategoryLocation (in) (in) (in)(ft) (in) (in) (in) ID P IcNet ET from SM DS ET Total ET TRESREURINR Q IADTWT SVFDSI G ra ss US F-31 9.77 1 64 7. 165 0113 81 7. 185 083 3 9 2 16 N/ I10 .9 51 52 7.670.00-0.25 GrassUSF-119.771.6415.274.8821.795.591.914.960.71 N /I12.541.48 2.270.00-0.04 GrassPS-4319.771.6415.130.9917.7 64.412.815.273.430.4013.722.75 5.330.80-0.29 Mixed Zone PS-4219.771.3419.631.0722.033 .862.006.382.790.2614.572.68 0.80-0.27-0.73 P S -411 9.77 2 451 7. 221 1120 .7 83 641 355 222 530 2613 682 86 1.67-0.01-1.08 PS-4019.772.2021.200.0023.401.360.006.921.36-0.1616.214.33 0.21-0.84-4.68 PS-3919.772.2020.680.0122.891.370.026.961.36-0.1016.203.650.240.12-4.68Annual 2004 Total for PS43-PS39 & USF3USF1Wetland ForestPeriod of RecordET (in) Runoff (in) Total Semi-Annual Results-2004 Table 3. Semi-Annual wate r budget results for 2004.

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66 The averaged value for observed SM ET fo r the grassland and forested wetland in 2002 was 20.35 inches (517 mm) to 30.95 inches (786 mm), respectively. This comprised approximately 27% and 41%, respectively of the observed annual precipitation of 75.3 inches (1,914 mm), a wetter than average period. In 2003, the average observed SM ET for the grassland and forest wetland was 18. 62 in. (473 mm) and 35.7 in. (908 mm), respectively, corresponding to 35% and 67% of observed annual precipitation of 53.1 in. (1,350 mm) for a normal rainfall year. For the winter and spring of 2004, SM ET ranged from 12.52 in. (318 mm) and 19.35 in. (491 mm) for the co rresponding landuse covers re spectively. This made up approximately 63% and 98% of the observed precipitation of 19.77 in. (502 mm) for the first six months in 2004. Depression storage ET was assumed to be equal to the difference between GPET and SM ET when the water table was near or at land surface. Highest DS ET volumes were observed in the upland area, where the depth to water table (DTWT) was consistently shallower, declining across the transect wells to a minimum value near the stream region. This corresponded directly to increasing DTWT progressi ng towards the stream. Daily and annual ET for the dura tion of the research were very similar to previous research findings for similar landuse covers in west-central Flor ida by Sumner (1996) with estimated daily ET rates ranging from 0. 008 in./day (0.2 mm/day) in late December 1993 to 0.2 in./day (5 mm/day) in mid-July 1994 and Bidlake et al., (1996), (Bidlake et al., 1993) with annual ET estimates ranging fr om 38.18 in./yr (970 mm/yr) for a cypress swamp type to 39.76 in./yr (1,010 mm/yr) for the dry prairie type, 38.97 in./yr (990

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67 mm/yr) for the marsh vegetation type and 41.73 in./yr (1,060 mm/yr) for the pine flatwood type (Bidlake et al., 1993). Annual averaged DS ET fluctuated in th e range of 10.83 in. (275 mm) to 4.25 in. (108 mm) making up 14% to 6% of the a nnual water budget for the grassland and forested wetland covers respectively in 2002, while 12.25 in. (311 mm) and 3.33 in. (85 mm) with a range of 23% to 6% range for the same landuse covers were observed in 2003. For the first six months in 2004 the ma gnitude of DS ET was 3.63 in. (92 mm) and 0.73 in. (18 mm), approximately 18% and 4%, corresponding to deeper ADTWT for this dryer period. The highest magnitude of DS ET was observed in the summer months when the water table was at or near land surface with high PET stress. In summer months DS ET became the single largest ET component for the upland region. Total ET, sum of Ic, SM ET and DS ET, re vealed somewhat expected variability across the transect. Higher total ET was observe d near the stream and lower values in the upland area. In 2002, a wet year with 75.34 in (1914 mm) of rainfall, total ET made up 49% to 56% of precipitation correspondin g to grassland and forested wetland respectively. In 2003, a dryer year with 53. 13 in. (1350 mm) of rainfall observed, values ranged from 68% to 85%, for the same respec tive landuse. In the firs t half of 2004, total ET made up in excess of 90% of the precipita tion volume for the grassland. For forested wetland total ET was higher than pr ecipitation by approximately 112%. Systematically higher TRE and SRE and ne t runoff volumes were observed in the upland region and diminished to ward the stream. Highest values were observed in summer seasons while lowest values were observed in winter, spring and fa ll seasons. SRE runoff was not observed in every season partic ularly near the stream region.

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68 The highest TRE and SRE volumes were observed in the upland area. This is contrary to popular hill slope runoff models that suggest runo ff is greater near the stream. SRE is defined as the observed rainfall ex cess when DTWT is shallow enough that the capillary fringe is at or near land surf ace thereby making the soil effectively fully saturated. For the Myakka soil s at the study site, this corr esponded to approximately 1 ft (0.3 m) from land surface. Consistent with the DTWT transition, lower TRE and SRE runoff volumes were observed near the stream region. The TRE values in 2002 made up 63% and 51% of the rainfall volume for grassland and forested landuse respectively. In 2003, the ob served magnitudes made up 61% to 40% respective to the same landuse regime. For 2004, the observed made up 29% to 15% of the observed rainfall volume. SRE runoff trailed be hind TRE making up 57% and 38% of the precipitation for grassla nd and forested landuse respectively in 2002 while lower values in the range of 58% to 32% were observed in 2003. In the 1st half of 2004, the SRE made up 17% and 6% of the total observed rainfall for the upland and forest land, respectively. The results for 2004 only represent the winter and spring periods which are characterist ically low runoff periods. Net runoff (NR) values were consistently highest during the summer months, in 2002 and 2003. However, relatively high NR ra tes were observed in the fall of 2002, directly associated with highe r than average precipitation vo lume for that season. Similar observations of high NR conditions prevailed in the un-characteristically wet spring of 2003. Overall higher NR volumes were observed in the upland areas ra ther than the nearstream areas. In 2002, the NR made up appr oximately 49% and 45% of the water budget across the transect wells for grassland and forest wetland respectively. In 2003, NR was

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69 38% and 34% respectively. The NR declined si gnificantly in the firs t six months of 2004 to approximately 11% for both landuse covers. This was consistent with lower rainfall and associated water table decline. Systematically higher Hortonian runoff was observed near the stream while minimal to none was observed in the upland re gion. Hortonian runoff behavior revealed that this particular flow mechanism o ccurs only during intense storm periods. Observed variability in monthly averaged crop coefficients deviate from simple sinusoidal pattern of monthly averaged PET. Higher values of Kc are observed in the peak growth period, spring time, and again in the fall period. This double peak behavior warrants more investigation but is probably attr ibuted to SM availability, solar radiation reduction in the cloudy summer or decline in PET. Other meteorological elements, relative humidity and wind, may also be influencing this behavior. The average depth to water table, ADTWT was consistently shallower in the upland grassy region for most of the study period and was sustained near land surface during the wet periods for an extended period of time. This behavior wa s not consistent for forested wetland covers where consistently d eeper fluctuations in ADTWT were observed including the wet period. For near the str eam region ADTWT was rarely sustained near land surface, even during the wet periods, a nd consistently deepest depth was observed than any other stations. Data filtering was required with the FD R technique for rem oving the effect of equipment noise. Multiple moving averagi ng techniques, 1, 4, 12 and 24 hr central moving averaging technique was performed to all integrated changes in SM record. The hourly averaged SM values did not effec tively account for removal of the equipment

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70 noise effect. The 24 hr averaging period were simply too long and would have interfered with capturing the hourly variab ility of solar radiation on SM. The differences between 4 hr and 12 hr SM moving averaging results were not significant and this observation produced a comfort level to c onsider a conservative and re asonable approach and use the 12 hr SM averaging results. Data filter ing were also necessary for water table fluctuations. Similar reasoning were employed to account for equipment noise effect and air entrapment influence on wa ter table fluctuations and us e of approximately 6.5 hr central moving averaging produced accepta ble smoothing effect. The methodology and the model demonstrat ed daily and seasonal variability in the TSM ET for various vegetativ e land covers for this shallow water table environment. A substitute technique was required to compensa te for the FDR’s inability to accurately estimate TSM changes during wet periods and in the event of the equipment malfunction or erroneous data. Obviously, the most useful data and ou r first preference would have been to use site specific pan data howev er, to achieve the resolution sought and on a continuous basis proved to be highly challeng ing. Therefore, J&H empirical model was used for PET data. The model uses the most in fluential parameters of solar radiation and temperature. The data were obtained from FAWN for ONA station. This station was selected due to closest proximity to the resear ch site. The resultant PET data were further enhanced to adjust for temporal and special rainfall variability for the research site and account for the interception caption. This substitution produced acceptable result. SM measurements are performed at point s cale and then applied to the entire flow segment. This requires the assumption of homogenous soil conditi ons across each model section.

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71 In almost every quarter, occurrences of higher infiltration than precipitation were observed. This observed beha vior had a tendency to be more pronounced with higher rainfall intensities. Model calibration will be help ful. Rise in SM are also observed at night time and in the absence of rain fall. These SM increases are ty pically observed in the second and the third sensors for the upland but for ne ar the stream region they are observed in multiple layers and in the deeper region. Summary One of the indications of how well ET es timation methods perform in Florida is whether or not the annual estimate falls within the expected limits. Temporal variability in annual PET in many parts of Florida is sli ght. A comparison of annual ET rates for grass land cover and forested wetland region were ma de against annual ET results generated by different techniques and models that were previously employed. The comparisons of the results are presented in Table 4 and graphica lly shown in Figure 31. Reviewing the data reveals the relative similarity of estimated ET for the grassland and forested wetland using the TSM model approach vs. previous methods. Excluding isolated variation, the annual TSM ET results fall well within the expected range for the duration of the research. A comparison of annual Site PET rates fo r the research site was made against annual PET results generated by different mode ls for open water. The Highest PET values were observed by J&H model while very similar values were observed for the site PET vs. other models for previous researches. Comparis ons of the results are shown in Figure 32. The TSM model allows for small or large scale (daily, weekly, monthly, quarterly and annual) ET estimation for multiple landuse regimes. A substitute technique/model is

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72 required for wet periods, when DTWT is near landsurface. Inclusion of estimated DS ET, based on site PET data utilizing J&H model, pr oduced acceptable results for this research. GrassForest/Wetland LysimeterSM Measurements2 Annual (1993-1996)SouthFloridaAbtew (1996)--52.4 EBBR & ECM Meteorological Measurements 16 Months West-Central FloridaBidlake (1996)-38.241.7 EBBR & EBWSP Meteorological Measurements 16 Months West-Central FloridaBidlake & Boetcher (1996)88.38-55.9 EBBR Meteorological Measurements 2 Annual SouthFloridaGerman (2000)-42.448.1 LysimeterSM Measurements3 Annual SouthFloridaMao (2002)-46.7 LysimeterSM Measurements3 Annual SouthFloridaMao (2002)-50.7 Soil Moisture MeasurementsFDRAnnual (2002)West-Central FloridaRoss/Rahgozar (2006)75.3436.9541.67 Soil Moisture MeasurementsFDRAnnual (2003)West-Central FloridaRoss/Rahgozar (2006)53.1735.6745.32 Soil Moisture MeasurementsFDR Semi-Annual(1/04-6/04) West-Central FloridaRoss/Rahgozar (2006)19.7717.822.00 Penman & Modified Priestley Taylor Meteorological Measurements 2 AnnualWest-Central FloridaSumner (1996)51.826.7ECM & Priestley -Taylor Approach Meteorological Measurements 2 AnnualNorth-FloridaSumner (2001)51.839Water Budget Balance Water Budget Balance Long Term 16 Countr i es Across the Globe Zhang (2001)5227.238.2 Total ET ET Model TechniquePeriod of ResearchReferencePrecipitation Region Table 4. ET results for grass and forest using various ET models.

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73 0 10 20 30 40 50 60 1995199619971998199920002001200220032004 Referenced Periods (Years)ET Using Various Methods (in) Research Site, SM TETGrass (2006) Research Site, SM TETGrass (2006) Research Site, SM TETForest (2006) Research Site, SM TETForest (2006) Sumner, ECM & PT ETCypress & Pine Forest (2001) Sumner, Penman-PT, ECM ETDeforested Natal-grass (1996) Zahng-WBB ETGrass (2001) Zahng,WBB ETForest (2001) Mao, Lysimeter ETCattails (2002) Mao, Lysimeter ETSawgrass (2002) Bidlake, EBBR, ECM & ECEBBR, Pine flatwood (1996) Figure 31. Estimated ET using various met hods for grassland and forested wetland.

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74 0 10 20 30 40 50 60 70 80 199920002001200220032004 Period of Record (Years)Annual PET vs. Site PET (in) J&H Model PET, (2002) J&H Model PET, (2003) GERMAN, PET-Bowen-ratio/Energy Balance, (2000) ABTEW, LAKE ET-Weather Parameter, (2001) Site PET, (2002) Site PET, (2003) Mao, (open water) PET-Lysimeters, (2002) Figure 32. Estimated potential ET using various methods for open water vs. site PET. Conclusions FDR soil moisture sensors can be ut ilized to gain accurate soil water measurements at multiple depth intervals with negligible disturbances after initial installation. Employing FDR al ong flow transects can yiel d water budget fluxes including ET for small time scale resolution. Data filtering is required with the FDR sensors deployed. The method can then be used to i nvestigate seasonal vari ability in the TSM ET for various vegetative land covers at leas t in shallow water table settings. More investigation is required to see if the technique works for deeper DTWT. Simultaneous test of this method with other well known methods will prove useful. FDR technique is not reliable in meas uring TSM fluxes during periods when depth to water table is near land surface. A substitute technique is required during these

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75 periods such as assuming the actual ET rate may proceed at PET. With this assumption, a potential ET model is required such as a pa n or Penman measurement approach. Use of PET, particularly during wet periods, is considered an acceptable estimation of ET demand (Hillel and Guron, 1973; Hillel, 1997). Accurate estimates of local PET will enhance the predictive capabilit ies of the model. Therefore, the TSM approach must be considered a viable method only after ackno wledging this additi onal data need and assumption. A potential weakness of this technique is that the measurements are performed at point scale and then applied to the entire flow segment. It is clear that variability in vegetable cover and soil conditions exist ac ross each model section. FDR soil moisture measurements of total profile water stor age were generally good, with some minor exceptions. In almost every quarter, occurrenc es of higher infiltration than precipitation were observed for some events. This phenomen on, also observed in previous research Walker et al., (2004) is mo re pronounced with higher rainfall intensities. While the integration approach may be a contributing factor in this observe d behavior, soil’s structural and textural charac teristics in various layers ma y play a role. Installation of sensors in each horizon will help in understand ing if the observed behavior is surface or profiled controlled. Calibrati on for soils containing high clay and organic matter may also prove helpful. The observed daily, monthly, and annual ET re sults were consistent with previous research findings for west-central Florida employing different tec hniques and approaches for the grassland and forested wetland la nduse. This provides further evidence that, despite observed weaknesses, this approach can serve as an alte rnative methodology to

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76 measure ET in field settings w ith added benefits of resolving ET components and other water budget fluxes.

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77 REFERENCES Allen, R. G., L. S. Pereira, D. Raes, and M. Smith. (1999). Crop evaporation: Guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56, FAO. Rome. Abtew, W. and J. Okeysekera, (1995b). Estimat ion of Energy Requirements of Morning Dew Evaporation from Leaf Surfaces. Water Resources Bulletin 31(2):217-225. Abtew, W., J. (1996a). “ Evapotranspirati on measurements and modeling for three wetland systems.” “ J. Am. Water Resour. Assoc., 32(3), 465-473. Abtew, W., J. (2001). “Evaporation Estimates for Lake Okeechobee in South Florida”. Journal of Irrigation Drainage E ngineering, 127(3), 140:147. Abtew, W., J. Okeysekera, M. Irizarry-Oritz, D. Lyons and A. Reardon. (2003). Evapotranspiraton Estimation for South Florida. Proceedings of World Water and Environmental Resources Congress 2003 a nd Related Symposia, P. Bizier and P.A. DeBarry, eds. ASCE. Alsanabani, M.M. (1991). Soil water determinati on by time domain reflectometry: sampling domain and geometry Ph.D. thesis. Department of Soil and Water Sciences, Univ. of Arizona, Tuscan, AZ 85721. Baker, J. M., and R. J. Lascano. (1989) The spatial sensitivity of time-domain refectometry. Soil Sci. 147:378-384. Bidlake W. R., Woodham, W.M. and Lopez, M.A.(1996). Evapotrans piration from Areas of Native Vegetation in West-Central Fl orida. U.S. Geological Survey Water – Survey Paper 2430. Bidlake W. R., Boetcher, P. F.(1996). Near –Surface Water balance of an undeveloped upland site in West-Central Florida. U. S. Geological Survey Water –Supply Paper 2452. Bidlake, W. R., Woodham, W.M., and Lop ez, M.A., (1993), Eva potranspiration from areas of native vegetation in WetsCent ral Florida: U.S. Geological Survey Open File Report 93-415, 35p.

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78 Bouten, W., Heimovaara, T. J., A., (1992). Spat ial patterns of thr oughfall and soil water dynamics in a Douglas fir stand. Water Resources Research 28 (12), 3227-3233. Bridge, B. J., Y. Sabburg, K.D. Habash, Y.A. Ball, and N.H. Hancock, 1996. The dielectric behavior of clay soils and its application to time domain reflectometry. Aust. J. Soil. Res. 34:825-835. Brooks, H. K., (1981). Guide to the physiogra phic divisions of Fl orida: Gainsville, Florida Cooperative Extension Service, Institute of Food and Agricultural Services. Buss, P. 1993. The use of capacitance based m easurements of real time soil water profile dynamics for irrigation schedu ling. In Under pressure. I rrig. 93. Proc. Natl. Conf. Irrig. Assoc. Australia and the Na tl. Committee on Irrig. And Drainage, Launceston, Tasmania. 17-19 May 1993. Irri g. Assoc. of Australia. Homebush, NSW. Crave, A., Gascuel-Odoux, C., (1977). The influence of topography on time and space distribution of soil surfa ce water content. Hydrologi cal Processes 11, 203-210. Dawson, T. E., (1995). Determining water use by trees and forests from isotopic, energy balance and transpiration anal ysis: the roles of tree si ze and hydraulic lift. Section of Ecology and Systematics, Carson Ha ll, Cornell University, Ithaca, NY 14853, USA. Tree Physiology 16, 263-272. Dalton, F. N., Herkelrath, W. N., Rawlins, D. S. and Rhoades, J. D., (1984). Time domain reflectometry: Simultaneous meas urement of soil water content and electrical conductivity with a single probe, Science 224, 989-990. Dean, T. J., J. P. Bell, and A.J.B. Baty, (1987). Soil moisture measurement by an improved capacitance technique, Part I. Sensor design and performance. J. Hydrol. (Amsterdam) 93:67-78. Dolan, T. J., A. J. Hermann, S.E. Bayley, and J. Zoltek, Jr., (1984) Evapotranspiration of a Florida, U.S.A., Freshwater We tland. J. of Hydrology 74:355-371. Doorenbos, J. and Pruitt, W. O., (1977) Guidelines for Predicting Crop Water Requirements. FAO Irrigation and Drai nage Paper 24, F ood and Agriculture Organization of the Unit ed Nations, Rome. Engman, E. T., (1991). Applications of micr owave remote sensing of soil moisture for water resources and agriculture. Re mote Sens. Environ. 35, 213-226. Engman, E. T., and Chauhan, B, (1995) Status of microwave soil moisture measurements with remote sensing. Remote Sens. Eviron. 51, 189-198.

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79 Evett R. Steven, Howell A. Terry, Steiner L. Jean, and Cresap, L. James, (1993). Evapotranspiration by Soil Water Balan ce Using TDR and Ne utron Scattering. Evett, R.S. and J. L. Steine r, (1995). Precision of neutron sc attering and capacitance type soil water content gauges from field calib ration. Soil Sci. Soc. Am. J. 59:961-968. Famiglietti, J. S., Devereaux, J. A., Laymon, C., Tsegaye, T., Houser, P.R., Jackson, T.J., Graham, S.T., Rodell, M., Van Oevelen, P.J., (1990). Ground-based investigation of spatial-temporal soil moisture variability within remote sensing footprints during Southern Great Plains 1997 hydrol ogy experiment. Water Resour. Res. 35, 1839-1851. Gardner, C. M., F.T. Ulaby, M. T. Hallik aninen, and M. A. El-Rayes, 1985. Microwave dielectric behavior of wet soil –part II: Dielectric mixing models. IEEE Trans. Geosci. Remote Sens. 23:35-46. German, E. R. (2000). Regional Evaluation of Evapotranspiration in the Everglades. USGS. Water-Resources Investigations Report 00-4217, Tallahassee, FL. Grayson, R.B., Western, A.W ., (1998). Towards areal estimation of soil water content from point measurements: time and space st ability of mean response. J. Hydrol. 207, 68-82. Herkelrath, W. N., S.P. Hamburg, and F. Murphy. (1991). Automatic, real-time monitoring of soil moisture in a remote field area with time-domain reflectometry. Water Resour. Res. 27:857-864. Hanks, R. J., and Shawcroft, R. W. (1965). An economical lysimeter for evapotranspiration studies. Agron. J. 57, 634-636. Hanson, R. L. (1991). “ Evapotranspirati on and Drought.” In; Na tional Water Summary 1988-89—Hydrologic Events Floods and Drought s. R.W. Paulson, E.B. Chase, R.S. Roberts and D.W. Moody (eds.). USGS, Water-Supply paper 2375, 99-104. Hargreaves, G. H. and Sama ni, Z. A. (1985). Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture, 1(2):96-99. Harrold, L. L. (1966).Measuring evapotranspi ration by lysimetry.In: “ Evapotranspiration and Its Role in Water Resources Manageme nt.” Am. Soc. Agr. Eng., St. Joseph, MI. Hawley, M. E. Jackson, T.J. McCuen R. H. (1983). Sorface soil moisture variation on small agricultural watersheds. J. Hydrol 62: 170-200.

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80 Henninger, D.L., Peterson, G.W., Engman, E. T., (1976). Surface soil moisture within a Watershedvariations, factor es influencing, and relationship to surface runoff. Soil Science Society of America Journal 40, 773-776. Hillel, D. (1997). Small-Scale Irrigation fo r Arid Zones: Principles and Options, Development Monograph No.2. Unite d Nations Food and Agriculture Organization, Rome. Hillel, D. (1982). Negev: Land, Water and li fe in a Desert Envi ronment. Praeger, New York. Hillel, and Guron, Y. (1973). Relation between Evapotranspiration rate and maize yield. Water Resour. Res. 9, 743-748. Hills, R. C., Reynolds, S. C., (1969). Illustrations of soil moisture variability in selected areas and plots of different sizes Journal of Hydrology 8, 27-47. Jackson, I. J., (1975). Relationships between rainfall parameters and interception by tropical forest. Journal of Hydrology 24, 215-238. Jackson, T. J. and Schmugge, T. J. (1989). Pa ssive microwave remote sensing system for soil moisture: Some supporting research. IEEE Trans. Geosci. Remote Sens. GE27, 225-235. Jensen, M. E. and Haise, H. R., (1963). Estimating evapotranspiration from solar radiation .J. Irrig. Drainage Div. ASDE, 89: 15-41. Jones, J. W., Allen, L. H., Jr. Shih, S.F., Rogers, J.S., Hammond, L.C., Smajstrla, A.G., and Martsolf, J.D., (1984). Estimated and measured evapotranspiration for Florida climate, crops, and soils, Gainesville, Florida Agricultural Experiment Stations, Institute of Food and Agricultural Scie nces, Technical Bulletin 840, 65 p. Itenfisu, D., R. L. Elliot, R.G. Allen and I.A. Walter. (2000). Comparison of Reference Evapotranspiration Calculation across a Ra nge of Climates. Proc. Of the National Irrigation Symposium, November 2000, Phoe nix, AZ, American Society of Civil Engineers, Environmental and Water Resources Institute, New York, NY. Ladekarl, U. K., (1997). Estima tion of the components of soil water balance in a Danish oak stand from measurements of soil mo isture using TDR. Journal of Forest Ecology and Management, Vol. 104. May 1998. pp 227-238. Lin, D. S., Mancini, M., Troch, P., Wood, E. F., and Jackson, T. J. (1994). Comparisons of remotely sensed and model simulate d soil moisture over a heterogeneous watershed. Remote Sensing of Environment 48, 159-171.

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81 Mao, L. M., Bergman, M. J. and Tai, C. (2002). Evapotranspiration Measurement and Estimation of Three Wetland Environments in the Upper St. Johns River Basin, Florida”. Journal of the American Wa ter Resources Association, 5(38), 12711285. Mitsch, W. J. and J. G. Gosselink., (1993) Wetlands, Second Edition, Van Nostrand Reinhold, New York, NY. Mohanty, B. P., Famiglietti, J. S., Skaggs T. H., (2000a). Evolu tion of soil moisture spatial structure in a mixe d vegetation pixel during th e Southern Great Plains 1997 (SGP97) Hydrology Experiment. Wa ter Resources Research 36 (12), 36753687. Monteith, J. L., (1965). Evaporation and envi ronment, in: The state and movement of water in living organisms, Symposium of the Society of E xperimental Biology: San Diego, California (G.E. Fogg, ed.), A cademic Press, New York, p.205-234. Moore, I. D., Burch, G. I., (1988). Topogra phic effects on the distribution of surface soil water and the location of ephemeral moisture gullies. Transactions of the ASAE 31 (4), 1098-1107. Nachabe, M., Shah, N., Ross, M., Vomacka, J., (2005). Evapot ranspiration of Two Vegetative Covers in a Shallow Water Ta ble Environment. So il Sciences Society of America Journal 69, 492-499. Nyberg, L., (1996). Spatial vari ability of soil wate r content in the c overed catchment at Gardsjon, Sweden. Soil Sciences Soci ety of America Journal 56, 1267-1271. Paltineanu I. C. and Starr, J. L., (1997) Real-time Soil Water Dynamics Using Multisensor Capacitance Probes: Laboratory Calibration. Soil Sci. Soc. Am. J. 61: 1576-1585 (1997). Penman, H. L., (1948). Natural evaporation from open water, bare soil, and grass: Proceedings of Loyal Society of Lon don, Series A, v. 193, p. 120-146. Phene, C. J., McCormic, R. L., Davis, K. R., and Oierro, J., (1989). A lysimeter system for precise evapotranspiration measuremen ts and irrigation control. Trans. Am. Soc. Agric. Eng. 32, 477-484. Priestley, C. H. B., and Taylor, R. J., (1972) On the assessment of surface heat flux and evaporation using large-scale parameters : Monthly Weather Review, v. 100, no. 2, p. 81-92. Reid, I., (1973). The influence of slope orie ntation upon the soil moisture regime, and its hydrogeomorphological signifi cance. Journal of Hydr ology 19, 309-321.

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82 Ross, M. A., Trout, K. E., Swarna, P., Said A, Rahgozar, M. S. (2005). Micro-scale highresolution measurement of su rface and groundwater interac tion in a coastal plain, shallow water table. University of Sout h Florida, Tampa, FL, Final Report. Said, A., Nachabe, M., Ross, M. A., Vom acka, J., (2004). Methodology for Estimating Specific Yield in Shallow Water Envir onment Using Continuous Soil Moisture Data. Journal of Irrigati on and Drainage Engineer ing, Vol. 131, No. 6, November/December 2005, pp.533-538. Schellekens, J., Bruijnzeel, L. A., Scatena, F. N., Bink, N. J., Holwerda, F., (2000). Evaporation from a tropical rain forest., Luquillo Experimental Forest. Eastern Puerto Rico. Water Resources Research 36, 2183-2196. Shuttleworth, W. J., Calder, I. R., (1979). Has the Priestley Taylor equation any relevance to forest evaporation?. Journal of Applied Meteorology 18, 639-646. Smajstrla, A. G., (1990). Ag ricultural Field Scale Irri gation Requirements Simulation (AFSIRS) Model. Agricultural Engineeri ng Department, University of Florida. 252 pp. Stephen, J. C. (1959). Evapotra nspiration studies pert aining to the agricultural watersheds in Florida. USDA. ARS. Soil and Water Conservation Research Division. Fort Lauderdale, FL, 39.1-39.31. Schmugger, T. (1990). Measurements of surface soil moisture and temperature. In: Hobbs, R. J., and Mooney, H. A., ed s., “Remote sensing of Biosphere Functioning.” Springer-Verlag, New York. Sumner D. M. (1996) Evapotra nspiration from successional vegetation in a deforested area of the Lake Wales Ridge, Florida. U.S. Geological Survey; Water-Resource Investigation Report 96-4244. Sumner D. M. (2001) Evapotra nspiration from a Cypress and Pine Forest Subjected to Natural Fires, Volusia County, Flor ida, 1998-1999. U.S. Geological Survey; Water-Resource Investigation Report 01-4245. Topp, G. C., Davis, J. J., Annan, A. P., (1980). Electromagnetic de termination of soil water content: measurements in coaxial transmission lines. Water Resour. Res. 16, 574-582. Topp, G. C., and Davis, J. L. (1985). Time-Domain reflectomerty (TDR) and its application to irrigation scheduling. In: Hillel, D., ed., “Advan ces in irrigation,” Vol. 3. Academic Press, San Diego.

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83 Topp, G. C., (1993). Soil water content. p. 541-557. In M.R. Carter (ed.) Soil sampling and methods of analysis. Le wis Publ., Boca Raton, FL. van Bavel, C. H. M., and Myer s, L. E. (1962). An automatic weighing lysimeter. Agr. Eng. 43, 580-583. van Bavel, C. H. M., and Hillel, D. (1975). A simulation study of soil heat and moisture dynamics as affected by a dry mulch. In: “Proc. Summer Comput. Simulate. Conf.,” San Francisco, C.A. Si mulation Councils, LaJolla, C.A. van Bavel, C. H. M., and Hillel, D. (1976). Calculating potential and actual evaporation from a bare soil surface by simulation of c oncurrent flow of water and heat. Agr. Meteorol. 17, 453-476. van Bavel, C. H. M., Lascano, R.J., and Baker, J. M. (1985). Calibrating two-probe, gamma-gauge densitometers, Soil Sci. 140, 393-395. Viessman, W., Klapp, J. W., Lewis, G. L. and Harbaugh, T. E. (1977). Introduction to Hydrology, Harper & Row, New York. Visher, F. N. and Hughes, G. H. (1969). The difference be tween rainfall and potential evaporation in Florida, 2nd Ed. Florida Bureau of Geology Map Series 32, Tallahassee, Fl. Walker, J. P., Willgoose, G. R., and Kalma, J. D. (2004). In situ measurement of soil moisture: a comparison of techniques. Journal of Hydrology 293, 85-99. Walter, I. A., R. G. Allen, R. Elliot, M. E. Jensen, D. Itenfisu, B. Mecham, T.A. Howell, R. Snyder, P. Brown, S. Ec hings, T. Spofford, M. Hatte ndorf, R.H. Cuenca, J.L. Wright, D. Martin. (2000). ASCE’s Sta ndardized Reference Evapotranspiration Equation. Proc. Of the Watershed Mana gement 2000 Conference, June 2000, Ft. Collins, CO, American Society of Civil Engineers, St. Joseph, MI. Watson, K., R. Gatto, P. Weir, and P. Buss, (1995). Moisture and salinity sensor and method of use. U.S. Patent 5 418 466. Date issued: 23 May. year Waylen, P. R. and Zorn, R. (1998). “Predi ction of mean annual flows in North and Central Florida.” Journal of American Water Resources Association. 34(1), 149157. Western, A. W., Grayson, R. B., Bl’oschl, G., Willgoose, G. R., McMahoon, T. A., (1999a). Observed spatial organization of soil moisture and its relation to terrain indices. Water Resources Research 35 (3), 797-810.

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84 Whalley, W. R., T.Y. Dean, and P. I zzard, (1992). Evaluation of the capacitance technique as a method for dynamically meas uring soil water content. J. Agric. Eng. Res. 52:147-155. White, I., and Perroux, K. M. (1987). Use of so rptivity to determine field soil hydraulic properties. Soil Sci, Soc, Am, J. 51, 1093-1101. Wilson, D. J., Westren, A. W., Grayson, R. B., Berg, A. A., Lear M. S., Rodell, M., Famiglietti, J. S., Woods, R. A., and Mc Mahon, T. A. (2003). Spatial distribution of soil moisture over 6 and 30 cm de pth, Mahurangi river catchment, New Zealand. Journal of Hydrology, Vol. 276, May 2003. pp. 254-274. Zegelin S. J., I. White, and G.F. Russe ll. (1992). A critique of the time domain reflectometry technique for determining field soil water content. p, 187-208. In G.C. Topp et al. (ed.) Advantages in m easurement of soil physical properties; Bringing theory into practice. SSSA Spec. Publ. 30. SSSA, Madison, WI. Zinke, P. J., (1967). Forest interception studie s in the United States. In: Sopper, W. E., Lull, H. W. (Eds.). International Sy mposium on Forest Hydrology. Pergamon Press, New York, pp. 137-160.

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85 APPENDICES

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86 Appendix A: Soil Descripti on at the Field Study Site An intensive filed study was conducted at field-scale to measure hydrologic response of a small (185 acres) basin tributary to a first-order perennial stream in westcentral Florida (Ross et al. 2004) Data summarized here are discussed in more detail in Ross et al. (2004). Direct push drilling sample results, were performed along most transect wells. Samples were used for evaluation of textural classification of the soil, saturated hydraulic conductivity and porosity. A samp le of the result for USF3 is shown in Figure 33. Higher clay concentrations at shallow depths were observed near USF3 a nd USF1. The depth to confining clay layer for USF3 and USF1 are near 5.4 ft (1.65 m) and 4.375 ft (1.33 m) respectively. High concentrations of organic ma tter in the upper region were observed near some stations overlaying typical sandy/silty soil in lower horiz ons. Soil characteristics of PS42 and PS41 did not reveal high organic content in the upper region, although similar characteristics in the remaining horizons were prevalent. Review of particle size analysis performed on collected samples show a relative decrease in particle diameter with depth. Consistent with grain size di stribution vertical hydraulic co nductivity also decreased with depth and this trend was not ed in all soil stations.

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87 Appendix A: (Continued) Figure 33. Direct push drilling results near USF3.

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88 Appendix B: Influence of Temporal Vari ability in Soil Moisture Averaging on ET Results For ET estimation all negative (I-ET-L) cell values in the numerical model were separated from the positive cell values by a simple algorithm in the model. Vertical soil moisture observations with capacitance shift devices in sandy soils are very precise and relatively stable. However, integration over depth to get small fluctuations pushes the limit and the signal can be noisy. Five minut e values averaged hour ly were ultimately averaged over a 12 hour period using a cen tral moving averagi ng technique. This technique was also used with water table elev ations when soil moisture data was absent and the Sy model was used. The influence of SM averaging was used on ET results and is shown in Figures 34 and 35 for station PS43 and PS40 respectively. From the graphs it is observed that variable SM averaging has a greater influence on some stations (e.g.; PS43) than others (PS40). For the grassland land cover, 24 hour SM averaging for the most part resulted in lowest SM ET while the hourly averaging resu lted in the highest SM ET. This was also consistent for forested land covers. The di fference between hourly vs. 12 and 24 hrs SM averaging is considerably highe r in winter of 2004 than any other period. This behavior was not observed for the forested wetland. Given that the ET cycle is primarily radi ation driven, the 12 hour averaging was considered more appropriate than longer or sh orter periods considered For this research 12 hour moving averages were used as a mi ddle approach toward achieving results for SM ET. The magnitudes of other components of the water budget such as infiltration and TRE are also influenced by the averaging period selected.

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89 Appendix B: (Continued) -12.0 -10.0 -8.0 -6.0 -4.0 -2.0 0.0 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04 SeasonsAdj. SM-ET (in) Adj.SM-ET (1hr),PS43 Ad. SM ET(4hr)-PS43 Ad j SM ET ( 12 hr ) -PS43 Ad j SM ET ( 24 hr ) -PS43 Figure 34. Temporal variability in soil mo isture for grassland cover (Station PS43). -16.0 -14.0 -12.0 -10.0 -8.0 -6.0 -4.0 -2.0 0.0 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04 SeasonsAdj. SM-ET (in) Adj.SM-ET (1hr),PS40 Ad. SM ET(4hr)-PS40 Adj. SM ET (12 hr)-PS40 Adj. SM ET(24 hr)-PS40 Figure 35. Temporal variability in soil moisture for forest cover (Station PS40).

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90 Appendix C: Techniques for Estimation of Potential ET, Site Potential ET, Ground Potential ET and Adjusted SM The PET values were estimated using the empirical equation of Jensen and Haise (1963). ) 08 0 ) 025 0 (( 2450 &ave S H JT R ETP where ETPJ&H = monthly mean of daily potential evapotranspiration (mm/day); Rs = monthly mean of daily (t otal) solar radiation (Kj/m2 /day); Ta = monthly mean of daily air temperature (o C). The input parameters for the equation we re instantaneous hourly resolution for solar radiation and temperature. The solar ra diation and temperatur e data were obtained from Florida Automated Weather Network (FAWN) ( http://fawn.ifas.ufl.edu/ ), stored in Mine data from the FAWN archived weather da ta. The data collected from the ONA site were utilized due to close proximity of this s ite to the research site. A pan factor of 0.7 was employed uniformly to J&H model PET reco rds and results were further adjusted to account for temporal and spatial variability for th e research site as site PET. The site PET records were further refined to account for interception capture (I c). The new set are termed ground potential ET (GPET). The quarterly magnitudes of estimated P ET, site PET and GPET for full calendar year in 2002, 2003 and for the first six m onths in 2004 are presen ted graphically in Figure 36 and in Tables 5 and 6 respectively.

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91 Appendix C: (Continued) 0 5 10 15 20 25 30 W02SP02S02F02W03SP03S03F03W04SP04 QuartersPET,s (in) J&H Model PET Site PET GPET Figure 36. Quarterly values of potential ET, site potential ET a nd ground potential ET (GPET).

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92 Appendix C: (Continued) Table 5. Quarterly values computed for PET, site PET and GPET. AnnualQuarters 3rd (1/1/02-3/31/02) 4th (4/1/02-6/30/02) 5th (7/1/02-9/30/02) 6th (10/1/02-12/31/02) 7th (1/1/03-3/31/03) 8th (4/1/03-6/30/03) 9th (7/1/03-9/30/03) 10th (10/1/03-12/31/03) 11th (1/1/04-3/31/04) 12th (4/1/04-6/30/04)Period Of Record9.1 15.9 14.2 9.4 14.1 23.6 9.4 18.2 22.3 13.4 13.2 23.5 21.1 13.52004Quarterly Site PET with Uniform Pan Factor of 0.7 Adjusted with Rainfall Records (in)200213.6 26.3 9.7 Quarterly J&H Model PET Using FAWN-ONA Site's Solar Radiation & Temperature Data (in) 15.9 14.8 9.12003Quarterly GPET (in) 8.9 14.1 10.3 8.2 8.0 13.4 9.6 9.1 9.0 16.0 Table 6. Annual values computed for PET, site PET and GPET. Site PET with Uniform Pan Factor of 0.7 Adjusted with Rainfall Records (in) Annual 2002 1/1/02-12/31/02 Annual 2003 1/1/03-12/31/03 73.4 71.3 J&H Model PET Using FAWN-ONA Site's Solar Radiation & Temperature Data (in) Semi-Annual 2004 1/1/04-06/30/04 Period Of Record GPET (in) 39.9 41.5 40.2 25.0 49.5 48.5 27.5

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93 Appendix D: Daily Variability in SM and DS ET with Landuse Sample of observed daily ET and DS ET fo r the annual year in 2003 are shown in Figures 37 and 38 for the gr assland cover (PS43) and forested wetland (PS40) respectively. For grassland covers highest magnitudes of ET are observed in spring period while some fluctuations in ET magnitudes we re observed near station USF3 This pattern of behavior was also observed in 2002 & 2004. For forested wetland highe st ET demand are observed in the summer period. This trend in behavior was also observed in 2002. 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.351 / 2/2003 2 / 2/2003 3/2/2003 4/2/2003 5/2 / 2003 6/2 / 2003 7/2 / 2 0 03 8/2 / 2 0 03 9 /2 / 2 0 03 1 0/ 2 / 2 00 3 1 1/ 2 / 2 00 3 1 2/ 2 / 2 00 3DaysDaily TSM + DS ET (in) Daily TSM + DS ET PS43 Figure 37. Daily fluctuations in soil moistu re and depression st orage ET for grassland (PS-43) in 2003.

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94 Appendix D: (Continued) 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.401/2 / 2 0 03 2/2/2 0 03 3/ 2 / 2 003 4/ 2 / 2 003 5/2/2003 6/ 2 /2003 7/2/2003 8/ 2 /2003 9/ 2 /2003 10/2/200 3 11/2/200 3 12/2/2003DaysDaily TSM + DS ET (in) Daily TSM+DS ET PS40 Figure 38. Daily soil moisture and depression storage ET for forested wetland (PS-40) in 2003.

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95 Appendix E: Monthly Distribution of SM, DS and Ic ET and Quarterly Averaged DTWT Monthly TSM, DS and Ic ET, total ET (TET), magnitudes for grassland covers (PS43, USF3 and USF1) in 2002, 2003 (wet a nd dry year respecti vely) are shown in Figures 39 and 40 respectively. For the grass land cover hi ghest TET magnitudes are typically observed in the sp rings and summers extending into the fall seasons. Lowest TET magnitudes are typically observed in the wint er periods. Results are consistent with various models previously used for ET estimation. Monthly TET magnitudes for forested wetla nd covers (PS42, PS41 and PS40) in 2002, 2003 (wet and dry year respectivel y) are shown in Figures 41 and 42. For forested wetland cover highest TET magnitudes are typically observed in the springs, in particular the month of May, and summer extending to fall season. The lowest magnitudes are typically observed in the winter periods. Re sults are consistent with various models previously used for ET estimation. Quarterly averaged DTWT for grassland st ations (PS43, USF3 and USF1) and for forested wetland stations (PS 42, PS41 and PS40) for the duration of the research are shown in Figures 43 and 44. Shallowest averaged DTWT are observed in the wet periods for the two landuse covers. Consistently deepest average DTWT are obs erved in forested wetland region in support of higher ET demands. Despit e reasonably significant rainfall volume in the spring periods, ADTWT is the deepest across the transect wells in the same period supporting high ET demands coinciding with the most active growing period.

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96 Appendix E: (Continued) 0.0 1.0 2.0 3.0 4.0 5.0 6.0 JFMAMJJASOND MonthMonthly SM+DS+Ic ET (in) PS43 USF3 USF1 Figure 39. Monthly total soil moisture, de pression storage and in terception capture ET distribution for grassland cover (PS43, USF3 and USF1) in 2002. 0.0 1.0 2.0 3.0 4.0 5.0 6.0 JFMAMJJASOND MonthMonthly SM + DS+Ic ET (in) PS43 USF3 USF1 Figure 40. Monthly total soil moisture, de pression storage and in terception capture ET distribution for grassland cover (PS43, USF3 and USF1) in 2003.

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97 Appendix E: (Continued) 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 JFMAMJJASOND MonthMonthly SM+DS+Ic ET (in) PS42 PS41 PS40 Figure 41. Monthly total soil moisture, de pression storage and in terception capture ET distribution for forest covers (PS42, PS41 and PS40) in 2002. 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 JFMAMJJASOND MonthMonthly SM + DS+Ic ET (in) PS42 PS41 PS40 Figure 42. Monthly total soil moisture, de pression storage and in terception capture ET distribution for forest covers (PS42, PS41 and PS40) in 2003.

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98 Appendix E: (Continued) 0 1 2 3 4 5 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04ADTWT (ft) PS43 USF3 USF1 Figure 43. Quarterly averaged depth to water table for grassland stations (PS43, USF3 and USF1). 0 1 2 3 4 5 W-02SP-02S-02F-02W-03SP-03S-03F-03W-04SP-04ADTWT (ft) PS42 PS41 PS40 Figure 44. Quarterly averaged depth to water table for forested wetland stations (PS42, PS41 and PS40).

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99 Appendix F: Quarterly Water Budget Components 3rd Quarter Water Budget Components Total precipitation was near 5.24 inches Observed total ET ranged from 4.68 inches in the upland grassy region (PS43) to 5.19 in. (132 mm) in the forested wetland region near the stream (PS40). Lowest ET values were observe d in this winter. Total SM and Ic ET were second to rainfall. Relatively uniform total ET was observed across the transect wells. Highest total ET was observed near station UFS3 with a value of 7.5 in. (191 mm). Observed infiltration along the transect wells behaved in a uniform manner fluctuating just above or below 3 to slightly over 4 in. ( 76 to 102 mm). Minimal TRE was observed along the transect wells. This is the only quarter wh ere slightly higher r unoff was observed near the stream vs. the upland. Zero to negligible SRE runoff was observed for this quarter. ADTWT remained just below 4 ft (1.22 m) near all wells with the exception of PS41 where ADTWT was observed near 3.62 ft (1.1 m). Sh allower ADTWT was observed near stations USF3 and USF1. Total Lateral fl ows were observed to di minish progressively from 0.15 in. (3.8 mm) in the upland area to ab out -0.19 in. (-4.8 mm) near the stream. For the month of January SM data were missing for station PS43 and USF1 while relatively minimal gaps were periodically observed for the remaining stations. Observed quarterly results for all water budget components for PS4 3 through PS40 and USF3 and USF1 in this quarter are presented in Tables 7 and 8 respectively.

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100 Appendix F: (Continued) Table 7. Quarterly water budget resu lts for winter 2002 for PS43-PS39. Table (7) WINTER, 2002 (3 Qtr) (in/qtr)PS43PS42PS41PS40PS39 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Even t 0.050.040.080.070.07 ( 2 ) Total interce p tion ca p ture, EIc 0.850.721.191.091.09 ( 3 ) Saturation Rainfall Excess, SRE 0.000.000.000.000.00 ( 4 ) Total Rainfall Excess, TRE 1.030.550.861.191.18 ( 5 ) Net Runof f 1.030.550.861.191.18 ( 6 ) Infiltration, I 3.363.973.192.962.97 ( 7 ) Total Preci p itation, P 5.245.245.245.245.24 (8) Total Lateral Flow, QGW 0.150.080.03-0.190.01 (9) Total Change in Lateral Flow, QGW 0.15-0.07-0.05-0.230.21 ( 10 ) Total Observed Total Soil Moisture ET -3.83-4.00-4.00-3.81-3.55 (11) Adjusted TSM ET (with GPET) -3.83-4.00-4.00-3.81-3.55 (12) Difference Between Obs. & Adjusted TSM ET 0.000.000.000.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -3.83-4.00-4.00-3.81-3.55 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) 0.000.000.000.000.00 ( 15 ) De p ression Stora g e ET ( DS ET ) 0.000.000.000.000.00 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) 0.000.000.000.000.00 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -4.68-4.72-5.19-4.90-4.64 (18) Total Change in Storage, S 3.111.001.521.361.36 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 2.451.191.501.601.68 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) 2.160.021.151.591.59 (21) Soil Moisture Increase in the Absence of Rainfall Even t 1.550.210.930.650.73 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.000.000.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.31-0.15-0.09-0.450.42 (24) Avg. Depth to Water Table (ADTWT)(ft)4.144.093.624.253.44 H y drolo g ic Observations f or Winter 2002 3 QtrDerived Hydrologic Fluxes & Storages

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101 Appendix F: (Continued) Table 8. Quarterly water budget results for winter 2002 for USF3 and USF1. Table (8) WINTER, 2002 (3 Qtr) (in/qtr)USF3USF1 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Event0.050.05 ( 2 ) Total interce p tion ca p ture, EIc 0.870.87 ( 3 ) Saturation Rainfall Excess, SRE 0.400.04 ( 4 ) Total Rainfall Excess, TRE 0.800.16 ( 5 ) Net Runoff0.050.16 ( 6 ) Infiltration, I 3.574.21 ( 7 ) Total Preci p itation, P 5.245.24 (8) Total Lateral Flow, QGW 0.000.00 (9) Total Change in Lateral Flow, QGW 0.000.00 ( 10 ) Total Observed Total Soil Moisture ET -5.88-3.51 ( 11 ) Ad j usted TSM ET ( with GPET ) -5.88-3.51 (12) Difference Between Obs. & Adjusted TSM ET 0.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -4.91-3.51 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -1.720.00 ( 15 ) De p ression Stora g e ET ( DS ET ) -0.750.00 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -0.970.00 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -7.50-4.38 (18) Total Change in Storage, S 1.352.94 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 4.261.75 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) 1.080.51 (21) Soil Moisture Increase in the Absence of Rainfall Event0.731.07 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.000.00 (24) Avg. Depth to Water Table (ADTWT)(ft)2.842.71 3 QtrDerived Hydrologic Fluxes & Storages H y drolo g ic Observations f or Winter 2002

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102 Appendix F: (Continued) 4th Quarter Water Budget Components Total precipitation measured to 18.14 in (461 mm). The highest total ET values was observed almost along the entire transect wells, PS43-PS40, regardless of the landuse regime. Total ET was second to precipitation al ong the transect wells. PS-41 in the forested wetland region was the station with highest observed ET volume. For PS43 to PS40, infiltration was third to precipita tion, slightly lower than tota l ET, regardless of the landuse. Higher TRE runoff was observed in the upland region than near the stream. Observed SRE runoff was minimal in the upland region and gr adually diminished toward the stream to zero. Higher SRE were observed ne ar stations USF3 and USF1. Deeper ADTWT fluctuations were observed in this quart er along the transect wells ranging from 3 ft (0.91 m) near PS43 to 4. 53 ft (1.38 m) near the stream. ADTWT for USF3 and USF1 were shallower. None to negligible DS ET was observed across the transect wells PS43-PS40 but th e magnitude was considerable near stations USF-3 and USF-1. Total Lateral flows were observed to diminish progressively from the upland to near the stream. Minimal SM data were mi ssing for all stations except PS41 were no missing data was observed. Observed quarterly results for all water budget components for PS43 through PS40 and USF3 and USF1 in this quarter are presented in Tables 9 and 10 respectively.

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103 Appendix F: (Continued) Table 9. Quarterly water budget results for spring of 2002 for PS43-PS39. Table (9) SPRING, 2002 (4Qtr) (in/qtr)PS43PS42PS41PS40PS39 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Even t 0.050.040.080.070.07 ( 2 ) Total interce p tion ca p ture, EIc 1.221.011.831.631.63 ( 3 ) Saturation Rainfall Excess, SRE 1.261.180.380.000.00 ( 4 ) Total Rainfall Excess, TRE 6.944.714.534.114.13 ( 5 ) Net Runoff6.874.664.514.114.13 ( 6 ) Infiltration, I 9.9812.4211.7812.4012.38 ( 7 ) Total Preci p itation, P 18.1418.1418.1418.1418.14 (8) Total Lateral Flow, QGW 0.200.090.050.01-0.06 (9) Total Change in Lateral Flow, QGW 0.20-0.11-0.04-0.04-0.07 ( 10 ) Total Observed Total Soil Moisture ET -9.44-12.53-13.95-11.97-11.96 (11) Adjusted TSM ET (with GPET) -9.44-12.53-13.95-11.97-11.96 (12) Difference Between Obs. & Adjusted TSM ET 0.000.000.000.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -9.41-12.43-13.79-11.97-11.96 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -0.10-0.15-0.180.000.00 ( 15 ) De p ression Stora g e ET ( DS ET ) -0.07-0.05-0.010.000.00 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -0.03-0.10-0.160.000.00 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -10.73-13.59-15.79-13.60-13.59 (18) Total Change in Storage, S 5.317.946.426.396.39 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 4.868.338.696.636.62 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -0.95-0.72-1.21-1.80-1.80 (21) Soil Moisture Increase in the Absence of Rainfall Even t 0.240.000.910.280.28 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.000.000.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.39-0.21-0.08-0.08-0.14 (24) Avg. Depth to Water Table (ADTWT)(ft)3.383.973.744.533.92 Hy drolo g ic Observations f or S p rin g 2002 4 QtrDerived Hydrologic Fluxes & Storages

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104 Appendix F: (Continued) Table 10. Quarterly water budget results for spring 2002 for USF3 and USF1. Table (10) SPRING, 2002 (4 Qtr) (in/qtr)USF3USF1 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Event0.050.05 ( 2 ) Total interce p tion ca p ture, EIc 1.221.22 ( 3 ) Saturation Rainfall Excess, SRE 1.293.24 ( 4 ) Total Rainfall Excess, TRE 5.554.37 ( 5 ) Net Runoff5.043.76 ( 6 ) Infiltration, I 11.3712.55 ( 7 ) Total Preci p itation, P 18.1418.14 (8) Total Lateral Flow, QGW 0.000.00 (9) Total Change in Lateral Flow, QGW 0.000.00 ( 10 ) Total Observed Total Soil Moisture ET -8.23-9.03 ( 11 ) Ad j usted TSM ET ( with GPET ) -7.95-8.55 (12) Difference Between Obs. & Adjusted TSM ET -0.28-0.48 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -7.95-8.55 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -0.78-1.09 ( 15 ) De p ression Stora g e ET ( DS ET ) -0.50-0.61 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -0.28-0.48 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -9.68-10.38 (18) Total Change in Storage, S 5.105.81 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 3.515.70 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -1.110.92 (21) Soil Moisture Increase in the Absence of Rainfall Event0.360.64 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.000.00 (24) Avg. Depth to Water Table (ADTWT)(ft)2.792.52 H y drolo g ic Observations f or S p rin g 2002 4 QtrDerived Hydrologic Fluxes & Storages

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105 Appendix F: (Continued) 5th Quarter Water Budget Components The highest quarterly precipitation vol ume, totaling 27.78 in. (706 mm), was observed in this quarter. Total ET fluctuati on was observed from approximately 11 in. (279 mm) near PS43 to 13.43 in. (341 mm) near PS40. For USF3 and USF1 observed total ET fluctuated approximately within that range Highest infiltration was observed near the stream, PS40, of about 12.68 in. (322 mm). Fo r USF3 and USF1 the observed infiltration range was approximately 3 to 4.77 in. (76 to 121 mm). TRE runoff was second to precipitation for the upland gra ssy region ranging from 22.25 to about 19.62 in (565 to 498 mm) near station PS41. For near the stream total ET was second to precipitation. This behavior was not observed near station USF1. Quite on the contrary TRE near this station behaved similar to that of the upland grassy region with TRE prev ailing as the second dominant component in the water budget. SR E magnitude was almost identical to TRE except for station PS40 where lower value wa s observed. Considerably lower SRE runoff was observed near the stream region. ADTWT fluctuations were observed to range from just above 0.1 ft (3 cm) in the grassland region and dropping to 2.42 ft (0.7 4 m) near the stream. Deeper ADTWT was observed during this period near the stream region. This observation is supported by higher total ET demand, infiltration and considerably lower SRE runoff near the stream region. DS ET was approximately 5.69 to 5.68 in (145 mm) to fluctuating across the transect wells but for near the stream sta tion PS40 negligible va lue was observed. For stations USF3 to USF1 DS ET fluctuations were observed in the range of approximately 7.44 to 6.69 in. (189 to 170 mm).

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106 Appendix F: (Continued) Total Lateral flows were observed to fluctuat e in the range of 0.28 in. (7.1 mm) in the upland area to about 0.38 in. (10 mm) near th e stream. No missing SM data were observed for PS43 and minimal to neglig ible missing data were observe d on isolated basis for the remaining stations. Observed quarterly re sults for all water budget components for PS43 through PS40 and USF3 and USF1 in this qua rter are presented in Tables 11 and 12 respectively.

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107 Appendix F: (Continued) Table 11. Quarterly water budget re sults for summer 2002 for PS43-PS39. Table (11) SUMMER, 2002 (5 Qtr) (in/qtr)PS43PS42PS41PS40PS39 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Event0.050.040.080.070.07 ( 2 ) Total interce p tion ca p ture, EIc 2.421.983.713.293.29 ( 3 ) Saturation Rainfall Excess, SRE 22.2519.5519.623.013.47 ( 4 ) Total Rainfall Excess, TRE 22.3419.7319.6711.8111.86 ( 5 ) Net Runoff16.6415.5313.9911.5611.38 ( 6 ) Infiltration, I 3.026.074.4012.6812.63 ( 7 ) Total Preci p itation, P 27.7827.7827.7827.7827.78 (8) Total Lateral Flow, QGW 0.280.180.250.38-0.03 (9) Total Change in Lateral Flow, QGW 0.28-0.110.070.13-0.41 ( 10 ) Total Observed Total Soil Moisture ET -2.89-6.51-4.34-9.89-10.28 (11) Adjusted TSM ET (with GPET) -2.89-6.51-4.34-9.89-10.28 (12) Difference Between Obs. & Adjusted TSM ET 0.000.000.000.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -1.56-4.10-1.35-9.83-10.20 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -7.02-6.60-8.67-0.31-0.56 ( 15 ) De p ression Stora g e ET ( DS ET ) -5.69-4.20-5.68-0.25-0.48 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -1.33-2.40-3.00-0.06-0.08 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -11.00-12.68-13.73-13.43-14.05 (18) Total Change in Storage, S 0.120.480.075.705.70 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 0.220.860.124.214.30 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -0.71-2.01-2.74-4.21-4.21 (21) Soil Moisture Increase in the Absence of Rainfall Event0.130.420.690.180.17 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.000.000.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.56-0.210.150.26-0.70 (24) Avg. Depth to Water Table (ADTWT)(ft)0.540.650.502.422.11 Hy drolo g ic Observations For Summer 2002 5 QtrDerived Hydrologic Fluxes & Storages

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108 Appendix F: (Continued) Table 12. Quarterly water budget results for summer 2002 for USF3 and USF1. Table (12) SUMMER, 2002 (5 Qtr) (in/qtr)USF3USF1 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Event0.050.05 ( 2 ) Total interce p tion ca p ture, EIc 2.432.43 ( 3 ) Saturation Rainfall Excess, SRE 22.3820.57 ( 4 ) Total Rainfall Excess, TRE 22.3920.58 ( 5 ) Net Runoff14.9513.89 ( 6 ) Infiltration, I 2.964.77 ( 7 ) Total Preci p itation, P 27.7827.78 (8) Total Lateral Flow, QGW 0.000.00 (9) Total Change in Lateral Flow, QGW 0.000.00 ( 10 ) Total Observed Total Soil Moisture ET -2.98-3.96 ( 11 ) Ad j usted TSM ET ( with GPET ) -2.98-3.96 (12) Difference Between Obs. & Adjusted TSM ET 0.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -0.17-0.06 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -10.25-10.58 ( 15 ) De p ression Stora g e ET ( DS ET ) -7.44-6.69 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -2.81-3.90 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -12.85-13.07 (18) Total Change in Storage, S 0.070.87 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 0.140.32 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -1.25-1.06 (21) Soil Moisture Increase in the Absence of Rainfall Event0.150.24 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.000.00 (24) Avg. Depth to Water Table (ADTWT)(ft)0.150.10 Hydrologic Observations for Summer 2002 5 QtrDerived Hydrologic Fluxes & Storages

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109 Appendix F: (Continued) 6th Quarter Water Budget Components Total precipitation for this frontal stor m period was 24.18 in. (614 mm). Seasonally uncharacteristic precipitation volume of 24.18 in. (614 mm) was the co ntributing factor for TRE runoff to be second to pr ecipitation along the transect we lls regardless of the landuse regime. Total ET ranged from 7.55 in. (192 mm) near PS43 and grad ually increased to 11.11 in. (282 mm) near PS40. Higher total ET was observed near stations USF3 and USF1 than grassland station PS43. Total ET was rela tively high across the tr ansect wells for the fall period. This is attributed to SM ava ilability. Observed infiltration ranged from approximately 4.61 in. (117 mm) in the upland and fluctuated to about 7.41 in. (188 mm) near the stream. Relatively shallow ADTWT was observed in the upland but deeper fluctuation was observed near the stream region. For USF-3 and USF-1 the ADTWT was just near land surface. For near the stream region ADTWT was observe d in excess of three feet below land surface. Higher DS ET volume was observed in the upland grassy region, PS43, while negligible volume was observed near the stream. DS ET contributions for USF3 and USF1 was considerably higher than for PS43 making up almost half the total ET for this region. The total Lateral flows were observed to diminish almost progressively from the upland area to near the stream. Periodic missing SM data were observed for stations PS43, USF and USF1 and relatively minimal gaps were periodically observed for the remaining stations excep t station PS40 were negligib le SM data were missing. Observed quarterly results for all wate r budget components for PS43 through PS40 and USF3 and USF1 in this quarter are pres ented in Tables 13 and 14 respectively.

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110 Appendix F: (Continued) Table 13. Quarterly water budget re sults for fall 2002 for PS43-PS39. Table (13) FALL, 2002 (6 Qtr) (in)/qtrPS43PS42PS41PS40PS39 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Even t 0.050.040.080.070.07 ( 2 ) Total interce p tion ca p ture, EIc 1.281.041.961.741.74 ( 3 ) Saturation Rainfall Excess, SRE 17.8215.0015.5912.0612.45 ( 4 ) Total Rainfall Excess, TRE 18.2915.7216.4815.0315.07 ( 5 ) Net Runoff16.3814.2515.4514.9714.90 ( 6 ) Infiltration, I 4.617.425.747.417.37 ( 7 ) Total Preci p itation, P 24.1824.1824.1824.1824.18 (8) Total Lateral Flow, QGW 0.260.160.200.160.01 (9) Total Change in Lateral Flow, QGW 0.26-0.110.04-0.04-0.15 ( 10 ) Total Observed Total Soil Moisture ET -4.36-6.44-6.12-9.31-9.39 (11) Adjusted TSM ET (with GPET) -4.36-6.44-6.12-9.31-9.40 (12) Difference Between Obs. & Adjusted TSM ET 0.000.000.000.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -3.90-5.70-5.48-9.30-9.38 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -2.37-2.21-1.68-0.07-0.19 ( 15 ) De p ression Stora g e ET ( DS ET ) -1.91-1.47-1.04-0.06-0.17 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -0.46-0.74-0.650.00-0.02 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -7.55-8.95-9.12-11.11-11.30 (18) Total Change in Storage, S 1.172.681.291.291.29 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 1.141.551.523.143.10 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -0.51-0.230.020.480.48 (21) Soil Moisture Increase in the Absence of Rainfall Even t 0.120.220.330.290.34 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.000.000.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.53-0.220.09-0.09-0.30 (24) Avg. Depth to Water Table (ADTWT)(ft)1.211.451.363.122.68 Hy drolo g ic Observations f or Fall 2002 6 QtrDerived Hydrologic Fluxes & Storages

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111 Appendix F: (Continued) Table 14. Quarterly water budget re sults for fall 2002 for USF3-USF1. Table (14) FALL, 2002 (6Qtr) (in/qtr)USF3USF1 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Event0.050.05 ( 2 ) Total interce p tion ca p ture, EIc 1.251.25 ( 3 ) Saturation Rainfall Excess, SRE 19.7519.88 ( 4 ) Total Rainfall Excess, TRE 19.7519.88 ( 5 ) Net Runoff14.9015.89 ( 6 ) Infiltration, I 3.183.05 ( 7 ) Total Preci p itation, P 24.1824.18 (8) Total Lateral Flow, QGW 0.000.00 (9) Total Change in Lateral Flow, QGW 0.000.00 ( 10 ) Total Observed Total Soil Moisture ET -3.43-4.29 ( 11 ) Ad j usted TSM ET ( with GPET ) -3.43-4.29 (12) Difference Between Obs. & Adjusted TSM ET 0.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) 0.000.00 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -8.28-8.28 ( 15 ) De p ression Stora g e ET ( DS ET ) -4.85-3.99 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -3.43-4.29 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -9.53-9.53 (18) Total Change in Storage, S 1.84-0.83 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 3.211.48 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) 0.220.11 (21) Soil Moisture Increase in the Absence of Rainfall Event0.961.38 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.000.00 (24) Avg. Depth to Water Table (ADTWT)(ft)0.080.11 H y drolo g ic Observations f or Fall 2002 6 QtrDerived Hydrologic Fluxes & Storages

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112 Appendix F: (Continued) 7th Quarter Water Budget Components In the winter of 2003, 7th quarter, total ET was higher than rainfall across the transect wells. Higher total ET values were obser ved than the previous year, in parts due to higher DS ET contributions. Appreciable vari ability in TSM ET was observed across the transect wells corresponding to variability in land use. ADTWT fluctuated considerably deeper near the stream region than the upland. In USF-3 and USF-1 the ADTWT was considerably closer to and al most near land surface. Total observed precipitation was 6.38 in. ( 162 mm). In this season total ET is the dominant parameter in the hydrologic cycle. Higher TET was observed near the steam than the upland region. Minimal infiltration was obs erved in the upland but highest value was observed near the stream. Slightly higher TRE runoff was observed in the upland than near the stream. Observed TRE for all grassland regimes were similar in volume but slightly higher for USF3 and USF1. SRE trailed be hind TRE in the upland but zero volume was observed near the stream. Minimal negative ru noff values are indicative of no net runoffs. Considerably shallower ADTWT was observed near USF3 and USF1 in comparison with PS43 but deeper fluctuation wa s observed near the stream. DS ET behavior was vary similar to prev ious season, in volume and fluctuations, across the transect wells. For USF3 and USF1 DS ET ranged be tween 3.99 to 5.22 in. (101 to 133 mm) contributing to more than half the volume of total ET. To tal Lateral flows were observed to diminish progressively from the upland area to near the stream. Very minimal SM data were observed missing for PS41 and negligible data were missing for PS43.

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113 Appendix F: (Continued) No missing SM data were observed for PS42 and PS40. Moderate SM data were missing for USF3 and USF1. Observed quarterly re sults for all water budget components for PS43 through PS40 and USF3 and USF1 in this qua rter are presented in Tables 15 and 16 respectively.

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114 Appendix F: (Continued) Table 15. Quarterly water budget resu lts for winter 2003 for PS43-PS39. Table (15) WINTER, 2003 (7 Qtr) (in/qtr)PS43PS42PS41PS40PS39 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Event0.050.040.080.070.07 (2) Total interception capture, EIc 0.870.741.261.131.13 (3) Saturation Rainfall Excess, SRE 3.232.711.730.000.00 ( 4 ) Total Rainfall Excess, TRE 3.242.821.941.051.04 ( 5 ) Net Runoff1.001.26-0.210.920.75 ( 6 ) Infiltration, I 2.272.823.184.204.21 ( 7 ) Total Preci p itation, P 6.386.386.386.386.38 (8) Total Lateral Flow, QGW 0.260.140.29-0.08-0.04 (9) Total Change in Lateral Flow, QGW 0.26-0.120.15-0.370.04 ( 10 ) Total Observed Total Soil Moisture ET -3.53-4.31-4.17-8.66-8.37 ( 11 ) Ad j usted TSM ET ( with GPET ) -3.53-4.31-4.17-8.66-8.37 (12) Difference Between Obs. & Adjusted TSM ET 0.000.000.000.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -2.67-3.86-3.15-8.56-8.19 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -3.11-2.00-3.17-0.23-0.48 (15) Depression Storage ET (DS ET) -2.25-1.56-2.15-0.13-0.29 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -0.87-0.44-1.02-0.10-0.19 (17)Total ET (Adj. TSM ET, DS ET& Ic) -6.65-6.60-7.58-9.93-9.79 (18) Total Change in Storage, S -0.43-0.62-0.18-2.68-2.68 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 0.400.500.211.481.57 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -0.18-0.29-0.31-0.77-0.77 (21) Soil Moisture Increase in the Absence of Rainfall Event0.760.360.860.050.06 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.000.000.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.51-0.240.31-0.740.07 (24) Avg. Depth to Water Table (ADTWT)(ft)1.271.420.983.272.62 Hy drolo g ic Observations f or Winter 2003 7 QtrDerived H y drolo g ic Fluxes & Stora g es

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115 Appendix F: (Continued) Table 16. Quarterly water budget results for winter 2003 for USF3 and USF1. Table (16) WINTER, 2003 (7 Qtr) (in/qtr)USF3USF1 (1) Interception Storage, SIc (in)/Event 0.050.05 ( 2 ) Total interce p tion ca p ture, EIc 0.870.87 ( 3 ) Saturation Rainfall Excess, SRE 3.853.71 ( 4 ) Total Rainfall Excess, TRE 3.953.71 ( 5 ) Net Runoff-0.04-1.50 ( 6 ) Infiltration, I 1.561.80 ( 7 ) Total Preci p itation, P 6.386.38 (8) Total Lateral Flow, QGW 0.000.00 (9) Total Change in Lateral Flow, QGW 0.000.00 ( 10 ) Total Observed Total Soil Moisture ET -1.93-1.73 ( 11 ) Ad j usted TSM ET ( with GPET ) -1.93-1.73 (12) Difference Between Obs. & Adjusted TSM ET 0.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -0.63-0.23 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -5.29-6.72 (15) Depression Storage ET (DS ET) -3.99-5.22 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -1.29-1.50 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -6.79-7.82 (18) Total Change in Storage, S -0.090.51 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 0.050.08 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -0.040.10 (21) Soil Moisture Increase in the Absence of Rainfall Event0.260.41 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.000.01 (24) Avg. Depth to Water Table (ADTWT)(ft)0.680.44 H y drolo g ic Observations f or Winter 2003 7 QtrDerived Hydrologic Fluxes & Storages

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116 Appendix F: (Continued) 8th Quarter Water Budget Components This season is a mixture of partially front al and partially convective storm pattern. On the average, observed precipitation totaling 21.82 in. (554 mm) is rather typical for the region and the season. Total ET for this period of active plant growing season fluctuated in the range of 12.2 to 15.82 in. (310 to 402 mm) in the upland area to 13.58 in. (345 mm) near the stream at PS40. Highest total ET wa s observed near PS41. For US3 and USF1 the observed total ET was 10.52 to 12.31 in. (267 to 313 mm) respectively. The highest total ET magnitude was observed in the spring quart er regardless of the land use cover. For PS43 through PS40 transect wells, ET was unque stionably the second dominant component in the hydrologic cycle with distinct variabil ity to land use across the transect wells. Excluding grassland (PS43), observed inf iltration ranked as the third component along the transect wells. High TRE runoff vol ume was observed in the grassland zones while considerably lesser fluctuations were observed in forested wetland regions. Observed SRE fluctuations were similar to TRE but le sser in volume particularly near the stream region. A gradual decline in ADTWT was observe d from the grassland to near the stream region were deepest ADTWT was observed. Despite significant precipitation volume ADTWT was deeper in the upla nd than the winter quarter. Typical DS ET behavior was observed across most transect wells, higher in upland grassy areas and diminishing towards the stream region, except USF-1 were highest volume was observed. Total Lateral flows were observed to diminish progressively from the upland area to near the stream region. Very minimal SM data were missing for PS43 and PS40. Some SM data were observed missing for USF3 and USF1.

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117 Appendix F: (Continued) Observed quarterly results for all wate r budget components for PS43 through PS40 and USF3 and USF1 in this quarter are pres ented in Tables 17 and 18 respectively.

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118 Appendix F: (Continued) Table 17. Quarterly water budget re sults for spring 2003 for PS43-PS39. Table (17) SPRING, 2003 (8 Qtr) (in/qtr)PS43PS42PS41PS40PS39 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Event0.050.040.080.070.07 (2) Total interception capture, EIc 1.461.192.241.991.99 (3) Saturation Rainfall Excess, SRE 11.037.667.154.715.88 ( 4 ) Total Rainfall Excess, TRE 12.089.288.267.527.52 ( 5 ) Net Runoff10.589.147.617.397.43 ( 6 ) Infiltration, I 8.2811.3511.3212.3112.31 ( 7 ) Total Preci p itation, P 21.8221.8221.8221.8221.82 (8) Total Lateral Flow, QGW 0.260.140.12-0.12-0.04 (9) Total Change in Lateral Flow, QGW 0.26-0.12-0.02-0.230.08 ( 10 ) Total Observed Total Soil Moisture ET -9.23-13.64-12.93-11.46-11.24 ( 11 ) Ad j usted TSM ET ( with GPET ) -9.23-13.64-12.93-11.46-11.24 (12) Difference Between Obs. & Adjusted TSM ET 0.000.000.000.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -8.82-13.43-12.55-11.35-11.14 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -1.92-0.35-1.03-0.24-0.18 (15) Depression Storage ET (DS ET) -1.51-0.14-0.65-0.13-0.09 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -0.41-0.21-0.38-0.11-0.10 (17)Total ET (Adj. TSM ET, DS ET& Ic) -12.20-14.98-15.82-13.58-13.31 (18) Total Change in Storage, S 0.000.510.032.712.71 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 1.513.892.732.222.30 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -0.71-1.74-2.66-2.36-2.36 (21) Soil Moisture Increase in the Absence of Rainfall Event0.841.961.221.101.20 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.731.631.010.931.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.51-0.24-0.04-0.470.16 (24) Avg. Depth to Water Table (ADTWT)(ft)1.722.302.363.622.83 Hy drolo g ic Observations f or S p rin g 2003 8 QtrDerived H y drolo g ic Fluxes & Stora g es

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119 Appendix F: (Continued) Table 18. Quarterly water budget results for spring 2003 for USF3 and USF1. Table (18) SPRING, 2003 (8 Qtr) (in/qtr)USF-3USF-1 (1) Interception Storage, SIc (in)/Event 0.050.05 ( 2 ) Total interce p tion ca p ture, EIc 1.461.46 ( 3 ) Saturation Rainfall Excess, SRE 11.0811.71 ( 4 ) Total Rainfall Excess, TRE 13.4412.31 ( 5 ) Net Runoff11.319.44 ( 6 ) Infiltration, I 6.968.09 ( 7 ) Total Preci p itation, P 21.8621.86 (8) Total Lateral Flow, QGW 0.000.00 (9) Total Change in Lateral Flow, QGW 0.000.00 ( 10 ) Total Observed Total Soil Moisture ET -6.94-7.98 ( 11 ) Ad j usted TSM ET ( with GPET ) -6.94-7.98 (12) Difference Between Obs. & Adjusted TSM ET 0.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -5.84-5.11 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -3.23-5.74 (15) Depression Storage ET (DS ET) -2.12-2.87 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -1.10-2.87 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -10.52-12.31 (18) Total Change in Storage, S 1.060.40 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 1.633.43 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -1.19-1.10 (21) Soil Moisture Increase in the Absence of Rainfall Event0.210.00 (22) Soil Moisture Increase When Rainfall Event Not Recorded1.031.62 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.000.00 (24) Avg. Depth to Water Table (ADTWT)(ft)1.270.97 H y drolo g ic Observations f or S p rin g 2003 8 QtrDerived Hydrologic Fluxes & Storages

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120 Appendix F: (Continued) 9th Quarter Water Budget Components Precipitation amount for this convective period was 21.58 in. (548 mm). Total ET fluctuated in the range of 11.38 to 11.84 in (289 to 301 mm) in the upland grassland areas while progressively increasing to about 15.47 in. (393 mm) near the stream region PS40. Observed infiltration was considerably higher near the stream than the upland grassy region. TRE runoff was the 2nd largest observed component in the upland grassy region. Close to and near the stream region lower TRE runoff was observed. Total ET was the 2nd largest observed component of the hydrologic cycle near the stream region. Observed infiltration behaved in a revers e pattern to TRE, in that, low infiltration values were observed in the upland grassland areas while fo r near the stream region higher infiltration were observed. SRE runoff tra iled just behind TRE runoff al ong the transect wells except for nears the stream region were considerab ly lower volume were observed. ADTWT for the upland grassland region was consistently at or near land surface while deepest ADTWT is observed only near the stre am. For forested regions fl uctuations were deeper. The highest DS ET is observed in this qua rter particularly in the upland while diminishing toward the stream where negligib le volume was observed. Total Lateral flows were observed to diminish progressively from the upland area to near the stream. Minimal SM data were missing for this quarter along a ll stations except USF1 were moderate SM data were observed missing. Observed quarter ly results for all water budget components for PS43 through PS40 and USF3 and USF1 in this quarter are presented in Tables 19 and 20 respectively.

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121 Appendix F: (Continued) Table 19. Quarterly water budget re sults for summer 2003 for PS43-PS39. Table (19) SUMMER, 2003 (9 Qtr) (in/qtr)PS43PS42PS41PS40PS39 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Even t 0.050.040.080.070.07 (2) Total interception capture, EIc 2.281.873.483.083.08 (3) Saturation Rainfall Excess, SRE 15.6310.6112.033.923.95 ( 4 ) Total Rainfall Excess, TRE 15.8111.5813.048.538.49 ( 5 ) Net Runoff10.249.909.628.538.47 ( 6 ) Infiltration, I 3.498.135.069.9710.01 ( 7 ) Total Preci p itation, P 21.5821.5821.5821.5821.58 (8) Total Lateral Flow, QGW 0.310.150.250.00-0.04 (9) Total Change in Lateral Flow, QGW 0.31-0.160.10-0.25-0.04 ( 10 ) Total Observed Total Soil Moisture ET -3.53-8.51-5.13-12.39-12.31 ( 11 ) Ad j usted TSM ET ( with GPET ) -3.53-8.51-5.13-12.39-12.31 (12) Difference Between Obs. & Adjusted TSM ET 0.000.000.000.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -1.78-7.71-3.77-12.39-12.26 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -7.32-2.47-4.780.00-0.06 (15) Depression Storage ET (DS ET) -5.57-1.68-3.420.00-0.02 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -1.75-0.80-1.360.00-0.04 (17)Total ET (Adj. TSM ET, DS ET& Ic) -11.38-12.06-12.03-15.47-15.41 (18) Total Change in Storage, S 0.110.700.06-2.14-2.15 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 0.641.790.841.671.71 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) 1.042.851.302.802.79 (21) Soil Moisture Increase in the Absence of Rainfall Event0.220.780.640.250.25 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.180.260.130.180.18 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.61-0.310.20-0.50-0.08 (24) Avg. Depth to Water Table (ADTWT)(ft)0.571.250.872.912.30 Hy drolo g ic Observations f or Summer 2003 9 QtrDerived H y drolo g ic Fluxes & Stora g es

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122 Appendix F: (Continued) Table 20. Annual water budget results for summer 2003 for USF3 and USF1. Table (20) SUMMER, 2003 (9 Qtr) (in/qtr)USF3USF1 (1) Interception Storage, SIc (in)/Event 0.050.05 ( 2 ) Total interce p tion ca p ture, EIc 2.282.28 ( 3 ) Saturation Rainfall Excess, SRE 16.1615.38 ( 4 ) Total Rainfall Excess, TRE 16.3915.39 ( 5 ) Net Runoff10.989.89 ( 6 ) Infiltration, I 2.913.91 ( 7 ) Total Preci p itation, P 21.5821.58 (8) Total Lateral Flow, QGW 0.000.00 (9) Total Change in Lateral Flow, QGW 0.000.00 ( 10 ) Total Observed Total Soil Moisture ET -2.90-4.07 ( 11 ) Ad j usted TSM ET ( with GPET ) -2.90-4.07 (12) Difference Between Obs. & Adjusted TSM ET 0.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -1.17-1.01 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -7.13-8.55 (15) Depression Storage ET (DS ET) -5.40-5.49 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -1.72-3.06 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -10.58-11.84 (18) Total Change in Storage, S 0.110.05 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 0.140.59 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) 0.801.27 (21) Soil Moisture Increase in the Absence of Rainfall Event0.380.35 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.130.19 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.020.00 (24) Avg. Depth to Water Table (ADTWT)(ft)0.610.22 H y drolo g ic Observations f or Summer 2003 9 QtrDerived Hydrologic Fluxes & Storages

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123 Appendix F: (Continued) 10th Quarter Water Budget Components Precipitation for this frontal storm period was measur ed at 3.35 in. (85 mm). Total ET for this dry and presumably low active plant growing season fluctuated in the ranged of bout 6.1 in. (155 mm) in the upland area while a relatively uniform volume with slight fluctuations above 9 in. (229 mm) were observed for the remaining stations. Lesser total ET was observed near stations USF3 and USF1 to a maximum of 4.95 in. (126 mm). In this quarter total ET was the dominant component in the hydrologic cycle regardless of the landuse regime. Relatively unifo rm infiltration was observed across the transect wells. Observed infiltration was the third to precipita tion. Minimal to negligible TRE runoff were observed across the transect wells. Zero SRE were observed regardless of the landuse type. Relatively deep ADTWT was observed in the upland grassland while gradually declining deeper toward the stream. In 2003, ADTWT was the deepest across th e transect wells in this quarter. DS ET contributi ons were minimal to negligib le across transects wells and none was observed near the stream region. Very similar behavioral characteristics of the upland region were observed near USF-3 and USF-1. Lateral flows fluctuated from the upland wh ile steadily declining to negative values near the stream region. Some SM data were periodically missing near for stations PS42 and USF3 but moderate data were missing for USF1. Negligible SM data were missing for station PS40 while no missing SM data we re observed for stations PS43 and PS41. Observed quarterly results for all wate r budget components for PS43 through PS40 and USF3 and USF1 in this quarter are pres ented in Tables 21 and 22 respectively.

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124 Appendix F: (Continued) Table 21. Quarterly water budget re sults for fall 2003 for PS43-PS39. Table (21) FALL, 2003 (10 Qtr) (in/qtr)PS43PS42PS41PS40PS39 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Even t 0.050.040.080.070.07 (2) Total interception capture, EIc 0.430.370.590.540.54 (3) Saturation Rainfall Excess, SRE 0.000.000.000.000.00 ( 4 ) Total Rainfall Excess, TRE 0.390.090.080.120.12 ( 5 ) Net Runof f 0.030.020.000.120.12 ( 6 ) Infiltration, I 2.532.892.682.692.69 ( 7 ) Total Preci p itation, P 3.353.353.353.353.35 (8) Total Lateral Flow, QGW 0.220.120.08-0.24-0.06 (9) Total Change in Lateral Flow, QGW 0.22-0.10-0.04-0.320.17 ( 10 ) Total Observed Total Soil Moisture ET -5.34-8.83-8.65-8.51-8.08 ( 11 ) Ad j usted TSM ET ( with GPET ) -5.34-8.83-8.65-8.51-8.08 (12) Difference Between Obs. & Adjusted TSM ET 0.000.000.000.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -5.24-8.78-8.56-8.51-8.08 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -0.46-0.11-0.170.000.00 (15) Depression Storage ET (DS ET) -0.36-0.07-0.080.000.00 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -0.11-0.05-0.090.000.00 (17)Total ET (Adj. TSM ET, DS ET& Ic) -6.13-9.27-9.32-9.05-8.62 (18) Total Change in Storage, S -2.65-4.75-5.48-4.75-4.75 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 0.161.320.310.660.69 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -0.370.25-0.372.392.39 (21) Soil Moisture Increase in the Absence of Rainfall Even t 0.310.120.300.110.13 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.000.000.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.530.160.09-0.610.37 (24) Avg. Depth to Water Table (ADTWT)(ft)2.773.113.194.263.39 Hy drolo g ic Observations f or Fall 2003 10 QtrDerived H y drolo g ic Fluxes & Stora g es

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125 Appendix F: (Continued) Table 22. Annual water budget results for fall 2003 for USF3 and USF1. Table (22) FALL, 2003 (10 Qtr) (in/qtr)USF3USF1 (1) Interception Storage, SIc (in)/Event 0.050.05 ( 2 ) Total interce p tion ca p ture, EIc 0.430.43 ( 3 ) Saturation Rainfall Excess, SRE 0.000.00 ( 4 ) Total Rainfall Excess, TRE 0.140.06 ( 5 ) Net Runoff-0.70-1.07 ( 6 ) Infiltration, I 2.782.86 ( 7 ) Total Preci p itation, P 3.353.35 (8) Total Lateral Flow, QGW 0.000.00 (9) Total Change in Lateral Flow, QGW 0.000.00 ( 10 ) Total Observed Total Soil Moisture ET -4.43-4.25 ( 11 ) Ad j usted TSM ET ( with GPET ) -4.43-4.25 (12) Difference Between Obs. & Adjusted TSM ET 0.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -4.05-3.83 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -1.22-1.55 (15) Depression Storage ET (DS ET) -0.84-1.13 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -0.38-0.42 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -4.85-4.95 (18) Total Change in Storage, S -1.291.58 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 0.692.47 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -0.48-0.16 (21) Soil Moisture Increase in the Absence of Rainfall Event0.631.75 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.000.00 (24) Avg. Depth to Water Table (ADTWT)(ft)2.081.84 H y drolo g ic Observations f or Fall 2003 10 QtrDerived Hydrologic Fluxes & Storages

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126 Appendix F: (Continued) 11th Quarter Water Budget Components In the winter of 2004, observed precipita tion measured near 9.15 in. (232 mm). Total ET for this relatively dry and minimal pl ant growing season fluctuated in the ranged of about 7 in. (178 mm) in the upland grassland areas and fluctuating to about 8.8 in. (224 mm) near the stream region. Total ET was the second dominant component regardless of the landuse regime. Observed infiltration was lower in magnitude for the grassland than near the stream. TRE runoff were observed acr oss the transect well s ranging higher in magnitudes in the upland while gradually decr easing to minimal values near the stream. Higher TRE was observed near USF3 and US F1. SRE runoff trailed behind TRE runoff across the transect wells. ADTWT was obser ved shallower in the upland with gradual decline toward the stream where the deepes t ADTWT was observed. Observed DS ET was minimal across the transect wells except for near the steam where zero magnitude was observed. For USF-3 and USF-1 some of the hi ghest DS ET was observed at both stations. This was believed consistent with the shallowest ADTWT observed at these stations. Lateral flows fluctuated from the upland wh ile steadily declining and fluctuating to negative values near the stream region. Some SM data were observe d missing for stations PS42, PS41 and PS40 and USF1. No SM data were observed missing for stations PS43 or USF3. Observed quarterly results for all wa ter budget components for PS43 through PS40 and USF3 and USF1 in this quarter are pr esented in Tables 23 and 24 respectively.

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127 Appendix F: (Continued) Table 23. Quarterly water budget resu lts for winter 2004 for PS43-PS39. Table (23) WINTER, 2004 (11 Qtr) (in/qtr)PS43PS42PS41PS40PS39 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Event0.050.040.080.070.07 (2) Total interception capture, EIc 0.690.571.010.910.91 (3) Saturation Rainfall Excess, SRE 2.791.961.350.000.02 ( 4 ) Total Rainfall Excess, TRE 3.542.562.120.780.76 ( 5 ) Net Runoff2.551.491.010.780.75 ( 6 ) Infiltration, I 4.926.026.027.467.48 ( 7 ) Total Preci p itation, P 9.159.159.159.159.15 (8) Total Lateral Flow, QGW 0.230.150.17-0.16-0.05 (9) Total Change in Lateral Flow, QGW 0.23-0.080.02-0.330.11 ( 10 ) Total Observed Total Soil Moisture ET -5.82-5.31-4.50-8.79-8.71 ( 11 ) Ad j usted TSM ET ( with GPET ) -5.26-5.06-4.32-7.88-7.45 (12) Difference Between Obs. & Adjusted TSM ET -0.56-0.25-0.19-0.91-1.26 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -4.62-4.86-4.09-7.88-7.37 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -1.63-1.27-1.340.00-0.09 ( 15 ) De p ression Stora g e ET ( DS ET ) -0.99-1.07-1.110.00-0.01 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -0.64-0.20-0.230.00-0.08 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -6.94-6.70-6.44-8.79-8.37 (18) Total Change in Storage, S 2.414.594.802.852.88 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 1.673.152.943.723.77 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) 0.170.060.60-0.56-0.56 (21) Soil Moisture Increase in the Absence of Rainfall Even t 1.880.640.370.120.45 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.000.000.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.47-0.170.05-0.660.22 (24) Avg. Depth to Water Table (ADTWT)(ft)1.902.002.173.893.12 H y drolo g ic Observations f or Winter 2004 11 QtrDerived Hydrologic Fluxes & Storages

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128 Appendix F: (Continued) Table 24. Annual water budget results fo rm winter 2004 for USF3 and USF1. Table (24) WINTER, 2004 (11 Qtr) (in/qtr)USF3USF1 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Event0.050.05 ( 2 ) Total interce p tion ca p ture, EIc 0.690.69 ( 3 ) Saturation Rainfall Excess, SRE 5.051.74 ( 4 ) Total Rainfall Excess, TRE 6.024.47 ( 5 ) Net Runoff1.880.90 ( 6 ) Infiltration, I 2.443.99 ( 7 ) Total Preci p itation, P 9.159.15 (8) Total Lateral Flow, QGW 0.000.00 (9) Total Change in Lateral Flow, QGW 0.000.00 ( 10 ) Total Observed Total Soil Moisture ET -1.99-3.62 ( 11 ) Ad j usted TSM ET ( with GPET ) -1.98-2.64 (12) Difference Between Obs. & Adjusted TSM ET -0.01-0.98 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -1.33-1.62 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -4.80-4.59 ( 15 ) De p ression Stora g e ET ( DS ET ) -4.14-3.57 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -0.66-1.02 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -6.82-6.90 (18) Total Change in Storage, S 1.022.56 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 0.391.03 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -0.130.95 (21) Soil Moisture Increase in the Absence of Rainfall Event0.181.16 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.000.00 (24) Avg. Depth to Water Table (ADTWT)(ft)1.101.17 H y drolo g ic Observations f or Winter 2004 11 QtrDerived Hydrologic Fluxes & Storages

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129 Appendix F: (Continued) 12th Quarter Water Budget Components Precipitation for this partially frontal storm period was m easured at 10.62 in. (270 mm). This is lower than typical magnitude for this season. Total ET for this highly active plant growing season fluctuated in excess of 10.8 in. (274 mm) in the upland area while gradually increasing to about 14.6 in. (371 mm) near the st ream region. Total ET near stations USF3 and USF1 fluctu ated in the range of almost 7 to 14.9 in. (178 to 378 mm) respectively. With the excepti on of upland regions total ET wa s the dominant component of the water budget in this quarter. Relatively uniform infiltration volume was observed across the transect wells regardless of the landuse. Minimal TRE r unoff and negligible SRE runoff were observed across the transect wells re gardless of the landuse type. ADTWT was the deepest in this quarter while gr adually declining toward the stream region. Zero DS ET was observed across the transect wells and minimal values were observed near USF3 and USF1. Lateral flows fluctuated from the upland while steadily declining to zero near the stream region. Moderate SM data were observed missing periodically for PS43 and USF3 while minimal SM data was observed missing for PS42, PS41 and USF1. No missing SM data were observed for station PS40. Observed quarterly results fo r all water budget components for PS43 through PS40 and USF3 and USF1 in th is quarter are presen ted in Tables 25 and 26 respectively.

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130 Appendix F: (Continued) Table 25. Quarterly water budget re sults for spring 2004 for PS43-PS39. Table (25) SPRING, 2004 (12 Qtr) (in/qtr)PS43PS42PS41PS40PS39 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Even t 0.050.040.080.070.07 (2) Total interception capture, EIc 0.950.771.441.291.29 (3) Saturation Rainfall Excess, SRE 0.020.040.000.000.00 ( 4 ) Total Rainfall Excess, TRE 0.881.301.520.590.60 ( 5 ) Net Runoff0.881.301.520.590.60 ( 6 ) Infiltration, I 8.798.557.668.748.73 ( 7 ) Total Preci p itation, P 10.6210.6210.6210.6210.62 (8) Total Lateral Flow, QGW 0.170.110.080.00-0.06 (9) Total Change in Lateral Flow, QGW 0.17-0.05-0.03-0.09-0.05 ( 10 ) Total Observed Total Soil Moisture ET -9.87-14.56-12.90-13.32-13.24 ( 11 ) Ad j usted TSM ET ( with GPET ) -9.87-14.56-12.90-13.32-13.24 (12) Difference Between Obs. & Adjusted TSM ET 0.000.000.000.000.00 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -9.87-14.56-12.90-13.32-13.24 (14) Shallow Water TSM ET+ ET from DS (DTWT 1 FT BLS)0.000.000.000.000.00 ( 15 ) De p ression Stora g e ET ( DS ET ) 0.000.000.000.000.00 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) 0.000.000.000.000.00 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -10.82-15.33-14.34-14.61-14.53 (18) Total Change in Storage, S 2.91-3.79-3.13-2.64-2.64 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 3.603.232.283.193.19 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -0.46-0.79-1.68-4.12-4.12 (21) Soil Moisture Increase in the Absence of Rainfall Even t 0.850.040.270.010.01 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.000.000.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.33-0.11-0.06-0.18-0.11 (24) Avg. Depth to Water Table (ADTWT)(ft)3.613.363.564.774.17 H y drolo g ic Observations f or S p rin g 2004 12 QtrDerived Hydrologic Fluxes & Storages

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131 Appendix F: (Continued) Table 26. Quarterly water budget results for spring 2004 for USF3 and USF1. Table (26) SPRING, 2004 (12 Qtr) (in/qtr)USF3USF1 ( 1 ) Interce p tion Stora g e, SIc ( in ) /Event0.050.05 ( 2 ) Total interce p tion ca p ture, EIc 0.950.95 ( 3 ) Saturation Rainfall Excess, SRE 0.030.17 (4) Total Rainfall Excess, TRE 1.151.12 ( 5 ) Net Runoff0.28-0.19 ( 6 ) Infiltration, I 8.528.55 ( 7 ) Total Preci p itation, P 10.6210.62 (8) Total Lateral Flow, QGW 0.000.00 (9) Total Change in Lateral Flow, QGW 0.000.00 ( 10 ) Total Observed Total Soil Moisture ET -5.21-12.79 ( 11 ) Ad j usted TSM ET ( with GPET ) -5.17-12.63 (12) Difference Between Obs. & Adjusted TSM ET -0.04-0.16 (13) Deep Water TSM ET(DTWT > 1 FT BLS) -4.68-11.93 (14) Shallow Water TSM ET+ ET from DS ( DTWT 1 FT BLS ) -1.37-2.01 ( 15 ) De p ression Stora g e ET ( DS ET ) -0.87-1.31 (16) Shallow Water TSM ETET from DS (DTWT 1 FT BLS ) -0.50-0.70 ( 17 ) Total ET ( Ad j TSM ET, DS ET& Ic ) -6.99-14.89 (18) Total Change in Storage, S 6.65-0.29 (19) Upstream Runoff Infiltration (Observed Infiltration Several Hours After a Rainfall Event) 3.003.93 (20) Depression Storage Infiltration/ET: Increase/Decrease Observed from Two Hours after a Rainfall Event up to 24 hrs or the Next Event, Whichever Shorter (Using Hourly TSM Integration) -0.12-0.99 (21) Soil Moisture Increase in the Absence of Rainfall Event0.350.03 (22) Soil Moisture Increase When Rainfall Event Not Recorded0.000.00 (23) Balance (B) ( I+ Q+ET ( SM & S y) S+19+21+22 ) 0.000.00 (24) Avg. Depth to Water Table (ADTWT)(ft)1.931.80 H y drolo g ic Observations f or S p rin g 2004 12 QtrDerived Hydrologic Fluxes & Storages

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132 Appendix G: Comparison of Observed Hourly SM+DS ET with Site PET The hourly, monthly and quarterly comp arison between site PET and observed and adjusted hourly, monthly an d quarterly SM+DS ET, for gr assland (PS-43) and Forest (PS-40), in 2002 and 2003 are s hown in Figures 45 through 56. Recall, J&H model were utilized using FAWN (ONA) site solar radi ation and temperature data to compute J&H PET. A pan factor of 0.7 was employed uni formly across the board and adjusted for research site rainfall records and intercepti on capture for simulation of site PET. Results are presented in SI units. Results in 2002The hourly site PET do minates the profile for the winter and spring period for the grassland cover in 2002. The gap is not considerably during the wet period for the same year. For the monthly and quarterly scale the domination of the site PET over TSM+DS ET is prevalent for the gra ssland except for the months of November and December where considerably closer range was observed. The highest site PET was observed in the month of May and the highest TSM+DS ET were almost equal in May and July. Noteworthy that the DS ET contri bution is considerable during wet period. Lowest TSM+DS ET demand is observed in winter season but Lowest Site PET is observed in December driven by unusual rainfall events. On quarterly basis is gap is the narrowest toward the end of the year believe d to be associated with uncharacteristic rainfall events.

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133 Appendix G: (Continued) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.41 / 1 / 2 0 0 2 2/ 1 /2002 3/1/2002 4 / 1 /2002 5/ 1 /2002 6 / 1 / 2 0 0 2 7 / 1 / 2 0 0 2 8/1/2 0 0 2 9 / 1 / 2 0 0 2 10/1/2002 11/1/ 2 0 0 2 1 2 / 1 / 2002HoursHourly Site PET and SM+DS ET (mm) Site PET O&A TSM+DS ET-PS43 Figure 45. Hourly site potential ET vs. obser ved and adjusted total soil moisture and depression storage ET for grassl and covers (PS43) in 2002. 0 20 40 60 80 100 120 140 160 180 123456789101112 MonthsSite PET and SM + DS ET (mm) Site PET O&A TSM+DS ET-PS43 Figure 46. Monthly site potenti al ET vs. observed and adjusted total soil moisture and depression storage ET for gr assland (PS43) in 2002.

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134 Appendix G: (Continued) 0 50 100 150 200 250 300 350 400 450 W02SP02S02F02 QuartersSite PET and SM + DS ET (mm) Site PET O&A TSM+DS ET-PS43 Figure 47. Quarterly site potenti al ET vs. observed and adjust ed total soil moisture and depression storage ET for gr assland (PS43) in 2002. For forested wetland the hourly site P ET dominates the TSM+DS ET profile during the winter and summer period. The magnitude of site PET and TSM+DS ET is nearly the same for the remainder of the year. The observed beha vior during the fall season is attributed to signi ficant and unusual rainfall events resulting in higher TSM ET. The highest TSM+DS ET is observed in Augu st. On quarterly basis the domination of site PET is prevalent except for the fall s eason where the magnitude of TSM+DS ET is higher than site PET. The peak quarterly magnitudes were ob served in the spring season. Lowest TSM+DS ET demand is obs erved in winter season.

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135 Appendix G: (Continued) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.41 / 1/2002 2 / 1/2002 3 / 1/2002 4 / 1/200 2 5/1/2002 6 / 1/2002 7 / 1/2 0 0 2 8 / 1 / 2 0 0 2 9 / 1/2002 1 0 / 1 / 2 0 0 2 1 1/1/2002 1 2 / 1 / 2 0 0 2HoursHourly Site PET and SM+DS ET (mm) Site PET O&A TSM+DS ET-PS40 Figure 48. Hourly site potential ET vs. obser ved and adjusted total soil moisture and depression storage ET for fore st wetland (PS40) in 2002. 0 20 40 60 80 100 120 140 160 180 123456789101112 MonthsSite PET and SM+DS ET (mm) Site PET O&A TSM+DS ET-PS40 Figure 49. Monthly site potenti al ET vs. observed and adjusted total soil moisture and depression storage ET for forest (PS40) in 2002.

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136 Appendix G: (Continued) 0 50 100 150 200 250 300 350 400 450 W02SP02S02F02 QuartersSite PET and SM+DS ET (mm) Site PET O&A TSM+DS ET-PS40 Figure 50. Quarterly site potenti al ET vs. observed and adjust ed total soil moisture and depression storage ET for forest (PS40) in 2002. Results in 2003The hourly s ite PET dominates the profile fo r the grassland cover during early winter and the normal wet season in 2003. This observed behavior is attributed to SM availability during theses periods. Is olated higher values for TSM+DS ET were attributed to the use of hourly SMD directly following a rain fall event. On monthly basis the highest site PET and TSM+DS ET coinci ded in the month of May. The lowest monthly volumes of the two ET components are observed in December and February respectively. On quarterly basis the dominati on of site PET is prevalent for each quarter although the gaps are considerably narrower during the dry period.

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137 Appendix G: (Continued) The peak quarterly volume was observed in the spring season wh ile relatively equal magnitudes were observed in the winter a nd fall of 2003 for the grassland cover. 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.41/1/2003 2/1 /2 00 3 3/1/2003 4 / 1 /2 00 3 5/1/2003 6 / 1 /2 00 3 7/1/2003 8 / 1 /2 0 03 9/1/2003 1 0 / 1 /2 00 3 11/1/2003 1 2 / 1 /2 00 3HoursHourly Site PET and SM+DS ET (mm) Site PET O&A. TSM + DS ET-PS43 Figure 51. Hourly site potential ET vs. obser ved and adjusted total soil moisture and depression storage ET for gr assland (PS-43) in 2003.

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138 Appendix G: (Continued) 0 20 40 60 80 100 120 140 160 180 123456789101112 MonthsSite PET and SM+DS ET (mm) Site PET TSM + DS ET, PS43 Figure 52. Monthly site potenti al ET vs. observed and adjusted total soil moisture and depression storage ET for gr assland (PS43) in 2003. 0 50 100 150 200 250 300 350 400 450 W03SP03S03F03 QuartersSite PET and SM + DS ET (mm) Site PET TSM+DS ET,PS43 Figure 53. Quarterly site potenti al ET vs. observed and adjust ed total soil moisture and depression storage ET for gr assland (PS43) in 2003.

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139 Appendix G: (Continued) For forested wetland the gap between TSM+DS ET and site PET is uniformly narrow during 2003 period. Narrowest gap be tween the hourly TSM+DS ET and site PET is observed in the winter and the fall pe riods. Isolated higher values of TSM+ DS ET are attributed to the hourly fluctuations of SMD. Hi ghest monthly site PET is observed in May while for TSM+DS ET the hi ghest volume is observed in July. Higher TSM+DS ET in January is the re sidual effect of the significa nt rainfall events observed in the last days in December of 2002 resulting in wet antecedent SM condition and higher TSM+DS ET. On quarterly basis the domina tion of site PET is prevalent during the growing season and the wet period. Simulated site PET and TSM+DS ET matched closely in the winter and the fall period. 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.41/1 /200 3 2/1 / 2003 3/1 / 2003 4/1 / 2003 5/1 /200 3 6/1 /200 3 7/1 /2 003 8/1 /2 003 9 /1 /2003 10/1/2 0 03 11 /1/20 03 12 /1/20 03HoursHourly Site PET and SM+DS ET (mm) Site PET O&A TSM+DS ET-PS40 Figure 54. Hourly site potential ET vs. obser ved and adjusted total soil moisture and depression storage ET for fore sted wetland (PS-40) in 2003.

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140 Appendix G: (Continued) 0 20 40 60 80 100 120 140 160 180 123456789101112 MonthsSite PET and SM+DS ET (mm) Site PET O &A TSM+DS ET-PS40 Figure 55. Monthly site potenti al ET vs. observed and adjusted total soil moisture and depression storage ET for fore sted wetland (PS40) in 2003. 0 50 100 150 200 250 300 350 400 450 W03SP03S03F03 QuartersSite PET and SM+DS ET (mm) Site PET O&A TSM+DS ET-PS40 Figure 56. Quarterly site potenti al ET vs. observed and adjust ed total soil moisture and depression storage ET for fore sted wetland (PS40) in 2003.

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141 Appendix H: Sample of Observed Quarterly SM ET with Adjusted SM ET and GPET for Grass and Forested Land in 2003 Comparison of observed quarterly estim ated TSM ET, Adjusted SM ET and GPET for grassland station (PS-43) and fore sted wetland (PS-42) 2003 are presented in Figures 57 and 58 respectively. Recall for ET estimation all negative (I-ET) cell values in the numerical model were separated from the positive cell values by writing a simple algorithm in the model, for each time step (dt), and placed in a sepa rate column corresponding to each station and averaged over a 12 hour period. Hourly ET we re adjusted using the observed ET values from the SM data, while filter ing the data such that observe d ET values smaller than the minimum GPET values with central moving in 24 hour period with a 1.1 multiplier was used with GPET value averaged over 3 hour period as a substitute. It was explained earlier how GPET data were obtained. In summer of 2003, 9th quarter, GPET de picted in Figure 57 dominates the profile for grassland cover. Isolated adju stments are observed fo r the grassland cover associated with observed TS M ET. The difference between the GPET and the observed and adjusted TSM ET may appear low. Recall the influence of DS ET is not included here. In the summer of 2003, 9th quarter, GPET also dominates the profile for the forested wetland region. Gr aph for this landuse cover is depicted in Figure 58. TSM ET adjustments are more frequently observed for the forested wetland. Considerably narrowest gap between observed and adjust ed TSM ET and GPET is observed for the

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142 Appendix H: (Continued) forested wetland region than grassland cover, in respons e to higher ET demand and in direct response to landuse change. -0.06 -0.05 -0.04 -0.03 -0.02 -0.01 0.00 28-Jun-0318-Jul-037-Aug-0327-Aug-0316-Sep-036-Oct-03 HourlyET (in) GPET Obs. SM ET-PS43 Adj. SM ET-PS43 Figure 57. Quarterly ground pot ential ET (GPET) with observed and adjusted soil moisture and depression storage ET for grassland (PS43) summer 2003.

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143 Appendix H: (Continued) -0.06 -0.05 -0.04 -0.03 -0.02 -0.01 0.00 28-Jun-0318-Jul-037-Aug-0327-Aug-0316-Sep-036-Oct-03 HourlyET (in) GPET Obs. SM ET-PS42 Adj. SM ET-PS42 Figure 58. Quarterly ground pot ential ET (GPET) vs. observed and adjusted total soil moisture and depression storage ET for forested (PS42) in summer 2003.

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ABOUT THE AUTHOR Mandana Seyed Rahgozar was born in 1959 in Teharn, Iran. On February 23, 1977 she entered United States soil. She attended Rainsville State Jr. College in Rainsville, Alabama from 1977 to 1979 a nd obtained an AA de gree. She attended Alabama A&M University in Huntsville, Alabama from 1979 to 1981 and obtained the bachelor’s degree in Civil E ngineering. She immediately m oved to Tampa, Florida. After trying the private sector for a s hort while she was employed by Pinellas County Schools since 1982 as the district’s Civil Engineer. In 1991 she obtained her licen se/registration from Flor ida Board of Professional Engineers in the state of Florid a. Shortly after sh e enrolled at the University of South Florida in Tampa, Florida in the Civil and Environmental Engineering Department where she obtained her Master’s in spring of 1994 and immediatel y pursued the candidacy for Ph.D. program also in Civil and Environmen tal Engineering. She completed the program requirements in the fall of 2006.


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Rahgozar, Mandana Seyed.
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Estimation of evapotranspiration using continuous soil moisture measurement
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by Mandana Seyed Rahgozar.
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[Tampa, Fla] :
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2006.
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ABSTRACT: A new methodology is proposed for estimation of evapotranspiration (ET) flux at small spatial and temporal scales. The method involves simultaneous measurement of soil moisture (SM) profiles and water table heads along transects flow paths. The method has been applied in a shallow water table field site in West-Central Florida for data collected from January 2002 through June 2004. Capacitance shift type moisture sensors were used for this research, placed at variable depth intervals starting at approximately 4 in. (10 cm) below land surface and extending well below the seasonal low water table depth of 59 in. (1.5 m). Vegetation included grassland and wetland forested flatwoods. The approach includes the ability to resolve multiple ET components including shallow and deep vadose zone, surface interception capture and depression storage ET. Other components of the water budget including infiltration, total and saturation rainfall excess runoff, net runoff, changes in storage and lateral groundwater flows are also derived from the approach. One shortcoming of the method is the reliance on open pan or other potential ET estimation techniques when the water table is at or near land surface. Results are compared with values derived for the two vegetative covers from micrometeorological and Bowen ratio methods. Advantages of the SM method include resolving component ET.
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Dissertation (Ph.D.)--University of South Florida, 2006.
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Text (Electronic dissertation) in PDF format.
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Adviser: Mark A. Ross, Ph.D.
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West Central Florida.
Vadose zone hydrology.
Shallow water table.
Potential ET.
Groundwater ET.
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