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Estimating Groundwater Recharge in Porous Media Aquifers in Texas

Estimating Groundwater Recharge in Porous Media Aquifers in Texas. Bridget Scanlon Kelley Keese Robert Reedy Bureau of Economic Geology Jackson School of Geosciences Univ. of Texas at Austin. Purpose and Scope.

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Estimating Groundwater Recharge in Porous Media Aquifers in Texas

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  1. Estimating Groundwater Recharge in Porous Media Aquifers in Texas Bridget Scanlon Kelley Keese Robert Reedy Bureau of Economic Geology Jackson School of Geosciences Univ. of Texas at Austin

  2. Purpose and Scope Estimate recharge rates for major aquifers (porous media) in Texas based on unsaturated flow modeling.

  3. Outline • Methods • Study design • Model description • Input data • Results • Conclusions

  4. Modeled Study Areas

  5. Different Modeling Scenarios Assess relative importance of climate, soils, and vegetation on simulated recharge • Monolithic sand profile, no vegetation – effect of climate on recharge • Monolithic sand profile + vegetation – effect of vegetation on recharge • Layered soil profile, no vegetation – effect of soil layering on recharge • Layered soil profile + vegetation – most realistic case

  6. Outline • Methods • Study design • Model description • Input data • Results • Conclusions

  7. Model • UNSAT-H code (1-D finite difference, PNNL) • 5 m profile • Boundary conditions: • upper boundary condition: daily weather 1961 – 1990 • lower boundary condition: free drainage • Initial conditions • Model output: • recharge, runoff, ET, water storage change • pressure and water content

  8. Water Balance Equation R = P – ET – R0 – DS R = recharge P = precipitation ET = evapotranspiration R0 = runoff DS = change in soil water storage

  9. Outline • Methods • Study design • Model description • Input data • Results • Conclusions

  10. Average Annual Precipitation Map

  11. 1961-1990 Average Annual Precipitation and PET for Selected Weather Stations

  12. Average Soil Profile Clay Content (STATSGO)

  13. Online Soils Databases and Pedotransfer Functions SSURGO (Soil Survey Geographic) database (1:24,000 scale) Similar soils data to STATSGO + water retention points at -3.3 and -150 m. Pedotransfer function: transforms available soils data into hydraulic parameters (K(q), h(q)) Rosetta neural network Input: Sand, silt, and clay percentages, bulk density and water retention at -3 m head and -150 m head Database: water retention h(q) and saturated hydraulic conductivity (Ks) Output: water retention functions and saturated hydraulic conductivity

  14. Distribution of Dominant Vegetation Types in Texas

  15. Vegetation Parameters • Type of vegetation shrubs, grasses, crops, trees • Fractional vegetation coverage • Leaf Area Index (LAI) one sided green leaf area per unit ground area in broadleaf canopies • Root depth • Root length density

  16. Outline • Methods • Study design • Model description • Input data • Results • Conclusions

  17. Different Modeling Scenarios Assess relative importance of climate, soils, and vegetation on simulated recharge • Monolithic sand profile, no vegetation – effect of climate on recharge • Monolithic sand profile + vegetation – effect of vegetation on recharge • Layered soil profile, no vegetation – effect of soil layering on recharge • Layered soil profile + vegetation – most realistic case

  18. Relationships Between Average Annual Precipitation and Simulated Area-Weighted Average Annual Recharge (1961 – 1990) R = 1.0

  19. Map of Recharge based on Nonvegetated Monolithic Sand Scenario 25% of P 61% of P

  20. Different Modeling Scenarios Assess relative importance of climate, soils, and vegetation on simulated recharge • Monolithic sand profile, no vegetation – effect of climate on recharge • Monolithic sand profile + vegetation – effect of vegetation on recharge • Layered soil profile, no vegetation – effect of soil layering on recharge • Layered soil profile + vegetation – most realistic case

  21. Relationships Between Average Annual Precipitation and Simulated Area-Weighted Average Annual Recharge (1961 – 1990) R = 0.96

  22. Variations of Recharge with different Vegetation Covers within one Simulated Site, Bastrop County Soil Profiles: sand, PaE, TfB, Afc

  23. Vegetated Monolithic Sand Profile 0% of P 32% of P

  24. Different Modeling Scenarios Assess relative importance of climate, soils, and vegetation on simulated recharge • Monolithic sand profile, no vegetation – effect of climate on recharge • Monolithic sand profile + vegetation – effect of vegetation on recharge • Layered soil profile, no vegetation – effect of soil layering on recharge • Layered soil profile + vegetation – most realistic case

  25. Relationships Between Average Annual Precipitation and Simulated Area-Weighted Average Annual Recharge (1961 – 1990) R=0.79

  26. Variations of Recharge with different Soil Profiles within one Simulated Site, Bastrop County Soil Profiles: sand, PaE, TfB, Afc

  27. Average Soil Profile Clay Content (STATSGO) Simulated Runoff 260 mm/yr 60 mm/yr 170 mm/yr 150 mm/yr 50, 25 mm/yr 10 mm/yr 0.1 mm/yr 15 mm/yr 150 mm/yr 315 mm/yr 430mm/yr 30 mm/yr

  28. Simulated Recharge Distribution based on Nonvegetated Layered Soil Profiles 4% P 26% P

  29. Different Modeling Scenarios Assess relative importance of climate, soils, and vegetation on simulated recharge • Monolithic sand profile, no vegetation – effect of climate on recharge • Monolithic sand profile + vegetation – effect of vegetation on recharge • Layered soil profile, no vegetation – effect of soil layering on recharge • Layered soil profile + vegetation – most realistic case

  30. Relationships Between Average Annual Precipitation and Simulated Area-Weighted Average Annual Recharge (1961 – 1990) R=0.95

  31. Map of Simulated Recharge based on the Power Law Relationship Power model Reduction Factor 11 – 109 0.2% - 7% P Reduction Factor 2 – 7 2% - 10% P

  32. Simulated Average Annual Drainage (mm/yr) Sensitivity of Recharge to Variations in Leaf Area Index, Root Depth, Root Length Density, and Bare Area 1 - 4 Represent Different Soil Profiles

  33. Summary/Conclusions • Monolithic sand profile • 54 mm/yr in W Texas to 720 mm/yr in E Texas • represents 25% to 61% of precipitation • Vegetated sand profile • 0 mm/yr in W Texas to 377 mm/yr in E Texas • represents 0% to 32% of precipitation • Layered soil profile • 18 mm/yr in W Texas to 226 mm/yr in E Texas • represents 4% to 26% of precipitation • Layered soil profiles + vegetation • 0.1 mm/yr in W Texas to 114 mm/yr in E Texas • represents 0.1% to 10% of precipitation

  34. Summary/Conclusions • Monolithic sand profile • 54 mm/yr in W Texas to 720 mm/yr in E Texas • represents 25% to 61% of precipitation • Vegetated sand profile • 0 mm/yr in W Texas to 377 mm/yr in E Texas • represents 0% to 32% of precipitation • Layered soil profile • 18 mm/yr in W Texas to 226 mm/yr in E Texas • represents 4% to 26% of precipitation • Layered soil profiles + vegetation • 0.1 mm/yr in W Texas to 114 mm/yr in E Texas • represents 0.1% to 10% of precipitation

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