2004 Denver Annual Meeting (November 7–10, 2004)

Paper No. 10
Presentation Time: 1:30 PM-5:30 PM


KEESE, Kelley E., SCANLON, Bridget R. and REEDY, Robert C., Jackson School of Geosciences, University of Texas at Austin, 10100 Burnet Rd, Bldg. 130, Austin, TX 78758, keese@mail.utexas.edu

Quantitative estimates of recharge are critical for optimal management of water resources. The purpose of this study was to evaluate the use of unsaturated-flow modeling with readily available online data to estimate recharge over a range of climate (arid – humid), vegetation (crops, shrubs, grasses, forests), and soils (fine – coarse) on the basis of data from Texas, US. Long-term simulations were conducted for the period 1961 – 1990 for 13 sites that corresponded to counties near representative meteorological stations using the 1-D code UNSAT-H. Simulated drainage at the base of 5-meter profiles was equated to recharge. Soil hydraulic properties were estimated from SSURGO soils data using pedotransfer functions. Point recharge for each vegetation and soil-profile layering combination was regionalized using GIS coverages of vegetation and soil types for each site. Spatially and temporally averaged recharge rates are more appropriate for water resources management than point estimates at a single time. Recharge rates for vegetated layered systems ranged from 0 mm/yr in arid regions to 114 mm/yr in humid regions and were positively correlated with precipitation (r=0.8), which indicates that long-term precipitation can be used as a predictor of average recharge rates in these regions. Simulated recharge rates compared favorably with previous estimates based on unsaturated and saturated zone field studies and modeling. Various scenarios were simulated to evaluate sensitivity of model output to different factors. Simulated average recharge rates for bare sand ranged from 54 to 720 mm/yr, which are much greater than those simulated for vegetated layered soil profiles and indicate that climate is not a limiting factor for recharge. Layering of soil profiles reduced recharge rates relative to those for monolithic sands by factors of 2 – 10. These sensitivity analyses illustrate the relative importance of climate, vegetation, and soils in controlling recharge. Recharge results from this study were used as input to groundwater models by adjusting recharge with topography and by including a scaling factor to account for varying permeability of underlying geologic units. This modeling approach using online data provides a valuable tool for recharge estimation and can be used to evaluate changes in recharge in response to climate variability and land-use change.