Impacts of Watershed Physical Properties and Land Use on Baseflow at Regional Scales

Abstract

Study region: Texas, USA Study focus: Texas is a large state in the US that experiences a diversity of climate conditions and water demands. In this study, 130 stream gauging sites and their associated watershed physical and geological properties were used to develop multiple regression models to predict the Baseflow Index (BFI) across Texas. Calculated BFI was derived from daily streamflow data from 1980 to 2017 using the two-parameter recursive digital filtering approach of the Web-based Hydrograph Analysis Tool (WHAT). Three scenarios were developed and validated. The first two scenarios related BFI to topography, climate, and land use. The third scenario used surface geology, soil type and hydrogeology parameters. New hydrological insights for the region: The models developed showed high performance, low bias, and low relative errors to predict BFI, with R2 values varying from 0.72 to 0.99, and strong agreement with filtered BFI values. The results further showed that there was no specific pattern for BFI variation across Texas ranging from 0.29 to 0.51. Outputs indicated that models developed for scenarios 1 and 3 had higher prediction performance. Additionally, evapotranspiration (ET) contributed to lower model accuracy, since the ET was not categorized as proportional to the percentages of cultivated areas within each basin, but was generalized to represent the whole catchment. The developed models that are reported here can support further research in groundwater modeling and baseflow prediction for ungauged sites that have similar characteristics.

Keywords

• Baseflow index
• Geological mapping
• Watershed properties
• Prediction
• Regression
• Texas