Evaluating infiltration models and pedotransfer functions: Implications for hydrologic modeling

Soil is a critical medium that governs hydrological processes in a landscape; however, soil data quality and resolution are not given much emphasis during watershed modeling and developing practical management practices, especially in data scarce regions such as in the Ethiopian highlands. This is primarily because measuring most soil parameters is costly, laborious, and at times impractical. Infiltration models and Pedotransfer functions (PTFs) may bridge this gap by estimating such complex soil parameters from easily measurable ones. However, most infiltration models and PTFs were developed for temperate regions and there is no comprehensive experimental or modeling work done to evaluate the robustness of such approaches in the Ethiopian highlands. Therefore, this study aims to i) evaluate the performance of three infiltration models, namely Horton, Koistakov, and Philip in simulating soil infiltration rates and ii) test the reliability of nine PTFs in estimating saturated hydraulic conductivity and soil moisture contents at field capacity and permanent wilting point in a case study in the Anjeni watershed. Soils in the Anjeni watershed on average contain higher percentages of clay and silt with 42 and 34%, respectively; and have acidic pH and low organic matter. Steady infiltration rate (f(s)) and saturated hydraulic conductivity (Ks) ranged between 0.19 and 30.6 mm h(-1) and 0.19 and 3.3 mm h(-1) respectively. All the three infiltration models fitted observed data very well with R-2 and Nash-Sutcliffe efficiency (NS) values between 0.95 and 0.97 each. While the Horton and Koistakov models had the same R-2 and NS values, the Horton provided smaller Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) values. Some of the tested PTFs showed promising results in estimating saturated hydraulic conductivity and soil moisture content; however, all PTFs showed limitations which warrant further evaluation using observed data. This study showed that soil hydrologic parameters vary significantly even within a small area, and widely available soil datasets (e.g., Africa Soil Information Service (AfSIS) and FAO Harmonized World Soil Database) fail to reflect actual field conditions. This suggests that emphasis should be given to soil data quality and resolution during watershed modeling, and land and water management planning.