Ponding Requirements for Recharge Efficiency Across Soil–Plant Systems

Abstract

Sustained surface ponding is often required to initiate groundwater recharge in semi-arid environments due to dry antecedent moisture and high evapotranspiration demand. The ponding duration needed to generate recharge depends on soil texture, vegetation, evaporative conditions, and antecedent moisture, forming a nonlinear system that is difficult to predict without numerical modeling. This study uses a HYDRUS-1D ensemble workflow to identify the ponding duration required for 10% of infiltration to become potential recharge (RR = 0.10) across 1,326 soil textures defined at 2% sand–silt–clay increments and four cover types (bare soil and three vegetation scenarios with increasing root depth and transpiration potential). Eight additional variant cases modified root depth, transpiration rate, antecedent moisture, and event connectivity to quantify their influence on ponding requirements. Potential recharge was defined as water from ponding crossing a 5 m depth within 50 years.Recharge feasibility declined sharply in soils containing more than 20% clay. Vegetation substantially increased the required duration, including a 27-fold median increase from bare soil to pasture grass, with further increases for deeper-rooted vegetation. Comparisons among textures with similar saturated hydraulic conductivity revealed contrasting behavior: silt loams exhibited faster initial infiltration, earlier recharge response, and the highest sensitivity to changes in antecedent moisture, transpiration, and rooting characteristics. Sand-dominated textures showed the lowest sensitivity to changes in these features. The fixed-pressure-head spin-up used to initialize soil moisture introduced systematic texture-dependent biases, producing unrealistically wet initial states in fine-textured soils and excessively dry states in coarse-textured soils. These biases influenced estimated ponding requirements. Incorporating realistic wetting–drying cycles or climatic forcing is recommended for future modeling to generate representative antecedent moisture conditions.