Evaluation of Effective Rainfall Estimation Methods under Contrasting Climatic Conditions in Vietnam: A Soil–Water Balance Modeling Approach Considering Management Allowable Depletion

Abstract

Effective rainfall ( P eff ) is an important parameter in irrigation requirement estimation and water management; however, current estimation methods still exhibit substantial deviations under different climatic conditions. This study evaluates the performance of three P eff estimation methods (fixed-percentage, USDA-SCS, and regional regression) relative to a soil–water balance (SWB) model across three representative climatic regions of Vietnam during the 1981–2020 period while also considering the influence of management allowable depletion (MAD). The fixed-percentage method produces the largest deviations, particularly during extreme years, by neglecting initial soil moisture and saturation limits. The USDA-SCS and regional regression methods substantially improve the results through nonlinear mechanisms; however, they still fail to represent the dynamic behavior of soil water. The SWB model indicates that P eff strongly depends on root-zone moisture conditions. As MAD increases from 0.3 to 0.7, rainfall storage capacity increases, leading to corresponding reductions in irrigation requirement (IR). These findings highlight the importance of incorporating dynamic soil water conditions into P eff estimation to improve the reliability of irrigation planning and water management under contrasting climatic conditions.