Optimizing Soil Hydraulic Parameters in RZWQM2 under Fallow Conditions

Abstract

Robust estimation of soil hydraulic parameters is essential for predicting soil water dynamics and related biogeochemical processes; however, uncertainties in estimated parameter values limit a model's ability for prediction and application. In this study, methods of global analysis (Latin hypercube sampling, LHS) and gradient‐based optimization (PEST, parameter estimation software) were explored to calibrate soil hydraulic parameters in the Root Zone Water Quality Model (RZWQM2). Six methods of estimating Brooks–Corey parameters of the soil water retention curve and saturated hydraulic conductivity were evaluated to simulate daily soil water dynamics under fallow conditions in eastern Colorado. The calibrated soil hydraulic parameters showed similar trends with soil depth for the different estimation methods in RZWQM2 but resulted in large differences between simulated and observed soil water contents. The PEST optimization based on soil type values as initial estimates gave reasonable soil water responses but with some unrealistic soil hydraulic parameters and soil evaporation. Overall, errors in simulated soil water contents were reduced by using LHS to initialize and constrain the PEST parameter space, which also stabilized the cross‐validation results. Calibration results using water content measurements at four depths (30, 60, 90, and 150 cm) were similar to results using 10 depths (30, 40, 50, 60, 70, 80, 90, 120, 150, and 170 cm). Calibrating soil hydraulic parameters remains challenging, but the combined calibration procedures (LHS + PEST) with cross‐validation can reduce parameter uncertainties and improve model performance.