Uncertainty analysis of hydrological parameters of the APEXgraze model for grazing activities

Abstract

Researchers in hydrological sciences have developed agro-hydrological models to study water quantity and quality in small-scale watersheds. These models, however, often exhibit significant uncertainty in both parameters and response variables. The study aims to address limited research on the uncertainty range of runoff-related parameters in watershed models, particularly those analyzing the impact of grazing operations. It also seeks to improve existing uncertainty analysis protocols because these protocols rely on parameter distributions, which are often difficult to determine. A generalized uncertainty analysis protocol that statistically considers multiple acceptable solutions from calibrated agro-hydrological models was developed. This approach employed a variant of the Agricultural Policy eXtender (APEX) model with an expanded grazing module called APEXgraze to perform uncertainty analysis of runoff and sediment-related parameters. Four small-scale watershed models were developed for calibration: a) native prairie, b) native prairie under grazing operations, c) cereals (winter wheat and one season of oats), and d) the same cereals under grazing operations in a semi-arid region of Oklahoma, United States. This work demonstrated that a simplified uncertainty analysis approach effectively captured the internal dynamics of hydrological processes within a statistically significant range of parameters. This observation was evidenced by a small range of water balance in both magnitude and percentage. The procedure also helped identify redundant parameters in sensitivity and uncertainty analyses. The proposed generalized uncertainty analysis protocol offers a reliable method for assessing hydrological models' internal dynamics and identifying critical parameters. This approach can enhance the accuracy of watershed models, particularly in regions with grazing operations.