Using DSSAT-MODFLOW to determine the controls of groundwater storage and crop yield in groundwater-based irrigated regions

Linked hydro-agronomic modeling systems are often used to evaluate the impact of climate change or management strategies on both groundwater and crop yield. However, these modeling studies have been performed without a detailed assessment of the factors that jointly control groundwater storage and crop yield. The objective of this paper is to present results from a study that applied sensitivity analysis to the linked DSSAT-MODFLOW modeling system to determine the governing environmental and management factors that control groundwater storage and crop yield in an intensively irrigated groundwater region basin. Methods are applied to Finney County, in southwest Kansas, USA. Sensitivity analysis was accomplished using the Morris screening method followed by the Sobol’ variance-based method using random sampling. A combination of soil, hydrologic, plant cultivar, and climate parameters are included in the analysis. A combination of Python scripts and SimLab pre- and post-processing routines were used to generate values of parameters, update model files for DSSAT and MODFLOW, run the model simulations, and calculate sensitivity indices. Results indicate that climatic parameters account for 44%, 29%, 40%, and 36% variation in maize, soybean, winter wheat, and sorghum yields. Hydrogeologic parameters (i.e., hydraulic conductivity, specific yield, and riverbed conductance) have relatively low influence on crop yield. Water table elevation, recharge, and irrigation pumping are considerably sensitive to soil- and climate-related parameters, while evapotranspiration, river leakage, and groundwater discharge are highly influenced by hydrogeological parameters. These results can be used to explore effects of management strategies on groundwater and agricultural sustainability in similar regions in the face of a changing climate.