Abstract
Groundwater models are often used to assess the impact of climate or management strategies on groundwater resources in arid and semiarid regions of the world. However, these models do not account for crop growth and crop yield, and thus cannot be used for evaluating long-term impacts of climate and management strategies on water use efficiency and farm profitability of agricultural systems while managing the aquifers sustainably. This study presented a linkage between DSSAT, an agronomic model, and MODFLOW, a groundwater flow model. The linkage between these two models occurred on an annual basis, with rates of irrigation and deep percolation from an ensemble of field-scale DSSAT simulations converted to pumping rates and recharge rates for the MODFLOW simulation. MODFLOW simulated groundwater head, which can be used to update saturated thickness and thereby well capacities for each pumping well in the model domain. Simulated well capacities were then used to constrain irrigation applications in the DSSAT simulations during the following growing season. Python scripts were used to convert output from one model to input files for the other model. The DSSAT-MODFLOW modeling system was applied to the Ogallala aquifer underlying Finney County, Kansas, a region experiencing significant groundwater depletion due to irrigation practices, and was tested against observed water table elevation and crop yield. Over a decadal period, well capacity decreased by > 50 % for many pumping wells in the county. A no-irrigation scenario for this same time period resulted in average water table elevation increasing by 2 m, but also a 70 % decline in crop yield. Additional work is needed to balance groundwater conservation with crop yield. The DSSAT-MODFLOW modeling system can be used in regions worldwide to assess changes in irrigation technologies, crop selection, and climate change adaptation strategies.
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