Abstract
A comprehensive modeling framework utilizing MIKE-SHE to investigate the feasibility of enhancing livestock production while concurrently mitigating the impact of grassland ecosystems on surface water quality is presented. In this study, a modeling framework that simulates nitrogen transport was developed using a physically based distributed hydrologic model, MIKE SHE. The model was calibrated and validated using observed overland flow and water quality data from El Reno, Oklahoma's Water Resources and Erosion Unit watersheds. Different scenarios involving variations in timing, duration, and frequency of grazing activities, stocking rates, and climate conditions were simulated using the calibrated MIKE-SHE model. The goal was to explore the extent of the influence of these aspects of grazing on water quality through these scenario simulations. The results provided valuable insights into the key factors for developing an intelligent grazing decision tool to delineate targeted grazing windows that optimally balance heightened livestock production with environmental sustainability. The study's findings showed that the observed variability in existing literature originates mainly from climatic differences, with precipitation being the primary driver of nutrient loss, while evapotranspiration and soil moisture conditions are secondary factors. The simulations revealed that the impact of grazing on nitrogen loss in the pasture is evident only when grazing activities, irrespective of the stocking rate, duration, and frequency, occur under weather conditions conducive to nutrient loss in the pasture. These intertwined processes suggest that the impact of grazing on nitrogen loss can only be generalized within the context of the prevailing weather conditions in the pasture. Hence, strategically matching grazing activities with prevailing weather patterns can increase livestock production while promoting environmental sustainability in pasture management.
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