Modeling of conservation practices’ effects on nutrients and sediment load reduction from commercial cotton fields using APEX

Mapping agricultural pollution sources typically requires extensive monitoring and resources but biophysical models can facilitate pollutant mapping from single or multiple agricultural areas within a watershed and offer a more efficient solution. This study employed the Agricultural Policy Environmental eXtender (APEX) model version 1501 to simulate nutrient and sediment loads, as well as crop yield, from commercial cotton fields under the presence and absence of a filter strip/cover crop treatment. The daily data used for model calibration and validation included total surface runoff, sediment and nutrient loads calculated from surface runoff samples collected at the edge of the 7.8 ha cotton control field during the study period from 2015 to 2022 in the Lower Mississippi River Basin in Arkansas. Sensitivity analysis, calibration, and validation were performed using the APEX auto-calibration and uncertainty estimator for the control field. The calibrated model for the control field was then applied to the treatment field that had cover crops and filter strips. The model's performance was assessed using R², Nash-Sutcliffe efficiency (NSE), Percentage bias (PBIAS), and root mean standard deviation ratio (RSR). The analysis demonstrated that the implementation of cover crops and filter strips significantly reduced runoff, sediment, total phosphorus, and total nitrogen loads (p < 0.05). The simulation results indicated that the cover crop and filter strip treatment reduced runoff by 41 %, sediment load by 58 %, total phosphorus (TP) by 63 %, and total nitrogen (TN) by 56 % compared to the control field. The simulated cotton yield results indicated no significant difference in cotton lint production due to the cover crop and filter strip applications (p > 0.05). The results demonstrated that cover crops and filter strips effectively reduce pollutant load while maintaining crop yield, reinforcing their value as sustainable conservation practices.