基于LOADEST和模拟退火算法的农业非点源污染调控措施研究OA

Agricultural non-point source pollution not only threatens the ecological balance of water bodies but also poses potential risks to human health.For large-scale agricultural regions,especially those experiencing rapid changes in cropping patterns,the mechanisms by which these patterns influence the transport and control of pollution remain difficult to elucidate.This study focuses on the Ningxia Yellow River Irrigation District,employing the LOADEST model to investigate the spatiotemporal characteristics of pollutant loads.By integrating multi-year monitored data on farmland export coefficients and cropping patterns,we assessed the spatiotemporal variability of the impacts of cropping patterns on pollutant loads and economic benefits.The results indicate that pollutant loads in The Fourth Drainage Area(Disipaiyu)of the Ningxia Yellow River Irrigation District demonstrated pronounced spatiotemporal heterogeneity.After optimizing the cropping pattern using an improved simulated annealing algorithm,the economic benefit increased by an average of RMB 855.35 per kg,while the peak total nitrogen load decreased by 73.923 t.Correlation analysis confirmed the potential existence of previously unrecognized implicit relationships between changes in cropping patterns and farmland export coefficients.Furthermore,adjusting the cropping pattern can effectively mitigate agricultural non-point source pollution while concurrently enhancing economic returns.