节水灌溉Issue(6)：63-72,80,11.DOI:10.12396/jsgg.2025446
基于LOADEST和模拟退火算法的农业非点源污染调控措施研究
Research on Agricultural Non-Point Source Pollution Control Measures Based on LOADEST and Simulated Annealing Algorithm
摘要
Abstract
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.关键词
农业非点源污染/LOADEST模型/SOBOL敏感性分析/改进的模拟退火算法/经济效益/种植结构调整Key words
agricultural non-point source pollution/LOADEST model/SOBOL sensitivity analysis/improved simulated annealing algorithm/economic benefits/cropping pattern adjustment分类
农业科技引用本文复制引用
庞明月,李超超,彭文发,贾茹,李芸,顾靖超..基于LOADEST和模拟退火算法的农业非点源污染调控措施研究[J].节水灌溉,2026,(6):63-72,80,11.基金项目
国家重点研发项目专题(2022YFC3002902) （2022YFC3002902）
国家自然科学基金项目(52369005). （52369005）
