中国海洋大学学报（自然科学版）2026，Vol.56Issue(6)：53-65,13.DOI:10.16441/j.cnki.hdxb.20250182
基于SWAT模型的小清河流域典型农药入海通量数值模拟研究
Numerical Simulation of the Typical Pesticides Fluxes into the Sea in the Xiaoqing River Basin Based on the SWAT Model
摘要
Abstract
Pesticide pollution from non-point sources poses a threat to coastal ecosystems,yet accurate watershed models for estimating pesticide flux to the sea remain scarce.In this study,we applied the Soil and Water Assessment Tool(SWAT)to simulate the flux of typical pesticides into the sea in the Xiaoqing River Basin.Using multi-year hydrological observations and pesticide survey data from 2022-2023,we optimized key parameters related to pesticide transport and transformation.The model was calibrated and validated against measured date on the flux into the sea of atrazine,nicosulfuron,and chlorpyrifos.Results revealed a consistent decline in the flux into the sea of atrazine,nicosulfuron,and chlorpyrifos from 2013 to 2022,with total reductions of approximately 71%,69%,and 58%,respec-tively.By 2022,the estimated fluxes reached 166 kg for atrazine,1.30 kg for nicosulfuron,and 0.54 kg for chlorpyrifos.Seasonal variations in flux for all three pesticides displayed a bimodal pattern,with peaks in March and July.The bimodal patterns of the herbicides atrazine and nicosulfuron differed sig-nificantly(p<0.05),while that of the insecticide chlorpyrifos showed no significant difference(p>0.05).Spatially,pesticide fluxes were concentrated in flat,agricultural subbasins,forming distinct hotspots.The primary source areas of pesticide load to Laizhou Bay were identified as agricultural subbasins in Weifang City,Zibo City,Guangrao County(Dongying),and Zhangqiu City(Jinan).This study offers a sci-entific basis for managing non-point source pesticide pollution in the Xiaoqing River Basin.关键词
SWAT模型/莠去津/烟嘧磺隆/毒死蜱/入海通量/小清河流域Key words
SWAT model/atrazine/nicosulfuron/chlorpyrifos/flux into the sea/Xiaoqing river basin分类
海洋科学引用本文复制引用
邢梦雪,韩如月,赵婧,鲁丽,戴宇飞,李克强..基于SWAT模型的小清河流域典型农药入海通量数值模拟研究[J].中国海洋大学学报（自然科学版）,2026,56(6):53-65,13.基金项目
国家自然科学基金青年基金项目(42507508) （42507508）
崂山实验室科技创新项目(LSKJ202203904)资助Supported by the National Science Foundation for Young Scientists of China(42507508) （LSKJ202203904）
the Scientific and Technological Innovation Project of Laoshan Laboratory(LSKJ202203904) （LSKJ202203904）
