基于社会-经济因子修正的沱江流域农业面源总磷污染负荷时空演变研究

Spatial-temporal evolution of agricultural non-point sources of total phosphorus pollution loads in Tuojiang River watershed based on correction of social-economic factors

本研究选取沱江流域为研究区域,引入社会-经济因子,采用修正的排污系数法估算该流域污染负荷。首先基于流域28个区县2011—2017年的人口和农作物产量等相关数据,采用GM(1,1)预测法预测其在2021—2025年期间的变化趋势,其次采用修正的排污系数法计算各区县农业面源总磷(TP)污染负荷,最后利用探索性空间数据分析方法(ESDA)探索2025年各污染源TP污染负荷空间变化特征,结果表明:2021—2025年,TP污染负荷总体将呈逐年递增趋势,增量将为266.34 t,增幅将为2.18%,各污染源TP污染负荷贡献率将表现为畜禽养殖>农田固废>农田径流>农村生活污水>农村生活垃圾。与2017年相比,2025年农村生活污水和农村生活垃圾TP污染负荷较高的区县将减少,而农田径流、农田固废和畜禽养殖TP污染负荷较高的区县将增加。2017年与2025年修正后的各污染源TP污染负荷最大值出现的区县具有较大的差异。2025年,修正前后各污染源TP污染负荷局部集聚特征差异显著,且修正后的各污染源TP污染负荷将表现为同污染程度集聚。因此,基于沱江流域社会-经济因子修正的流域各农业面源TP污染负荷评估不仅能考虑排污系数的区域差异性,也能更深层地揭示TP污染负荷的空间集聚效应,且该修正方法具有所需参数少、操作简单的特点,能推广到其他相似流域的水环境管理与污染防治中。

The traditional estimation of pollution loads ignores the impact of temporal-spatial heterogeneity of socio-economic factors on the calculation results,which do not objectively reflect the actual pollution situation.Therefore,the study selected the Tuojiang River watershed as the study site and adopted the corrected pollution discharge coefficient method based on socio-economic factors to estimate total phosphorus(TP)pollution loads in the watershed.First,based on statistical data(such as population and cultivated land area,crop production,and the number of livestock)of 28 counties located in the watershed from 2011 to 2017,the GM(1,1)model was used to predict the variation trend from 2021 to 2025.This study then calculated the TP pollution loads of each district(county)from diverse pollution sources using the corrected pollution discharge coefficient method in the future. Finally, exploratory spatial data analysis(ESDA) was used to explore the spatial distribution variation of TP pollution loads from diverse pollution sources in 2025. The results are as follows: from 2021 to 2025, the total TP pollution loads will increase steadily by 2.18%, and the increment will be 266.34 t. Among them, TP pollution loads from rural domestic sewage, rural domestic waste, and livestock and poultry pollution sources will decrease gradually, whereas TP pollution loads from agricultural runoff and agricultural solid waste pollution sources will increase yearly. The contributions of TP pollution loads from diverse pollution sources to total TP pollution loads are as follows:livestock and poultry, agricultural solid waste, agricultural runoff, rural domestic sewage, and rural domestic waste. From a spatial perspective, compared with 2017, the number of districts(counties)with high TP pollution loads from rural domestic sewage and rural domestic waste pollution sources will decrease. However, agricultural runoff, agricultural solid waste, and livestock and poultry pollution sources will increase. Moreover, there are differences in the districts(counties)with the highest TP pollution loads in 2017 and 2025. In 2025, the difference in the local cluster patterns of uncorrected and corrected TP pollution loads will be prominent. After modification, TP pollution loads from diverse pollution sources show a pattern that is similar to the pollution level cluster. The evaluation of TP pollution loads from various pollution sources in the Tuojiang River watershed based on the correction of socio-economic factors not only considers the temporal-spatial differentiation of pollution discharge coefficients but also reveals the spatial cluster pattern of TP pollution loads. The method has the characteristics of fewer parameters and easy operation, which can be extended to water environment management and pollution prevention in other similar watersheds.