长江流域总氮排放量预测

水环境污染是长江流域突出的环境问题之一,预测污染物排放特征可为流域水污染防治提供科学基础.本研究综合采用灰色理论预测模型、Conversion of land use and its effects at small region extent(CLUE-S)模型以及 Integrated valuation of ecosystem services and tradeoffs(InVEST)模型,预测2025年长江流域非点源以及点源总氮排放趋势.结果表明:①非点源总氮排放呈减少趋势,2015～2025年区域非点源总氮排放量减少23.96％,中下游农业区总氮排放骤减,而上游局部地区呈增加趋势;②点源总氮排放总体呈现增加趋势,2015～2025年区域点源总氮排放量增加1.79％,主要是由于城镇废水排放的增加以及中下游沿江城市群生活污水排放显著增加,而中下游丘陵地区点源总氮排放呈现减少趋势;③长江流域总氮排放量呈现减少趋势,2015～2025年减少2.67％,但仍有37.64％区域呈现总氮排放增加的趋势.长江流域未来应加强对上游面源污染治理以及中下游工业、城镇废水排放的管控.采用多模型结合的手段可以精细揭示了长江流域总氮排放空间格局及未来趋势,可为明确流域总氮排放控制目标提供科学基础,也可为实现高效的水环境治理提供科学依据.

Prediction of Total Nitrogen Load in Yangtze River Basin

Water pollution is one of the serious environmental problems in the Yangtze River Basin. Predicting the trend of pollutant load can provide a scientific foundation for watershed ecological management. In this study, we used CLUE-S, InVEST, and grey system prediction models to predict the nonpoint and point total nitrogen (TN) pollution load under future ecological management and economic development scenario in the Yangtze River Basin and analyze the change in TN pollution load from 2015-2025. The results showed that, during 2015 to 2025, the nonpoint TN loads had been reduced by 23.96%. Nonpoint TN load decreased sharply in the middle and downstream watershed, whereas it increased in some upstream watersheds. The point TN load increased by 1.79%, which was mainly attributed to the increase in domestic wastewater. The municipal TN load in urban agglomerations increased significantly, whereas the point TN load decreased in some hilly areas of middle and downstream watershed. Overall, the TN load is predicted to decrease by 2.67% in 2025 but it still increases in 37.64% area of Yangtze River basin. Furthermore, more effective measures should be taken to control the nonpoint pollution in upper stream and point pollution from industrial and municipal areas in middle and downstream reaches. This approach based on multiple ecological models can accurately illustrate the future TN load spatial pattern and evolutionary trend, which can provide more detailed information on watershed TN control targets and improve the efficiency of watershed pollution control management.