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Stochastic sensitivity analysis of nitrogen pollution to climate change in a river basin with complex pollution sources

机译:复杂污染源河流流域气候变化的随机敏感性分析

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It is increasingly recognized that climate change could impose both direct and indirect impacts on the quality of the water environment. Previous studies have mostly concentrated on evaluating the impacts of climate change on non-point source pollution in agricultural watersheds. Few studies have assessed the impacts of climate change on the water quality of river basins with complex point and non-point pollution sources. In view of the gap, this paper aims to establish a framework for stochastic assessment of the sensitivity of water quality to future climate change in a river basin with complex pollution sources. A sub-daily soil and water assessment tool (SWAT) model was developed to simulate the discharge, transport, and transformation of nitrogen from multiple point and non-point pollution sources in the upper Huai River basin of China. A weather generator was used to produce 50 years of synthetic daily weather data series for all 25 combinations of precipitation (changes by -10, 0, 10, 20, and 30%) and temperature change (increases by 0, 1, 2, 3, and 4 degrees C) scenarios. The generated daily rainfall series was disaggregated into the hourly scale and then used to drive the subdaily SWAT model to simulate the nitrogen cycle under different climate change scenarios. Our results in the study region have indicated that (1) both total nitrogen (TN) loads and concentrations are insensitive to temperature change; (2) TN loads are highly sensitive to precipitation change, while TN concentrations are moderately sensitive; (3) the impacts of climate change on TN concentrations are more spatiotemporally variable than its impacts on TN loads; and (4) wide distributions of TN loads and TN concentrations under individual climate change scenario illustrate the important role of climatic variability in affecting water quality conditions. In summary, the large variability in SWAT simulation results within and between each climate change scenario highlights the uncertainty of the impacts of climate change and the need to incorporate extreme conditions in managing water environment and developing climate change adaptation and mitigation strategies.
机译:越来越认识到,气候变化可能对水环境质量产生直接和间接影响。以前的研究主要集中在评估气候变化对农业流域的非点源污染的影响。少数研究评估了气候变化对河流水质的影响,复杂点和非点污染源。鉴于差距,本文旨在建立一个随机评估水质对河流污染源的未来气候变化的敏感性的框架。开发了一种亚日土壤和水评估工具(SWAT)模型以模拟中国上海河流域多点和非点污染源的排放,运输和转化。使用天气发生器为所有25个降水组合产生50年的合成日常天气数据系列(通过-10,0,10,20和30%的变化)和温度变化(增加0,1,2,3和4℃)方案。生成的每日降雨系列被分解为每小时刻度,然后用于驱动子地区SWAT模型,以模拟不同气候变化方案下的氮循环。我们在研究区的结果表明,(1)总氮(TN)负载和浓度都对温度变化不敏感; (2)TN载荷对降水变化非常敏感,而TN浓度是适度敏感的; (3)气候变化对TN浓度的影响比其对TN载荷的影响更加不稳定; (4)个人气候变化场景下的TN负荷和TN浓度的广泛分布说明了气候变异在水质条件下的重要作用。总之,每个气候变化情景内部和之间的SWAT模拟结果的大变化凸显了气候变化影响的不确定性,以及在管理水环境中融合极端条件的需要以及发展气候变化适应和缓解策略的不确定性。

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