文章摘要
典型环状河网突发水污染溯源研究
Methodology for identifying the source of sudden water pollution in typical looped river network
投稿时间:2024-04-12  修订日期:2024-05-30
DOI:
中文关键词: 环状河网  污染溯源  反问题  突发水污染  机理-数据
英文关键词: looped river network  pollution source identification  inverse problem  sudden water pollution  mechanism-data
基金项目:国家自然科学基金青年基金项目(52109047),国家重点研发计划项目(2023YFC3209403-03)
作者单位邮编
王家彪 中山大学 519082
赵铜铁钢 中山大学 
蔡思宇 中国水利水电科学研究院 
赵建世* 清华大学 100084
陈晓宏 中山大学 
王浩 中国水利水电科学研究院 
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中文摘要:
      伴随着快速的城镇化进程,我国突发水污染问题日益突出。污染发生后,首要任务是确定污染源以实施应急处置。国内外关于突发水污染溯源的研究颇多,但普遍不适用于环状河网区,究其原因,环状河网区溯源问题具有严重不适定性,溯源计算复杂、求解难度高。为此,本文提出了一种可实现环状河网突发水污染溯源的新方法,内容包括:(1)将河网溯源分解为“河网”和“河道”两级开展;(2)利用BP神经网络算法计算河网中污染溯源所在具体河道,并由水流水质模型推算该河道出口处污染物浓度过程,实现河网级溯源;(3)采用逆向位置概率密度方法计算出污染事件具体排放位置、排放时间和排放总量,实现河道级溯源;(4)将所提出方法应用于某典型环状河网,结果表明该方法可有效识别出河网中的突发水污染源。研究成果可服务于复杂河网区突发水污染的应急处置、责任明确及预案管理等,具有重要实践意义和广阔应用前景。
英文摘要:
      With the rapid urbanization process, the problem of sudden water pollution in China is becoming increasingly prominent. After pollution occurs, the primary task is to identify the source of pollution for emergency disposal. Nowadays, there are many studies on the sudden water pollution source identification, but they are generally not applicable to the looped river network cases. The reason for this issue is that the problem of identifying pollution source in a looped river network is severely ill-posed, involving complex calculations and being rather difficult to solve. Therefore, this research proposes a creative method for identifying the source of sudden water pollution in a looped river network, which includes: (1) the task of identifying pollution source is divided into two steps: the first step involves identifying the river with a pollution source, and the second step involves identifying detailed information about the pollution; (2) at the first step, the BP neural network algorithm is used to calculate the specific river where a pollution source is located, and the flow and water quality models are further used to calculate the concentration of pollutants at the outlet of the identified river when observations are not available in this river; (3) at the second step, after the river identified, the detailed information of pollution source including the release position, the release time, and the release mass, can be further estimated using the backward location probability density method; (4) the proposed method has been applied to a typical looped river network case, and the results show that this method can effectively identify the source of sudden water pollution from a looped river network. This research achievement can serve for the emergency response, responsibility management, and pre-emergency planning of sudden water pollution in the river network areas, with great practical significance and broad application prospects.
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