水科学进展2017，Vol.28Issue(6)：943-952,10.DOI:10.14042/j.cnki.32.1309.2017.06.015
地下水污染源识别的数学方法研究进展
Advances in mathematical methods of groundwater pollution source identification
摘要
Abstract
Using limited observation data of groundwater quality, models of groundwater pollution source identification can be used to estimate the locations, leakage rate, and the dominant processes of the pollution sources, which thus can provide a reference for formulating remedial schemes for groundwater pollution. Based on the principles and theo-ries of pollutant movement and source identification, this paper presents an overview of existing mathematical methods, including direct methods (inverse particle tracing methods and regularization-based methods) and indirect methods (optimization-based and probability-based methods). The main problems in the application of these methods are ① the complexity of groundwater pollution source identification, ② groundwater organic contamination, and③ the low efficiency of model calculation. Integrated research of soil-groundwater systems, instrumentation-based groundwater pollution monitoring, identification of NAPL pollutants, and GPU-based heterogeneous parallel computing will be the keys to groundwater pollution source identification in the future.关键词
地下水污染源识别/非适定性/优化算法/贝叶斯推理/非水相流体Key words
groundwater pollution source identification/Ill-posedness/optimization/Beyesian inference/non-aqueous phase liquid分类
天文与地球科学引用本文复制引用
王景瑞,胡立堂..地下水污染源识别的数学方法研究进展[J].水科学进展,2017,28(6):943-952,10.基金项目
国家自然科学基金资助项目(41572220) （41572220）
北京市自然科学基金资助项目(J150002)The study is financially supported by the National Natural Science Foundation of China (No. 41572220). （J150002）
