Optimal Monitoring Network and Ground-Water–Pollution Source Identification
Optimal Monitoring Network and Ground-Water–Pollution Source Identification
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DOI：
10.1061/(asce)0733-9496(1997)123:4(199
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发表时间：
1997-07
影响因子：
3.1
通讯作者：
P. S. Mahar;B. Datta
中科院分区：
文献类型：
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作者：
P. S. Mahar;B. Datta
提出了一种结合地下水水质监测网络优化设计和水源识别优化模型的方法。在三步法的第一步中，嵌入式非线性优化模型用于初步识别污染源（规模，位置和持续时间的活动）的基础上观察到的浓度数据从任意位于现有的威尔斯。第二步利用这些初步的识别结果和模拟优化方法来设计一个最佳的监测网络，可以在随后的时间段实施。在第三步中，利用在设计的监测井位置处的观测浓度数据来更准确地识别污染物源。监测网络的设计本质上可以是动态的，在随后的时间段内顺序安装监测威尔斯。监测网络可以分阶段实施，以便利用来自时变（动态）网络的观测浓度数据形式的更新信息。所提出的方法的性能评价表明，这种方法的潜在适用性，并显示出显着的改进，在识别未知的地下水污染源有限的观测数据。
A methodology combining an optimal ground-water–quality monitoring network design and an optimal source-identification model is presented. In the first step of the three-step methodology, an embedded nonlinear optimization model is utilized for preliminary identification of pollutant sources (magnitude, location, and duration of activity) based on observed concentration data from arbitrarily located existing wells. The second step utilizes these preliminary identification results and a simulation optimization approach to design an optimal monitoring network that can be implemented in the subsequent time periods. In the third step, the observed concentration data at the designed monitoring well locations are utilized for more accurate identification of the pollutant sources. The design of the monitoring network can be dynamic in nature, with sequential installation of monitoring wells during subsequent time periods. The monitoring network can be implemented in stages, in order to utilize the updated information in the form of observed concentration data from a time-varying (dynamic) network. The performance evaluation of the proposed methodology demonstrates the potential applicability of this methodology and shows significant improvement in the identification of unknown ground-water–pollution sources with limited observation data.