Identification of Contaminant Source Characteristics and Monitoring Network Design in Groundwater Aquifers: An Overview

Abstract

<p align="justify"> <span style="font-family:verdana;">The groundwater system is often polluted by different sources of contamination where the sources are difficult to detect. The presence of contamination in groundwater poses significant challenges to its delineation and quantification. The remediation of a contaminated site requires an optimal decision making system to identify the pollutant source charac</span><span style="font-family:verdana;">t</span><span style="font-family:verdana;">eristics accurately and efficiently. The source characteristics are generally identified using contaminant concentration measurements from arbitrary or planned monitoring locations. To effectively characterize the sources of pollution, the monitoring locations should be selected appropriately. An efficient monitoring network will result in satisfactory char</span><span style="font-family:verdana;">a</span><span style="font-family:verdana;">cterization of contaminant sources. On the other hand, an appropriate design of monitoring network requires reliable source characteristics. A coupled iterative sequential source identification and dynamic monitoring network design, improves substantially the accuracy of source identification model. This paper reviews different source identification and monitoring network design methods in groundwater contaminant sites. Further, the models for sequential integra</span><span style="font-family:verdana;">tion of these two models are presented. The effective integration of source identification and dedicated monitoring net</span><span style="font-family:verdana;">work design models, distributed sources, parameter uncertainty, and pollutant geo-chemistry are some of the issues which need to be addressed in efficient, accurate and widely applicable methodologies for identification of unknown pollutant sources in contaminated aquifers.</span> </p

Application of Simulated Annealing and Adaptive Simulated Annealing in Search for Efficient Optimal Solutions of a Groundwater Contamination related Problem

“…Also, only if the global optimum solution is found, it may represent the accurate solution to the source identification problem. Nonuniqueness in the system response may introduce alternate optimal solutions, although each globally optimal [5,20,21]. This is due to the fact that different sets of stresses (i.e., contaminant sources) can result in identical responses (resulting spatial and temporal concentrations).…”

“…In this methodology, the numerical models for simulation of the flow and transport process are internally linked to the optimization algorithm. Chadalavada and Datta [1] and Amirabdollahian and Datta [21] presented an overview of the pollution source identification simulation-optimization approaches.…”

Reliability Evaluation of Groundwater Contamination Source Characterization under Uncertain Flow Field

“…Amirabdollahian and Datta [2] presented an overview on pollutant source identification techniques and discussed some of the relevant issues in this area. The linked simulation optimization technique characterizes the contamination sources by an internal linkage between flow and contaminant transport simulation models and the selected optimization technique [3]- [5].…”

Identification of Groundwater Pollution Sources by a SCE-UA Algorithm-Based Simulation/Optimization Model

“…There is a large body of literature dedicated to resolving this problem. Atmadja and Bagtzoglo [7] and Amirabdollahian and Datta [8] provided a comprehensive review of approaches to solve inverse source-identification problems in groundwater systems. The recent research by Prakash and Datta [9] improved the accuracy of source identification through an optimized groundwater monitoring network.…”