CHARACTERIZATION OF GROUNDWATER POLLUTION SOURCES BY KRIGING BASED LINKED SIMULATION OPTIMIZATION

Abstract

Often untreated wastes are buried underground as convenient method of disposal. These clandestine disposal methods are adopted to offset the cost incurred in proper waste management. Though there might be short term economic gain to the disposer but the long-term impact of such disposal manifests in form of groundwater pollution, which if left unchecked would potentially pollute the entire aquifer. Any contaminated aquifer treatment technique requires prior information about the pollutant sources characteristics. Thus, characterization of unknown groundwater pollution sources becomes imperative in remediation process. The first step involves the identification of number of sources and their locations. In a clandestine scenario the entire study area is treated as a potential source and the search for the actual source can be extensively rigorous in space and time. To overcome this challenge a kriging based zoning is adopted to narrow down the search space for the actual sources in a limited data availability scenario. A comparative analysis of two methods is presented; first method where only (Simulated Annealing based Linked Simulation Optimization) SALSO is used, and second method where kriging based zoning plus SALSO is adopted for pollution source characterization. It is found that kriging method clubbed with SALSO gives significantly better results compared to initial results. A boundary of Indian Institute of Technology Patna with hypothetical hydro-geological parameters is used to test the developed method. The location of the pollutant sources is easily identified when a kriging based Simulated Annealing Linked Simulation Optimization (KSALSO) method is adopted.