Application of a link simulation optimization model utilizing quantification of hydrogeologic uncertainty to characterize unknown groundwater contaminant sources
Journal Publication ResearchOnline@JCUAbstract
In existing groundwater contamination source characterization methodologies, simulation models estimate the contamination concentration in the study area. In order to obtain reliable solutions, it is essential to provide the simulation models with reliable hydrogeological properties. In real-life scenarios often high level of uncertainty and variability is associated with the hydrogeological properties. This study focuses on quantifying the hydrogeological parameter uncertainty to enhance the accuracy of identifying contamination release histories. Tracer experiment results at the Eastlakes Experimental Site, located in Botany Sands Aquifer, in New South Wales, Australia, are utilized to examine the performance and potential applicability of the methodology. In the selected study area, the hydrogeological heterogeneity in the microscopic scale, specifically the hydraulic conductivity, has substantial effect on the transport of pollutants. Among available tracer information, Bromide is studied as a conservative contaminant. Using possible realizations of the flow field, a coefficient of confidence (COC) is calculated for each field monitoring locations and times. Higher COC implies that the result of simulation models at that specific monitoring location and time is more reliable than other contaminant concentration data. Therefore, the optimization model should emphasise matching the corresponding estimated and observed contamination concentrations to accurately identify the contaminant release locations and histories. The linked simulation–optimisation method is utilised to optimally characterise the Bromide sources. Performance evaluation results demonstrate that the proposed methodology recovers pollution source characteristics more accurately compared to the methodology which does not consider the effect of hydrogeological parameter uncertainty.
Journal
Modeling Earth Systems and Environment
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N/A
Volume
5
ISBN/ISSN
2363-6211
Edition
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Issue
1
Pages Count
13
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Publisher
Springer
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EISSN
N/A
DOI
10.1007/s40808-018-0522-1