Optimization of Groundwater Quality Monitoring Network Using Risk Assessment and Geostatistic Approach

The sampling data from the groundwater quality monitoring network (GQMN) can not only characterize the properties of the natural resource in groundwater system, but also delineate contaminated area and risk potential by human activities. This study aimed to provide a process for designing GQMN for non-existing monitoring well using Nantou area in Taiwan as the example. First, this study have integrated four contributing factors (land use, soil media, topography and population) of both vulnerability map and hazard map to calculate the Contamination Risk Index (CRI) via Geographic Information System (GIS) model. The results of the map demonstrated that the spatial distribution of the highest contamination risk potential and provided the preliminary deployment of the spatial locations of the candidate monitoring wells. According to the deployment of the candidate monitoring wells, this study used the geostatistical approach to calculate the percentage of the total area with acceptance accuracy of the candidate monitoring wells for different threshold. Based on the defined performance, the available monitoring networks for different threshold of three cases are estimated. The information can support the designer or the decision maker to design appropriate monitoring network whether they have a limited funding or not.