Spatio-temporal design for a water quality monitoring network maximizing the economic value of information to optimize the detection of accidental pollution

Abstract

Abstract The reduction of damage due to water pollution requires good knowledge of the quality of surface waters. The Water Quality Monitoring Networks (WQMNs) have evolved over time according to the objectives of each one of them: knowledge of long-term quality evolution, search for the origin of pollution, detection of accidental pollution, etc. Information provided by WQMNs could be improved by a spatial approach, optimizing the location or the number of monitoring stations, or by a temporal approach, optimizing the sampling frequency. However, there is a cost for monitoring water quality. In this article, we show, for the first time, how the estimation of the Economic Value of Information (EVOI) can be used to determine the spatio-temporal design of the network. With the example of a network that aims to detect accidental pollution, we show how to calculate the EVOI according to the spatial and temporal network design (number and location of stations, temporal accuracy of measurement) and how to define this design by maximizing the EVOI. This will allow us to answer questions such as: Are the expenses invested in the networks justified? With an additional budget, is it better to add a station or to increase the temporal accuracy of the measurement of existing stations? What is the optimal spatial and temporal design of the network when working with a fixed budget?