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Water quality monitoring networks are playing an important role in acquiring information concerning water quality. This has led to reflections regarding the type and the quantity of information provided by the monitoring networks and thus on the Economic Value of Information (EVOI).
In this study, we will focus on determining the optimal location of monitoring stations in a river in order to minimize detection time for accidental pollution. We construct a theoretical model to compare the EVOI of a physically optimized monitoring network, with only hydrological concerns, and an economically optimized monitoring network, optimizing the EVOI, with three scenarios of vulnerability along the river.
Our results show that the benefit of adding monitoring stations is decreasing with the number of stations. Then according to the cost of the monitoring station, a finite number of stations is recommended. Moreover, we show that the advantage of optimizing the EVOI compared to physical optimization is relative to the context, namely the number of stations, and the vulnerability scenarios. Then, according to the additional cost of economic optimization, the physical optimization could be recommended.
