Optimal Monitoring Network Design for Wind-Driven and Tidal Estuaries

Abstract

Water quality is an important aspect of health assessment of rivers, lakes, and estuaries, which requires systematic data collection from various components of the aquatic environment. The analysis of this data is used to judge the health state of these environments. It is well known that long-term surveillance of surface waters is costly. Thus, sound strategies are necessary to select the best locations of monitoring stations to collect the most reliable data efficiently to improve the performance of a monitoring system. This can be accomplished by optimizing the location of monitoring stations with respect to the hydrodynamic and transport characteristics of the surface water system. It is expected that such an approach may improve the effectiveness and also reduce the overall cost of the monitoring system. Since the hydrodynamics and the contaminant migration pathways in surface waters are complex, the optimal solution of this problem is also complex. To analyze this problem, a two-dimensional hydrodynamic simulation model is developed using the finite-element method. The best monitoring locations are selected that minimize the detection time of the potential contaminant presence in the surface water body and maximizes the reliability of the system performance. Due to the nonlinear nature of the hydrodynamics, a genetic algorithm (GA) is used for the solution of the optimization problem. Examples are provided for wind-driven hydraulic circulation for a circular lake, and tidal and wind-driven circulation in a natural tidal estuary.