Even though the necessity of water quality monitoring systems is increasing, and though mobile watery quality monitoring systems using the combination of automatic measuring devices and autonomous vehicles is becoming available, research on effective deployment of such systems is not studied well. The locations or paths to take the measurement are one of the most important design factors to maximize the performance of water quality monitoring systems, and they needs to be optimized to maximize the monitoring performance. To solve these optimization problems, multi-objective genetic algorithms were proposed and developed. The proposed optimization procedures were applied to hypothetical circular lakes and Lake Pontchartrain in order to obtain optimal monitoring locations, straight monitoring paths, and higher-order monitoring paths under various conditions. Also, the effect of various parameters such as the speed of a monitoring vessel, the weights of possible scenarios, and etc. are investigated. The optimization models found optimal solutions efficiently while reflecting various effects of complex physical settings. The results from the optimizations show that distribution of possible source locations is an important factor that affects optimal solutions greatly. In a closed water body, wind is major forcing that determines hydrodynamics and contaminant transport, and it affects optimal solutions as well. Straight monitoring lines do not perform very well due to their incapability to cover the irregular boundaries of water bodies. Higher-order optimal monitoring paths overcome this difficulty and perform well up to a comparable level of a few stationary monitoring locations even under realistic and transient conditions.
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Optimization of paths and locations of water quality monitoring systems in surface water environments
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