Abstract
A methodology for evaluation of risk for a river water quality management problem is presented. A fuzzy waste load allocation model is solved with a simulation-optimization approach for obtaining optimum fractional removal levels for the dischargers to the river system.With the optimal fractional removal levels, sensitivity analysis and first-order reliability analysis are applied to identify key random variables which influence the water quality simulation model output, and key checkpoints where the model output is more likely to be affected (i.e., has high variability). Frequency distributions of the output variable are obtained at the key checkpoints using Monte Carle simulation with the key random variables as input variables. The event of low water quality at a checkpoint in a river system is considered as a fuzzy event, with appropriate membership functions defined for the fuzzy risk of low water quality. With the help of fuzzy membership functions and frequency distributions, fuzzy risk levels are computed at the key checkpoints. The proposed methodology is demonstrated through a case study of Tunga-Bhadra River in southern India.
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