River Water Quality Modeling Under Dual-Uncertainties: A Fuzzy-Parameterized Stochastic Simulation Method

Xiaosheng Qin and Ye Xu

DHI-NTU Water and Environment Research Centre and Education Hub, Nanyang Technological University, Nanyang Avenue, Singapore;

School of Civil and Environmental Engineering, Nanyang Technological University, Nanyang Avenue, Singapore.

9th International Conference on Hydroinformatics HIC 2010, Tianjin, CHINA 

A hybrid fuzzy-stochastic modeling approach was proposed to investigate the effects of dual uncertainties (presented as combinations of fuzzy membership functions and/or probability distribution functions) on water quality modeling and risk assessment. The hybrid approach integrated water quality simulation program, fuzzy transformation method, and Monte Carlo simulation technique into a general modeling framework, and could handle uncertain parameters expressed as fuzzy-parameterized stochastic variables. Water quality models are widely used to address the relationships between the pollutant loadings and environmental responses in river systems and analyze the potential impacts of alternative pollution-control plans. However, a remarkable limitation of current water quality models is their incapability in handling system complexities where high uncertain information exists.

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