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This paper presents an optimization methodology to calibrate the nodal demand in the model of water supply distribution systems. The matrix analysis has been carried out to get the sensitive coefficients matrix for the model of water distribution systems. Singular value decomposition is applied to calculate search director of optimization by solving the sensitive coefficients matrix, which is more efficient than the finite-difference method. Two cases are used to show the performance of this algorithm. The first case is a hypothetical water distribution network showing the calculation of the optimization vector. The second case is the application of real-life water distribution system in Hangzhou, China, which shows the determination of the cutoff singular value and the search step size in one-dimensional search. The calibrated model has been also validated using the measured data. The results have shown that the proposed algorithm is reliable and effective in real-time system. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the Genetic Algorithms (GA) and Bayesian Model Averaging (BMA) were used to simultaneously conduct calibration and uncertainty analysis for the Soil and Water Assessment Tool (SWAT). In this combined method, several SWAT models with different structures are first selected; next GA is used to calibrate each model using observed streamflow data; finally, BMA is applied to combine the ensemble predictions and provide uncertainty interval estimation. This method was tested in two contrasting basins, the Little River Experimental Basin in Georgia, USA, and the Yellow River Headwater Basin in China. The results obtained in the two case studies show that this combined method can provide deterministic predictions better than or comparable to the best calibrated model using GA. The 66.7% and 90% uncertainty intervals estimated by this method were analyzed. The differences between the percentage of coverage of observations and the corresponding expected coverage percentage are within 10% for both calibration and validation periods in these two test basins. This combined methodology provides a practical and flexible tool to attain reliable deterministic simulation and uncertainty analysis of SWAT. [Copyright &y& Elsevier]