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Titlebook: Advances in Water Resources & Hydraulic Engineering; Proceedings of 16th Changkuan Zhang,Hongwu Tang Conference proceedings 2009 Springer-

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,Posterity and Writing ‘for the Day’,, of deriving the TUHs are prone to produce a saw-tooth TUH, because of the mistaken data, or/and simplification of the hydrological process (to be linear) of the river basin. This paper applies a so-called Goal Attainment (GA) method to obtain an optimal TUH. The GA method is a multi-objective opti
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,Posterity and Writing ‘for the Day’,nique (GLUE) and the variance based Sobol’ technique. The former assess the likelihood of a model to describe a system recognizing that model and data are subject to uncertainty; the latter statistically evaluates the uncertainty in the estimation of model parameter values. Both are commonly used in
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https://doi.org/10.1007/978-1-4471-3985-0d the underlying surface characteristics of the thirteen catchments in Dongjiang basin. The flow duration curve for the each catchment is obtained by the traditional method, and, then the flows of various exceedance percentages Q. are calculated. Based on the relationship between the flow of various
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https://doi.org/10.1007/b138515genetic algorithm to solve the disadvantage of the standard genetic algorithm’s inaccuracy of coding and low-precision. The improved genetic algorithm gets better results in calibration of the three-source XinAnJiang model. Contraposing the shortage of traditional single objective optimization, this
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