Document Type : Research Paper

**Authors**

**Abstract**

By using regionalization methods information from gauged sites transform to desired site. Up until now a variety of regionalization approaches have been proposed. In every site it is necessary to evaluate these methods and select the best method. It is of interest to understand how spatial weighted least square regression method based on depth function flood quantiles (SWLSR) compare with multivariate regression (MR) and Physiographical space-based kriging (PSK) methods. In each iteration desired station regarded as ungauged site then using genetic algorithm depth functions weights were optimized, finally (regarding) by taking account similarity between desired site and others sites flood quantiles corresponding to different return periods were estimated. By means of a leave-one-out cross-validation procedure, the performance of SWLSR was compared to MR and PSK methods for prediction of 10, 50 and 100 yr for 26 gauging station in the Southern Alborz. . The Result showed SWLSR approach yielded lower root-mean-square estimation errors and higher Nush Sutcliffe criteria thaneither the MR or the PSK approaches. PSK method estimated foold discharge in ungaged basin better than MR. In depth based approach Nush Sutcliffe criteria values for flood quintiles (Nash–Sutcliffe efficiency values for 10,50 and 100 yr floods were 0.64, 0.65 and 0.65 respectivly) three corresponding to different return periods were similar.In this method relative error to area in small catchment were biger than those obtained in big catchment.

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**Main Subjects**

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August 2016

Pages 363-375