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Low Flow Regionalization Modeling

S. Eslamian, M. Biabanaki

Abstract


There are generally no measurements in the parts of river that the low flow estimates are required. For overcoming this problem, the regional analysis has been often used. In this paper, using the mean daily flow statistics from 41 hydrometric stations in Karkheh basin, Iran after checking the region homogeneity by cluster method and Andrew’s curves, low flow analysis has been performed by several models namely: multivariate regression for determining the relations between low flow values and hydrologic characteristics of basin (MRLF), index low flow method (ILFM), regionalization model of frequency formula parameters (RFFP, determining regression equation between mean and standard deviation of low flows and hydrologic characteristics of basin) and hybrid low flow model (HLFM). The error tests of regional models for four mentioned methods in comparison with point analysis in the basis of mean relative error (MRE) and root of mean square error (RMSE) criteria show that for 5, 10, 20, 25, 50 and 100 years return periods, MRLF and ILFM have more accuracy in comparing with RFFP and HLFM. In the basis of MRE, ILFM and also in the basis of RMSE, MRLF are suitable methods for low flow modeling in this basin. Also the results show that MRLF and ILFM for the low and moderate return periods (about 50 years) and RFFP and HLFM for the high return periods (higher than 50 years) do not have a significant difference by 5 percent of confidence level. Finally for comparing HLFM with the other three methods, a relative error criterion has been determined. The results show that HLFM for 5, 10, 20, 50 and 100 years return periods displays the MRE of 86.6, 7.5, 15.8, 60.11, 73.20 and 257.5 percent and also the RMSE of 2.5, 2.75, 2.52, 1.99, 1.75 and 1.56, respectively. On this basis, HLFM is determined as the third rank of importance after the two models, MRLF and ILFM. Also, it indicates more accuracy while comparing with RFFP.

Keywords


Karkheh basin, Hybrid model, Multivariate regression, Flow regionalization, Low flow, Cluster analysis, Index flow, Hydrologic drought

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