Determination of the Best Hierarchical Clustering Method for Regional Analysis of Base Flow Index in Kerman Province Catchments

The lack of complete coverage of hydrological data forces hydrologists to use the homogenization methods in regional analysis. In this research, in order to choose the best Hierarchical clustering method for regional analysis, base flow and related index were extracted from daily stream flow data using two parameter recursive digital filters in 43 hydrometric stations of the Kerman province. Physiographic, climatic and hydrological parameters were calculated. Using factor analysis of 14 parameters, six factors including: hydrograph recession constant, mean annual precipitation, actual evapotranspiration, permeability, topography (slope and height) and curve number were chosen as the most important independent factors. Hierarchical clustering of catchments using independent factors in different methods including: Nearest neighbor, Furthest neighbor, Centroid clustering and Ward were down. Then the regional equations using linear regression at 1% significant level for each homogeny region were determined. To compare and evaluate the accuracy and efficiency of the models, Independence errors, Colinerity and normal distribution of errors were tested. The results showed that “Centroid clustering method " because of low relative error with the amount of 27.137% for zone A and 36.89% for zone B of homogeneous region, minimum standard error of the estimate and the high correlation coefficient, diagnosed as the best homogeneity method to estimate regional base flow index in the study area.