Hydrological Regionalization in Relation to Accuracy of Maximum Discharge Estimation

To facilitate the transfer of data from basins with statistical data to basins without statistical data, regionalization in hydrology is generally used. Efficient data transfer can be performed by dividing the region into homogeneous areas. In the present study, cluster analysis method was employed to divide different hydrological areas into homogeneous areas. Using factor analysis, the importance of independent variables such as, area, average annual rainfall, average height, and basin slope was determined. Based on the homogeneity test by cluster analysis method, two hydrologic homogeneous areas were determined. Using flood mark and multiple regression methods, two models for the region and homogeneous areas were obtained. The accuracy and performance assessment using models were compared with the three control areas and maximum value discharge in the study area. The relative mean absolute error index was used for the comparison. Results show that homogeneous areas have a higher determination coefficient and lower standard error than the models. In addition, when the return period increased, R2 and SE values also increased. Comparative results between the relative error models in homogeneous areas show that the amount of error in homogeneous areas is less than that of the whole region. The study confronts the limitation of less data usability to estimate the longer return period values, developed a homogeneous regional model for the case study, as well. key words: Cluster analysis, Homogeneity, Regional analysis, Classification.