Document Type : Research Paper
Authors
1 Scientific Board, Soil Conservation and WatershedManagement Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran
2 Associate Professor, Soil Conservation and WatershedManagement Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran
Abstract
Estimating the runoff coefficient that is influenced by morphometric, geologic and hydro-climatologically factors are the most important issues in hydrology and information of its role in the planning and management of water resources is more important. Clustering catchments is the best method for the analysis of hydrological parameters in the absence of full coverage of hydrological data. In this research, twenty two hydrometric stations with common period from 1974 to 1999 were selected. Physiographic parameters of the catchments were extracted. Runoff coefficient was calculated and then base flow was extracted from using one parameter recursive digital filters. Lithological units using digital geological map, with the scale of 1: 250,000, based on expert opinion divided on two classes and area covered by each unit in each catchment were calculated. Factor analysis using 15 parameters were conducted. Catchments using independent factors in different hierarchy methods includes: nearest neighbor, furthest neighbor, median clustering, centroid clustering and Ward method were classified. Then, the regional equations using linear regression at 1% significant level were determined. To compare and evaluate the accuracy and efficiency of the models, independence errors, colinerity and normal distribution of error were tested. The results of factor analysis showed that all variables are to be classified in terms of five factors which 85.9% of the variance was included. Results of homogeneity showed that the basins in homogeneous methods of nearest neighbor, furthest neighbor, centroid clustering and median clustering, were all the same and classified in two groups with the similar components. The results of accuracy assessment showed that the accuracy of nearest neighbor methods was more accurate, and because of low relative error (25.4%) and MAE of 7.85 and RMSE of 9.62 was diagnosed as the best method for regional analyzing of runoff coefficient in the study area.
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