Davood Mokhtari; Arash Zandkarimi; Sheida Zandkarimi
Volume 3, Issue 8 , December 2016, , Pages 53-72
Abstract
Received: 2015.07.09 Accepted: 2016.10.19 Davood Mokhtari[1]* Arash Zandkarimi[2] Sheida Zandkarimi[3] Abstract Rainfall is counted as the main entrance in hydrologic modeling. Efficient network of the rain gauge stations are the ones having an appropriate density and favorable estimations of rainfall ...
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Received: 2015.07.09 Accepted: 2016.10.19 Davood Mokhtari[1]* Arash Zandkarimi[2] Sheida Zandkarimi[3] Abstract Rainfall is counted as the main entrance in hydrologic modeling. Efficient network of the rain gauge stations are the ones having an appropriate density and favorable estimations of rainfall in locations without any station. In order to optimize the position of the rain gauge stations, different methods have been proposed, among which the geo-statistical methods are widely used. The present study aimed to assess the status of the rain gauge stations of Kordestan Province, and to optimize their position based on geo statistical methods. In this study, in order to evaluate the accuracy of various interpolation methods, the Ordinary Kriging method with circular function was detected to be more credible compared to other models and that it was the most suitable interpolation method in the distribution of rainfall in the province. Furthermore, in order to optimize and estimate the errors of the current stations, the precipitation data from 145 meteorological stations were used, and given the sheer size of the study area and great changes to rainfall data, area segmentation or clustering of the stations was done, and the whole area was divided into 8 clusters. The results of the optimization based on the Kriging coefficient of variation indicated that, by the addition of new 17 proposed stations to the rain gauge network in the province, the values of spatial coefficient of variation of annual rainfall has decreased between 0.21 to 6.67 percent, and close to 12% from the central to the south, and in western areas, respectively. The results of this study have a great importance on the use of geo-statistical methods in optimization, and the generated maps are of high practical value for the executive agencies (Ministry of Energy, the National Weather Service, etc.). [1]- Associate Professor Professor Department of Geomorphology, University of Tabriz (Corresponding Autor), Email:d_mokhtari@tabrizu.ac.ir. [2]- Master Student Remote Sensing, University of Tabriz . [3]- M.A. Land Use-Environmenta, University of Payam Noor Tehran East.
