Prioritization of Morphometric Factors Influencing the Creation Alluvial Fans Southern Slopes of Alborz, in the Semnan Province, Using Multivariate RegressionModels

Subject Areas : forest

عیسی Jokar sarhangi ¹ (دانشیار گروه جغرافیا دانشگاه مازندران)
رضا Esmaeili ² (استادیار گروه جغرافیا ، دانشگاه مازندران)
سمیه Fakhroddin ³ (دانشجوی کارشناسی ارشد ژئومرفولوژی دانشگاه مازندران)

Received: 2015-08-27 Accepted : 2016-07-16 Published : 2017-01-22

Keywords: multiple regression, alluvial fans, Morphometry, southern slope Alborz,

Abstract :

  There are relations between water basins and alluvial fans as important forms in arid and semi an arid region which show the dimensions of alluvial fans and also indicate the impacts of different factors in the formation of alluvial fans quantatively. With respect to the fact that the dimensions of alluvial fans are under influence of their  morphometric factors of watershed basins; this research used morphmetrical  features to find the most suitable model in the southern slops of  Alborz Semnan province. For this purpose, 44 water basins and alluvial fans associated with them were determined using 1:500000 topographic maps. Also for more accuracy Google Earth Pro6 software, were used. In the next stage, 11 watershed physiographic characteristics were obtained including: area, perimeter, mean of height, elevation, gradient, basin length, total length of waterways, and length of the main channel, basin shape coefficient, main channel gradient, and drainage density with the help of Geographic Information System (GIS). Then relationship between alluvial fans Dimension as a dependent variable with the quantities of basin morphology as independent variables were analyzed using SPSS software and multiple regression. The results indicate that  among the independent factors,  the variables of area, perimeter, length, area, channel length, main channel length and the density of water drainage basins, had the most influence on the development of alluvial fans respectively and able to find a regression model.

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