a prediction model for assessing special discharge a case study:fars province,iran

Fars province in Southern Iran has been selected as a test area to develop a statistical model for predicting the special discharge using different parameters which affect discharge amount. The special discharge data were gathered at 30 hydrometric stations at outlet of different basins in the study area. The data as effective parameters on discharge have been gathered from the records, reports and mainly maps produced by the different departments of the Ministries of Agriculture and Energy of Iran. The GIS analysis of various parameters and discharge data considered proved useful for understanding their relationship in a statistical software. To find a regression equation, average of special discharge for each basin has been considered as dependent variables while the effective parameters on discharge including ten morphometric parameters, fourteen physiographic parameters, two climatic parameters, two soil parameters, one vegetation parameter and one geology parameter are considered as independent variables. For this purpose, the regression equations for two methods of ‘enter’ and ‘stepwise’ in software of SPSS have been established. The linear regression equations define the variations of the special discharge depending on the parameters and also give an idea about the levels of relations. The results obtained show that the relations between the special discharge and some parameters especially rainfall data and some physiographic parameters do exist.