Review the Effect of Classification Algorithm of Satellite Images on the Runoff Curve Number and Maximum Flood Discharge by the Assistance of GIS and RS

Land use is an important feature in run off process, which affects on permeation, erosion, evaporation and transpiration. In this study, the effect of classification algorithm of satellite images of land use maps and run off curve number and also flood discharge with the help of GIS and RS have been reviewed. This study has been conducted on Mansourabad Birjand catchment area and with the assistance of land sat 7 (ETM+) satellite images. Land use map was determined by maximum probability algorithm, minimum distance and Mahalanobis distance by the use of satellite images. Then vegetation cover map was prepared by the help of NDVI index and the map of soil hydrology group by using soil, geology and topographic maps. Through incorporating the maps of land use, vegetation cover and soil hydrology group in GIS and by the use of SCS table, the maps of run off curve number for each of algorithms were determined.Further, for evaluating the correctness of the obtained curve number from each algorithm, maximum flood discharged by the use of HEC-HMS modle was calculated and compared with the measured values. The results showed that maximum probability algorithms and Mahalanobis distance with rating Kappa coefficient of 0.7 and 0.65 accordingly and discharge correctness of 80% and 72% with the measured results are the best methods for classifying the satellite images. Also, this study showed that changing classification algorithm has a very high effect on the curve number and flood discharge