Application of NRCS CN rainfall-runoff modelling using GIS and remote sensing technology in esen river basin

Natural Resources Conservation Service (NRSC) method is one of the rainfall-runoff method which was developed by United States Department of Agricultural (USDA). In this case NRCS method is used for estimating the flood peak from rainfall data. This rainfall data, between 1967-1986 is obtained by DSİ and DMİ meteorological gauged stations used as input data in NRCS method and is also avaiable as daily, monthly and yearly. Estimating the flood peak from CN numbers, watershed characteristics will be determined. The CN number is essential to estimate the peak discharge and it is accomplished with using the soil type, land use and antecedent moisture condition (AMC). Determining this pyhsical area characteristics is possible using GIS and remote sensing (RS) technologies. RS and GIS are efficient tools in rainfall and runoff analysis. Land use data can be created by Erdas Imagine software which is a kind of remote sensing technology. Using the multitemporal Landsat satellite image of the study area is classified with Erdas Imagine. The average value of curve number for all sub-basins were calculated by assigning weights with area of land use classes. Remote sensing technology can provide conventional methods in rainfall-runoff studies. The other characteristics like the area, slope, aspect, flow length data and calculating the drainage network is possible to estimate with using ArcGIS software from topographic map. Evaluation of the results for this study distinct all of these watershed characteristics, the antecedent moisture condition (AMC) is calculated from 5 day prior rainfall. This parameter effects the flood peak seriously if the soil is under "low", "average" and "high" condition. These 3 of antecedent moisture condition may affect flood peak variability. In addition to antecedent moisture, such deterministic influences included storm duration, intensity distribution and seasonal variations. An another result of this study, the SCS CN method can be applied to large watersheds with multiple land uses but the smaller or mid-sized catchments are more avaiable to give the favorable values.