Application of remote sensing and GIS techniques in SCS-CN model (Case Study: Balarood Basin, Khuzestan)

Abstract

One of the main problems in flood predicting is often lack of hydrological and climatic data in most basins of Iran. Soil Conservation Service Curve Number (SCS-CN) method is used to estimate the maximum flood discharge in the ungauged basins. In this study, the runoff height and the maximum flood discharge were estimated by SCS-CN method in Balarood Basin on Khuzestan Province of Iran. Firstly, geometric correction, enhancement and nearest neighbor algorithm of object-oriented classification on Landsat 8 satellite’s OLI sensor images were used to prepare the land use maps. Then the soil hydrological groups and curve number (CN) were determined for each sub-basin using land use map. Finally, the runoff and maximum flood discharge of the basin were estimated by SCS-CN method. The results indicated that the Balarood basin had three soil hydrological groups A, B, and C, with 60.64, 11.62, and 27.74% respectively. The CN of the basin was 62.81. The maximum soil water retention (S) of Dokohe, Anarki and Mongareh sub-basins and the basin calculated were 7.5, 16.8, 17, and 15 cm respectively. The height of runoff and maximum flood discharge of them were estimated 0.05, 0.06, 0.73, 0.12 cm and 71, 67.2, 435, 282.1 m3/s respectively. The results also demonstrated the good efficiency of remote sensing and GIS techniques in study on SCS-CN method.

Keywords

• balarood basin
• gis
• nearest neighbor algorithm
• object-oriented classification
• runoff