22-06-2013, 03:16 PM
Mapping and Prediction of Surface Run-off using SCS-CN Method
Mapping and Prediction.doc (Size: 1.86 MB / Downloads: 31)
Abstract:
The hydrological gauging stations are sparse in India, thus most of the catchments remain ungauged. In absence of rainfall and discharge data for such catchments the hydrological process remain a black box. In this research study, estimation of daily flood discharge for small ungauged watersheds has been carried out using Soil Conservation Services-Curve Number (SCS-CN). The research catchment Varekhadi is about 442 km2 and is a part of Lower Tapi basin in Western India. The catchment has been delineated into five sub-watersheds using BASIN model based on digital elevation model (DEM) at 30m cell size. Earlier the DEM was prepared using Survey of India Topo-sheets of 1:50,000 scale and global positioning system (GPS) based survey at selected location. Accuracy estimates on DEM were carried out through field check which shows mean accuracy of 3.0m for Amli, Zankhwaw, Visdaliya, Godsambha and Wareli. Hydrological parameters required for the model such as hydrological soil group, land use and incidence soil moisture were prepared in GIS and remote sensing software. First the field samples were collected; later laboratory analysis was carried out using proctor test and sieve analysis for determination of soil group falling under group B and group C of soils. Landsat 7ETM+ image band 2, 3, 4 have been merged with PAN band 8 [15m] for classification of land use. A supervised classification approach using maximum likelihood classifier has been employed for preparation of land use map and topographic map is used for verification. The final classification shows good compromise between actual and classified image.
Introduction:
Most of the watersheds in India are ungauged, having no past records of the rainfall-runoff process. There are several flow estimation methods for ungauged catchments such as rational method, SCS-curve number method, cook’s method and unit hydrograph method. The Soil Conservation Service developed curve number method for predicting direct runoff or infiltration from rainfall excess of ungauged watershed. Soil and landuse parameters which control surface runoff can be evaluated and mapped significantly through Landsat Thematic Mapper (Sharma K D et al. 1992). Remote sensing and GIS techniques are widely used in the determination of spatial distribution of the catchments ecosystem characteristics and their impact on catchments hydrology (Tekeli Y I et al, Sharma et al. 2001). ArcCN tool developed and applied SCS-CN method for estimating run-off and preparing CN and run-off maps (Zhan X et al, 2004). Effect of Land cover change on runoff curve number estimation is also being studied for (Wehmeyer L L et al ,2010).
Soil Conservation Service (SCS) model has been applied in the present study for the estimation of flood discharge from small watershed Varekhadi, a tributary of Lower Tapi Basin. The research watershed is about 442 km2, is situated near Mandvi in Surat district. This method involves various types of information related to land-use, Hydrologic Soil Group. Eradas 9.1 and ArcGIS 9.2 (ArcCN tool) software was used for the rectification soil and land use map and also to derive SCS Curve Number (CN) for study area.
Basin Description:
The study area for estimation of surface run-off is Varekhadi sub-watershed of Lower Tapi Basin in India. Varekhadi sub-watershed is a tributary of Tapi River located near Mandvi and is 40 km upstream of Surat city as given in Figure 1. As discussed above that research area has been a part of Lower Tapi Basin in Gujarat State, India. The length of Varekhadi tributary is approx 50 km, having a geographical area is 442 km2 (figure 1). The sub-watershed consist of 1 urban centre zankhwaw, 150 rural villages, and 2 major storage reservoirs Issar and Amli dams located in the study area. The dam storage is mainly used for flood control during monsoon and for irrigation post-monsoon season through artificially built side slope canals. The right bank canal from Kakrapar weir located 30km upstream also passes through sub-watershed which is predominantly used for irrigation.
Generating Landuse/Landcover map
The Landuse/Landcover map of Varekhadi watershed has been generated be remote sensing satellite data. The image of Landsat-7 ETM+ (10 Nov 2001) Band 2,3,4 with 30 meter spatial resolution and PAN with 15 meter ground resolution have been selected for landuse/landcover mapping. FCC image has been merged with PAN band and got new FCC image with 15 m Resolution. Image geometric correction has been done and land use/ land cover map derived using supervised classification with field sample. Land use/Land cover categories in the study area are built-up land, agriculture, forest, fellow land, water bodies and other as shown in figure 2(a) and statistics in table 1.
Generating CN map
The Arc CN extension of ArcGIS was used to generate the CN map of Varekhadi watershed. The hydrologic soil group field from the soil map and the land use field from the land use map were selected for intersection. After intersection, a map with new polygons representing the merged soil hydrologic group and land use (land-soil map) was generated. After this process the appropriate CN value was assigned for each polygon of the Land-Soil map figure 2©.
Conclusion
The SCS-CN method has been used for surface run-off estimation for a part of Lower Tapi Basin and it gives good results for rainfall-runoff modeling. It will be useful for flood forecasting, flood contribution of each watershed and flood discharge measurements. It will be verified to with real discharge data and other methods. For lower tapi basin and un-gauged catchment this method may be good tool for runoff estimation. The effect of climatic parameter on runoff has been observed by changing certain parameters in landuse and rainfall. Runoff was reduced while converting agricultural land into built up land. Rainfall- runoff relationship was also established which was produced by considering rainfall of last 10 years.