26. Analysis of Spatio-Temporal Pattern of Runoff at National Level Derived Using Remote Sensing Data and Curve Number Approach

An attempt has been made to analyse the spatial and temporal pattern of runoff computed through SCS-CN moel using multi-data remote sensing data and soil and weather parameters. The CN method was incorporated in Geographical Information System (GIS) cell based modelling. The Normalized Difference Vegetation Index (NDVI) images of Spot Vegetation sensor were used in this study. Temporal data acquired at monthly interval were processed to arrive at hydrological land cover classes. Climatological rainfall data of 376 stations spread over the mainland were used to generate monthly rainfall pattern through the Inverse Square Distance interpolation technique. Irrigation Atlas at 1 million scale prepared by Survey of India were used to derive basin and sub basin boundaries. Soil texture map was derived from Survey of India's National Agricultural Atlas. The analysis showed that highest runoff depth (1812 mm) was observed in Brahmaputra basin. Lowest runoff was observed in Rajasthan and Saurashtra basin, which was about 210 mm. Four months starting from July accounted for ninety per cent runoff in almost all basins. Brahmaputra, Narmada and Mahanadi basin responded very well to the rainfall, i.e., high runoff coefficient, whereas, very low runoff coefficient is found in Cauvery and Pennar. The paper describes the methodology and results obtained for each basin. The advantage of using satellite remote sensing data for such large area studies, particularly in spatial domain are highlighted.