Gupta, PK, Panigrahy, S (2008). Predicting the spatio-temporal variation of run-off generation in India using remotely sensed input and Soil Conservation Service curve number model. CURRENT SCIENCE, 95(11), 1580-1587.
The Soil Conservation Service curve number (SCS CN) model has been used in the GIS environment to compute run-off at spatio-temporal scales using remote sensing-derived rainfall for 2004 and climatic normal (1951-80) rainfall data. The SCS CN model takes into account land use/land cover, antecedent soil moisture condition and hydrological soil groups. Temporal 10-day composite Normalized Difference Vegetation Index images of SPOT-VGT sensor, and daily remote sensing-derived rainfall data at 10 km resolution from the NOAA Climate Prediction Centre have been used to generate the land cover and antecedent moisture condition (degree of saturation) respectively. Hydrological soil groups were prepared using the soil texture and their infiltration and drainage characteristics. Run-off coefficient maps were generated using the CN-based rainfall excess run-off. Wetland rice-growing areas of West Bengal, India were used to calculate threshold run-off coefficient (0.2) to identify run-off potential areas for major river basins of India during the monsoon season (June to September). There was a large difference in the spatial pattern of run-off estimated for the year 2004 compared to using normal climatic rainfall data. Area estimates for run-off potential were also found to vary significantly for the climatic normal and in-season (2004) data. The spatial variability showed high run-off potential in the western India river basins like Mahi, Luni, rivers of Saurashtra and Sabarmati in 2004. Run-off potential areas over India have been found to increase abruptly from June (158,700 km(2)) to July (712,300 km(2)), and decrease from August (633,400 km(2)) to September (142,000 km(2)) during 2004.