The most basic challenges of hydrology are the prediction and quantification of catchment surface runoff. Surface runoff information is required for watershed management purpose. It is a function of many variables including rainfall intensity and duration, soil type, soil moisture, land use, cover, and slope. In the study runoff was estimated using two models in Upper Krishna river basin, Maharashtra. NRCS-CN method and SHETRAN model was used to find runoff depth.
Monthly Runoff was calculated using NRCS-CN model and daily runoff computed for each catchment using SHETRAN for the year 2012. Landsat 7 (with resolution 30 m) satellite data for the year 2012 has been used for the preparation of land use land cover (LU/LC) map. The hydrologic soil group is mapped using GIS platform. SHETRAN, requires more number of parameters to run the model while NRCS-CN method involves the use of a simple empirical formula and readily available tables and curves. Both model used Land use map and soil data as main input. Validation was done using measured runoff recorded in discharge gauge stations. Results of the study show that land use changes determined from satellite images are useful in studying the runoff response of the un-gauged basins. Study reveals that there is no significant difference between measured and estimated runoff depths. Using NRCS-CN method for each sub-catchment, statistically positive correlations were detected between observed and estimated runoff depth (0.6