Spatio-temporal runoff estimation using TRMM satellite data and NRSC-CN method of a watershed of Upper Subarnarekha River basin, India

Abstract

Geographical Information System (GIS) and Remote Sensing (RS) have acquired great significance in the recent years for estimation of runoff from watersheds and agricultural fields. This study has made use of the well-established tool, Natural Resources Conservation Service Curve Number (NRCS-CN) method to observe runoff over the study area in conjunction with GIS and RS. Pixel-wise runoff depth of the catchment was estimated by incorporating Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) data, Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis data for the years 2001–2011, and Landsat Enhanced Thematic Mapper (ETM)+ Land Use/Land Cover (LULC) information within the simple rainfall-runoff model. NRSC-CN was modified for Indian condition and the Hydrologic Engineering Center’s Geospatial Hydrologic Modeling System (HEC-Geo-HMS) extension was utilized for evaluating the Curve Number (CN). Rainfall-Runoff model was executed to compute pixel-wise runoff, utilizing the model builder interface of ARC GIS 10. It was observed that there had been an increase in the average runoff depth ranging from 2.25 to 2.48 mm in different micro-watersheds of the study area. There was also an increase in total runoff depth from 61.24 to 68.47 m following an increase in mean CN value from 55 in the year 2001 to 57 in the year 2011. This indicated a lesser increase in lower runoff level range and a greater increase in higher runoff level range. In terms of runoff within the watershed, a higher percentage of its micro-watersheds showed lower runoff range compared to the micro-watersheds with higher runoff range. A direct correlation was observed between reduction in agriculture with increased runoff, increase in open land, and decrease in vegetation.