Geospatial Technique for Runoff Estimation Based on SCS-CN Method in Upper South Koel River Basin of Jharkhand (India)

Jharkhand state is characterized by plateau terrain and facing sever water scarcity largely on account of high runoff generated by adequate annual rainfall of about 1400mm per year. The run-off is one of the important hydrologic variables used for assessment of potential water yield of a watershed and appropriate measures for ground water recharging. The quantity and rate of runoff is influenced by rainfall parameters and conjointly by many alternative watershed factors viz., kind of construction of catchment, physical nature of the soil, distribution and type of vegetative cover, degree and length of slope, shape form and size of watershed. When the speed of precipitation exceeds the speed at that water infiltrates into the soil considered as runoff. Run-off volume and also the runoff rate will increase as watershed size will increase [1]. SCN based rainfall-runoff model are mostly used for computation of runoff [2] as compare to conventional techniques i.e expensive and need hydrological and meteorological data measurement. The rainfall-runoff studies by conventional techniques enhance to large extent because of remote sensing tools and technologies. Interpretation of satellite data help us to demarcate thematic information on land use, soil, vegetation, drainage, hydrogeomorphology etc that combined with rainfall parameter and topographic parameters (slope, contour and height) provide the crucial inputs data during rainfall-runoff models computation. Geo-referenced database is prepaired in Geographical data system (GIS) based on information extracted from remote sensing and different sources .Therefore, the utilization of a GIS is most popular over the conventional techniques for deduce surface run-off and analyzing the factors accountable for runoff. The runoff information in Jharkhand is very scarce because of dominantly forest covered regions and only available at few limited sites. Also, the majority of the agricultural watersheds in India are ungauged, having nil historical records of the rainfall-run-off processes [3]. In the Jharkhand with dominantly forest lined regions the correct info on run-off is scarce and present at very limited sites. There are various models used for runoff estimation some of them are SWAT model i.e soil and water assessment tools, autoregressive integrated moving average(ARIMA), Seasonal autoregressive integrated moving (SARIMA) model, artificial neural network, fuzzy model and SCS-CN model etc was used for long term runoff forecasting. Among the various methods used for rainfall-run-off estimation, the soil conservation service curve number [4] (renamed as natural resources conservation services curve number (NRCSCN)) (USDA 1994) technique has been mostly applied to ungauged watershed systems to establish the rainfall-run-off relations [5,6] and proved to be accurate and fast for surface runoff estimation [7]. This approach is cheap, simple to use through minimum information and provides adequate results [4-10].The NRCS-CN technique is largely accepted by scientists, forester’s hydrologists, water resources planners and engineers meant for the estimation of surface run-off. Bhuyan et al. [11] used the modified curve number (CN) technique designed for predicting surface run-off by adjusting the CNs based on expected Antecedent moisture Condition (AMC) ratio. Daily storm events data was used to estimate run-off using NRCS-CN technique [12] in the Damodar Barakar catchment in Jharkhand, India. Many regions in Jharkhand are drought prone with unpredictable rainfall pattern, rendering kharif crops mostly susceptible to agricultural drought during the rainfall period [13]. Because of hard rock undulating terrain most of the rainfall water goes as runoff and therefore, rainwater move down slope and inadequately recharge Volume 1 Issue 7 2017