ESTIMATION OF RUNOFF FOR BINA RIVER BASIN USING CURVE NUMBER MODEL AND GIS TECHNIQUES

Abstract

Rainfall-Runoff computation of any basin plays a vital role in development of the water resources project of any country. Looking on the industrial importance of Bina river basin situated in Central India, this basin was selected for rainfall-runoff modeling by implementing the SCS CN conceptual model with the variation in initial abstraction ratio value, along with the GIS tool. Runoff assessment is carried out using daily rainfall data, gauge-discharge data, meteorological data of Bina river basin, India. A new trial was made to estimate the runoff more precisely by varying the Initial Abstraction Ratio for the Bina river basin. The Bina catchment area of 1120 km2 has all over hydrologic soil type C & D, which indicates high runoff potential on ground. Results specify a initial abstraction ratio (λ) value of 0.20 gives a better fit to the data and proved to be more precise for use in runoff calculations in comparison to λ = 0.1, 0.15 and 0.25. The model was evaluated on the Nash-Sutcliffe Efficiency criteria and the coefficient of determination (R2 ) for the years 1997, 1998, 2003 and 2007. The model showed Nash-Sutcliffe efficiency in the range of 0.70 to 0.90 and R2 values in the range of 0.71 to 0.94. The Composite Curve Number came out to be 77 for the basin. It was concluded that initial abstraction ratio λ = 0.1, 1.15 results in slight over prediction for this catchment while λ = 0.25 slightly under predicts the runoff. This research study indicates that the SCS CN model when employed with GIS tool becomes more useful for the hydrological study of any basin having hydrologic soil group C & D, with customary value of λ = 0.2.