Rainfall-runoff estimation for a catchment is of vital importance in most of the hydrologic analysis for water resources planning. This study envisages the rainfall-runoff modeling using MIKE 11 NAM model in Vinayakpur intercepted catchment in Chhattisgarh state. The model was calibrated using measured stream flow data for the period 2001 to 2004 and then validated from period 2005 to 2007. The calibration and validation procedures were carried out to provide a satisfactory estimation. The simulated runoff occurred maximum in August (1681.63 cumecs) and minimum in April (84.14 cumecs). The outputs of the calibrated model were used in water resources management model viz., MIKE basin as they normally work based on monthly flows with a large time horizon. The optimum values of nine NAM model parameters obtained during calibration procedure were used for simulation. The reliability of MIKE 11 NAM was evaluated based on Nash-Sutcliffe coefficient, correlation coefficient (r 2) and root mean square error (RMSE). The R 2 value of model calibration and validation were observed to be 0.79 and 0.75, respectively.
SUMMARYLong-term field experiments were conducted at Agra, Solapur and Hisar from 2000 to 2008 to identify efficient tillage and nutrient management practices and to develop predictive models that would describe the relationship between crop yields and monthly rainfall for rainfed pearl millet grown on arid and semi-arid Inceptisol, Vertisol and Aridisol soils. Nine treatments comprising a factorial combination of three tillage practices, viz., conventional tillage (CT), low tillage + interculture (LT1) and low tillage + herbicide (LT2) and three fertilizer treatments viz., 100% N from an organic source (F1), 50% organic N + 50% inorganic N (F2) and 100% inorganic N (F3) were tested in a split-plot design at the three locations. Studies revealed that tillage and fertilizer treatments, and their interactions, significantly influenced pearl millet grain yields at the three locations. Prediction models describing the relation between grain yield and monthly rainfall indicated that rainfall occurring in June, July and August at Agra; June and July at Solapur; and June and August at Hisar significantly influenced pearl millet grain yield attained by different treatments. The R2 values of the model ranged from 0.64 to 0.81 at Agra; 0.63 to 0.92 at Solapur, and 0.75 to 0.89 at Hisar. When averaged over all the treatment combinations, mean pearl millet grain yields varied from 1590 to 1744 kg ha−1 at Agra; 1424 to 1786 kg ha−1 at Solapur; and 1675 to 1766 kg ha−1 at Hisar while their corresponding sustainability yield indice (SYI) varied from 35.4 to 42.2%, 19.9 to 45.6% and 64.1 to 68.3%, respectively. At Agra (Inceptisol), CTF3 resulted in significantly higher mean net returns (Rs 11 439 ha−1), benefit-cost ratio (2.33), rainwater use efficiency (RWUE) (3.52 kg ha−1 mm−1) and the second best SYI (39.9%). At Solapur (Vertisol), the LT1F3 resulted in significantly higher net returns (Rs 12 818 ha−1), benefit-cost ratio (3.52), RWUE (3.89 kg ha−1 mm−1) and the fourth best SYI (42.6%). At Hisar (Aridisol), the LT1F3 treatment gave higher net returns (Rs 3866 ha−1), benefit-cost ratio (1.26), RWUE (5.05 kg ha−1 mm−1) and the fourth best SYI (67.8%). These treatment combinations can be recommended for their respective locations to achieve maximum RWUE, productivity and profitability.
River basin planning and management are primarily based on the accurate assessment and prediction of catchment runoff. A continuous effort has been made by the various researchers to accurately assess the runoff generated from precipitation by developing various models. In this paper conceptual hydrological MIKE 11 NAM approach has been used for developing a runoff simulation model for Arpasub-basin of Seonath river basin in Chhattisgarh, India. NAM model has been calibrated and validated using discharge data at Kota gauging site on Arpa basin. The calibration and validation results show that this model is capable to define the rainfall runoff process of the basin and thus predicting daily runoff. The ability of the NAM model in rainfall runoff modelling of Arpa basin was assessed using Nash–Sutcliffe Efficiency Index (EI), coefficient of determination (R2) and Root Mean Square Error (RMSE). This study demonstrates the usefulness of the developed model for the runoff prediction in the Arpa basin which acts as a useful input for the integrated water resources development and management at the basin scale.
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