Development and validation of surface water yield model (SWYMOD) for fitting curve numbers of different land uses in micro-watershed of Ranga Reddy district, Telangana

Abstract

A surface water yield model (SWYMOD) was developed and validated by integrating SCS CN method and on-farm reservoir (OFR) water budgeting with the objective of generating CN (Curve Number) values of land uses of agriculture, forest and farm roads in a micro watershed of 14.5 ha area in Ranga Reddy district of Telangana state, India. The watershed is provided with on farm Reservoir (OFR) as storage structure for monitoring the daily water balance components of runoff, seepage and evaporation on daily basis. The watershed covers agriculture (7 ha), forest (7 ha) and farm roads (0.5 ha) with Alfisols as major soil group. The model was developed based on iterative procedure of estimating runoff as storage depth in OFR with the criterion of model efficiency (ME>90%) calculated using observed and simulated OFR storage depths. The model requires input file of date, rainfall, observed water loss, storage depth, seepage and evaporation on daily basis. The model was calibrated with the observed data of 2008 for initial abstraction (Ia = 0.2S, 0.25 S and 0.3 S) and validated with 2009 and 2010 observed data. The initial abstraction of Ia=0.2 S was found to have the maximum ME of 94.48% as compared to Ia=0.25 S and 0.3 S for the set of CN values of 67, 33 and 72 for agriculture, forest and farm roads with weighted curve number of 49 which is less than the other initial abstraction values. SWYMOD was validated with two years of observed data of 2009 and 2010 with ME of 95% indicating close agreement with observed and simulated water storage depth hydrographs of OFR. These curve numbers fixed by the SWYMOD are found to differ from SCS CN values for AMC II condition of micro-watershed. This study indicates the necessity of generating CN values with changed rainfall pattern in semi arid areas in view of climate change for accurate estimation of water yield/runoff and optimizing the design parameters of rainwater harvesting structures like OFR.