Simulation of Water Balance Components Using SWAT Model at Sub Catchment Level

Abstract

Simulation of Water Balance Components (WBCs) is import for sustainable water resources development and management. The Soil Water and Assessment Tool (SWAT) is a semi-distributed hydrological model to estimate the WBCs by forcing the hydrological response unit (HRU) and meteorological variables. The developed model simulates five WBCs viz. surface runoff, lateral flow, percolation, actual evapotranspiration and soil water at sub catchment level. To demonstrate the model compatibility a case study taken over Chittar catchment, Tamilnadu, India. The catchment was divided in to 11 sub catchments. The ten year interval LULC (i.e., 2001 and 2011), twenty year daily meteorological data (i.e., 2001–2020) and time invariant soil and slope data were used in developing the water balance model. Developed model was calibrated and evaluated with river gauge monthly discharging using SUFI-2 algorithm in SWAT-CUP. The model calibration performed in two stage i.e., pre-calibration (2001–2003) and post-calibration (2004–2010). The model performance was evaluated with unseen river gauge discharging data (i.e., 2011–2015). Then, results of statistical outputs for the model were coefficient of determination (R2) is 0.75 in pre-calibration, 0.94 in post-calibration and 0.81 in validation. Further strengthen the model confidential level the sub catchments level monthly actual evapotranspiration were compared with gridded global data GLEAM v3.6a. Finally, the developed model was simulate the five WBCs whereas, surface runoff, lateral flow, percolation, actual evapotranspiration and soil water at sub catchment level during 2001–2020. The sub catchment level WBCs trend helps to make fast and accurate decision. At all 11 sub catchments a long drought was observed during 2016–2018 due to failure of northeast monsoon. The WBCs were directly reinforced by their north east monsoon which gives the major portion of rainfall i.e., September to December. Hence all the WBCs were directly correlated with rainfall with or without time lag. By understanding the sub catchment level of monthly WBCs over the Chittar catchment is useful for land and water resource management.