Abstract

For rainfall-runoff modelling in the river-reservoir integrated catchment-command areas, the use of the Soil and Water Assessment Tool (SWAT-2012) is limited due to improper description of crop-field dynamics in the model framework. To model the dominant paddy-field hydrology in most of the catchments in Asian countries with tropical monsoon-type climatology, SWAT couples a pothole module in place of the conventional Curve Number (CN) approach. Although few pothole modules exist in the literature, their conceptual frameworks have a number of calibration parameters which could generally increase the model uncertainty with the underestimation of high flows and overestimation of low flows. To account for the physical dynamics of water transport in paddy fields, in the rainfall-runoff transformation process of a catchment, this study advocates an enhanced pothole approach integrated with the SWAT considering the sub-surface soil moisture movement under ponding and drying soil conditions, evapotranspiration flux under alternate wetting and moisture stress conditions, and contribution of irrigation return flow from the paddy fields. Subsequently, the enhanced SWAT-Pothole approach (SWAT-EP) was evaluated in the Kangsabati River catchment-reservoir-command (12,014.70 km2) in the eastern India. The results reveal that the proposed enhanced model performed the best as compared to the existing SWAT-Pothole approaches and the conventional SWAT-CN approach in modeling the catchment response and evapotranspiration flux. Moreover, the proposed approach is more parsimonious, with 17 numbers of initial calibration parameters as compared to 25 parameters in the existing ones. The performance evaluation measures and quantile regression based uncertainty analysis reveal that the proposed SWAT-EP pothole model has the best performance in reproducing both the high and low flow estimates, actual evapotranspiration, as well as overall streamflow hydrodynamics with a scope of wider applicability in many world-river catchments.

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