A comparative study of conceptual rainfall-runoff models GR4J, AWBM and Sacramento at catchments in the upper Godavari river basin, India
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Accurate catchment level water resource assessment is the base for integrated river basin management. Due to the complexity in model structure and requirement of a large amount of input data for semi-distributed/distributed models, the conceptual models are gaining much attention in catchment modelling these days. The present study compares the performance of three conceptual models, namely GR4J, Australian Water Balance Model (AWBM) and Sacramento for runoff simulation. Four small catchments and one medium catchment in the upper Godavari river basin are selected for this study. Gap-filled daily rainfall data and potential evapotranspiration (PET) measured from the same catchment or adjacent location are the major inputs to these models. These models are calibrated using daily Nash–Sutcliffe efficiency (NSE) with bias penalty as the objective function. GR4J, AWBM and Sacramento models have four, eight and twenty-two parameters, respectively, to optimise during the calibration. Various statistical measures such as NSE, the coefficient of determination, bias and linear correlation coefficient are computed to evaluate the efficacy of model runoff predictions. From the obtained results, it is found that all the models provide satisfactory results at the selected catchments in this study. However, it is found that the performance of GR4J model is more appropriate in terms of prediction and computational efficiency compared to AWBM and Sacramento models.
KeywordsRainfall-runoff model GR4J AWBM Sacramento Source calibration
The authors would like to acknowledge the Water and Land Management Institute (WALMI), Aurangabad, the Godavari Marathwada Irrigation Development Corporation (GMIDC), Aurangabad and eWater, Australia, for providing necessary data for this study. The authors are thankful to WALMI and GMIDC for funding a project related to the present study. We gratefully thank suggestions of Dr Carl Daamen (eWater) and Dr Avinash Garudkar (WALMI) that have significantly improved this study.
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