Comparative evaluation of conceptual and physical rainfall–runoff models

R. K. Jaiswal, Sohrat Ali, Birendra Bharti
2020 Applied Water Science  
The design of water resource structures needs long-term runoff data which is always a problem in developing countries due to the involvement of huge cost of operation and maintenance of gauge discharge sites. Hydrological modelling provides a solution to this problem by developing relationship between different hydrological processes. In the past, several models have been propagated to model runoff using simple empirical relationships between rainfall and runoff to complex physical model using
more » ... ysical model using spatially distributed information and time series data of climatic variables. In the present study, an attempt has been made to compare two conceptual models including TANK and Australian water balance model (AWBM) and a physically distributed but lumped on HRUs scale SWAT model for Tandula basin of Chhattisgarh (India). The daily data of reservoirs levels, evaporation, seepage and releases were used in a water balance model to compute runoff from the catchment for the period of 24 years from 1991 to 2014. The rainfall runoff library (RRL) tool was used to set up TANK model and AWBM using auto and genetic algorithm, respectively, and SWAT model with SWATCUP application using sequential uncertainty fitting as optimization techniques. Several tests for goodness of fit have been applied to compare the performance of conceptual and semi-distributed physical models. The analysis suggested that TANK model of RRL performed most appropriately among all the models applied in the analysis; however, SWAT model having spatial and climatic data can be used for impact assessment of change due to climate and land use in the basin. 3 48 Page 2 of 14 represent different components of the hydrological process through recharge and depletion. The conceptual models are usually lumped in nature and use the same value of parameters for the whole watershed and ignored the spatial variability of watershed characteristics. The conceptual models strongly rely on observed data, and results depend on the quality of input data used in the model. Large numbers of conceptual models have been proposed in the past including Sacramento model (Brazil and
doi:10.1007/s13201-019-1122-6 fatcat:6gyzgzcttbac7pizf23sdckdla