MODELLING BENUE RIVER WATER BALANCE FOR CLIMATE IMPACTS ASSESSMENT USING LUMPED HYDROLOGICAL MODELS AND COMPUTER-BASED PROGRAM

Abstract

Some water balance models have been developed to predict runoff using parameters such as precipitation and potential evapotranspiration. In this study, three lumped monthly water balance models of different levels of complexity and structures were compared in Benue River basin with 30 years runoff data, featuring different climatic conditions. The models are Modified Thornthwaite model, GR2M and GR5M models. The models were calibrated and validated using Klemes’ split-sample test, and differential split-sample test. Measured runoff for Benue River basin acquired from Global Runoff Data Center (GRDC) and rainfall and potential evaporation data from Global Gridded Climatology, were used to calibrate and validate the models’ parameters. Three assessment criteria used for model performance evaluation are Kling-Gupta efficiency (KGE), water balance error (WBE) and root mean square error (RMSE). A computer-based program tagged MWBModels was also developed using C Sharp 4.0 and WPF 4.5.1. Model-View-Viewmodel (MVVM) architectural pattern was utilized for the program while Extensible Application Markup Language (XAML) was used to develop the graphical user interface. Algorithms of the three earlier mentioned water balance models were incorporated into the program, using C Sharp. MWBModels uses the algorithms of the models and input parameters to analyze rainfall and potential evapotranspiration records extracted from the input comma separated values (CSV) file. The program was used for simulating the validation dataset earlier used for the split-sample test and it displays result in both tabular and graphical formats. Results showed that GR2M outperformed other models in both tests with a WBE of 0.23 in the differential split test, indicating that the model can be used for climatic impact assessment