Modelling riverflows in the Volta Basin of West Africa: a data-driven framework
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The PhD research was undertaken in the 400,000 km2 Volta Basin which extends from longitude 5o 30 W to 2o 00E and from latitude 5 30o N to 14o 30 N and occupies various areas of the six West African countries of Benin, Togo, Ghana, La Cote d’Ivoire, Burkina Faso and Mali. The research involved the development of a modelling framework for monthly riverflow prediction in the basin and was undertaken in two parts.
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First, a spatio-temporal linear dynamic model employing the Kalman smoother and the Expectation-Maximisation (EM) algorithm was developed and applied to filling in short gaps in daily riverflow series in the basin. This model was found to be a very good and powerful tool for filling in such data gaps. Then, two non-linear modelling frameworks - a non-linear autoregressive and moving average with exogenous input (NARMAX) polynomial and a data-based mechanistic (DBM) modelling framework - were developed and applied to the monthly rainfall-runoff series in the basin for river catchment runoff prediction. The NARMAX model was able to capture much of the nonlinearity in the runoff generation process and provided good predictions of riverflow. However, it is a purely black-box formulation providing no physical interpretation of the runoff process in the basin. The DBM framework was very successful in representing the runoff mechanism in the basin, adequately predicting monthly river runoffs. In addition, this framework also provided physically interpretable results at the catchment scale. Results from the DBM modelling framework showed that monthly runoff in the basin can be interpreted to occur in two pathways: a fast flow pathway and a slow, mainly delayed flow, pathway. Also catchment effective rainfall in the basin was found to have a power law relationship with catchment runoff. The results also showed that the Identification of unit Hydrographs And Component flows from Rainfall, Evaporation and Streamflow (IHACRES) type effective rainfall-catchment wetness non-linear relationship in which the basin drying time constant is exponentially related to basin potential evaporation, was suitable for characterising the runoff processes in the basin. Therefore, it can be recommended from the results of this research, that data-driven approaches be considered as the most appropriate for riverflow modelling in the Volta Basin. This is due, in part, to the fact that the approaches provide very good results that are, to some extent, physically interpretable and also because the quality, quantity and diversity of hydrological data used for riverflow modelling in the basin are too poor to enable effective use of the more elaborate distributed hydrological models.
