This dataset provides a set of hydrometric indices for about 1500 stations across Africa with daily discharge data. These indices represent mean flow characteristics and extremes (low flows and floods), allowing us to study the long-term evolution of hydrology in Africa and support the modeling efforts that aim at reducing the vulnerability of African countries to hydro-climatic variability.

Input data (and model parameters) are significant sources of uncertainty that should be quantified. In southern Africa, water use data are among the most unreliable sources of model input data because available databases generally consist of only licensed information and actual use is generally unknown. The study assesses how uncertainty impacts the estimation of surface water resources of the Mogalakwena and Shashe sub-basins when using the databases that are currently available.

Channel transmission losses play a significant role in the water balance of the Limpopo River Basin, therefore understanding loss processes and quantifying the impact on water resources is integral for advancing knowledge and improving water resource management. Using three functions of the Pitman Model, loss simulations were conducted and results indicate that all three functions are able to simulate losses,albeit with differing magnitudes. Better quantification requires reliable observed data.

The paper investigates the use of GIS to come up with model parameters. This is part of a process of simplifying model use. The findings show that existing GIS data can be used for estimating model parameters as the outcomes of the research show that model outputs are consistent with previously estimated measures. This research is part of a development of a model which can estimate soil loss and sediment delivery at broad spatial and temporal scales to improve catchment management.