ABOUT THE PROJECT
The Zambezi River, the fourth largest river in Africa, is shared by eight countries: Zambia (42%), Angola (18%), Namibia (1%), Botswana (1.5%), Zimbabwe (16%), Tanzania (2%), Malawi (7.5%) and Mozambique (12%). The Zambezi has a catchment area of 1.37 million km2, a length of 2 660 km and an average discharge of 4 100 m3/s at the outlet. In the main stream, there are two major hydropower dams: Kariba in Zambia/Zimbabwe and further downstream the Cahora Bassa dam in Mozambique; additional hydropower plants are planned in the Zambezi River and its tributaries. The operation of both dams rely on the ability of accurately forecasting the floods that enter the reservoir. In both cases, this is a major challenge due to lack of information from ungauged tributaries. Therefore, increased insight in the hydrology of the ungauged tributaries in the Zambezi between Kariba and Cahora Bassa is necessary for more reliable flow predictions, better operation of the dams, reducing flood hazard and community flood risk, energy and agricultural production. Accurate estimates of inflow are important for the prediction of floods, droughts and for the energy production. Operating the dams for these multiple purposes is a major challenge due to lack of information on the contribution from ungauged tributaries.
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In the Zambezi River Basin, due to high rainfall variability there are regular droughts, but also extreme flood events. Almost every year, communities are affected by natural floods originating from upstream but also from backwater effects from Cahora Bassa reservoir. The floods pose negative impacts on the environment, such as destruction of the infrastructure or low crop yields affecting the food security and economy. On the other side, floods also have positive impacts such as maintaining healthy ecosystem dynamics and providing fertile soil enabling double cropping within a year. Therefore, communities resist to relocate as their livelihoods depend on the floodplains.
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During this research project, a landscape and ecology-based hydrological model will be developed using ground observations and remote sensed data for the forcing, calibration and/or constraints to obtain the correct spatial heterogeneity. The focus will be on the Luangwa, the largest most unregulated tributary, but also other tributaries between both reservoirs will be modelled.