CHARACTERIZING HYDROLOGICAL PROCESSES WITHIN THE DATA-SCARCE ENVIRONMENT OF THE CONGO BASIN
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The Congo Basin in Africa is the world’s second largest river basin. Centrally located and with the greatest water resources in Africa, the basin is a vital resource for water and energy supply for a continent with increasing needs for safe water and energy. The Congo Basin’s streams and rivers could be impacted by human activities in the region, notably by land cover and land use change (LCLUC) considering the strong interactions between hydrology and ecosystem processes in the humid tropics. It could impact flow discharge downstream Congo River and hydropower potential at the Inga hydroelectric site, the largest such installation in Africa, located 150km upstream from the river’s mouth. The seasonal rainfall regime, to which the Congo River owes its regular flow regime, play an important role in mediating freshwater resources. An improvement to our baseline information on the Congo’s rainfall and streamflow dynamics allows for a greater quantitative understanding of the basin’s hydrology, necessary for the current and future management of Congo Basin water resources. The hydrometeorological observation network in the Congo Basin is very limited, and this environment of scarce ground data necessitates the use of remotely-sensed data for hydrological modeling.
This dissertation reports the use of hydrological modeling supported by remotely-sensed data to 1) characterize precipitation and climate in the Congo Basin, 2) characterize daily streamflow across the basin, 3) assess the hydrological response to LCLUC, including the additional response caused by climatic feedbacks following LCLUC. The study uses rainfall gauge data within the Democratic Republic of Congo (DRC) to re-calibrate a TRMM science product. It then describes a physically-based parameterization of a semi-distributed hydrological model, augmented with a spatially-distributed calibration that enables the model to simulate hydrologic processes in the Congo Basin, including the slowing effect of the basin’s central wetlands, the Cuvette Centrale. Model simulations included scenarios of 25% to 100% conversion of the Basins forest cover to agricultural mosaic and compared simulated flows to those of the current baseline conditions. The dissertation also reports on the estimated impacts of the hydrological response to LCLUC on the river’s hydropower potential.
Re-calibration of TRMM improved rainfall accuracy at the gauges by 15% and correctly captured important rainfall patterns such as the ones representative of the highland climate.
Model calibration of daily streamflow resulted in a model with high predictive power (Nash–Sutcliffe coefficient of efficiency of 0.70) when compared to Kinshasa gauge downstream Congo River, near its outlet. Model shows realistic seasonal and spatial patterns that can be explained by the ITCZ-driven rainfall patterns in the Congo Basin. Models of the direct effects alone of 25% to 100% forest conversion produce increases in peak flows of 7% to 8%, respectively, relative to the baseline, and decreases in low flow of 1% and 6%, for 75% and 100% forest conversion respectively, relative to the baseline. However, 25% and 50% forest conversion produce increases in low flows of 3% and 1% respectively indicating a possible sensitivity of the hydrological response to the spatial variability of forest conversion. Models of the combined direct and indirect effects of 25% to 100% conversion produce decreases in peak flows of 7% to 5% respectively and decreases in low flow of 8% to 11% respectively. Model estimates of the impacts on hydropower potential range from 11% decrease during dry season to 10% increase during rainy season, with greater impacts (year-round decrease) for increasing LCLUC models including indirect effect. The modeled loss in hydropower potential during dry season reaches -5,797 MW corresponding to the hydropower potential of countries such as Zambia or Angola and of grand projects such as the Grand Ethiopian Renaissance Dam.
The dissertation has showed the adequacy of TRMM precipitation products for Congo Basin rainfall regime representation and daily flow estimation particularly in capturing the timing and the seasonality of the flow. The results of these modeling efforts can be useful in research and decision-making contexts and validate the application of satellite-based hydrologic models driven for large, data-scarce river systems such as the Congo Basin by producing reliable baseline information.
We recommend a prioritization of further data collection and more gauges installation required to enable further satellite-derived data calibration and models simulations. Likewise, the results from LCLUC analysis support the need for field campaigns to better understand sub-watersheds responses and to improve the calibration of currently used simulation models.