review · CATENA
This research evaluated the Global Assessment of Soil Degradation mapping tool alongside literature, gauging station records from Brazzaville, and Landsat satellite imagery to assess erosion across the Congo River Basin. Upper catchments represent the primary sediment sources, with the Upper Congo exporting the highest total volume and the Kasai sub-basin exhibiting the highest specific production rate at 8.92 tonnes per square kilometre per year. Water-induced topsoil loss is the dominant degradation type across 32 percent of the basin, while 39 percent remains stable natural terrain. Overall basin erosion levels are generally low, yet satellite analysis reveals an ongoing increase in river sediment concentrations over time. The study highlights unexplained sediment dynamics across sub-basins and establishes strategic sampling sites to direct future field investigations.
Mapping soil loss across large river systems is crucial for water resource management, infrastructure protection, and catchment conservation. By locating the primary sources of sediment and identifying discrepancies between static maps and increasing river sediment levels, this work helps environmental authorities target monitoring efforts and prioritises interventions in the most degraded catchments.
This work represents early-stage scoping research with no immediate commercial product. Catchment management authorities, environmental consultancies, and hydrological engineering organisations could use the identified sampling sites and validation approach to design targeted sediment monitoring frameworks. However, because the work primarily serves to direct future scientific field studies into unexplained sediment dynamics, any applied or commercial deployment remains at a distance from real-world use.
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This study uses the Global Assessment of Soil Degradation (GLASOD) to map sediment sources and erosion process types within the Congo Basin as part of a scoping study to guide a basin wide sedimentation study. The GLASOD map is validated using information from literature and published sediment concentration data at the Brazzaville gauging station, which includes over 95% of the basin area. Validation is complemented by analysis of timelapse satellite images and surface water transition maps derived from Landsat images. The upper catchments are shown to be the main sources of sediment, with the largest exporter by quantity being the Upper Congo sub-basin followed by the Kasai. In terms of severity, the Kasai has the highest specific sediment production rates at 8.92 t/km2/year, followed by the Sangha and Upper Congo at 8.52 t/km2/year and 7.61 t/km2/year, respectively. The dominant erosion/degradation type is the loss of topsoil through water erosion (sheet erosion), occurring in 32% of the entire Congo Basin area, followed by loss of nutrients and organic matter through chemical degradation, 21% of area. The mapping also shows that a large proportion of the Basin (39%) consists of stable terrain under natural conditions, without any human induced erosion. The erosion levels in the Basin are generally low with the predominant mapped erosion processes occurring mostly infrequently and with low levels of severity. The GLASOD map performs satisfactorily as a tool for mapping erosion sources and process types, but fails to explain the process dynamics within the sub-basins, for example, the high sediment exportation rates published for the Sangha sub-basin despite consisting mainly of stable natural terrain (84%). Analysis of satellite images shows an increase in sediment concentration in the Congo River's waters over the years. However, this temporal increase in sediment concentration is neither reflected in the GLASOD map nor the quantitative studies reviewed for this paper, pointing to the urgent need for future research on sediment dynamics in the Basin. Questions are also raised on the roles of the Malebo Pool and Cuvette Centrale in the sediment transport processes of the Basin. The questions raised, and observations made from this study have been used to identify strategic sampling sites for further field studies.
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DOI: 10.1016/j.catena.2019.02.030
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