This study interprets the recent history of Lake Kivu, a tropical lake in the East African Rift Valley. The current gross sedimentation was characterized from a moored sediment trap array deployed over 2 years. The past net sedimentation was investigated with three short cores from two different basins. Diatom assemblages from cores were interpreted as reflecting changes in mixing depth, surface salinity and nutrient availability. The contemporary sediment trap data indicate seasonal variability, governed by diatom blooms during the annual mixing in the dry season, similar to Lakes Malawi and Tanganyika. The ratio of settling fluxes to net sediment accumulation rates implies mineralization rates of 80–90% at the sediment-water interface. The sediment cores revealed an abrupt change ~40 years ago, when carbonate precipitation started. Since the 1960s, deep-water methane concentrations, nutrient fluxes and soil mineral inputs have increased considerably and diatom assemblages have altered. These modifications probably resulted from a combination of three factors, commonly altering lake systems: the introduction of a non-native fish species, eutrophication, and hydrological changes inducing greater upwelling. Both the fish introduction and increased rainfall occurred at the time when the onset of carbonate precipitation was observed, whereas catchment population growth accompanied by intensified land use increased the flux of soil minerals already since the early twentieth century due to more intense erosion.

During this study, we investigated the seasonal variability of the concentration and the stable isotope composition of several inorganic and organic matter (OM) reservoirs in the large, oligotrophic and deep tropical Lake Kivu (East Africa). Data were acquired over 1 year at a fortnightly temporal resolution. The δ¹³C signature of the dissolved inorganic carbon (DIC) increased linearly with time during the rainy season, then suddenly decreased during the dry season due to vertical mixing with ¹³C-depleted DIC waters. The δ¹³C signature of the particulate organic carbon pool (POC) revealed the presence of a consistently abundant methanotrophic biomass in the oxycline throughout the year. We also noticed a seasonal shift during the dry season toward higher values in the δ¹⁵N of particulate nitrogen (PN) in the mixed layer and δ¹⁵N-PN was significantly related to the contribution of cyanobacteria to the phytoplankton assemblage, suggesting that rainy season conditions could be more favourable to atmospheric nitrogen-fixing cyanobacteria. Finally, zooplankton were slightly enriched in ¹³C compared to the autochthonous POC pool, and the δ¹⁵N signature of zooplankton followed well the seasonal variability in δ¹⁵N-PN, consistently 3.0 ± 1.1 ‰ heavier than the PN pool. Together, δ¹³C and δ¹⁵N analysis suggests that zooplankton directly incorporate algal-derived OM in their biomass, and that they rely almost exclusively on this source of OM throughout the year in general agreement with the very low allochthonous OM inputs from rivers in Lake Kivu.

Inappropriate land management leads to soil loss with destruction of the land’s resource and sediment input into the receiving river. Part of the sediment budget of a catchment is the estimation of soil loss. In the Ruzizi catchment in the Eastern Democratic Republic of the Congo (DRC), only limited research has been conducted on soil loss mainly dealing with local observations on geomorphological forms or river load measurements; a regional quantification of soil loss is missing so far. Such quantifications can be calculated using the Universal Soil Loss Equation (USLE). It is composed of four factors: precipitation (R), soil (K), topography (LS), and vegetation cover (C). The factors can be calculated in different ways according to the characteristics of the study area. In this paper, different approaches for calculating the single factors are reviewed and validated with field work in two sub-catchments of Ruzizi River supplying the water for the reservoirs of Ruzizi I and II hydroelectric dams. It became obvious that the (R)USLE model provides the best results with revised R and LS factors. C factor calculations required to conduct a supervised classification using the Maximum Likelihood Procedure. Different C factor values were assigned to the land cover classes. The calculations resulted in a soil loss rate for the predominantly occurring Ferralsols and Leptosols of around 576 kt/yr in both catchments, when 2016 landcover and precipitation are used. This represents an area-normalized value of 40.4 t/ha/yr for Ruzizi I and 50.5 t/ha/yr for Ruzizi II due to different landcover in the two sub-catchments. The mean value for the whole study area is 47.8 t/ha/yr or even 27.1 t/ha/yr when considering land management techniques like terracing on the slopes (P factor). This work has shown that the (R)USLE model can serve as an easy to handle tool for soil loss quantification when comprehensive field work results are sparse. The model can be implemented in Geographic Information Systems (GIS) with free data; hence, a validation is crucial. It becomes apparent that the use of high resolution Sentinel 2a MSI data as the basis for C factor calculations is an appropriate method for considering heterogeneous Land Use Land Cover (LULC) patterns. To transfer the approach to other regions, the calculation of factor R needs to be modified.

Hydroelectric power (HP) represents the main source of electricity in Africa, including the Democratic Republic of Congo. The demand for new dam construction is high, and major projects are currently progressing through planning and implementation stages. New HP dams should comply with both past and emerging environmental requirements. River systems need water to maintain hydraulic and ecological functions. Flow regime disturbance can prevent rivers from providing their ecosystem services and disrupt riparian communities. Most dammed rivers in Africa are understudied, however, in terms of their environmental flow requirements. This study analysed the hydrological regime and water quality of the Ruzizi River. The research investigated conditions of minimum water flow and hydropeaking at the Ruzizi I HP dam in terms of land management constraints and ecological impacts. According to Gumbel’s hydrological model, a discharge of ∼130 m³/s showed the longest return period (12 years) among the most recurrent flows. By contrast, the maximum recorded discharge of 143 m³/s showed a return time of 76 years. Any discharge between 46 and 120 m³/s could occur at any time within three years. The discharge–hydropower production relationship for the power plant provided a possible minimum environmental flow of 28 m³/s (i.e., 25%). Drinking water quality was assessed according to WHO water quality index (WQI) standards. Turbidity (i.e., total suspended solids) upstream and downstream of dams correlated strongly with rainfall (r = 0.8; n = 12) and land use. WQI values observed in excess of WHO drinking water standards indicate that the Ruzizi River is currently unsuitable for drinking water purposes.