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The Sahel has been the focus of scientific interest in environmental-human dynamics and interactions. The objective of the present study is to contribute to the recent debate on the re-greening of Sahel. The paper examines the dynamics of barren land in the Sahel of Burkina Faso through analysis of remotely-sensed and rainfall data from 1975–2011. Discussions with farmers and land management staff have helped to understand the anthropogenic efforts toward soil restoration to enable the subsistence farming agriculture. Results showed that area of barren land has been fluctuating during the study period with approximately 10-year cyclicity. Similarly, rainfall, both at national and local levels has followed the same trends. The trends of the area of barren land and rainfall variability suggest that when rainfall increases, the area of barren land decreases and barren land increases when rainfall decreases. This implies that rainfall is one of the main factors driving the change in area of barren land. In addition, humans have contributed positively and negatively to the change by restoring barren lands for agriculture using locally known techniques and by accelerating land degradation through intensive and inappropriate land use practices.
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
The Late Tertiary to Quaternary evolution of the Ntem interior delta in SW Cameroon shall be modelled. A step fault was formed along neotectonically remobilized Precambrian structures. Uncalibrated 14C-datations in this ‘sediment trap’ show Pleistocene to Holocene ages. Both within and below the interior delta pebbles and clasts which are cemented in an iron and manganese matrix were found. These ‘fanglomerates’ are used to discuss different processes of the younger evolution also concerning climatic fluctuations in the study area.