Abstract:The Ndop Plain, located along the Cameroon Volcanic Line (CVL), is a volcano-tectonic plain, formed by a series of tectonic movements, volcanic eruptions and sedimentation phases. Floods (annually) and landslides (occasionally) occur with devastating environmental effects. However, this plain attracts a lot of inhabitants owing to its fertile alluvial soils. With demographic explosion in the plain, the inhabitants (143,000 people) tend to farm and inhabit new zones which are prone to these geohazards. In this paper, we use field observations, laboratory analyses, satellite imagery and complementary methods using appropriate software to establish hazard (flood and landslide) maps of the Ndop Plain. Natural factors as well as anthropogenic factors are considered. The hazard maps revealed that 25% of the area is exposed to flood hazard (13% exposed to high flood hazard, 12% to moderate) and 5% of the area is exposed to landslide hazard (2% exposed to high landslide hazard, 3% to moderate). Some mitigation measures for floods (building of artificial levees, raising foundations of buildings and the meticulous regulation of the flood guards at Bamendjing Dam) and landslides (slope terracing, planting of trees, and building retaining walls) are proposed.
Up to date, tropical mountainous ecosystems still lack in depth information on soil and environmental characteristics which are major factors limiting optimum crop production. The objective of this work was to study soil characteristics and to evaluate the land capability level for the production of some common tropical crops in mountainous ecosystem soils of North West Cameroon. Soil sampling was done following a randomized complete block design (RCBD) with four replications for three topographic positions (upslope, midslope and footslope) and at two depths (0 -20 cm and 20 -100 cm). It was completed by standard laboratory analyses. The fertility capability classification (FCC) system enabled to identify soil limitations and to classify soils into FCC units. Land and climate were evaluated by simple limitation and parametric methods. Globally, the soils were dark-colored, sandy clayey to clayey, compact and very acidic (pHH 2 O = 4.3 -5.8). The organic matter (3.7% -5.1% dry matter), total nitrogen (0.08% -0.56%) and available phosphorus (22.1 to 30.9 mg·kg −1 ) recorded for the 0 -20 cm depth then reduced with depth but midslope values were also lower. The C/N ratio varied between 9 and 45. Low C/N values appeared mostly in 0 -20 cm depth at the upslope and downslope soils and subsurface soils of midslope position. Exchangeable Ca was very low to low (1.43 -3.6 cmol + kg DOI: 10.4236/gep.2018.67002 16 Journal of Geoscience and Environment Protection was the most relatively concentrated base in all the soils. There was a clear variation of most of the soil properties along the slope and with depth. The soils were classified in the FCC system as aek for the upslope soils, Caek for the midslope soils and Cagk for the footslope soils. The principal limitations to production of huckleberry, beans, maize and potatoes were heavy rainfall, wetness, steep slope, soil texture/structure and low soil fertility. These constraints might be overcome by farming at the end of the raining season, contour ploughing, terracing, fertilization and liming.
In this work, we explored a novel approach to integrate both geo-environmental and soil geomechanical parameters in a landslide susceptibility model. A total of 179 shallow to deep landslides were identified using Google Earth images and field observations. Moreover, soil geomechanical properties of 11 representative soil samples were analyzed. The relationship between soil properties was evaluated using the Pearson correlation coefficient and geotechnical diagrams. Membership values were assigned to each soil property class, using the fuzzy membership method. The information value method allowed computing the weight value of geo-environmental factor classes. From the soil geomechanical membership values and the geo-environmental factor weights, three landslide predisposition models were produced, two separate models and one combined model. The results of the soil testing allowed classifying the soils in the study area as highly plastic clays, with high water content, swelling, and shrinkage potential. Some geo-environmental factor classes revealed their landslide prediction ability by displaying high weight values. While the model with only soil properties tended to underrate unstable and stable areas, the model combining soil properties and geo-environmental factors allowed a more precise identification of stability conditions. The geo-environmental factors model and the model combining geo-environmental factors and soil properties displayed predictive powers of 80 and 93%, respectively. It can be concluded that the spatial analysis of soil geomechanical properties can play a major role in the detection of landslide prone areas, which is of great interest for site selection and planning with respect to sustainable development at Mount Oku.
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