For the sustainable use of groundwater, this study analyzes groundwater potential in Western Cameroon Highlands using artificial neural network model (ANN), GIS tools and remote sensing. Twelve factors believed to influence the groundwater occurrence were selected from literature and field investigations and used as input data. Satellite ALOS PALSAR, LANDSAT OLI, SRTM data processing techniques and GIS spatial analysis tools were used to prepare these maps. Pumping rates from 189 wells were considered as groundwater potential data and randomly divided into a training and a test sets. An ANN based on the relationship between groundwater productivity data and the above factors was implement on MATLAB. Each factor
The climate variability has affected pejoratively the groundwater recharge in Soubre area. Thus, the simulation of surface flows is an answer to the problematic of water supply in the area. The aim of this study is the simulation of surface flows in Debo catchment by estimating flood flows. The methodology is based on the application of morphological transfer function (MTF) of DEMIURGE software (Digital Elevation Model In Urgency). It consisted of the determination of fractal parameters related to water systems, the estimation of maximum flow at the outlet, the study of the sensitivity of the simulated hydrographs based on the simulation time step. The results show that the reference time is t = 20 minutes. For simulation times different from t = 20 minutes, the geomorphologic pulse histograms (GPH) do not fit the times transfer frequency histogram. The specific flow at the outlet of the catchment is 3.394 m3.s-1 for a rise time of 31.33 hours under the assumption of a uniform effective rainfall of 1 mm. The maximum flows simulated evolve with the rainfall blade and the rushed water. For a blade of 188.08 mm past, the maximum flow rate is at least 634.111 m3.s-1. For a rise time of 33 h 20 minutes, the volumes assessed are estimated at 1.06.108 m3.
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