The Niayes area is home to the Quaternary sands of the northern Senegalese coastline. It offers economic potentialities such as it attracts industry and farmer. Thus, the pressures of anthropogenic origins combined with pejorative climatic conditions, expose it to environmental and social risks, to the extent that the vulnerability of groundwater to pollution calls on researchers and decision-makers. The study presented in this article aims to assess the level of groundwater vulnerability to pollution, using three methods: DRASTIC, SINTACS and SI. The Arc Gis software was used. The parameters used as input data include hydraulic conductivity, static groundwater level, soil type, topographic slope and recharge. Several degrees of vulnerability are identified from south to north ranging from "low" to "high". It is noteworthy that the further away from the coast, the lower the vulnerability and the overall vulnerability of the area, with high-vulnerability areas. To validate our results, we have superimposed a map of nitrate concentration with those of the vulnerabilities to see the most suitable method with this type of pollutant. Comparison of the different results makes it possible to deduce that the SI method is the most appropriate for the assessment of the vulnerability to nitrate pollution, with a 70% coincidence rate between the nitrate concentrations and the different classes of vulnerability.

The objective of the present work is to contribute to the study and the numerical modelling of the hydric erosion in the plateau of Thiès: through an application to the watershed of Kissane, according to the USLE (Universal Soil Loss Equation) model. The establishment of the USLE model requires data on the topography, the land use, the climatology and the pedology. One of the major difficulties in the elaboration of the model was the collection of relevant data. Indeed, the rural commune of Noto more exactly the village of Kissane is relatively little informated by the scientific bibliography. The geographical reference data on the topography, the precipitation, the land use either non-existent, or incomplete or obsolete on a small scale and the geo-referenced digital data are even rarer. The study, the combination of the data and in the modelling were operated in a Geographical Information System (GIS). Every factor is a digital estimation of a precise component that affects the gravity of the soil erosion in a given place. The realization of the land use map from the visual interpretation assisted by GIS, from the satellite imaging Landsat that covers the watershed of Kissane facilitated the extraction of the vegetation cover map, what allowed defining with more precision the most sensitive areas with erosion risk.