Application of Remote Sensing, Gis, and the Sintacs Method for the Assessment of Groundwater Vulnerability and Quality in the Mefou Watershed (Cameroon)

Abstract

Ndjounguep Juscar, Amaya Adama, Monentyam Njoully Pascaline and Kah Elvis

Groundwater constitutes the primary source of domestic and agricultural water supply in the Mefou watershed, Centre Region, Cameroon. Rapid urban expansion, agricultural intensification, and inadequate sanitation infrastructure increasingly threaten its sustainability. This study integrates the SINTACS parametric model, Remote Sensing (RS), and Geographic Information Systems (GIS) to assess intrinsic and specific groundwater vulnerability, coupled with physicochemical and bacteriological quality analyses. Seven hydrogeological parameters (Depth to water, Effective infiltration, Vadose zone, Soil texture, Aquifer characteristics, Hydraulic conductivity, and Slope) were spatially analyzed and weighted under the SINTACS framework. Land use derived from Sentinel-2 imagery was incorporated to evaluate specific vulnerability to nitrates (NO3−) and Escherichia coli. Results indicate that 58% of the watershed exhibits moderate vulnerability, 27% high vulnerability, and 8% very high vulnerability, primarily associated with shallow groundwater depths (<5 m), permeable lateritic soils, and fractured crystalline formations. Water quality analysis reveals nitrate concentrations exceeding WHO guidelines in 32% of sampled points and widespread bacteriological contamination in shallow wells. The Groundwater Quality Index (GWQI) classified 46% of samples as poor to very poor. The integration of SINTACS with RS–GIS proved effective for identifying priority protection zones. Immediate management measures are recommended in high-vulnerability urban–agricultural interfaces.

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