Groundwater Vulnerability Assessment to Pollution using DRASTIC and SINTACS Methods in Northwestern Douala Basin, Cameroon.

Abstract

Groundwater is a principal water source in Northwestern Douala Basin in the Littoral Region of Cameroon. The resource is vulnerable to diverse sources of pollutants as agriculture is practiced on a large scale, especially with the presence of a banana plantation in the zone which uses agrochemicals that can deteriorate the quality of the resource. This study employed the DRASTIC and SINTACS models, integrated with GIS tools to evaluate groundwater vulnerability to pollution. A total of 220 wells and boreholes were sampled within Bomono, Souza, Kombe, Moyouka I, Moyouka II, Mbanga and Njombe–Penja. Additionally, the DRASTIC and SINTACS models were modified using sensitivity analysis to adjust the recommended weight value. Standard vulnerability maps of the basin revealed three vulnerability zones for the DRASTIC model: low vulnerability (23%), moderate vulnerability (12%) and high vulnerability (65%). In comparison, the SINTACS model revealed two vulnerability zones of moderate vulnerability (40%) and high vulnerability (60%). Results of sensitivity analysis showed that the area comprises low vulnerability (30%) and moderate vulnerability (70%) for DRASTIC while the SINTACS revealed very low vulnerability (30%), low vulnerability (36%) and moderate vulnerability (34%). Results of both single parameter sensitivity analysis and map removal sensitivity analysis revealed that depth to the water level, impact of vadose zone and recharge have a great influence on aquifer vulnerability. It was noticed that areas of high nitrate concentration correlated with areas of high vulnerability to contamination. Also, depth to water level, impact of vadose zone, and recharge emerged as key factors influencing aquifer vulnerability. Therefore, it is recommended that sustainable farming techniques should be adopted in order to reduce agrochemical usage especially in vulnerable zones, and also establish monitoring programs that could track groundwater quality over time.