A statistical model to predict groundwater vulnerability against pollution: a support to design groundwater quality monitoring programs

Ouedraogo, Issoufou;Vanclooster, Marnik
(2015) Workshop Exploring new data for SMART monitoring of water SDG targets (IHP-HWRP) — Location: Maastricht (The Netherlands) (30.November.2015)

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Abstract
Groundwater is a crucial natural resource supporting the development of the African continent, but it is subjected to many pressures. According to Xu and Usher, (2006), degradation of groundwater is the most serious water resources problem in Africa. Nitrate is a common groundwater contaminant and a good indicator of the anthropogenic degradation of groundwater quality. Statistical models can be deployed to predict the spatial distribution of nitrate in groundwater in terms of environmental and anthropogenic attributes. The purpose of this study is to identify such a statistical model to map nitrate contamination in groundwater at the pan African scale, supporting regional groundwater quality monitoring programs.
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Ouedraogo, I., & Vanclooster, M. (2015). A statistical model to predict groundwater vulnerability against pollution: a support to design groundwater quality monitoring programs. Workshop Exploring new data for SMART monitoring of water SDG targets (IHP-HWRP), Maastricht (The Netherlands). https://hdl.handle.net/2078.5/188657