About GAP Maps

Analysing groundwater for geogenic contaminants such as arsenic and fluoride is time-consuming and costly. Maps highlighting areas with a high contamination hazard can aid decisionmakers in undertaking more targeted drinking water surveys.

Innovative methods for producing such maps have been developed, essentially involving the correlation (logistic regression) of groundwater quality point data with geospatial datasets of predictor variables (e.g. geology, soil or climate). The accuracy of these predictive models has been demonstrated in various countries, for example, Vietnam, Indonesia (Sumatra), China, Pakistan and Burkina Faso.

GAP facilitates the development of such maps by providing the necessary statistical modelling framework and builtin datasets (GAP public layers). Users can also upload their data to produce hazard maps of their contaminant and area of interest.

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