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Multi-Criteria Decision Analysis and GIS Approach for Prioritization of Drinking Water Utilities Protection Based on their Vulnerability to Contamination

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Abstract

This work presents the use of multi-criteria decision analysis (MCDA) as a decision tool to facilitate the process of prioritization of drinking wells that would need more protection before contamination risk. In this study, three aspects of the protection of the groundwater quality were taken into account: natural, anthropic and technical. From these aspects, elements more representative were selected, which can be quantified with available and easily accessible information. Considering those elements, selection criteria were defined which have been represented by: population distribution indicator, human development index, land use, index for aquifer vulnerability to contamination, well age and well yearly pumping rate. The developed method has been applied to drinking supply wells located in the Toluca Valley aquifer (Mexico), and implied the generation of the thematic maps of the defined selection criteria. For the MCDA, the values of each map were converted to the same scale, each criterion was weighted in function of its importance according to the objective and there were aggregated by the way of a lineal combination. The obtained result is a map that shows the level of protection priority of the supply wells. This map can offer information to the stakeholder in a relative short time and contribute to accelerate the actions aimed to protect the quality of the vital underground liquid.

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Acknowledgments

We thank anonymous reviewer for comments to improve the manuscript. This study was funded by Universidad Autónoma del Estado de México (Project 2600/2008U). Particular thanks are given to CONAGUA.

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Correspondence to M. V. Esteller.

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Alvarado, A., Esteller, M.V., Quentin, E. et al. Multi-Criteria Decision Analysis and GIS Approach for Prioritization of Drinking Water Utilities Protection Based on their Vulnerability to Contamination. Water Resour Manage 30, 1549–1566 (2016). https://doi.org/10.1007/s11269-016-1239-4

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