Groundwater Monitoring Network Design Using GIS and Multicriteria Analysis

The objective of this investigation was to use multicriteria analysis to analyze and model the main criteria that influence the optimal design of a network to monitor groundwater levels. The multicriteria analysis was performed using a GIS (IDRISI Selva). The Toluca Valley aquifer (Mexico) was chose...

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Bibliographic Details
Published in:Water resources management 2015-07, Vol.29 (9), p.3175-3194
Main Authors: Esquivel, Juan M., Morales, Guillermo P., Esteller, María V.
Format: Article
Language:English
Subjects:
Analytic hierarchy process
Aquifers
Atmospheric Sciences
Case studies
Civil Engineering
Criteria
Decision making
Design engineering
Design optimization
Earth and Environmental Science
Earth Sciences
Environment
Environmental monitoring
Fuzzy sets
Geographic information systems
Geotechnical Engineering & Applied Earth Sciences
Groundwater
Groundwater levels
Hierarchies
Hydraulic gradient
Hydrogeology
Hydrology/Water Resources
Mathematical models
Methods
Monitoring
Networks
Priorities
Studies
Water monitoring
Water resources management
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Summary:The objective of this investigation was to use multicriteria analysis to analyze and model the main criteria that influence the optimal design of a network to monitor groundwater levels. The multicriteria analysis was performed using a GIS (IDRISI Selva). The Toluca Valley aquifer (Mexico) was chosen as the case study. The definition and importance of the criteria (factors and constraints) that influence the design of the monitoring network were based on available information and consultations with experts in the topic. The factors considered were: rate of decline in groundwater levels, decline in groundwater levels, rise in groundwater levels, cracks, vertical hydraulic gradient, and density of wells. The Analytical Hierarchy Process (AHP) was used to weight the factors, resulting in a consistency ratio of 0.08. The weighted linear combination (WLC) method was then applied which resulted in a map identifying the locations of the priority areas to be monitored. The results show that 1.0 % of the study region corresponds to very high priority monitoring areas, 1.8 % to high priority areas, another 1.8 % to medium priority, 4.4 % to low priority and 91 % to very low priority monitoring areas. The proposed method can be used by government and public and private organizations to determine monitoring strategies that support water resources management.
ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-015-0989-8