The unbearable fuzziness of being sustainable: an integrated, fuzzy logic-based aquifer health index

Abstract

We introduce a groundwater sustainability index offering a novel combination of features. It is holistic in the sense that it incorporates both water quantity and water quality indicators. The former employs the signal-to-noise ratio of long-term trends estimated via robust regression; the latter uses concentration of the primary contaminant of concern. A fuzzy inference system integrates these unlike metrics. The system also explicitly encodes expert knowledge and stakeholder values, and directly acknowledges subjectivity in environmental condition “grading,” through the use of linguistic rules and fuzzy sets, respectively. The fuzzy rule base is constructed such that poor environmental conditions captured by one measure are not hidden by good performance in another. A standard Mamdani (max–min) inference engine is used with centroid defuzzification. The outcome is an intuitively accessible index ranging from 0 to 100. The method is demonstrated using examples from the Abbotsford-Sumas aquifer, an important and managerially challenging transboundary (Canada–US) water resource.Editor D. Koutsoyiannis; Associate editor E. RozosCitation Fleming, S.W., Wong, C., and Graham, G., 2014. The unbearable fuzziness of being sustainable: an integrated, fuzzy logic-based aquifer health index. Hydrological Sciences Journal, 59 (6), 1154–1166. http://dx.doi.org/10.1080/02626667.2014.907496