Fuzzy modelling to identify key drivers of ecological water quality to support decision and policy making

Marie Anne Eurie Forio, Ans Mouton, Koen Lock, Pieter Boets, Thi Hanh Tien Nguyen, Minar Naomi Damanik Ambarita, Peace Liz Sasha Musonge, Luis Dominguez-Granda and Peter L.M. Goethals

Environmental Science & Policy, 2017, vol. 68, issue C, 58-68

Abstract: Water quality modelling is an effective tool to investigate, describe and predict the ecological state of an aquatic ecosystem. Various environmental variables may simultaneously affect water quality. Appropriate selection of a limited number of key-variables facilitates cost-effective management of water resources. This paper aims to determine (and analyse the effect of) the major environmental variables predicting ecological water quality through the application of fuzzy models. In this study, a fuzzy logic methodology, previously applied to predict species distributions, was extended to model environmental effects on a whole community. In a second step, the developed models were applied in a more general water management context to support decision and policy making. A hill-climbing optimisation algorithm was applied to relate ecological water quality and environmental variables to the community indicator. The optimal model was selected based on the predictive performance (Cohen’s Kappa), ecological relevance and model’s interpretability. Moreover, a sensitivity analysis was performed as an extra element to analyse and evaluate the optimal model. The optimal model included the variables land use, chlorophyll and flow velocity. The variable selection method and sensitivity analysis indicated that land use influences ecological water quality the most and that it affects the effect of other variables on water quality to a high extent. The model outcome can support spatial planning related to land use in river basins and policy making related to flows and water quality standards. Fuzzy models are transparent to a wide range of users and therefore may stimulate communication between modellers, river managers, policy makers and stakeholders.

Keywords: Fuzzy logic; Environmental variables; Decision support systems; River basin management (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1462901116308917
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:enscpo:v:68:y:2017:i:c:p:58-68

DOI: 10.1016/j.envsci.2016.12.004

Access Statistics for this article

Environmental Science & Policy is currently edited by M. Beniston

More articles in Environmental Science & Policy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().