6533b82cfe1ef96bd129017b
RESEARCH PRODUCT
Decision-Making Tools to Manage the Microbiology of Drinking Water Distribution Systems
Gonzalo Del OlmoStewart HusbandIsabel DoutereloJoby BoxallSilvia CarpitellaJoaquín Izquierdosubject
lcsh:Hydraulic engineeringComputer sciencemedia_common.quotation_subjectGeography Planning and Developmentwater quality monitoringDEMATEL02 engineering and technology010501 environmental sciencesAquatic Science01 natural sciencesBiochemistryFuzzy logicDistribution systemWater quality monitoringlcsh:Water supply for domestic and industrial purposeslcsh:TC1-9780202 electrical engineering electronic engineering information engineering03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edadesFTOPSISIntegrated management0105 earth and related environmental sciencesWater Science and Technologymedia_commonlcsh:TD201-50006.- Garantizar la disponibilidad y la gestión sostenible del agua y el saneamiento para todosDrinking water distribution systemsIntegrated approachMultiple-criteria decision analysisInterdependenceRisk analysis (engineering)drinking water distribution systemsMicrobiological assessmentMulti-criteria system analysismicrobiological assessment020201 artificial intelligence & image processingWater qualityMATEMATICA APLICADAmulti-criteria system analysisReal world datadescription
[EN] This paper uses a two-fold multi-criteria decision-making (MCDM) approach applied for the first time to the field of microbial management of drinking water distribution systems (DWDS). Specifically, the decision-making trial and evaluation laboratory (DEMATEL) was applied removing the need for reliance on expert judgement, and analysed interdependencies among water quality parameters and microbiological characteristics of DWDS composed of different pipe materials. In addition, the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) ranked the most common bacteria identified during trials in a DWDS according to their relative abundance while managing vagueness affecting the measurements. The novel integrated approach presented and proven here for an initial real world data set provides new insights in the interdependence of environmental conditions and microbial populations. Specifically, the application shows as the bacteria having associated the most significant microbial impact may not be the most abundant. This offers the potential for integrated management strategies to promote favourable microbial conditions to help safeguard drinking water quality.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2020-05-01 | Water |