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A web-based spatial decision support system for monitoring the risk of water contamination in private wells / Yu Lan in Annals of GIS, vol 26 n° 3 (July 2020)  

Public [article]  inAnnals of GIS > vol 26 n° 3 (July 2020) . - pp 293 - 309 Titre : A web-based spatial decision support system for monitoring the risk of water contamination in private wells Type de document : Article/Communication Auteurs : Yu Lan, Auteur ; Wenwu Tang, Auteur ; Samantha Dye, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 293 - 309 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] arsenic [Termes IGN] base de données localisées [Termes IGN] Caroline du Nord (Etats-Unis) [Termes IGN] contamination [Termes IGN] eau souterraine [Termes IGN] interpolation spatiale [Termes IGN] krigeage [Termes IGN] pollution des eaux [Termes IGN] prévention des risques [Termes IGN] puits [Termes IGN] santé [Termes IGN] surveillance sanitaire [Termes IGN] système d'aide à la décision [Termes IGN] système d'information géographique [Termes IGN] WebSIG Résumé : (auteur) Long-term exposure to contaminated water can cause health effects, such as cancer. Accurate spatial prediction of inorganic compounds (e.g. arsenic) and pathogens in groundwater is critical for water supply management. Ideally, environmental health agencies would have access to an early warning system to alert well owners of risks of such contamination. The estimation and dissemination of these risks can be facilitated by the combination of Geographic Information Systems and spatial analysis capabilities – i.e., spatial decision support system (SDSS). However, the use of SDSS, especially web-based SDSS, is rare for spatially explicit studies of drinking water quality of private wells. In this study, we introduce the interactive Well Water Risk Estimation(iWWRE), a web-based SDSS to facilitate the monitoring of water contamination in private wells across Gaston County, North Carolina (US). Our system implements geoprocessing web services and generates dynamic spatial analysis results based on a database of private wells. Environmental health scientists using our system can conduct fine-grained spatial interpolation on 1) a particular type of contaminant such as arsenic, 2) on various subsets through a temporal query. Visuals consist of an estimation map, cross validation information, Kriging variance and contour lines that delineate areas with maximum contaminant levels (MCL), as set by the US Environmental Protection Agency (EPA). Our web-based SDSS was developed jointly with environmental health specialists who found it particularly critical for the monitoring of local contamination trends, and a useful tool to reach out to private well users in highly elevated contaminated areas. Numéro de notice : A2020-583 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2020.1798508 Date de publication en ligne : 30/07/2020 En ligne : https://doi.org/10.1080/19475683.2020.1798508 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95905 [article]