Distributed data collection and web-based integration for more efficient and informative groundwater pollution risk assessment. (February 2018)

• Record Type: Journal Article
• Authors: Sege, Jon; Ghanem, Marwan; Ahmad, Waseem; Bader, Hanadi; Rubin, Yoram
• Is Part Of: Environmental modelling & software. Volume 100(2018)
• Page Start: 278
• Page End: 290
• Publication Date: 2018-02
• Subjects: Distributed data collection -- Web-based GIS -- Risk assessment -- Groundwater -- Pollution; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.11.027
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: We present a web-based software platform for assimilation of field data on groundwater vulnerability and assessment of groundwater pollution risk. Groundwater vulnerability and risk assessments couple hydrogeologic characterization and pollution source information to provide a relative measure of risk to a groundwater supply. Vulnerability is based solely on hydrogeologic factors, while risk also considers pollution hazards. Previous studies have identified two key limitations in the collection of pollution hazards information: detailed investigations throughout a study area are extremely time-consuming, and pollution inventories are not regularly updated to reflect changes in land use. This paper presents a methodology to address these two limitations by allowing broad-based effort to collect pollution hazard parameters in the field using GPS-tagged smartphone forms and incorporating the new information rapidly into a web-based risk modelling framework. To demonstrate this approach, a case-study is presented from the Natuf Basin in the Ramallah-Al Bireh Governorate of Palestine. Highlights: Decentralized data collection & processing are applied to a groundwater risk model. A modified time-dependent risk modelling algorithm is proposed. Model results are recomputed daily as new inputs are collected from the field. Difficulties in groundwater risk modelling are overcome using a web-based framework. Model results are available on the web and accessible to multiple users.