Accident Trend Prediction of Heavy Metal Pollution in the Heshangshan Drinking Water Source Area Based on Integrating a Two-Dimensional Water Quality Model and GIS
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Medientyp:
E-Artikel
Titel:
Accident Trend Prediction of Heavy Metal Pollution in the Heshangshan Drinking Water Source Area Based on Integrating a Two-Dimensional Water Quality Model and GIS
Beteiligte:
Ding, Xiaowen;
Fang, Ping
Erschienen:
MDPI AG, 2019
Erschienen in:Sustainability
Sprache:
Englisch
DOI:
10.3390/su11153998
ISSN:
2071-1050
Entstehung:
Anmerkungen:
Beschreibung:
<jats:p>In recent years, water pollution accidents have frequently occurred, which have caused enormous economic loss and an adverse social impact. In this study, an accident trend prediction system was developed based on integrating a two-dimensional water quality model and GIS, and Arsenic (As) was adopted as a typical pollutant to study the temporal-spatial changes of heavy metal pollutions under different hydrological and meteorological conditions in the Heshangshan drinking water source area. The simulation for a recent accident indicated that pollutant changes were influenced by lateral diffusion, longitudinal diffusion, flow velocity, water flow, and the self-purification of the water body. It took 79.5 min for the As concentration to meet the water quality standard during the dry period, while it spent 61.3 min, 71 min, and 52 min in the impound period, falling period, and flood period, respectively. The emergency response times were 32 min (in the flood period), 38 min (in the impound period), 48 min (in the falling period), and 52 min (in the dry period). Furthermore, wind speed and wind direction also had impacts on pollutant spread. The times in which the maximum values met the water quality standard were 71 min (southeast wind), 77 min (southwest wind), and 87 min (no wind). The emergency response times were 38 min (southeast wind), 49 min (southwest wind), and 59 min (no wind). This study not only provides a reference for relevant departments and managers to carry out a risk assessment, disaster prevention, and emergency management after actual pollution accidents, but also makes up for the lack of research on the spatial-temporal change of heavy metal pollutants.</jats:p>