Application of GIS and Multi-Criteria Statistical Techniques in Assessing Water Quality in the Coastal Province of Vietnamese Mekong Delta

Q3 Environmental Science
N. Giao, Huynh Thi Hong Nhien
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引用次数: 1

Abstract

The study was conducted to evaluate the quality and spatial distribution of surface water quality in Soc Trang, a coastal province using Geographic information system (GIS) and multivariate statistical analysis. Water monitoring data was collected from 19 sampling locations with 19 parameters were analyzed from February 2019 to August 2020. The results indicated that water quality was contaminated with organic matters, nutrients, coliforms and salinity. Water quality index (WQI=22–73) indicated that water quality was from poor to medium level. Cluster analysis (CA) classified 19 monitoring sites into 7 groups and 19 months into 3 seasons including rainy season, rainy season-early dry season, dry season-early rainy season. CA results showed that the location and frequency of water quality monitoring could be significantly reduced, saving up to 75% the monitoring costs. The maps of the polluted parameters (TSS, DO, BOD, COD, TOC, NH4+-N, NO2--N, Coliform, Fe, Cl-) illustrated that the areas located in the interior fields and near the sea had poorer water quality compared to the areas adjacent to the Hau River. The combination of multivariable statistics and GIS was very useful for spatial and temporal analysis of water quality monitoring data.
GIS和多准则统计技术在越南湄公河三角洲沿海省水质评价中的应用
利用地理信息系统(GIS)和多元统计分析方法,对沿海省份Soc Trang的地表水水质质量及其空间分布进行了评价。2019年2月至2020年8月,收集了19个采样点的水监测数据,分析了19个参数。结果表明,水质受到有机质、营养物、大肠菌群和盐度的污染。水质指数(WQI= 22-73)表明水质由差到中。聚类分析(CA)将19个监测点分为7组,19个月分为雨季、雨季-早旱季、旱季-早雨季3个季节。CA结果表明,可以显著减少水质监测的位置和频率,可节省高达75%的监测成本。污染参数(TSS、DO、BOD、COD、TOC、NH4+-N、NO2——N、大肠菌群、Fe、Cl-)图显示,内陆和近海地区的水质较差。多变量统计与GIS的结合对水质监测数据的时空分析非常有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Applied Environmental Research
Applied Environmental Research Environmental Science-Environmental Science (all)
CiteScore
2.00
自引率
0.00%
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