Water quality assessment and the influence of landscape metrics at multiple scales in Poyang Lake basin
Water quality assessment and the influence of landscape metrics at multiple scales in Poyang Lake basin
复制标题
鄱阳湖流域多尺度水质评价及景观指标影响
DOI：
10.1016/j.ecolind.2022.109096
复制
发表时间：
2022-08
影响因子：
6.9
通讯作者：
Hongwei Zhang
中科院分区：
文献类型：
--
作者：
Jinying Xu;Yang Bai;Hailin You;Xiaowei Wang;Zhifei Ma;Hongwei Zhang
• NH 4 + -N, TN, COD Mn , DO, F.coli and TP were chosen for the WQI min. • The WQI min indicated the better water quality of FR and XS. • Water quality was impacted: landscape configuration > land use type > topography. • Landscape influences water quality more during the dry season and at buffer scale. • Spatial scale change of water quality was most sensitive to land use composition. Stream water quality has been increasingly deteriorated in recent decades because of anthropogenic activities. Assessing water quality via key environmental parameters and quantifying the respective influence of landscape metrics like landscape configuration, land use composition and topography, which can overall represent anthropogenic activities, can facilitate the development of improved water quality management strategies. However, few studies concentrate on the quantitative effect of these landscape metrics groups on the change of key water quality parameters. In this study, with Poyang Lake basin, we selected key factors of the 14 environmental variables for the cost-effective water quality evaluation model of the minimum water quality index (WQI min ) by the random forest method and quantified the contribution of different groups of landscape metrics on key water quality parameters by redundancy analysis and variance partitioning analysis. The results indicated that six water quality parameters of ammonium (NH 4 + -N), total nitrogen (TN), permanganate index (COD Mn ), dissolved oxygen (DO), fecal coliforms ( F.coli ) and total phosphorus (TP) can significantly represent the overall water quality of the Poyang Lake basin. Based on WQI min , the water quality of Fuhe River and Xiushui River was significantly better than that of Ganjiang River, Raohe River, and Xinjiang River in Poyang Lake basin. The contribution of landscape metrics to water quality variation followed the order of landscape configuration (19.0–22.5%) > land use composition (5.2–20.2%) > topography (5.7–8.0%). Here, Build-up land was the environmental factor contributing most significantly to the variation in water quality at both spatial and seasonal scales (5.7–21%). Build-up land, Agricultural land, Contagion index and Cohesion index were positively correlated with TN, TP, COD Mn , and NH 4 + -N and negatively with DO at different scales; Grassland, Forest land, Hypsometric Integral index, Slope, and Mean Shape index showed the opposite relationship. The influence of these landscape types changed with spatial and seasonal scales, more significantly explaining variations in water quality during the dry season and at buffer scale. Changes in water quality at the spatial scale were most sensitive to land use composition. Our results represent a basis for the improvement of water quality management.
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DOI：
10.1016/j.scitotenv.2021.146661
发表时间：
2021-03
期刊：
The Science of the total environment
影响因子：
--
作者：
Hui Ying Pak;C. J. Chuah;E. L. Yong;S. Snyder
通讯作者：
Hui Ying Pak;C. J. Chuah;E. L. Yong;S. Snyder
DOI：
10.3390/ijerph16122149
发表时间：
2019-06
影响因子：
--
作者：
Qing Gu;Hao Hu;Li-gang Ma;L. Sheng;Su Yang;Xiaobin Zhang;Minghua Zhang;Kefeng Zheng;Lisu Chen
通讯作者：
Qing Gu;Hao Hu;Li-gang Ma;L. Sheng;Su Yang;Xiaobin Zhang;Minghua Zhang;Kefeng Zheng;Lisu Chen
影响因子：
3
作者：
Kannel, Prakash Raj;Lee, Seockheon;Khan, Siddhi Pratap
通讯作者：
Khan, Siddhi Pratap
影响因子：
5.8
作者：
W. Shi;J. Xia;Xiang Zhang
通讯作者：
W. Shi;J. Xia;Xiang Zhang
影响因子：
6.9
作者：
Zakariya Nafi' Shehab;N. Jamil;A. Aris;Nur Syuhadah Shafie
通讯作者：
Zakariya Nafi' Shehab;N. Jamil;A. Aris;Nur Syuhadah Shafie