Identifying the water quality variation characteristics and their main driving factors from 2008 to 2020 in the Yellow River Basin, China

被引:8
作者
Liu, Shasha [1 ]
Qiu, Yue [1 ]
Fu, Rui [1 ]
Liu, Yun [2 ]
Suo, Chengyu [1 ]
机构
[1] Univ Sci & Technol Beijing, Sch Energy & Environm Engn, Beijing 100083, Peoples R China
[2] China Natl Environm Monitoring Ctr, Beijing 100012, Peoples R China
关键词
Water quality; Spatiotemporal dynamics; Driving factors; Human activities; Generalize linear model; Yellow River Basin; DISSOLVED-OXYGEN; POLLUTION; WETLAND; URBANIZATION; TEMPERATURE; DISCHARGE; LAKES;
D O I
10.1007/s11356-023-27142-7
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Understanding of the water quality dynamics and their main influence factors is crucial for sustainable water environment management especially in the sensitive ecosystem area. Here, the spatiotemporal dynamic of water quality in the Yellow River Basin from 2008 to 2020 and its relationship with physical geography, human activities, and meteorology were studied by using Pearson correlation test, and a generalized linear model. The results showed that water quality was significantly improved since 2008, which was reflected from the decreasing trend of the permanganate index (CODMn) and ammonia nitrogen (NH3-N), and increasing trend of the dissolved oxygen (DO). However, the total nitrogen (TN) remained severely polluted with average annual concentration inferior to level V. Spatially speaking, the water quality in the upper and lower reaches was better than that of the middle reaches. The whole basin was severely contaminated by TN with 2.62 +/- 1.52, 3.91 +/- 1.71, and 2.91 +/- 1.20 mg L-1 from upper, middle, and lower reaches, respectively. Thus, TN should be paid much attention in the water quality management of the Yellow River Basin. The water quality improvement could be attributed to the reduction of pollution discharges and ecological restoration. Further analysis found the variation of water consumption and increase of forest and wetland area contributed 39.90% and 47.49% for CODMn and 58.92% and 30.87% for NH3-N, respectively. Meteorological variables and total water resources contributed slightly. This study is expected to provide in-depth insights for the water quality dynamics and their response to human activities and natural factors in the Yellow River Basin, which could provide theoretical references for water quality protection and management.
引用
收藏
页码:66753 / 66766
页数:14
相关论文
共 63 条
[1]   Contribution rates analysis for sources apportionment to special river sections in Yangtze River Basin [J].
Bai, Hui ;
Chen, Yan ;
Wang, Yonggui ;
Song, Zhen ;
Tong, Hongjin ;
Wei, Yao ;
Yu, Qing ;
Xu, Ziyi ;
Yang, Shuihua .
JOURNAL OF HYDROLOGY, 2021, 600
[2]   Nitrogen-containing organic compounds: Origins, toxicity and conditions of their photocatalytic mineralization over TiO2 [J].
Bamba, Drissa ;
Coulibaly, Mariame ;
Robert, Didier .
SCIENCE OF THE TOTAL ENVIRONMENT, 2017, 580 :1489-1504
[3]   Modelling regional futures at decadal scale: application to the Kimberley region [J].
Boschetti, Fabio ;
Lozano-Montes, Hector ;
Stelfox, Brad .
SCIENTIFIC REPORTS, 2020, 10 (01)
[4]   Insights into water sustainability from a grey water footprint perspective in an irrigated region of the Yellow River Basin [J].
Chen, Jie ;
Gao, Yanyan ;
Qian, Hui ;
Jia, Hui ;
Zhang, Qiying .
JOURNAL OF CLEANER PRODUCTION, 2021, 316 (316)
[5]   Sustainable development in the Yellow River Basin: Issues and strategies [J].
Chen, Yi-ping ;
Fu, Bo-jie ;
Zhao, Yan ;
Wang, Kai-bo ;
Zhao, Meng M. ;
Ma, Ji-fu ;
Wu, Jun-Hua ;
Xu, Chen ;
Liu, Wan-gang ;
Wang, Hong .
JOURNAL OF CLEANER PRODUCTION, 2020, 263
[6]   Balancing green and grain trade [J].
Chen, Yiping ;
Wang, Kaibo ;
Lin, Yishan ;
Shi, Weiyu ;
Song, Yi ;
He, Xinhua .
NATURE GEOSCIENCE, 2015, 8 (10) :739-741
[7]   Biofloc technology in aquaculture: Beneficial effects and future challenges [J].
Crab, Roselien ;
Defoirdt, Tom ;
Bossier, Peter ;
Verstraete, Willy .
AQUACULTURE, 2012, 356 :351-356
[8]   Mixed spatial scale effects of landscape structure on water quality in the Yellow River [J].
Dou, Jinghui ;
Xia, Rui ;
Chen, Yan ;
Chen, Xiaofei ;
Cheng, Bingfen ;
Zhang, Kai ;
Yang, Chen .
JOURNAL OF CLEANER PRODUCTION, 2022, 368
[9]   The global abundance and size distribution of lakes, ponds, and impoundments [J].
Downing, J. A. ;
Prairie, Y. T. ;
Cole, J. J. ;
Duarte, C. M. ;
Tranvik, L. J. ;
Striegl, R. G. ;
McDowell, W. H. ;
Kortelainen, P. ;
Caraco, N. F. ;
Melack, J. M. ;
Middelburg, J. J. .
LIMNOLOGY AND OCEANOGRAPHY, 2006, 51 (05) :2388-2397
[10]   Spatial Differentiation and Influencing Factors of Water Pollution-Intensive Industries in the Yellow River Basin, China [J].
Du, Haibo ;
Ji, Xuepeng ;
Chuai, Xiaowei .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (01)