Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 851, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.scitotenv.2022.157942
Keywords
Water quality index; Driving factor; Risk assessment; Spatial-temporal patterns; Qinghai-Tibet Plateau
Categories
Funding
- National Natural Science Foundation of China [42173064]
- National Science & Technology Infrastructure of China
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This study analyzed the spatiotemporal distribution and trends of water quality in the northeastern Qinghai-Tibet Plateau. The results showed that most monitoring stations had alkaline water and experienced a decrease in water temperature and dissolved oxygen. Parameters such as chemical oxygen demand, permanganate index, five-day biochemical oxygen demand, total phosphorus, and fluoride exhibited a downward trend. Total nitrogen concentration showed no significant decrease. Elevation, urban land, cropland, temperature, and precipitation were identified as factors influencing water quality. Rivers monitored had a relatively low risk of degradation in water quality between 2015 and 2019.
The Qinghai-Tibet Plateau (QTP) is the source for many of the most important rivers in Asia. It is also an essential eco-logical barrier in China and has the characteristic of regional water conservation. Given this importance, we analyzed the spatiotemporal distribution patterns and trends of 10 water quality parameters. These measurements were taken monthly from 67 monitoring stations in the northeastern QTP from 2015 to 2019. To evaluate water quality trends, major factors influencing water quality, and water quality risks, we used a series of analytical approaches including Mann-Kendall test, Boruta algorithm, and interval fuzzy number-based set-pair analysis (IFN-SPA). The results re-vealed that almost all water monitoring stations in the northeastern QTP were alkaline. From 2015 to 2019, the water temperature and dissolved oxygen of most monitoring stations were significantly reduced. Chemical oxygen de-mand, permanganate index, five-day biochemical oxygen demand, total phosphorus, and fluoride all showed a down-ward trend across this same time frame. The annual average total nitrogen (TN) concentration fluctuation did not significantly decrease across the measured time frame. Water quality index (WQI-DET) indicated bad or poor water quality in the study area; however, water quality index without TN (WQI-DET ') reversed the water quality value. The difference between the two indexes suggested that TN was a significant parameter affecting river water quality in the northeastern QTP. Both Spearman correlation and Boruta algorithm show that elevation, urban land, cropland, temperature, and precipitation influence the overall water quality status in the northeastern QTP. The results showed that between 2015 and 2019, most rivers monitored had a relatively low risk of degradation in water quality. This study provides a new perspective on river water quality management, pollutant control, and risk assessment in an area like the QTP that has sensitive and fragile ecology.
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