Macro-environment oscillation notably up risk of water quality degradation: A case study in Shanxi Reservoir, China
Water quality deterioration in reservoirs threats human drinking water safety. It can be influenced by the macro-processes of meteorology, hydrology, and pollution. However, the mechanism of macro-environment affect water quality risk still is unclear. Water quality is a complex system which should...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X24015231 |
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| author | Wangwei Cai Jihong Xia Zewen Liu Jiayi Zu Shuyi Ji Yue Wang Qihua Wang |
| author_facet | Wangwei Cai Jihong Xia Zewen Liu Jiayi Zu Shuyi Ji Yue Wang Qihua Wang |
| author_sort | Wangwei Cai |
| collection | DOAJ |
| description | Water quality deterioration in reservoirs threats human drinking water safety. It can be influenced by the macro-processes of meteorology, hydrology, and pollution. However, the mechanism of macro-environment affect water quality risk still is unclear. Water quality is a complex system which should be able to adapt to small fluctuation of macro-environment, but turn into deterioration under significant macro-environment oscillation. Shanxi Reservoir in Zhejiang, China, a large reservoir with a total storage capacity of 1.82 billion m3 was used as the study area to test this hypothesis. Monthly macro-environment data from 2014 to 2022 (sample size = 108), including 10 factors of meteorology, hydrology, and pollution, was used to create a Macro-Environment Index (MEI) by Principal Component Analysis. And the water quality data (sample size = 2914) was used to develop a Water Quality Index (WQI) based on Mahalanobis Distance. Bayes methods were used to analyze the relationship between monthly MEI changes (|ΔMEI|) and WQI variations (ΔWQI). Results showed that macro-environment change weakly (|ΔMEI|<0.4) with the overall probability of 41.7 %, strongly (|ΔMEI|≥0.4) with 58.3 %, and acutely (|ΔMEI|≥1) with 26.7 %. While water quality has a 51.7 % chance of water quality deterioration (ΔWQI > 0), significantly increasing (P < 0.01) to 63.6 % when |ΔMEI|≥0.4, and significantly reducing (P < 0.01) to 36.7 % when |ΔMEI|<0.4. |ΔMEI|≥1 leads to a significant jump (P < 0.01) in rapid water quality deterioration (ΔWQI ≥ 0.15) risk from 31.7 % to 62.5 %. Based on Bayesian Inference, we successfully used |ΔMEI| as the independent variable for predicting the probability of water quality deterioration. These findings underscore the importance of monitoring macro-environment changes to assess reservoir water quality risks. |
| format | Article |
| id | doaj-art-8f5b14c8e8b6444f96dc09c10a011d16 |
| institution | Kabale University |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-8f5b14c8e8b6444f96dc09c10a011d162025-01-31T05:10:45ZengElsevierEcological Indicators1470-160X2025-01-01170113066Macro-environment oscillation notably up risk of water quality degradation: A case study in Shanxi Reservoir, ChinaWangwei Cai0Jihong Xia1Zewen Liu2Jiayi Zu3Shuyi Ji4Yue Wang5Qihua Wang6College of Agricultural Science & Engineering, Hohai University, Nanjing, 211100, Jiangsu Province, China; Jiangsu Province Engineering Research Center for Agricultural Soil-Water Efficient Utilization, Carbon Sequestration and Emission Reduction, Nanjing, 211100, Jiangsu Province, China; Corresponding authors.College of Agricultural Science & Engineering, Hohai University, Nanjing, 211100, Jiangsu Province, China; Corresponding authors.College of Agricultural Science & Engineering, Hohai University, Nanjing, 211100, Jiangsu Province, ChinaCollege of Agricultural Science & Engineering, Hohai University, Nanjing, 211100, Jiangsu Province, ChinaCollege of Agricultural Science & Engineering, Hohai University, Nanjing, 211100, Jiangsu Province, ChinaCollege of Agricultural Science & Engineering, Hohai University, Nanjing, 211100, Jiangsu Province, ChinaCollege of Agricultural Science & Engineering, Hohai University, Nanjing, 211100, Jiangsu Province, ChinaWater quality deterioration in reservoirs threats human drinking water safety. It can be influenced by the macro-processes of meteorology, hydrology, and pollution. However, the mechanism of macro-environment affect water quality risk still is unclear. Water quality is a complex system which should be able to adapt to small fluctuation of macro-environment, but turn into deterioration under significant macro-environment oscillation. Shanxi Reservoir in Zhejiang, China, a large reservoir with a total storage capacity of 1.82 billion m3 was used as the study area to test this hypothesis. Monthly macro-environment data from 2014 to 2022 (sample size = 108), including 10 factors of meteorology, hydrology, and pollution, was used to create a Macro-Environment Index (MEI) by Principal Component Analysis. And the water quality data (sample size = 2914) was used to develop a Water Quality Index (WQI) based on Mahalanobis Distance. Bayes methods were used to analyze the relationship between monthly MEI changes (|ΔMEI|) and WQI variations (ΔWQI). Results showed that macro-environment change weakly (|ΔMEI|<0.4) with the overall probability of 41.7 %, strongly (|ΔMEI|≥0.4) with 58.3 %, and acutely (|ΔMEI|≥1) with 26.7 %. While water quality has a 51.7 % chance of water quality deterioration (ΔWQI > 0), significantly increasing (P < 0.01) to 63.6 % when |ΔMEI|≥0.4, and significantly reducing (P < 0.01) to 36.7 % when |ΔMEI|<0.4. |ΔMEI|≥1 leads to a significant jump (P < 0.01) in rapid water quality deterioration (ΔWQI ≥ 0.15) risk from 31.7 % to 62.5 %. Based on Bayesian Inference, we successfully used |ΔMEI| as the independent variable for predicting the probability of water quality deterioration. These findings underscore the importance of monitoring macro-environment changes to assess reservoir water quality risks.http://www.sciencedirect.com/science/article/pii/S1470160X24015231Macro-environment IndexWater Quality IndexReservoirBayesian |
| spellingShingle | Wangwei Cai Jihong Xia Zewen Liu Jiayi Zu Shuyi Ji Yue Wang Qihua Wang Macro-environment oscillation notably up risk of water quality degradation: A case study in Shanxi Reservoir, China Ecological Indicators Macro-environment Index Water Quality Index Reservoir Bayesian |
| title | Macro-environment oscillation notably up risk of water quality degradation: A case study in Shanxi Reservoir, China |
| title_full | Macro-environment oscillation notably up risk of water quality degradation: A case study in Shanxi Reservoir, China |
| title_fullStr | Macro-environment oscillation notably up risk of water quality degradation: A case study in Shanxi Reservoir, China |
| title_full_unstemmed | Macro-environment oscillation notably up risk of water quality degradation: A case study in Shanxi Reservoir, China |
| title_short | Macro-environment oscillation notably up risk of water quality degradation: A case study in Shanxi Reservoir, China |
| title_sort | macro environment oscillation notably up risk of water quality degradation a case study in shanxi reservoir china |
| topic | Macro-environment Index Water Quality Index Reservoir Bayesian |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X24015231 |
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