1
|
Ding J, Chen Q, Chen Y, Xie X, Sun H, Zhang Q, Ma H. An optimization framework for basin-scale water environmental carrying capacity. J Environ Manage 2024; 351:119520. [PMID: 38043311 DOI: 10.1016/j.jenvman.2023.119520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 10/12/2023] [Accepted: 10/31/2023] [Indexed: 12/05/2023]
Abstract
The interaction between water environment and social economy at a basin scale is complex and challenging to quantify. To address this issue, this study proposes an integrated framework that builds parametric connections among water, contaminants, administrative regions, and social activities. The framework, known as the water environmental carrying capacity (WECC) optimization framework, effectively captures the intricacy of the interaction and integrates socio-economic parameter structure relationships, a water environmental model, a WECC optimization model, and a sensitivity analysis of regulatory parameters. Applied to the Anhui-Huaihe Basin in mid-eastern China, the framework considers nine administrative regions and three economic factors: industry, agriculture, and GDP per capita (pGDP). Results show that the current water environmental carrying capacity of the watershed is insufficient to meet socio-economic development requirements. After optimization, the WECC for industry, agriculture, and pGDP in the region increased by 22.40%, 26.59%, and 15.08% respectively. Overall COD and NH4-N discharge decreased by 13.6% and 14.7% respectively, effectively reducing pollution loads in rivers and enhancing sustainable development potential. At the regional scale, optimization for industry, agriculture, and pGDP exhibited different characteristics, but all aimed to improve efficiency by reducing the K value (pollution discharge/output value ratio). Regions with industrial treatment rates (αwt) below 0.8 should prioritize increasing treatment rates, while those above 0.8 should consider industrial upgrading for enhanced efficiency. For agriculture, important sensitive parameters for farming and livestock breeding are the proportion of high standard farmland (αs) and the scale breeding ratio (αb), which should be increased to above 0.15 and 0.83 respectively for all regions to achieve agricultural optimization. For pGDP optimization, the focus is on improving living environments and reducing pollution discharge, with crucial measures including collecting and treating rural domestic sewage, where the rural toilet improvement rate (αt) in each region should be increased to 0.78 or above. The results emphasize the need for both interregional allocation and intraregional planning to achieve comprehensive basin optimization and a harmonious balance between regional development and water environment.
Collapse
Affiliation(s)
- Jue Ding
- State Key Laboratory of Hydrology-Water Resources & Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210098, China; Center for Eco-Environment Research, Nanjing Hydraulic Research Institute, Nanjing, 210098, China
| | - Qiuwen Chen
- State Key Laboratory of Hydrology-Water Resources & Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210098, China; Center for Eco-Environment Research, Nanjing Hydraulic Research Institute, Nanjing, 210098, China.
| | - Yuchen Chen
- State Key Laboratory of Hydrology-Water Resources & Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210098, China; Center for Eco-Environment Research, Nanjing Hydraulic Research Institute, Nanjing, 210098, China
| | - Xianchuan Xie
- Key Laboratory of Poyang Lake Environment and Resource Utilization for Ministry of Education, School of Resource and Environment, Nanchang University, Nanchang, 330031, China
| | - Hao Sun
- State Key Laboratory of Hydrology-Water Resources & Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210098, China; Center for Eco-Environment Research, Nanjing Hydraulic Research Institute, Nanjing, 210098, China
| | - Qi Zhang
- State Key Laboratory of Hydrology-Water Resources & Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210098, China; Center for Eco-Environment Research, Nanjing Hydraulic Research Institute, Nanjing, 210098, China
| | - Honghai Ma
- State Key Laboratory of Hydrology-Water Resources & Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210098, China; Center for Eco-Environment Research, Nanjing Hydraulic Research Institute, Nanjing, 210098, China
| |
Collapse
|
2
|
Wang P, Deng H. Research on regional water environmental carrying capacity based on GIS and TOPSIS comprehensive evaluation model. Environ Sci Pollut Res Int 2023; 30:57728-57746. [PMID: 36967427 DOI: 10.1007/s11356-023-26574-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 03/16/2023] [Indexed: 05/10/2023]
Abstract
Water environmental carrying capacity (WECC) is an important indicator for assessing the coordination between the water environment and the social-economic-resources and environment subsystems. In this study, to determine the WECC of Changsha-Zhuzhou-Xiangtan urban agglomeration in Xiang River Basin, a three-level index system was established using an analytic hierarchy process. Because the previous evaluation system lacked continuous indicators, the results could not reflect the differences of WECC within the administrative units, thus, this study selected 4 continuous indicators, and finally an evaluation index system including 15 indicators was established. Based on the TOPSIS model and logistic regression model, the current situation and change trend of WECC in the study area were obtained in ArcGIS. The results showed that the comprehensive WECC in this region was inferior in 2020, particularly in urban concentrated areas, and it was extremely uneven in spatial distribution. The WECC decreased significantly from 2011 to 2014 and gradually improved from 2014 to 2020. According to the prediction results, the WECC will increase in the future, with an average value of 0.54 in 2025 and 0.60 in 2035. This study will have important guiding implications for the protection and improvement of the water environment in the study area and related areas.
Collapse
Affiliation(s)
- Peng Wang
- School of Resources & Safety Engineering, Central South University, Changsha, 410083, Hunan, People's Republic of China
| | - Hongwei Deng
- School of Resources & Safety Engineering, Central South University, Changsha, 410083, Hunan, People's Republic of China.
| |
Collapse
|
3
|
Chen S, He Y, Tan Q, Hu K, Zhang T, Zhang S. Comprehensive assessment of water environmental carrying capacity for sustainable watershed development. J Environ Manage 2022; 303:114065. [PMID: 34823905 DOI: 10.1016/j.jenvman.2021.114065] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 10/24/2021] [Accepted: 11/02/2021] [Indexed: 06/13/2023]
Abstract
Due to insufficient understanding of human-water interaction, many water-related problems arise in watersheds, posing severe threats to the sustainability of watershed development. Although water environmental carrying capacity (WECC) is a powerful tool to support sustainable development of watersheds, few studies considered aquatic ecological factors and uncertainty in indicator values, leading to losses of sample information in the evaluation of WECC. This paper developed a systematic framework for comprehensive WECC assessment that included the indicator system and a novel variable fuzzy pattern recognition (VFPR) approach. The WECC index system incorporated aquatic ecological factors, and addressed uncertainties associated with the indicator values. The proposed VFPR-based assessment model could realize successive evaluation to retain more original information of the sample and distinguish similar result values by treating the sample as having a continuous degree of membership instead of the traditional point form. In addition, it could be more adaptable to various circumstances including extreme cases, and closely reflect the impacts of indicator changes on the results. The established evaluation framework has been applied to Dongjiang River Basin in Guangdong Province. The spatial differences and main influencing factors of WECC in the study area were analyzed. Results show that 50% and 16.7% of the sub-regions in the study area would be subject to a poor level of WECC under pessimistic and optimistic circumstances, respectively. WECCs in the upper and lower reaches are the best and worst, respectively, which is in line with the levels of economic development in the Dongjiang River Basin. The proposed method can also be applicable to many other problems involving numerous indicators.
Collapse
Affiliation(s)
- Shuying Chen
- Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China
| | - Yanhu He
- Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China
| | - Qian Tan
- Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China; Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, 511458, China.
| | - Kejia Hu
- College of Water Resources and Civil Engineering, China Agricultural University, Beijing, 100083, China
| | - Tianyuan Zhang
- College of Water Resources and Civil Engineering, China Agricultural University, Beijing, 100083, China
| | - Shan Zhang
- College of Water Resources and Civil Engineering, China Agricultural University, Beijing, 100083, China
| |
Collapse
|