Analysis of Carrying Capacity and Obstacle Factors of Water Resources in Longnan City, China, Based on Driving–Pressure–State–Response and Technique for Order Preference by Similarity to an Ideal Solution Models
Abstract
:1. Introduction
2. Data Sources and Research Methods
2.1. Overview of the Research Area
2.2. Data Sources
2.3. Research Methods
2.3.1. Indicator System Construction
2.3.2. Entropy Weight Method
- Construct a matrix of i rows and j columns:
- Calculate the proportion of the j-th indicator Pj:
- Calculate the entropy of the j-th indicator Ej:
- Determine the weights of indicators wj:
2.3.3. TOPSIS Model
- Normalize the raw data to obtain a normalized matrix X = (Xij)m×n:The larger, the better the type of indicator:The smaller, the better the type of indicator:
- Multiply the normalized matrix with the weights of indicators wj to obtain the weighted standard matrix R = (rij)m×n:
- Determine the positive ideal solution Rj+ and the negative ideal solution Rj−:
- Determine the distances between the evaluation object and the positive and negative ideal solutions, Di+ and Di−:
- 5.
- Calculate the closeness K:The closer K is to 1, the better the evaluation result.
2.3.4. Obstacle Model
- The factor contribution degree Fij:
- The indicator deviation Vij:
- The obstacle degree of an indicator pij:
- The obstacle degree of a subsystem Pij:
3. Results and Discussion
3.1. Evaluation of Water Resource Carrying Capacity of Longnan City
3.1.1. Evaluation of Water Resource Carrying Capacity of DPSR Comprehensive System
3.1.2. Evaluation of Water Resource Carrying Capacity of DPSR Subsystems
- (1)
- The driving force subsystem
- (2)
- The pressure subsystem
- (3)
- The state subsystem
- (4)
- The response subsystem
3.2. Obstacle Factor Determination of Water Resource Carrying Capacity in Longnan City
3.2.1. Obstacle Analysis of Indicators
3.2.2. Obstacle Analysis of Subsystems
4. Conclusions and Suggestions
- (1)
- From 2009 to 2019, the overall water resource carrying capacity of Longnan City showed an upward trend;
- (2)
- From 2009 to 2019, the closeness of the driving force subsystem increased continuously, possessing the optimal carrying capacity; the closeness of the pressure subsystem presented a tendency of increase-decrease-increase; the carrying capacity of the state subsystem reached the peak of 0.85; and the carrying capacity of the response subsystem tended to decrease;
- (3)
- From the perspective of obstacle factors, the stress subsystem had the highest obstacle degree, followed by the subsystems of response, driving force, and state. The primary obstacle factors to the carrying capacity of water resources in Longnan City are the utilization of unconventional water resources, the proportion of eco-environmental water use, the volume of wastewater discharge, and the per capita urban daily water consumption.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Zhang, Z.; Lu, W.X.; Zhao, Y.; Song, W.B. Development tendency analysis and evaluation of the water ecological carrying capacity in the Siping area of Jilin Province in China based on system dynamics and analytic hierarchy process. Ecol. Modell. 2014, 275, 9–21. [Google Scholar] [CrossRef]
- Duda, A.M.; El-Ashry, M.T. Addressing the global water and environment crises through integrated approaches to the management of land, water and ecological resources. Water Int. 2000, 25, 115–126. [Google Scholar] [CrossRef]
- Liu, J.; Bao, Z.X.; Liu, C.S.; Wang, G.Q.; Liu, Y.; Wang, J.; Guan, X.X. Change law and cause analysis of water resources and water consumption in China in past 20 years. Hydro-Sci. Eng. 2019, 4, 31–41. [Google Scholar] [CrossRef]
- Yang, H.Y.; Sun, X.B.; Cheng, X.W.; Zhou, G.Y.; Sun, G.D. Comprehensive evaluation of water resources carrying capacity in Wefang based on the VIKOR method. Acta Sci. Circumstantiae 2020, 40, 716–723. [Google Scholar] [CrossRef]
- Jin, J.L.; Chen, P.F.; Chen, M.L.; Li, J.Q.; Xu, X.Y.; Chang, T. Bibliometric analysis of research progress on water resources carrying capacity based on knowledge map. Water Resour. Prot. 2019, 35, 14–24+57. [Google Scholar] [CrossRef]
- Li, R.Y.; Shu, L.C.; Lu, C.P.; Si, H.Y.; Hu, X.Y. Application and comparison of water resources carrying capacity evaluation methods in Jining city. Water Resour. Prot. 2018, 34, 65–70. [Google Scholar] [CrossRef]
- Xu, Z.Q.; Liu, X.Y.; Yuan, P.; Zhang, M.L.; Liao, C.G. Dynamic change of water environment carrying capacity in Nanjing city. Res. Environ. Sci. 2019, 32, 557–564. [Google Scholar] [CrossRef]
- Al-Kalbani, M.S.; Price, M.F.; O’Higgins, T.; Ahmed, M.; Abahussain, A. Integrated environmental assessment to explore water resources management in Al Jabal Al Akhdar, Sultanate of Oman. Reg. Environ. Change 2016, 16, 1345–1361. [Google Scholar] [CrossRef]
- Liu, J.T.; Liu, R.Y.; Xu, Y.X. Evaluation research on water resource carrying capacity of prefecture-level cities in Henan province. Yellow River 2022, 44, 53–58. [Google Scholar] [CrossRef]
- Feng, Z.; Chen, Y.; Yang, X. Measurement of spatio-temporal differences and analysis of the obstacles to high-quality development in the Yellow River Basin, China. Sustainability 2022, 14, 14179. [Google Scholar] [CrossRef]
- Liu, P.; Cheng, S.; Shang, M.; Gao, Y.; Wei, S. Effect of weight of water resources carrying capacity evaluation index on its evaluation results in Xinjiang, China. Sustainability 2023, 15, 2645. [Google Scholar] [CrossRef]
- Jin, J.L.; Liu, D.P.; Zhou, R.X.; Zhang, L.B.; Wu, C.G. Evaluation model of water resources carrying capacity based on projection pursuit weight optimization. Water Resour. Prot. 2021, 37, 1–6. [Google Scholar] [CrossRef]
- Zhang, Z.J.; Chen, F.L.; Long, A.H.; He, X.L.; He, C.F. Assessment of water resource security in an arid area based on an extension cloud model: A case study of Shihezi District. Arid. Zone Res. 2020, 37, 847–856. [Google Scholar] [CrossRef]
- Shi, X.X.; Yuan, C.L.; Qian, H.; Xu, P.P.; Zheng, L. Evaluation and obstacle factors of water resources carrying capacity in Hebei province based on DPSIR-TOPSIS model. J. Water Resour. Water Eng. 2021, 32, 92–99. [Google Scholar] [CrossRef]
- Gulishengmu, A.; Yang, G.; Tian, L.; Pan, Y.; Huang, Z.; Xu, X.; Gao, Y.; Li, Y. Analysis of water resource carrying capacity and obstacle factors based on GRA-TOPSIS evaluation method in Manas River Basin. Water 2023, 15, 236. [Google Scholar] [CrossRef]
- Zhi, X.; Anfuding, G.; Yang, G.; Gong, P.; Wang, C.; Li, Y.; Li, X.; Li, P.; Liu, C.; Qiao, C. Evaluation of the water resource carrying capacity on the north scope of the Tianshan Mountains, Northwest China. Sustainability 2022, 14, 1905. [Google Scholar] [CrossRef]
- Wang, G.; Xiao, C.L.; Qi, Z.W.; Meng, F.A.; Liang, X.J. Development tendency analysis for the water resource carrying capacity based on system dynamics model and the improved fuzzy comprehensive evaluation method in the Changchun city, China. Ecol. Indic. 2021, 122, 107232. [Google Scholar] [CrossRef]
- Xiao, Y.; Ou, Y.Q.; Qu, X.Y.; Zhang, L.P.; Zhang, X.; Jun, X. Determining the regional carrying capacity of the Wuhan city circle based on the improved ecological footprint method. J. Am. Water Resour. Assoc. 2021, 57, 585–601. [Google Scholar] [CrossRef]
- Jia, Y.; Wang, H. Study on water resource carrying capacity of Zhengzhou city based on DPSIR model. Int. J. Environ. Res. Public Health 2023, 20, 1394. [Google Scholar] [CrossRef]
- Yang, J.L.; Yang, P.; Zhang, S.Q.; Wang, W.Y.; Cai, W.; Hu, S. Evaluation of water resource carrying capacity in the middle reaches of the Yangtze River Basin using the variable fuzzy-based method. Environ. Sci. Pollut. Res. 2022, 30, 30572–30587. [Google Scholar] [CrossRef]
- Hu, M.Q.; Li, C.J.; Zhou, W.X.; Hu, R.N.; Lu, T. An improved method of using two-dimensional model to evaluate the carrying capacity of regional water resource in Inner Mongolia of China. J. Environ. Manag. 2022, 313, 114896. [Google Scholar] [CrossRef]
- Miao, Z.Y.; Feng, Y.; Liu, D.B. Spatial difference analysis of water resources carrying capacity in Henan province. Pearl River 2022, 43, 41–47. [Google Scholar] [CrossRef]
- Zhu, L.J.; Li, X.C.; Bai, Y.R.; Yi, T.L.; Yao, L.Q. Evaluation of water resources carrying capacity and its obstruction factor analysis: A case study of Hubei province, China. Water 2019, 12, 2573. [Google Scholar] [CrossRef]
- Liu, T.; Yang, X.H.; Zhao, K.Q.; Xue, Q.R. Dynamic evaluation of water resources carrying capacity based on set pair analysis: A case study of Sichuan province. Yangtze River 2019, 50, 94–100. [Google Scholar] [CrossRef]
- Du, X.F.; Li, Y.B.; Zhang, X.Y. Study on water resources carrying capacity of Zhengzhou city based on TOPSIS model. Yellow River 2022, 44, 84–88. [Google Scholar] [CrossRef]
- Hao, X.Y.; Zhang, X.; Yong, Z.Q. Spatial differences of water resources carrying capacity in Yulin city. J. Drain. Irrig. Mach. Eng. 2019, 37, 1037–1043. [Google Scholar] [CrossRef]
- Xu, Y.; Chen, J.; Xia, H.; Chu, L.L.; Zhang, X.Y. Evaluation of water resource carrying capacity in Huai’an city based on DPSR-improved TOPSIS model. J. Water Resour. Water Eng. 2019, 30, 47–52+62. [Google Scholar] [CrossRef]
- Guo, H.D.; Shao, J.L.; Xie, X.M.; Chai, F.X. Urban water resources carrying capacity based on pressure-state-response model. Water Resour. Prot. 2009, 25, 46–49. [Google Scholar] [CrossRef]
- Chen, Y.B.; Chen, J.H.; Li, C.X.; Feng, Z.Y. Indicators for water resources carrying capacity assessment based on driving forces-pressure-state-impact-response model. Shuili Xuebao 2004, 7, 98–103. [Google Scholar] [CrossRef]
- Wu, L.Z.; Zhao, X.; Cheng, Y.; Jing, J.N.; Jia, S.H.; Sun, D.Y. Evaluation of water resources carrying capacity and water resources security in Gansu section of Yellow River Basin. J. Drain. Irrig. Mach. Eng. 2021, 39, 897–903. [Google Scholar] [CrossRef]
- Li, S.P.; Zhao, H.; Wang, F.Q.; Yang, D.M. Evaluation of water resources carrying capacity of Jiangsu Province based on AHP-TOPSIS model. Water Resour. Prot. 2021, 37, 20–25. [Google Scholar] [CrossRef]
- Zuo, Q.T.; Zhang, Z.Z.; Wu, B.B. Evaluation of water resources carrying capacity of nine provinces in the Yellow River basin based on combined weight TOPSIS model. Water Resour. Prot. 2020, 36, 1–7. [Google Scholar] [CrossRef]
- Sun, Q.; Zhang, H.W.; Zhang, X.H. Resources and environment carrying capacity estimation and the obstacle fac-tors diagnosis for Henan province. J. Arid. Land. Resour. Environ. 2015, 29, 33–38. [Google Scholar] [CrossRef]
Target Layer | Ruler Layer | Indicator Layer | Code | Unit | Indicator Definition | Indicator Property | Weight |
---|---|---|---|---|---|---|---|
Water resource carrying capacity | Driving | per capita GDP | x1 | CNY | reflecting the level of economic development | + | 0.0147 |
urbanization rate | x2 | % | reflecting the level of urbanization | − | 0.0425 | ||
natural population growth rate | x3 | ‰ | reflecting the growth of population | − | 0.1507 | ||
urban population density | x4 | per/km2 | reflecting the magnitude of population pressure | − | 0.0585 | ||
Pressure | per capita urban daily water consumption | x5 | L | reflecting the situation of water utilization by urban residents | − | 0.0114 | |
proportion of eco−environmental water use | x6 | % | reflecting the demand and importance of ecological water utilization | + | 0.0785 | ||
wastewater discharge volume | x7 | 10,000 t | reflecting the pollution of the environment by wastewater | − | 0.0391 | ||
water consumption per 10,000 CNY of GDP | x8 | m3/10,000 CNY | reflecting the relationship between economic development and water consumption | − | 0.0750 | ||
State | per capita water resources | x9 | m3/per | reflecting the number of regional water resources | + | 0.0957 | |
rate of the development and utilization of groundwater | x10 | % | accessing the development and utilization of groundwater resources | − | 0.0761 | ||
water production modulus | x11 | 10,000 m3/km2 | representing regional water production capacity per unit area | + | 0.0850 | ||
annual precipitation | x12 | mm | reflecting regional precipitation | + | 0.0165 | ||
Response | popularity rate of urban water | x13 | % | reflecting the popularity level of urban water utilization | + | 0.1151 | |
daily capacity of wastewater treatment | x14 | 10,000 m3 | reflecting the capacity of regional wastewater treatment | + | 0.0063 | ||
unconventional water resource utilization | x15 | a hundred million m3 | reflecting the treatment and utilization of regional unconventional water resources | + | 0.1060 | ||
water-saving irrigation area | x16 | hm2 | reflecting the degree of regional agricultural water-saving | + | 0.0288 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Dang, X.; Zhao, X.; Kang, Y.; Liu, X.; Song, J.; Zhang, Y. Analysis of Carrying Capacity and Obstacle Factors of Water Resources in Longnan City, China, Based on Driving–Pressure–State–Response and Technique for Order Preference by Similarity to an Ideal Solution Models. Water 2023, 15, 2517. https://doi.org/10.3390/w15142517
Dang X, Zhao X, Kang Y, Liu X, Song J, Zhang Y. Analysis of Carrying Capacity and Obstacle Factors of Water Resources in Longnan City, China, Based on Driving–Pressure–State–Response and Technique for Order Preference by Similarity to an Ideal Solution Models. Water. 2023; 15(14):2517. https://doi.org/10.3390/w15142517
Chicago/Turabian StyleDang, Xiaofeng, Xuerui Zhao, Yanxia Kang, Xianyun Liu, Jiaqi Song, and Yuxuan Zhang. 2023. "Analysis of Carrying Capacity and Obstacle Factors of Water Resources in Longnan City, China, Based on Driving–Pressure–State–Response and Technique for Order Preference by Similarity to an Ideal Solution Models" Water 15, no. 14: 2517. https://doi.org/10.3390/w15142517
APA StyleDang, X., Zhao, X., Kang, Y., Liu, X., Song, J., & Zhang, Y. (2023). Analysis of Carrying Capacity and Obstacle Factors of Water Resources in Longnan City, China, Based on Driving–Pressure–State–Response and Technique for Order Preference by Similarity to an Ideal Solution Models. Water, 15(14), 2517. https://doi.org/10.3390/w15142517