# Water Resources Carrying Capacity Based on the DPSIRM Framework: Empirical Evidence from Shiyan City, China

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## Abstract

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## 1. Introduction

## 2. Literature Review

#### 2.1. The Concept of Carrying Capacity

#### 2.2. The Factors Causing Water Resource Overload or Water Shortages

#### 2.3. The Evaluation Method of Water Resources Carrying Capacity

^{3}/(person·year) in Beijing based on the water resources used in Beijing around 2002, Beijing’s urban population carrying capacity was defined as 5–6 million people. By 2003, the total population of Beijing had reached 14.56 million, with an urban population of 11.51 million. The actual population size had exceeded its carrying capacity by nearly double. The population exceeding its carrying capacity is the fundamental reason for the severe water shortage in the region [14]. (3) Some scholars have used multi-index or comprehensive index methods in their studies, such as the fuzzy comprehensive evaluation method used by Zhou, Z. et al. By establishing the evaluation index system of medium water quality safety and using the analytic hierarchy process (AHP) to weigh the evaluation indicators, a fuzzy comprehensive evaluation model was established. The model was applied to the Liantang Water demonstration base in Shenzhen, and the results showed that the method has a small error, avoids subjective randomness, and conforms to the actual situation [18]. Lv, A. et al. used the fuzzy comprehensive evaluation method to evaluate the vulnerability of the WRCC system in China, and the results showed that the risk of WRCC occurrence in North China was higher than that in South China, and that in developed areas, it was higher than that in developing areas. Among them, the Beijing–Tianjin–Hebei region is at the highest risk [2]. Wang, G. et al. combined the fuzzy comprehensive evaluation with the system dynamics model to study the carrying capacity of water resources, the results showed that if the current development model were continued, the carrying capacity of water resources in Changchun would continue to decline and remain at a lower ‘normal carrying’ level. The carrying capacity of water resources in Changchun City can be improved by changing the production mode and proportion of the national economy. The rational allocation of water resources and strengthening water ecological protection can significantly improve the carrying capacity of water resources and keep it in a ‘positive carrying’ state while maintaining stable economic and social development [19]. Wang, Y. et al. selected various indicators related to water resources, society, and the economy and established a comprehensive evaluation index system with multiple indicators. Research has shown that due to rapid development and population expansion, there is a serious shortage and overload of water resources in Wuhan. The future development of Wuhan is worrying, and the same concerns apply to Ezhou. Other cities in the Wuhan urban agglomeration, such as Xiaogan, Huanggang, Qianjiang, and Tianmen, have greater potential for carrying water resources [20]. (4) Wang, Y.F. et al., taking the Shendong mining area as the research object, used the gray prediction model to predict the water demand of the economy–society–ecosystem in the mining area from 2020 to 2030 under different scenarios, and the results showed that the allocation structure of water resources in the mining area needed to be further optimized, and the scale of water use in the mining area could not adapt to its carrying capacity [21]. (5) Yang, J.F. et al. constructed a water resources carrying capacity evaluation model based on the system dynamics model and used this method to evaluate the water resources status of Tieling in different scenarios. The results show that given the constraints represented by water resources, GDP growth is expected to trend to the s-curve growth model; rapid population growth may lead to earlier and more severe water resource constraints [22]. Hu, G.Z. et al. built a system dynamics model based on the five systems of population, ecology, water resources, water environment, and water ecology and studied the North Canal Basin’s water resources carrying capacity. It is estimated that the water environment and resource carrying rate will fall to 2.60 and 0.94, respectively, in 2025, while the water ecological carrying rate will remain stable at 10.98 [23]. Sun, Y. et al. took the five subsystems of the economy—population, supply and demand, land resources, water pollution, and management—as macroeconomic factors affecting the sustainable utilization of water resources and then used the system dynamics model to build a feedback loop and inventory flow chart of the system to simulate the changes in the water supply and demand situation and the future supply and demand gap from 2005 to 2020. The results showed that the water use efficiency in China would be significantly improved compared with that in 2005. By 2020, the gap between water supply and demand will reach 220 billion cubic meters, 4.8 times that of 2005 [24]. Feng, L.H. et al. simulated the water resources carrying capacity of Yiwu using the system dynamics method. If the current water supply level is maintained, the water supply of Yiwu will not be able to meet the requirements in the near future [9]. (6) Weng, X.R. et al. combined the economic, social, and ecological characteristics of using 26 specific evaluation indicators and evaluated and analyzed the carrying capacity of water resources in Chongqing via principal component analysis. The results show that the carrying capacity of water resources in Chongqing was continuously optimized and gradually enhanced from 2003 to 2017 [25]. Wu, F. et al. selected 13 indicators from the four aspects of the economy, society, environment, and water resources and analyzed the water resources carrying capacity of Huai’an City via principal component analysis. The results showed that the water resources carrying capacity of Huai’an City declined year by year from 2013 to 2019 [26]. Scenario simulation: Yang, Z. et al. designed five scenarios, conducted a simulation analysis of the water resources carrying capacity of Xi’an, and determined the city’s social, economic, water supply and demand, and wastewater discharge development from 2015 to 2020. If the current social development pattern is maintained, WRCC (0.32 in 2020) will change from ‘normal’ to ‘poor’ [27]. Yang, J.L. et al. calculated the water resources carrying capacity of the Three Gorges Reservoir Area from 2005 to 2020 using the variable fuzzy evaluation method. From 2005 to 2020, although the population and GDP of the urban agglomeration increased, the water supply capacity first increased and then decreased. From 2005 to 2020, the carrying capacity of water resources in the Three Gorges Reservoir area showed an increasing trend [28].

#### 2.4. Research Framework

## 3. Materials and Methods

#### 3.1. Study Area

#### 3.2. Dataset and Source

#### 3.3. Methods

#### 3.3.1. DPSIRM Framework

Criterion Layer | Indicator Layer | Properties | Calculation Methods | Reference |
---|---|---|---|---|

Driving force (D) | X_{D1} Per capita GDP (yuan) | Positive | From statistical data | [34,35] |

X_{D2} density of population | Negative | From statistical data | [34,35] | |

X_{D3} urbanization rate | Negative | From statistical data | [34,35] | |

Pressure (P) | X_{P1} Wastewater discharge per unit of industrial output value (t/10,000 CNY) | Negative | Amount of industrial wastewater discharge/industrial output value | [35,36] |

X_{P2} Household water consumption (10,000 m^{3}) | Negative | From statistical data | [36] | |

X_{P3} Average annual fertilizer application per unit cultivated land (kg/hm^{2}) | Negative | Amount of fertilizer application/cultivated area | [35,36] | |

Status (S) | X_{S1} Water resources per capita (m^{3}) | Positive | Amount of regional water resource/regional population | [34,35] |

X_{S2} Water resources per unit area (m^{3}/hm^{2}) | Positive | Amount of regional water resources/regional land area | [34,35] | |

X_{S3} Annual precipitation (100 million cubic meters) | Positive | From statistical data | [37] | |

Impact (I) | X_{I1} Proportion of guaranteed harvest area of drought and flood in cultivated land (%) | Positive | Guaranteed harvest area in drought and flood/cultivated area | [38] |

X_{I2} Water quality in line with Class I~III standard proportion | Positive | From statistical data | [35] | |

X_{I3} Forest coverage rate (%) | Positive | From statistical data | [38] | |

Response (R) | X_{R1} Sewage treatment rate (%) | Positive | From statistical data | [35,36] |

X_{R2} Length of drainage pipe (km) | Positive | From statistical data | [34] | |

Management (M) | X_{M1} Green coverage rate of built-up areas (%) | Positive | The annual built-up green cover area/green cover area | [34] |

X_{M2} Investment in wastewater treatment (10,000 CNY) | Positive | From statistical data | [36] |

#### 3.3.2. Index Weight Determination

- (1)
- Data standardization.

- (2)
- Calculate the entropy of the j-th index.

- (3)
- Calculate information on entropy redundancy.

- (4)
- Calculate the weights of each indicator.

#### 3.3.3. Obstacle Degree Model

## 4. Results

#### 4.1. Change in Comprehensive Score of Water Resources Carrying Capacity in Shiyan City

#### 4.2. Analysis of Water Resources Carrying Capacity Obstacle Degree

#### 4.2.1. Subsystem Obstacle Degree Analysis

#### 4.2.2. Obstacle Degree Analysis of Each Factor

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## References

- Vorosmarty, C.J.; Green, P.; Salisbury, J.; Lammers, R.B. Global water resources: Vulnerability from climate change and population growth. Science
**2000**, 289, 284–288. [Google Scholar] [CrossRef] [PubMed] - Lv, A.; Han, Y.; Zhu, W.; Zhang, S.; Zhao, W. Risk Assessment of Water Resources Carrying Capacity in China. J. Am. Water Resour. Assoc.
**2021**, 57, 539–551. [Google Scholar] [CrossRef] - Yi, L.; Yanzhao, Y.; Huimin, Y.; Zhen, Y. Research methods of water resources carrying capacity: Progress and prospects. J. Resour. Ecol.
**2018**, 9, 455–460. [Google Scholar] [CrossRef] - Gunasekara, N.K.; Kazama, S.; Yamazaki, D.; Oki, T. Water Conflict Risk due to Water Resource Availability and Unequal Distribution. Water Resour. Manag.
**2014**, 28, 169–184. [Google Scholar] [CrossRef] - Ren, C.; Guo, P.; Li, M.; Li, R. An innovative method for water resources carrying capacity research–metabolic theory of regional water resources. J. Environ. Manag.
**2016**, 167, 139–146. [Google Scholar] [CrossRef] - Hartvigsen, G. Carrying Capacity, Concept of. In Encyclopedia of Biodiversity, 2nd ed.; Academic Press: Cambridge, MA, USA, 2013; pp. 695–701. [Google Scholar] [CrossRef]
- Geores, M.E. Human–Environment Relationship: Carrying Capacity. In International Encyclopedia of the Social Behavioral Sciences; Elsevier: Amsterdam, The Netherlands, 2001; pp. 7038–7039. [Google Scholar] [CrossRef]
- Huang, N.S.; Kuang, Y.Q. The carrying capacity of resources and the problems of sustainable development in Guangdong Province. Econ. Geogr.
**2000**, 20, 52–56. (In Chinese) [Google Scholar] - Feng, L.H.; Zhang, X.C.; Luo, G.Y. Application of system dynamics in analyzing the carrying capacity of water resources in Yiwu City, China. Math. Comput. Simul.
**2008**, 79, 269–278. [Google Scholar] [CrossRef] - Song, X.; Kong, F.; Zhan, C. Assessment of Water Resources Carrying Capacity in Tianjin City of China. Water Resour. Manag.
**2010**, 25, 857–873. [Google Scholar] [CrossRef] - Motoshita, M.; Pfister, S.; Finkbeiner, M. Regional Carrying Capacities of Freshwater Consumption-Current Pressure and Its Sources. Environ. Sci. Technol.
**2020**, 54, 9083–9094. [Google Scholar] [CrossRef] - Zhang, S.; Xiang, M.; Yang, J.; Fan, W.; Yi, Y. Distributed hierarchical evaluation and carrying capacity models for water resources based on optimal water cycle theory. Ecol. Indic.
**2019**, 101, 432–443. [Google Scholar] [CrossRef] - Yang, L.; Wang, L. Comprehensive assessment of urban water resources carrying capacity based on basin unit: A case study of Qingdao, China. Water Supply
**2022**, 22, 1347–1359. [Google Scholar] [CrossRef] - Zhang, Y.; Chen, M.; Zhou, W.; Zhuang, C.; Ouyang, Z. Evaluating Beijing’s human carrying capacity from the perspective of water resource constraints. J. Environ. Sci.
**2010**, 22, 1297–1304. [Google Scholar] [CrossRef] [PubMed] - Aboelnga, H.T.; El-Naser, H.; Ribbe, L.; Frechen, F.-B. Assessing Water Security in Water-Scarce Cities: Applying the Integrated Urban Water Security Index (IUWSI) in Madaba, Jordan. Water
**2020**, 12, 1299. [Google Scholar] [CrossRef] - Bu, J.; Li, C.; Wang, X.; Zhang, Y.; Yang, Z. Assessment and prediction of the water ecological carrying capacity in Changzhou city, China. J. Clean. Prod.
**2020**, 277, 123988. [Google Scholar] [CrossRef] - Skoulikidis, N.T. The environmental state of rivers in the Balkans—A review within the DPSIR framework. Sci. Total Environ.
**2009**, 407, 2501–2516. [Google Scholar] [CrossRef] [PubMed] - Zhou, Z.; Zhang, X.; Dong, W. Fuzzy comprehensive evaluation for safety guarantee system of reclaimed water quality. Procedia Environ. Sci.
**2013**, 18, 227–235. [Google Scholar] [CrossRef] - Wang, G.; Xiao, C.; Qi, Z.; Meng, F.; Liang, X. 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] - Wang, Y.; Cheng, H.; Huang, L. Water resources carrying capacity evaluation of a dense city group: A comprehensive water resources carrying capacity evaluation model of Wuhan urban agglomeration. Urban Water J.
**2018**, 15, 615–625. [Google Scholar] [CrossRef] - Wang, Y.F.; Sun, K.; Li, L.; Lei, Y.L.; Wu, S.M.; Wang, F.; Luo, J.Y. The optimal allocation and the evaluation of water resources carrying capacity in Shendong mining area. Resour. Policy
**2022**, 77, 102738. [Google Scholar] [CrossRef] - Yang, J.F.; Lei, K.; Khu, S.; Meng, W. Assessment of Water Resources Carrying Capacity for Sustainable Development Based on a System Dynamics Model: A Case Study of Tieling City, China. Water Resour. Manag.
**2015**, 29, 885–899. [Google Scholar] [CrossRef] - Hu, G.Z.; Zeng, W.H.; Yao, R.H.; Xie, Y.X.; Liang, S. An integrated assessment system for the carrying capacity of the water environment based on system dynamics. J. Environ. Manag.
**2021**, 295, 113045. [Google Scholar] [CrossRef] - Sun, Y.; Liu, N.; Shang, J.; Zhang, J. Sustainable utilization of water resources in China: A system dynamics model. J. Clean. Prod.
**2017**, 142, 613–625. [Google Scholar] [CrossRef] - Weng, X.R.; Long, X.J.; Ye, Y.; Peng, F. Study on Water Resource Carrying Capacity of Chongqing City by DPSIR Coupling Model. J. Water Resour. Res.
**2020**, 9, 189–201. [Google Scholar] [CrossRef] - Wu, F.; Zhuang, Z.; Liu, H.L.; Shiau, Y.C. Evaluation of water resources carrying capacity using principal component analysis: An empirical study in Huai’an, Jiangsu, China. Water
**2021**, 13, 2587. [Google Scholar] [CrossRef] - Yang, Z.; Song, J.; Cheng, D.; Xia, J.; Li, Q.; Ahamad, M.I. Comprehensive evaluation and scenario simulation for the water resources carrying capacity in Xi’an city, China. J. Environ. Manag.
**2019**, 230, 221–233. [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.
**2023**, 30, 30572–30587. [Google Scholar] [CrossRef] [PubMed] - Borja, A.; Galparsoro, I.; Solaun, O.; Muxika, I.; Tello, E.M.; Uriarte, A.; Valencia, V. The European Water Framework Directive and the DPSIR, a methodological approach to assess the risk of failing to achieve good ecological status. Estuar. Coast. Shelf Sci.
**2006**, 66, 84–96. [Google Scholar] [CrossRef] - Sun, S.; Wang, Y.; Liu, J.; Cai, H.; Wu, P.; Geng, Q.; Xu, L. Sustainability assessment of regional water resources under the DPSIR framework. J. Hydrol.
**2016**, 532, 140–148. [Google Scholar] [CrossRef] - Vannevel, R. Using DPSIR and balances to support water governance. Water
**2018**, 10, 118. [Google Scholar] [CrossRef] - Gari, S.R.; Newton, A.; Icely, J.D. A review of the application and evolution of the DPSIR framework with an emphasis on coastal social-ecological systems. Ocean Coast. Manag.
**2015**, 103, 63–77. [Google Scholar] [CrossRef] - Jago-on, K.A.B.; Kaneko, S.; Fujikura, R.; Fujiwara, A.; Imai, T.; Matsumoto, T.; Zhang, J.; Tanikawa, H.; Tanaka, K.; Lee, B.; et al. Urbanization and subsurface environmental issues: An attempt at DPSIR model application in Asian cities. Sci. Total Environ.
**2009**, 407, 3089–3104. [Google Scholar] [CrossRef] [PubMed] - Chai, N.; Zhou, W. The DPSIRM—Grey cloud clustering method for evaluating the water environment carrying capacity of Yangtze River economic Belt. Ecol. Indic.
**2022**, 136, 108722. [Google Scholar] [CrossRef] - Wang, J.; Mu, X.; Chen, S.; Liu, W.; Wang, Z.; Dong, Z. Dynamic evaluation of water resources carrying capacity of the Dianchi Lake Basin in 2005–2015, based on DSPERM framework model and simulated annealing-projection pursuit model. Reg. Sustain.
**2021**, 2, 189–201. [Google Scholar] [CrossRef] - Long, X.; Wu, S.; Wang, J.; Wu, P.; Wang, Z. Urban water environment carrying capacity based on VPOSR-coefficient of variation-grey correlation model: A case of Beijing, China. Ecol. Indic.
**2022**, 138, 108863. [Google Scholar] [CrossRef] - Hazbavi, Z.; Sadeghi, S.H.; Gholamalifard, M.; Davudirad, A.A. Watershed health assessment using the pressure–state–response (PSR) framework. Land Degrad. Dev.
**2020**, 31, 3–19. [Google Scholar] [CrossRef] - Guo, Q.; Wang, J.; Zhang, B. Comprehensive evaluation of the water resource carrying capacity based on DPSIRM. J. Nat. Resour.
**2017**, 32, 484–493. (In Chinese) [Google Scholar]

**Figure 1.**The study area covers parts of Hubei Province in China. Colored areas show the studied city.

**Figure 2.**Change of water resources carrying capacity in Shiyan City. Note: The solid line is Comprehensive Score of Water Resources Carrying Capacity in Shiyan City; The dashed line is the trend line.

Indicator | Information Entropy e | Information Utility Value d | Weight Coefficient w |
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MMS_D1 | 0.8854 | 0.1146 | 5.90% |

NMMS_D2 | 0.7822 | 0.2178 | 11.20% |

NMMS_D3 | 0.8522 | 0.1478 | 7.60% |

NMMS_P1 | 0.9059 | 0.0941 | 4.84% |

NMMS_P2 | 0.8889 | 0.1111 | 5.71% |

NMMS_P3 | 0.8307 | 0.1693 | 8.71% |

MMS_S1 | 0.9437 | 0.0563 | 2.89% |

MMS_S2 | 0.9456 | 0.0544 | 2.80% |

MMS_S3 | 0.9064 | 0.0936 | 4.81% |

MMS_I1 | 0.8663 | 0.1337 | 6.87% |

MMS_I2 | 0.9387 | 0.0613 | 3.15% |

MMS_I3 | 0.9477 | 0.0523 | 2.69% |

MMS_R1 | 0.9163 | 0.0837 | 4.31% |

MMS_R2 | 0.9007 | 0.0993 | 5.11% |

MMS_M1 | 0.8322 | 0.1678 | 8.63% |

MMS_M2 | 0.7128 | 0.2872 | 14.77% |

Year | M Subsystem U Value | R Subsystem U Value | II Subsystem U Value | S Subsystem U Value | P Subsystem U Value | D Subsystem U Value |
---|---|---|---|---|---|---|

2011 | 0.1149 | 0.3117 (I) | 0.0861 | 0.1056 | 0.2043 (II) | 0.1775 (III) |

2012 | 0.2343 (I) | 0.2329 (II) | 0.0618 | 0.0978 | 0.1975 (III) | 0.1757 |

2013 | 0.2533 (I) | 0.1987 (II) | 0.1028 | 0.0964 | 0.1757 | 0.1731 |

2014 | 0.2639 (I) | 0.1695 (III) | 0.0944 | 0.1264 | 0.1606 | 0.1852 (II) |

2015 | 0.2592 (I) | 0.1713 (III) | 0.0834 | 0.1283 | 0.1621 | 0.1957 (II) |

2016 | 0.2212 (II) | 0.0542 | 0.0727 | 0.2117 (III) | 0.1900 | 0.2502 (I) |

2017 | 0.2361 (II) | 0.1080 | 0.1492 | 0.0000 | 0.2173 (III) | 0.2894 (I) |

2018 | 0.1672 | 0.0679 | 0.1993 (III) | 0.2690 (I) | 0.0890 | 0.2077 (II) |

2019 | 0.1963 (III) | 0.0429 | 0.1997 | 0.2418 (I) | 0.0838 | 0.2356 (II) |

2020 | 0.3081 (I) | 0.0301 | 0.2687 (II) | 0.0390 | 0.1224 | 0.2317 (III) |

2021 | 0.3342 (I) | 0.0000 | 0.2658 (II) | 0.0370 | 0.1942 (III) | 0.1689 |

Year | Category | No. 1 Obstacle | No. 2 Obstacle | No. 3 Obstacle |
---|---|---|---|---|

2011 | obstacle factors | R2 | R1 | P3 |

obstacle degree | 0.1691 | 0.1426 | 0.1169 | |

2012 | obstacle factors | R2 | M2 | P3 |

obstacle degree | 0.1437 | 0.1403 | 0.1301 | |

2013 | obstacle factors | M2 | R2 | P3 |

obstacle degree | 0.1631 | 0.1339 | 0.1212 | |

2014 | obstacle factors | M2 | P3 | D2 |

obstacle degree | 01715 | 0.1127 | 0.1101 | |

2015 | obstacle factors | M2 | R1 | P3 |

obstacle degree | 0.1640 | 0.1237 | 0.1133 | |

2016 | obstacle factors | D2 | P3 | M2 |

obstacle degree | 0.1452 | 0.1233 | 0.1142 | |

2017 | obstacle factors | M2 | D2 | P3 |

obstacle degree | 0.2325 | 0.1679 | 0.1230 | |

2018 | obstacle factors | M2 | I1 | S3 |

obstacle degree | 0.1638 | 0.1454 | 0.1232 | |

2019 | obstacle factors | M2 | I1 | S3 |

obstacle degree | 0.1963 | 0.1623 | 0.1201 | |

2020 | obstacle factors | M2 | I1 | P2 |

obstacle degree | 0.3063 | 0.2490 | 0.1224 | |

2021 | obstacle factors | M2 | I1 | P2 |

obstacle degree | 0.3240 | 0.2658 | 0.1627 |

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**MDPI and ACS Style**

Cheng, W.; Zhu, J.; Zeng, X.; You, Y.; Li, X.; Wu, J.
Water Resources Carrying Capacity Based on the DPSIRM Framework: Empirical Evidence from Shiyan City, China. *Water* **2023**, *15*, 3060.
https://doi.org/10.3390/w15173060

**AMA Style**

Cheng W, Zhu J, Zeng X, You Y, Li X, Wu J.
Water Resources Carrying Capacity Based on the DPSIRM Framework: Empirical Evidence from Shiyan City, China. *Water*. 2023; 15(17):3060.
https://doi.org/10.3390/w15173060

**Chicago/Turabian Style**

Cheng, Wenming, Jing Zhu, Xiaochun Zeng, Yuan You, Xuetao Li, and Jun Wu.
2023. "Water Resources Carrying Capacity Based on the DPSIRM Framework: Empirical Evidence from Shiyan City, China" *Water* 15, no. 17: 3060.
https://doi.org/10.3390/w15173060