A Pricing Model for Groundwater Rights in Ningxia, China Based on the Fuzzy Mathematical Model
Abstract
:1. Introduction
2. Materials and Methods
2.1. Research Area
2.2. Data Sources
2.3. Methods
2.3.1. Groundwater Rights Fuzzy Evaluation Model
- Save groundwater resources and improve the utilization rate of groundwater resources
- Protect groundwater resources and the water environment
- Encourage different funds to invest in groundwater resources’ development, utilization, allocation, conservation, and protection.
- (1)
- Sustainable development. Scientific and reasonable prices should coordinate the interests of governments, enterprises, and water users; coordinate ecological, economic, and social benefits; coordinate contemporary and future generation benefits; and ultimately realize the fairness and sustainability of water resources utilization in space and time.
- (2)
- Efficient utilization. The insufficient supply of groundwater makes it difficult to meet all needs. Therefore, from the economic perspective, we should pursue the best use of water under the guidance of price tools. This allows groundwater to be allocated to places with high utilization efficiency and to create more value. This involves striving to maximize the utilization of groundwater resources.
- (3)
- Fairness. Water resources are necessary for human production and life. As such, it is necessary to ensure the basic needs of all people, to ensure the fair allocation of groundwater in different regions and across different industries and groups. It is particularly important to ensure the water rights of vulnerable groups.
2.3.2. Factor Weights Calculation Method
- (1)
- According to the network hierarchy, the pricing indicators were compared pairwise. Setting a certain indicator as the criterion, the relative influence intensity of the other elements influencing the indicator was evaluated. Generally, the magnitude of influence was expressed with the numbers from 1 to 9.
- (2)
- Construct the unweighted supermatrix. The element in the matrix, for example, , was the degree of influence of the element i on the element j.
- (3)
- Similarly, the influence vectors between clusters were obtained by comparing two clusters with each other. The unweighted supermatrix was multiplied by the corresponding weight to obtain the weighted supermatrix. The power operation was applied to the weighted supermatrix, so that the power exponent tended to infinity. When every column element no longer changed, the limit matrix was obtained. The limit matrix shows the quantitative influence of all the indicators on the price, namely, the weights of indicators.
- (1)
- Data standardization. This paper used 0-1 standardization. The formula is:
- (2)
- Data normalization. The formula is:
- (3)
- Calculate the entropy of each indicator. The entropy of indicator i is calculated as Equation (11)–(12).
2.3.3. Price Calculation Model
3. Results and Discussion
3.1. Evaluation Indicators and Actual Value
3.2. Evaluation Criteria of Indicators
3.3. The Network Structure and Weights
3.4. Fuzzy Synthetic Evaluation of Groundwater Rights Price
3.5. Calculation of Groundwater Rights Price
4. Conclusions and Recommendations
Author Contributions
Funding
Conflicts of Interest
References
- Yue, C.; Wang, Q.; Li, Y. Evaluating water resources allocation in arid areas of northwest China using a projection pursuit dynamic cluster model. Water Supply 2019, 19, 762–770. [Google Scholar] [CrossRef]
- Zhang, J.; Lin, X.; Guo, B. Multivariate Copula-Based Joint Probability Distribution of Water Supply and Demand in Irrigation District. Water Resour. Manag. 2016, 30, 2361–2375. [Google Scholar] [CrossRef]
- Custodio, E. Aquifer overexploitation: What does it mean? Hydrogeol. J. 2002, 10, 254–277. [Google Scholar] [CrossRef]
- Goldfarb, W. Water Law, 2nd ed.; Lewis publishers, Inc.: Boca Raton, FL, USA, 1988. [Google Scholar]
- Ostrom, V.; Ostrom, E. Legal and Political Conditions of Water Resource Development. Land Econ. 1972, 48, 1–14. [Google Scholar] [CrossRef]
- Coase, R.H. The Nature of the Firm. In Essential Readings in Economics; Estrin, S., Marin, A., Eds.; Macmillan Education: London, UK, 1995; pp. 37–54. [Google Scholar]
- Bjornlund, H. Efficient Water Market Mechanisms to Cope with Water Scarcity. Int. J. Water Resour. Dev. 2003, 19, 553–567. [Google Scholar] [CrossRef]
- Grafton, R.; Libecap, G.; McGlennon, S.; Landry, C.; OBrien, B. An Integrated Assessment of Water Markets: A Cross-Country Comparison. Rev. Environ. Econ. Policy 2011, 5, 219. [Google Scholar] [CrossRef]
- Brooks, R.; Harris, E. Efficiency gains from water markets: Empirical analysis of Watermove in Australia. Agric. Water Manag. 2008, 95, 391–399. [Google Scholar] [CrossRef]
- Bauer, C.J. Bringing water markets down to earth: The political economy of water rights in Chile, 1976–1995. World Dev. 1997, 25, 639–656. [Google Scholar] [CrossRef]
- Boyd, T.; Brumley, J. Advancing the trade of groundwater entitlements in Australia. In WIT Transactions on Ecology and the Environment; Cunha, M., Brebbia, C.A., Eds.; WIT Press: Ashurst, UK, 2005; Volume 80, pp. 403–411. [Google Scholar]
- Khair, S.M.; Mushtaq, S.; Culas, R.J.; Hafeez, M. Groundwater markets under the water scarcity and declining watertable conditions: The upland Balochistan Region of Pakistan. Agric. Syst. 2012, 107, 21–32. [Google Scholar] [CrossRef] [Green Version]
- Manjunatha, A.V.; Speelman, S.; Aravindakshan, S.; Babu, A.T.S.; Mal, P. Impact of informal groundwater markets on efficiency of irrigated farms in India: A bootstrap data envelopment analysis approach. Irrig. Sci. 2016, 34, 41–52. [Google Scholar]
- Banerji, A.; Meenakshi, J.V.; Khanna, G. Social contracts, markets and efficiency: Groundwater irrigation in North India. J. Dev. Econ. 2012, 98, 228–237. [Google Scholar] [CrossRef] [Green Version]
- Zhang, L.; Wang, J.; Huang, J.; Rozelle, S. Development of Groundwater Markets in China: A Glimpse into Progress to Date. World Dev. 2008, 36, 706–726. [Google Scholar] [CrossRef]
- Skurray, J.H.; Pandit, R.; Pannell, D.J. Institutional impediments to groundwater trading: The case of the Gnangara groundwater system of Western Australia. J. Environ. Plan. Manag. 2013, 56, 1046–1072. [Google Scholar] [CrossRef]
- Feldman, M.; Lai, K.; Zhang, L. A Price-Anticipating Resource Allocation Mechanism for Distributed Shared Clusters. Comput. Sci. 2005. [Google Scholar] [CrossRef]
- Gill, B.; Webb, J.; Stott, M.; Cheng, X.; Wilkinson, R.; Cossens, B. Economic, social and resource management factors influencing groundwater trade: Evidence from Victoria, Australia. J. Hydrol. 2017, 550, 253–267. [Google Scholar] [CrossRef]
- Ioslovich, I.; Gutman, P.O. A model for the global optimization of water prices and usage for the case of spatially distributed sources and consumers. Math. Comput. Simul. 2001, 56, 347–356. [Google Scholar] [CrossRef]
- Sun, L.; Lu, W.; Yang, Q.; Martín, J.D.; Li, D. Ecological Compensation Estimation of Soil and Water Conservation Based on Cost-Benefit Analysis. Water Resour. Manag. 2013, 27, 2709–2727. [Google Scholar] [CrossRef]
- Tsitsifli, S.; Gonelas, K.; Papadopoulou, A.; Kanakoudis, V.; Kouziakis, C.; Lappos, S. Socially fair drinking water pricing considering the full water cost recovery principle and the non-revenue water related cost allocation to the end users. Desalin. Water Treat. 2017, 99, 72–82. [Google Scholar] [CrossRef]
- Gaydon, D.S.; Meinke, H.; Rodriguez, D.; McGrath, D.J. Comparing water options for irrigation farmers using Modern Portfolio Theory. Agric. Water Manag. 2012, 115, 1–9. [Google Scholar] [CrossRef]
- Yuan, J.; Wang, B.; Zhang, L.; Liu, Y. Game Analysis on Urban Tap Water Price under the Condition of Incomplete Information; Springer: Berlin, Germany, 2015; pp. 673–679. [Google Scholar]
- Lika, A.; Galioto, F.; Viaggi, D. Water Authorities’ Pricing Strategies to Recover Supply Costs in the Absence of Water Metering for Irrigated Agriculture. Sustainability 2017, 9, 2210. [Google Scholar] [CrossRef]
- Martinez, M.T.; Rodriguez-Ferrero, N. Ramsey Pricing for Cost Recovery Applied to Reservoir Infrastructure in Andalucía (Spain). Water Econ. Policy 2017, 3, 1–27. [Google Scholar]
- Wasimi, S.A. Planning for a Large Dam Project: The Case of Traveston Crossing Dam. Water Resour. Manag. 2010, 24, 2991–3015. [Google Scholar] [CrossRef]
- DeNooyer, T.A.; Peschel, J.M.; Zhang, Z.; Stillwell, A.S. Integrating water resources and power generation: The energy-water nexus in Illinois. Appl. Energy 2016, 162, 363–371. [Google Scholar] [CrossRef]
- Truong, C.H. A Two Factor Model for Water Prices and Its Implications for Evaluating Real Options and Other Water Price Derivatives. Can. J. Agric. Econ. 2014, 62, 23–45. [Google Scholar] [CrossRef]
- Hölting, B.; Coldewey, W.G. Groundwater Exploitation. In Hydrogeology; Hölting, B., Coldewey, W.G., Eds.; Springer: Berlin, Germany, 2019; pp. 203–230. [Google Scholar]
- De Vries, J.J.; Simmers, I. Groundwater recharge: An overview of processes and challenges. Hydrogeol. J. 2002, 10, 5–17. [Google Scholar] [CrossRef]
- Hazarika, N.; Nitivattananon, V. Strategic assessment of groundwater resource exploitation using DPSIR framework in Guwahati city, India. Habitat Int. 2016, 51, 79–89. [Google Scholar] [CrossRef]
- Fenichel, E.P.; Abbott, J.K.; Bayham, J.; Boone, W.; Haacker, E.M.K.; Pfeiffer, L. Measuring the value of groundwater and other forms of natural capital. Proc. Natl. Acad. Sci. USA 2016, 113, 2382–2387. [Google Scholar] [CrossRef] [Green Version]
- Abdelhafidh, H.; Bachta, M.S. Groundwater pricing for farms and water user association sustainability. Arab. J. Geosci. 2016, 9, 525. [Google Scholar] [CrossRef]
- Kerachian, R.; Fallahnia, M.; Bazargan-Lari, M.R.; Mansoori, A.; Sedghi, H. A fuzzy game theoretic approach for groundwater resources management: Application of Rubinstein Bargaining Theory. Resour. Conserv. Recycl. 2010, 54, 673–682. [Google Scholar] [CrossRef]
- Aissaoui, O.E.; Madani, Y.E.A.E.; Oughdir, L.; Allioui, Y.E. A fuzzy classification approach for learning style prediction based on web mining technique in e-learning environments. Educ. Inf. Technol. 2019, 24, 1943–1959. [Google Scholar] [CrossRef]
- Ghomi-Avili, M.; Jalali Naeini, S.G.; Tavakkoli-Moghaddam, R.; Jabbarzadeh, A. A fuzzy pricing model for a green competitive closed-loop supply chain network design in the presence of disruptions. J. Clean. Prod. 2018, 188, 425–442. [Google Scholar] [CrossRef]
- Zeng, W.; Li, D.; Yin, Q. Weighted Interval-Valued Hesitant Fuzzy Sets and Its Application in Group Decision Making. Int. J. Fuzzy Syst. 2019, 21, 421–432. [Google Scholar] [CrossRef]
- Fernandez, A.; Herrera, F.; Cordon, O.; Jesus, M.J.D.; Marcelloni, F. Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to? IEEE Comput. Intell. Mag. 2019, 14, 69–81. [Google Scholar] [CrossRef]
- Madhoo, Y.N. Political economy of water pricing policy: Empirical evidence from public utilities in Mauritius. Water Resour. Res. 2004, 40. [Google Scholar] [CrossRef]
- Mao, C.; Zhai, N.; Yang, J.; Feng, Y.; Cao, Y.; Han, X.; Ren, G.; Yang, G.; Meng, Q.X. Environmental Kuznets curve analysis of the economic development and nonpoint source pollution in the Ningxia Yellow River irrigation districts in China. Biomed. Res. Int. 2013, 2013, 267968. [Google Scholar] [CrossRef]
- Ningxia Water Resources Department. Ningxia Water Resources Bulletin (2013–2017); Ningxia Water Resources Department: Yinchuan, China, 2018. [Google Scholar]
- Gui-liang, T.; Chang-xin, X.; Wen-xuan, X.; Rong, P. Regional water right distribution model of multi-objective programming—An empirical study based on the data in Ningxia. In Proceedings of the 2010 International Conference on Management Science & Engineering 17th Annual Conference Proceedings, Melbourne, Australia, 24–26 November 2010; pp. 280–286. [Google Scholar]
- Xia, C.; Pahl-Wostl, C. The Development of Water Allocation Management in The Yellow River Basin. Water Resour. Manag. 2012, 26, 3395–3414. [Google Scholar] [CrossRef]
- Sun, L.; Li, C.; Cai, Y.; Wang, X. Interval Optimization Model Considering Terrestrial Ecological Impacts for Water Rights Transfer from Agriculture to Industry in Ningxia, China. Sci. Rep. 2017, 7, 3465. [Google Scholar] [CrossRef]
- Tang, L.; Zhang, W.J. Fuzzy Comprehensive Evaluation for Water Resources Sustainable Utilization of Ningxia. Adv. Mater. Res. 2012, 446, 2770–2775. [Google Scholar] [CrossRef]
- Ningxia Statistical Bureau. Ningxia Statistical Yearbook (2013–2017); China Statistics Press: Beijing, China, 2018. [Google Scholar]
- Ningxia Statistical Bureau. Ningxia Hui Autonomous Region Statistical Bulletin of National Economic and Social Development (2013–2017); Ningxia Statistical Bureau: Yinchuan, China, 2018. [Google Scholar]
- Hydrology Department. Monthly Report of Groundwater Regime in China; China Ministry of Water Resources: Beijing, China, 2018.
- China Water Web. China Tap Water Price 2013–2017. Available online: http://www.h2o-china.com/price/ (accessed on 17 March 2019).
- Guerrero García Rojas, H.R.; Garcia-Vega, D.; Herrera-Torres, H.A. Water Price Policy and Its Institutional Role as an Economic Instrument for Water Management. In Water Policy in Mexico: Economic, Institutional and Environmental Considerations; Guerrero García Rojas, H.R., Ed.; Springer International Publishing: Berne, Switzerland, 2019; pp. 137–152. [Google Scholar]
- Cooper, B.; Crase, L.; Pawsey, N. Best practice pricing principles and the politics of water pricing. Agric. Water Manag. 2014, 145, 92–97. [Google Scholar] [CrossRef]
- Ioris, A.A.R. The Value of Water Values: Departing from Geography towards An interdisciplinary Synthesis. Geogr. Ann. Ser. B Hum. Geogr. 2013, 95, 323–337. [Google Scholar] [CrossRef]
- Valmohammadi, C.; Dashti, S. Using interpretive structural modeling and fuzzy analytical process to identify and prioritize the interactive barriers of e-commerce implementation. Inf. Manag. 2016, 53, 157–168. [Google Scholar] [CrossRef]
- Xu, S.; Wang, T.; Hu, S. Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model. Int. J. Environ. Res. Public Health 2015, 12, 2230–2248. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Liu, T.; Deng, Y.; Chan, F. Evidential Supplier Selection Based on DEMATEL and Game Theory. Int. J. Fuzzy Syst. 2018, 20, 1321–1333. [Google Scholar] [CrossRef]
- Mei, Y.; Ye, J.; Zeng, Z. Entropy-weighted ANP fuzzy comprehensive evaluation of interim product production schemes in one-of-a-kind production. Comput. Ind. Eng. 2016, 100, 144–152. [Google Scholar] [CrossRef]
- Molinos-Senante, M.; Donoso, G. Water scarcity and affordability in urban water pricing: A case study of Chile. Util. Policy 2016, 43, 107–116. [Google Scholar] [CrossRef]
- García-Valiñas, M.A.; Martínez-Espiñeira, R.; González-Gómez, F. Affordability of residential water tariffs: Alternative measurement and explanatory factors in southern Spain. J. Environ. Manag. 2010, 91, 2696–2706. [Google Scholar] [CrossRef] [PubMed]
- Jia, Y.; Shen, J.; Wang, H. Calculation of Water Resource Value in Nanjing Based on a Fuzzy Mathematical Model. Water 2018, 10, 920. [Google Scholar] [CrossRef]
- Iskin, I.; Daim, T.; Kayakutlu, G.; Altuntas, M. Exploring renewable energy pricing with analytic network process—Comparing a developed and a developing economy. Energy Econ. 2012, 34, 882–891. [Google Scholar] [CrossRef]
- Zhang, J. Weighing and realizing the environmental, economic and social goals of tourism development using an analytic network process-goal programming approach. J. Clean. Prod. 2016, 127, 262–273. [Google Scholar] [CrossRef]
- Li, J.; Min, Q.; Li, W.; Bai, Y.; Yang, L.; Dhruba, B.G.C. Evaluation of water resources conserved by forests in the Hani rice terraces system of Honghe County, Yunnan, China: An application of the fuzzy comprehensive evaluation model. J. Mt. Sci. 2016, 13, 744–753. [Google Scholar] [CrossRef]
- Yanli, L.; DeLan, X. Environmental asset value of water resources in lake calculated in applying fuzzy mathematical method. In Proceedings of the 2nd International Conference on Information Science and Engineering, Hangzhou, China, 4–6 December 2010; pp. 2830–2833. [Google Scholar]
- Chica-Olmo, J.; González-Gómez, F.; Guardiola, J. Do neighbouring municipalities matter in water pricing? Urban Water J. 2013, 10, 1–9. [Google Scholar] [CrossRef]
- Beare, S.C.; Heaney, A.; Australian, B.O.A.A. Water Trade and the Externalities of Water use in Australia: Interim report: ABARE paper for Natural Resource Management Business Unit, AFFA; ABARE: Canberra, A.C.T., Australia, 2002; p. 5.
- Hamilton, J.R.; Whittlesey, N.K.; Halverson, P. Interruptible Water Markets in the Pacific Northwest. Am. J. Agric. Econ. 1989, 71, 63–75. [Google Scholar] [CrossRef] [Green Version]
- Young, M.; Macdonald, D.H.; Stringer, R.; Bjornland, H. Interstate Water Trading: A 2-year Review; Policy and Economic Research Unit, CSIRO Land and Water: Adelaide, Australia, 2000; Available online: http:// www.clw.csiro.au/publications/consultancy/2000/inter_trading.pdf (accessed on 18 July 2018).
River Basin | Unit | Groundwater Resources in Mountainous Areas | Groundwater Resources in Plain Areas | Double Counting between Mountainous Areas and Plain Areas | Groundwater Resources in the Subregion | |||
---|---|---|---|---|---|---|---|---|
Precipitation Recharge | Surface Water Recharge | Mountain Lateral Infiltration Recharge | Total | |||||
Areas Irrigated by the Yellow River | 108 m3 | 0 | 0.768 | 14.487 | 0.038 | 15.293 | 0.038 | 15.255 |
Zuli River | 108 m3 | 0.033 | 0 | 0 | 0 | 0 | 0 | 0.033 |
Qingshui River | 108 m3 | 0.857 | 0 | 0 | 0 | 0 | 0 | 0.857 |
Hongliugou River | 108 m3 | 0.028 | 0 | 0 | 0 | 0 | 0 | 0.028 |
Kushui River | 108 m3 | 0.066 | 0 | 0 | 0 | 0 | 0 | 0.066 |
The Huangyou Area | 108 m3 | 0.046 | 0 | 0 | 0 | 0 | 0 | 0.046 |
The Huangzuo Area | 108 m3 | 0.934 | 0.086 | 0 | 0.764 | 0.850 | 0.764 | 1.020 |
Hulu River | 108 m3 | 0.359 | 0 | 0 | 0 | 0 | 0 | 0.356 |
Jinghe River | 108 m3 | 1.667 | 0 | 0 | 0 | 0 | 0 | 1.667 |
Endorheic Drainage Area in Yanchi | 108 m3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Total | 108 m3 | 3.990 | 0.854 | 14.487 | 0.802 | 16.143 | 0.802 | 19.331 |
Ningxia Water Resources Bulletin 2013–2017 [48]; Monthly Report of Groundwater Regime in China January 2013–December 2017” [51] | Groundwater quality grade, average depth of shallow groundwater, the proportion of the groundwater supply, per capita groundwater withdrawal, agricultural water withdrawal, industrial water withdrawal, withdrawal for residential living use, and the proportion of overexploited groundwater area |
Ningxia Statistical Yearbook (2013–2017) [49]; China Tap Water Price 2013–2017” [52] | Population density, per capita groundwater resources, groundwater resources per unit area, and wastewater discharge |
Ningxia Autonomous Region Statistical Bulletin of National Economic and Social Development (2013–2017) [50] | Per capita GDP and per 104-yuan-GDP water consumption |
Cluster | Evaluating Indicator | Unit | Definition | Actual Number | ||||
---|---|---|---|---|---|---|---|---|
2013 | 2014 | 2015 | 2016 | 2017 | ||||
Environment | Groundwater Quality Grade | / | Characterizes the quality of groundwater | III | III | III | III | III |
Per Capita Groundwater Resources | m3 | Characterizes the scarcity of groundwater resources per capita | 338.30 | 321.99 | 312.60 | 275.13 | 283.45 | |
Groundwater Resources Per Unit Area | 102 m3/ km2 | Characterizes the scarcity of groundwater resources regionally | 427 | 412 | 403 | 359 | 373 | |
Average Depth of Shallow Groundwater | m | Characterizes the accessibility of groundwater | 2.34 | 2.26 | 2.29 | 2.30 | 2.41 | |
Proportion of Overexploited Groundwater Area | % | Characterizes the severity groundwater overexploitation | 1.43 | 1.43 | 1.43 | 1.43 | 1.43 | |
Society | Population Density | people/km2 | Characterizes the level of local population size | 1253 | 1295 | 1336 | 1343 | 1388 |
Per Capita Groundwater Withdrawal | m3 | Characterizes the level of groundwater demand | 85.0 | 82.7 | 76.9 | 78.6 | 81.1 | |
Agricultural Groundwater Withdrawal | 108 m3 | Characterizes the level of agricultural groundwater consumption | 1.168 | 1.142 | 1.253 | 1.296 | 1.567 | |
Industrial Groundwater Withdrawal | 108 m3 | Characterizes the level of industrial groundwater consumption | 2.594 | 2.426 | 1.847 | 1.638 | 1.436 | |
Residential Groundwater Use Withdrawal | 108 m3 | Characterizes the level of groundwater consumption in social life | 1.295 | 1.387 | 1.500 | 1.916 | 2.077 | |
Economy | Per Capita GDP | 103 yuan | Characterizes the regional economic level | 39.6 | 41.8 | 43.8 | 47.2 | 50.8 |
Per 104-yuan-GDP Water Consumption | m3 | Characterizes water use efficiency of regional economic sectors | 311 | 281 | 260 | 206 | 194 | |
Groundwater Supply Proportion | % | Characterizes the degree of reliance on groundwater | 7.7 | 7.8 | 7.3 | 8.2 | 8.4 | |
Wastewater Discharge | 107 ton | Characterizes the negative externality of economy | 38.5 | 37.3 | 32.0 | 33.9 | 30.7 |
Cluster | Evaluating Indicator | Unit | Character | Evaluation Criteria | ||||
---|---|---|---|---|---|---|---|---|
High | Relatively High | Common | Relatively Low | Low | ||||
Environment | Groundwater Quality Grade | / | + | >II | III | IV | V | <V |
Per Capita Groundwater Resources | m3 | - | 100.00 | 450.00 | 800.00 | 1150.00 | 1500.00 | |
Groundwater Resources Per Unit Area | 102 m3/ km2 | - | 200 | 900 | 1600 | 2300 | 3000 | |
Average Depth of Shallow Groundwater | m | + | 30.00 | 17.25 | 15.50 | 8.25 | 1.00 | |
Proportion of Overexploited Groundwater Area | % | + | 10.00 | 7.50 | 5.00 | 2.50 | 0.00 | |
Society | Population Density | people/km2 | + | 4500 | 3700 | 2900 | 2100 | 1300 |
Per Capita Groundwater Withdrawal | m3 | + | 200.0 | 150.0 | 100.0 | 50.0 | 0.0 | |
Agricultural Groundwater Withdrawal | 108 m3 | + | 100.000 | 75.500 | 51.000 | 26.500 | 2.000 | |
Industrial Groundwater Withdrawal | 108 m3 | + | 17.000 | 12.250 | 8.500 | 4.250 | 0.000 | |
Groundwater for Residential Living Withdrawal | 108 m3 | + | 10.000 | 7.500 | 5.000 | 2.500 | 0.000 | |
Economy | Per Capita GDP | 103 yuan | + | 100.0 | 82.5 | 65.0 | 47.5 | 30.0 |
Per 104-yuan-GDP Water Consumption | m3 | + | 200 | 155 | 110 | 65 | 20 | |
Groundwater Supply Proportion | % | + | 50.0 | 38.0 | 26.0 | 14.0 | 2.0 | |
Wastewater Discharge | 107 ton | + | 400.0 | 325.0 | 250.0 | 175.0 | 100.0 |
Cluster | Evaluating Indicator | Subjective Weight | Objective Weight |
---|---|---|---|
Environment | Groundwater Quality Grade | 0.0235 | 0.0736 |
Per Capita Groundwater Resources | 0.2515 | 0.0697 | |
Groundwater Resources Per Unit Area | 0.1977 | 0.0697 | |
Average Depth of Shallow Groundwater | 0.0145 | 0.0704 | |
Proportion of Overexploited Groundwater Area | 0.0099 | 0.0736 | |
Society | Population Density | 0.1281 | 0.0698 |
Per Capita Groundwater Withdrawal | 0.0178 | 0.0730 | |
Agricultural Groundwater Withdrawal | 0.0492 | 0.0693 | |
Industrial Groundwater Withdrawal | 0.0258 | 0.0740 | |
Groundwater for Residential Living Withdrawal | 0.0055 | 0.0692 | |
Economy | Per Capita GDP | 0.1724 | 0.0695 |
Per 104-yuan-GDP Water Consumption | 0.0717 | 0.0740 | |
Groundwater Supply Proportion | 0.0042 | 0.0705 | |
Wastewater Discharge | 0.0175 | 0.0738 |
Indicator | Unit | 2013 | 2014 | 2015 | 2016 | 2017 |
---|---|---|---|---|---|---|
Per Capita Disposable Income | yuan | 14,565.78 | 15,906.78 | 17,329.06 | 18,832.28 | 20,561.66 |
Per Capita Water Consumption of Residents | m3 | 26.28 | 28.25 | 29.82 | 32.59 | 33.73 |
Residents’ Tap Water Price 1 | yuan/ m3 | 2.06 | 2.06 | 2.06 | 2.06 | 2.31 |
Sewage Treatment Fee | yuan/ m3 | 0.85 | 0.85 | 0.85 | 0.85 | 0.85 |
Water Resources Fee | yuan/ m3 | 0.31 | 0.41 | 0.57 | 0.72 | 0.72 |
Water Supply Cost and Normal Profit | yuan/ m3 | 0.90 | 0.80 | 0.64 | 0.49 | 0.74 |
Per Capita Water Fee Expenditure | yuan | 54.14 | 58.20 | 61.42 | 67.13 | 77.92 |
Per Capita Real Disposable Income | yuan | 14,086.83 | 15,610.19 | 17,140.51 | 18,8553.97 | 20,237.85 |
Water Rate Affordability Indicator | % | 2 | 2 | 2 | 2 | 2 |
Ratio of Residents’ Water Fee Expenditure to Real Disposable Income | % | 0.38 | 0.37 | 0.36 | 0.36 | 0.39 |
Groundwater Rights Price | yuan/ m3 | 5.11 | 5.21 | 5.44 | 5.40 | 5.73 |
© 2019 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 (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Wang, Z.; Shen, J.; Sun, F.; Zhang, Z.; Zhang, D.; Jia, Y.; Zhang, K. A Pricing Model for Groundwater Rights in Ningxia, China Based on the Fuzzy Mathematical Model. Int. J. Environ. Res. Public Health 2019, 16, 2176. https://doi.org/10.3390/ijerph16122176
Wang Z, Shen J, Sun F, Zhang Z, Zhang D, Jia Y, Zhang K. A Pricing Model for Groundwater Rights in Ningxia, China Based on the Fuzzy Mathematical Model. International Journal of Environmental Research and Public Health. 2019; 16(12):2176. https://doi.org/10.3390/ijerph16122176
Chicago/Turabian StyleWang, Zeyu, Juqin Shen, Fuhua Sun, Zhaofang Zhang, Dandan Zhang, Yizhen Jia, and Kaize Zhang. 2019. "A Pricing Model for Groundwater Rights in Ningxia, China Based on the Fuzzy Mathematical Model" International Journal of Environmental Research and Public Health 16, no. 12: 2176. https://doi.org/10.3390/ijerph16122176
APA StyleWang, Z., Shen, J., Sun, F., Zhang, Z., Zhang, D., Jia, Y., & Zhang, K. (2019). A Pricing Model for Groundwater Rights in Ningxia, China Based on the Fuzzy Mathematical Model. International Journal of Environmental Research and Public Health, 16(12), 2176. https://doi.org/10.3390/ijerph16122176