Simulation of Urban Water Resources in Xiamen Based on a WEAP Model
Abstract
:1. Introduction
2. Study Area
3. Urban Water Resource Simulation Method
3.1. Simulation Model Based on the WEAP Platform
3.2. Water Demand Calculations
3.2.1. Primary Industry Water Demand
3.2.2. Secondary Industry Water Demand
3.2.3. Tertiary Industry Water Demand
3.2.4. Domestic Water Demand
3.2.5. Ecological Water Demand
3.3. Water Supply Priorities Used in the WEAP Model
4. Model Scenario Design
4.1. Basic Assumptions
4.2. Scenario Design for Projecting Future Water Demand
4.3. Scenario Design for Water Supply
5. Results and Discussions
5.1. Water Demand under Different Scenarios
5.2. Water Saving Potential
5.3. Water Shortages under Different Scenarios
5.4. Water Supply Alternatives
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Mekonnen, M.M.; Hoekstra, A.Y. Four billion people facing severe water scarcity. Sci. Adv. 2016, 2, e1500323. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- World Economic Forum (WEF). Global Risks 2015, 10th ed.; World Economic Forum: Geneva, Switzerland, 2015. [Google Scholar]
- Department of Economic and Social Affairs (DESA). The World Urbanization Prospects; Economic & Social Affairs; Department of Economic and Social Affairs: New York, NY, USA, 2014. [Google Scholar]
- Larsen, T.A.; Hoffmann, S.; Lüthi, C.; Truffer, B.; Maurer, M. Emerging solutions to the water challenges of an urbanizing world. Science 2016, 352, 928–933. [Google Scholar] [CrossRef] [PubMed]
- Paterson, W.; Rushforth, R.; Ruddell, B.L.; Konar, M.; Ahams, I.C.; Gironás, J.; Mijic, A.; Mejia, A. Water Footprint of Cities: A Review and Suggestions for Future Research. Sustainability 2015, 7, 8461–8490. [Google Scholar] [CrossRef] [Green Version]
- Liu, J.; Yang, W. Water sustainability for China and beyond. Science 2012, 337, 649–650. [Google Scholar] [CrossRef] [PubMed]
- National Bureau of Statistics (NBS). China’s Urbanization Rate Reached 56.10% in 2015; National Bureau of Statistics: Beijing, China, 2015.
- Li, X.; Shan, Q. Urbanization in the transition period: International experience and China’s prospects. Econ. Inf. 2013, 11, 151–154. [Google Scholar]
- Shi, C.; Jin, T.; Ren, H. Review on Studies about Typical Models of Water Resource Management. J. Anhui Agric. Sci. 2015, 10, 249–250. [Google Scholar]
- Labadie, J.; Larson, R. MODSIM8.1: River Basin Management Decision Support System, User Manual and Documentation; Colorado State University: Fort Collins, FL, USA, 2007; pp. 85–88. [Google Scholar]
- Andreu, J.; Capilla, J.; Sanchís, E. AQUATOOL, a generalized decision-support system for water-resources planning and operational management. J. Hydrol. 1996, 177, 269–291. [Google Scholar] [CrossRef]
- Sieber, J. WEAP Water Evaluation and Planning System. In Proceedings of the 3rd International Congress on Environmental Modelling and Software, Burlington, VT, USA, 9–13 July 2006. [Google Scholar]
- Haddad, M.; Jayousi, A.; Hantash, S.A. Applicability of WEAP as Water Management Decision Support System Tool on Localized Area of Watershed Scales: Tulkarem District in Palestine as Case Study. In Proceedings of the Eleventh International Water Technology Conference, Sharm El Sheikh, Egypt, 15–18 March 2007. [Google Scholar]
- Yates, D.; Purkey, D.; Sieber, J.; Huber-Lee, A.; Galbraith, H.; West, J.; Herrod-Julius, S.; Young, C.; Joyce, B.; Rayej, M. Climate driven water resources model of the Sacramento Basin, California. J. Water Resour. Plan. Manag. 2009, 135, 303–313. [Google Scholar] [CrossRef]
- Bharati, L.; Smakhtin, V.U.; Anand, B.K. Modeling water supply and demand scenarios: The Godavari-Krishna inter-basin transfer, India. Water Policy 2009, 11, 140–153. [Google Scholar] [CrossRef]
- Al-Omari, A.; Al-Quraan, S.; Al-Salihi, A.; Abdulla, F. A Water Management Support System for Amman Zarqa Basin in Jordan. Water Resour. Manag. 2009, 23, 3165–3189. [Google Scholar] [CrossRef]
- Höllermann, B.; Giertz, S.; Diekkrüger, B. Benin 2025—Balancing Future Water Availability and Demand Using the WEAP ‘Water Evaluation and Planning’ System. Water Resour. Manag. 2010, 24, 3591–3613. [Google Scholar] [CrossRef]
- Vicuña, S.; Mcphee, J.; Garreaud, R.D. Agriculture vulnerability to climate change in a snowmelt driven basin in semiarid Chile. J. Water Resour. Plan. Manag. 2012, 138, 431–441. [Google Scholar] [CrossRef]
- Rheinheimer, D.E.; Viers, J.H.; Sieber, J.; Kiparsky, M.; Mehta, V.K.; Ligare, S.T. Simulating High-Elevation Hydropower with Regional Climate Warming in the West Slope, Sierra Nevada. J. Water Resour. Plan. Manag. 2014, 140, 714–723. [Google Scholar] [CrossRef]
- Hamlat, A.; Errih, M.; Guidoum, A. Simulation of water resources management scenarios in western Algeria watersheds using WEAP model. Arab. J. Geosci. 2013, 6, 2225–2236. [Google Scholar] [CrossRef]
- Li, Q.; Sun, R.; Tian, L.; Wang, D.; Shi, C.; Li, Y.; Wang, Y. Application of WEAP Model to Water Resources and Water Environment Management in Binhai New Area of Tianjin City. J. Water Resour. Water Eng. 2010, 2, 56–59. [Google Scholar]
- Song, R.Y.; Liu, Q.Y.; Xu, Z.-H.; Meng, F.H. Optimization allocation of water resources in longkou city based on WEAP mode. China Rural Water Hydropower 2011, 4, 30–33. [Google Scholar]
- Li, X.; Zhao, Y.; Shi, C.; Sha, J.; Wang, Z.L.; Wang, Y. Application of Water Evaluation and Planning (WEAP) model for water resources management strategy estimation in coastal Binhai New Area, China. Ocean Coast. Manag. 2015, 106, 97–109. [Google Scholar] [CrossRef]
- Xiamen Statistical Bureau (XSB). Yearbook of Xiamen Special Economic Zone; Xiamen Statistical Bureau: Xiamen, China, 2015.
- Resources of Xiamen Municipality (XWR). Water Resources Bulletin in Xiamen; Bureau of Water Resources of Xiamen Municipality: Xiamen, China, 2015.
- Lin, J. Assessment of sustainable utilization of urban water resources in Xiamen City. Water Resour. Prot. 2010, 26, 51–56. [Google Scholar]
- Xiamen Municipal Government (XMG). The Strategic Planning of Water Resources in Xiamen (2015–2030); Xiamen Municipal Government: Xiamen, China, 2016.
- Stockholm Environment Institute (SEI). Water Evaluation and Planning System of User Guide; Stockholm Environment Institute: Stockholm, Sweden, 2006. [Google Scholar]
- Yates, D.; Sieber, J.; Purkey, D.; Huber-Lee, A. WEAP21—A demand-, priority-, and preference-driven water planning model Part 1: Model characteristics. Water Int. 2005, 30, 487–500. [Google Scholar] [CrossRef]
- Xiamen Municipal Government (XMG). Xiamen Master Plan; Xiamen Municipal Government: Xiamen, China, 2015.
- Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements; Irrigation and Drainage Paper No 56; Food and Agriculture Organization of the United Nations (FAO): Logan, UT, USA, 1998. [Google Scholar]
- Fujian Bureau of Quality and Technology Supervision (FQTS). Norm of Water Intake of Industries; Fujian Bureau of Quality and Technology Supervision: Fujian, China, 2013.
- Xiamen Bureau of Quality and Technology Supervision (XQTS). Norm of Industrial Water Use and Living Water Use; Xiamen Bureau of Quality and Technology Supervision: Xiamen, China, 2016.
- Environmental Protection Agency (EPA). Environmental Statistics in Xiamen. 2005-1015; Environmental Protection Agency of Xiamen: Xiamen, China.
Basic Parameters | 2015 1 | 2020 2 | 2030 2 | 2050 2 |
---|---|---|---|---|
Population (million) | 3.86 | 5.00 | 6.40 | 8.00 |
GDP (million RMB) | 346 | 509 | 1002 | 2300 |
Primary industry proportion (%) | 0.7 | 0.5 | 0.3 | 0.3 |
Secondary industry proportion (%) | 43.6 | 39.5 | 34.7 | 29.7 |
Tertiary industry proportion (%) | 55.7 | 60.0 | 65.0 | 70.0 |
Scenarios | Abbreviation | Main Assumptions |
---|---|---|
Planning Scenario 1 | PLS | Future island population size remains unchanged, while the mainland population rapidly increases, especially in the Xiangan District. Agricultural land coverage will gradually decline. The chemical industry will completely disappear before 2030. High-tech industries, such as the pharmaceutical, equipment, and electronics industries, will greatly expand. The pharmaceutical industry’s added value will increase from 1.51% to 12% of the total by 2050. Emerging service industries, such as tourism, culture, health and education, will increase. |
Technical Water-Saving Scenario | TWS | Compared with the PLS, the TWS scenario will adopt advanced technology to reduce water consumption. The irrigation coefficient for agriculture will be 0.72 in 2050 due to advanced technology such as dropper and sprinkler irrigation, compared to 0.55 in 2015. The water quotas for fishery and livestock enterprises will be reduced by 10% in 2050, relative to the PLS. For secondary industry, water recycling will be strengthened and water utilization efficiency improved. Tertiary industry and domestic users will use more water-saving appliances. Thus, water quotas for secondary and tertiary industries, as well as domestic water, will be reduced by 5%, 10% and 5% in 2050, respectively, compared with the PLS. Ecological water use for the TWS and PLS will be similar. |
Structural Water-Saving Scenario | SWS | Compared with the PLS, the SWS scenario will reduce the proportion of water-intensive industries. Examples include the elimination of the papermaking, printing, and chemical industries by 2020, with the maintenance of the pharmaceutical industry’s ratio of 1.51% through 2050. In contrast, the proportion of water-saving industries will increase, such as the equipment and electronics industries. |
Double Water-Saving Scenario | DWS | Compared with the PLS, the DWS utilizes advanced technology and industrial restructuring to reduce water consumption. The industrial structure proportions will be consistent with the SWS, and the water quotas will be consistent with the TWS. |
Water Source | River | Amount of Water (million m3) | Infrastructure Expenditure (million RMB) | Annual Operating Cost (million RMB) |
---|---|---|---|---|
Trans-basin water diversion 1 | Jiulongjiang | 200 | 1000 | 179 |
Tingjiang | 200 | 2500–2700 | 197 | |
Mingjiang | 200 | 3500 | 244 | |
Reclaimed water 2 | - | 170 | 1000 | 170 |
Seawater desalination 3 | - | 110 | 3000 | 550–770 |
Scenario | Year | Primary Industry | Secondary Industry | Tertiary Industry | Domestic Demand | Ecological Demand |
---|---|---|---|---|---|---|
- | 2015 | 20.33% | 26.78% | 18.41% | 32.04% | 2.44% |
PLS | 2050 | 4.88% | 31.24% | 24.07% | 35.45% | 4.35% |
TWS | 2050 | 5.08% | 32.84% | 24.03% | 33.24% | 4.83% |
SWS | 2050 | 5.25% | 26.09% | 25.88% | 38.11% | 4.68% |
DWS | 2050 | 5.48% | 27.51% | 25.93% | 35.87% | 5.21% |
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Kou, L.; Li, X.; Lin, J.; Kang, J. Simulation of Urban Water Resources in Xiamen Based on a WEAP Model. Water 2018, 10, 732. https://doi.org/10.3390/w10060732
Kou L, Li X, Lin J, Kang J. Simulation of Urban Water Resources in Xiamen Based on a WEAP Model. Water. 2018; 10(6):732. https://doi.org/10.3390/w10060732
Chicago/Turabian StyleKou, Limin, Xiangyang Li, Jianyi Lin, and Jiefeng Kang. 2018. "Simulation of Urban Water Resources in Xiamen Based on a WEAP Model" Water 10, no. 6: 732. https://doi.org/10.3390/w10060732
APA StyleKou, L., Li, X., Lin, J., & Kang, J. (2018). Simulation of Urban Water Resources in Xiamen Based on a WEAP Model. Water, 10(6), 732. https://doi.org/10.3390/w10060732