Simulation analysis of domestic water demand and its future uncertainty in water scarce areas

doi:10.1007/s11707-009-0047-z

Front Earth Sci Chin

0, Vol.

Issue () : 349-360 https://doi.org/10.1007/s11707-009-0047-z

RESEARCH ARTICLE

Simulation analysis of domestic water demand and its future uncertainty in water scarce areas

Shouke WEI¹(

), Albrecht GNAUCK¹, Alin LEI²

1. Department of Ecosystem and Environmental Informatics, Brandenburg University of Technology in Cottbus, Cottbus 03046, Germany; 2. Changjiang Water Resources Protection Institute, Wuhan 430051, China

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Abstract

This paper demonstrates a practical simulation approach to analyze domestic water demand and its future uncertainty in water scarce areas through a case study of Beijing, China. Analytic models and a forecasting model were constructed using statistic and econometric regression approaches. The analytic models were used to analyze the interrelationships between domestic water demand and some socio-economic factors of Beijing. The forecasting model was applied to predict domestic water demand from 2009 to 2015, and this model was validated by comparing the prediction values with the observations. Scenario analysis was applied to simulate uncertainty and risks in domestic water demand in the future. The simulation results proved that domestic water demand will increase from 13.9×10⁸ m³ to 16.7×10⁸ m³ from 2009 to 2015. Three more sustainable strategies were also found through scenario analysis. The simulation and modeling approaches and results would be very supportive for water decision makers in allocating water efficiently and making sustainable water strategies.

Keywords domestic water demand water scarcity modeling and simulation forecasting scenario analysis Beijing

Corresponding Author(s): WEI Shouke,Email:sigmundwei@yahoo.com

Issue Date: 05 September 2009

Cite this article:

Shouke WEI,Albrecht GNAUCK,Alin LEI. Simulation analysis of domestic water demand and its future uncertainty in water scarce areas[J]. Front Earth Sci Chin, 0, (): 349-360.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-009-0047-z
https://academic.hep.com.cn/fesci/EN/Y0/V/I/349

Fig.1 Sketch map of Beijing river system

Fig.2 Total water resources and water demand in different sectors in Beijing from 1986 to 2007

Fig.3 Ratio of domestic water demand to total water demand in Beijing from 1986 to 2007

Tab.1 Per capita urban and rural domestic water demand per day in Beijing from 1993 to 2005 /(L·p·d)

Fig.4 Matrix scatter plot of domestic water demand and some socio-economic factors in Beijing

Fig.5 Analyzing models of domestic water demand () versus. (a) Time variable (); (b) Consumer price index (); (c) rural and urban population ( & ); (d) rural and urban per capita net or discretionary income ( & ); and (e) domestic water demand in the previous year ((-1))

Fig.6 Domestic water demand forecasting model. (a) Domestic water demand () versus CPI (), urban per capita discretionary income () and its lag one ((-1)), and rural population (); (b) domestic water demand forecasting; (c) model of versus time variable () and (d) its projection; (e) model of versus and (f) its projection; (g) model of versus and (h) its projection

Tab.2 Observations of domestic water demand (), the forecasting results (), the residuals () and the errors ()/(×10 m)

Tab.3 Scenario description of the consumer price index (), urban per capita discretionary income () and rural population () from 2009 to 2015

Tab.4 Consumer prices index () under the three scenarios/ %

Tab.5 Urban per capita discretionary income () under the three scenarios (Yuan at 1978 price)

Tab.6 Rural population () under the three scenarios/(×10 persons)

Tab.7 Combination scenarios for domestic water demand forecast from 2009 to 2015

Fig.7 Sketch of domestic water demand () under the 27 scenarios

Fig.8 Domestic water demand () under 12 selected scenarios from 2009 to 2015

Tab.8 Domestic water demand under the three boundary scenarios /(×10 m)

Tab.9 Domestic water demand under the three highest water consumption scenarios /(×10 m)

Tab.10 Domestic water demand under the three lowest water consumption scenarios /(×10 m)

Tab.11 Domestic water demand under the three recommended scenarios /(×10 m)

1	Beijing Municipal Commission of Development and Reform (BMCDR) (2006). Water Resources Protection and Use Planning for 11th Five-year Plan of Beijing. Beijing: BMCDR (in Chinese)
2	Beijing Municipal Environmental Protection Bureau (BMEPB) (2005). Environmental Situation Bulletin 2005. Beijing:BEPB (in Chinese)
3	Beijing Statistical Bureau (BSB) (2001-2008). Beijing Statistical Yearbooks (2001-2008). Beijing: China Statistics Press (in Chinese)
4	Beijing Statistical Bureau (BSB) and Beijing Team of National Bureau of Statistics of China (BTNBSC) (2009). Beijing 2008 National Economic and Social Development Statistical Bulletin.http://www.bjstats.gov.cn [last accessed 22 Feb. 2009]
5	Beijing Water Authority (BWA) (2005). Beijing Water Resources Bulletin (2005). Beijing: BWA (in Chinese)
6	Cao X G (2003). Trend of water for industrial use in Beijing-Forecasting the industrial water consumption. Beijing City Planning and Construction Review , 6: 32–37 (in Chinese)
7	Changjiang Water Resources Protection Institute (CWRPI) (2005). Report on the Environmental Impacts of Middle Route of South-to-North Water Transfer Project. Wuhan: CWRPI (in Chinese)
8	Haihe River Water Conservancy Commission (HWCC) (1998-2006). The Haihe River Water Resource Bulletin (1998-2006). Tianjin: HRWRC (in Chinese)
9	Jia S F, Zhang S F (2003). Response of industrial water use to water price rising in Beijing. Journal of Hydraulic Engineering , 4: 10–113 (in Chinese)
10	Jiang W L (2004). The quandary and outlet of Beijing water resources. Science & Culture Science-Tech Waves , 1: 10–12 (in Chinese)
11	Leete R, Donnay F, Kersemaekers S, Schoch M, Shah M (2003). Global Population and Water. In: UNFPA report on Population and Development Strategies Series , number 6. New York: UNFPA
12	Li S T, Duan Z G (2006). Scenario analysis of water demand and water supply of Beijing during the period of 11th five-year. Beijing: China Regional CGE Modeling and its Policy Application Symposium
13	Li S T, Xu X Y (2004). South-to-North Water Transfer and China development. Beijing: Economic Science Press (in Chinese)
14	Ma D C (2006). Analysis of public policy on alleviating the conflict between water supply and water demand in Beijing. Heilongjiang Science and Technology of Water Conservancy , 1, 67–69 (in Chinese)
15	Ministry of Environmental Protection of the People’s Public of China (MEPPPC) (1996-2008). China Statistical Yearbook (1996-2006). Beijing: China Statistics Press (in Chinese)
16	Ministry of Water Resources of the People’s Public of China (MWRPPPC) (1998-2004). China Water ResourceS Bulletin (1998-2004). Beijing: MWRPPPC (in Chinese)
17	UN-CSD (1994). Review of sectoral clusters, first phase: human settlement and fresh water, freshwater resource. In: Report of the Secretary General of the UN, General Overview
18	Wang L Z (2005). Cooperative water resources allocation among competing users. A PhD. Dissertation . Waterloo: the University of Waterloo, Canada
19	Wei S K (2007). A survey on the situation of water resource and water management in China. In: Gnauck A, ed. Modelling and Simulation of Ecosystems . Aachen: Shaker-Verlag, 171–186
20	Wei S K, Gnauck A (2007a). Game theoretic approaches to model water conflicts on a river basin scale. In: Gnauck A, ed. Modelling and Simulation of Ecosystems . Aachen: Shaker-Verlag, 22–40
21	Wei S K, Gnauck A (2007b). Simulating water conflicts using game theoretical models for water resources management. In: Tiezzi E, Marques J C, Brebbia C A, J?rgensen S E (Eds). Ecosystems and Sustainable Development VI . Southampton, Boston: WIT Press, 3–12 doi: 10.2495/ECO070011
22	Wei S K, Gnauck A (2007c). Water supply and water demand of Beijing-A game theoretic approach for modeling. In: Gómez, J M , Sonnenschein M, Muller M, Welsch H, Rautenstrauch C, eds. Information Technologies in Environmental Engineering . Berlin Heidelberg: Springer Verlag, 525–536 doi: 10.1007/978-3-540-71335-7_51
23	Westmacott J R, Burn D H (1997). Climate change effects on the hydrologic regime within the Churchill-Nelson River Basin. J of Hydrol , 202: 263–279 doi: 10.1016/S0022-1694(97)00073-5
24	Wetzel G R (1983). Limnology (2nd ed.). Fort Worth. Philadelphia, San Diego, New York, etc.: Saunders College Publishing
25	Wolf A T (1999). Criteria for equitable allocations: the heart of international water conflict. Natural Resources Forum , 23: 3–30
26	World Bank (2002). World Development Indicators 2002. World Bank website. Available at www.worldbank.org [last accessed 28 Jan 2007]
27	Wu P L, Zhang W (2005). Water crisis and sustainable water resource utilization in Beijing. Journal of Liaoning Technical University , 24(3), 436–439 (in Chinese)
28	Xu Z X, Takeuchi K, Ishidaira H, Zhang X W (2002). Sustainability analysis for Yellow River water resources using the system dynamics approach. Water Resources Management , 16: 239–261 doi: 10.1023/A:1020206826669
29	ZhengY J, Li W P, Hao A B, Ye C (2007). The Emergency Water Supply in Beijing for Coping with the Consecutive Drought-Project report. The United Nations Educational, Scientific and Cultural Organization (UNESCO), China Institute for Geo-Environmental Monitoring (CIGEM), Beijing Geo-Environmental Monitoring Station (GEMS)

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