Modeling domestic water demand in Huaihe River Basin of China under climate change and population dynamics
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A statistical model has been developed to forecast domestic water demand by considering climate change, population growth, urbanization, lifestyle changes and technological advances. The developed model is used to forecast future domestic water demand in different sub-basins of Huaihe River Basin of China. The study reveals that mean temperature in Huaihe River Basin will increase by 0.7–1.6 °C, population will reach to 230 million, and 61.2% of the basin area will be urbanized by the year 2030, which will cause a sharp increase in domestic water demand. The increase in domestic water demand for 1 °C increase in mean temperature is found to vary between 0.549 × 108 and 5.759 × 108 m3 for different sub-basins of Huaihe River. The forecasted change in domestic water demand is also found to vary widely for different general circulation models (GCMs) used. The GCM BCC-CSM1-1 projected the highest increase in domestic water demand, 168.44 × 108 m3 in 2020, and the GISS-E2-R the lowest, 119.21 × 108 m3. On the other hand, the BNU-ESM projected the highest increase, 196.03 × 108 m3, and the CNRM-CM5 the lowest, 161.05 × 108 m3 in year 2030. Among the different sub-basins, the highest increase in water demand is projected in Middlestream of Huaihe River in the range of 46.9 × 108–65.5 × 108 m3 in 2020, and 61.3 × 108–76.1 × 108 m3 in 2030, which is supposed to cause serious water shortage and an increase in competition among water-using sectors.
KeywordsWater demand forecast Climate change Domestic water use Water resources management Huaihe River Basin
We are grateful to the National Natural Science Foundation of China (No. 51309155, 41330854), National Basic Research Program of China (No. 2010CB951104 and 2010CB951103), Strategic Consulting Projects of Chinese Academy of Engineering (NO:2016-ZD-08-05-02), Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research (NO:IWHR-SKL-201515) and the Asia-Pacific Network for Global Change (Grant No. ARCP2013-25NSY-Shahid) for providing financial support for this research. We are also thankful to anonymous reviewers and editors for their helpful comments and suggestions.
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