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Forecasting the Water Demand in Chongqing, China Using a Grey Prediction Model and Recommendations for the Sustainable Development of Urban Water Consumption

Author

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  • Hua’an Wu

    (College of Rongzhi, Chongqing Technology and Business University, Chongqing 401320, China)

  • Bo Zeng

    (College of Rongzhi, Chongqing Technology and Business University, Chongqing 401320, China)

  • Meng Zhou

    (Chongqing Key Laboratory of Electronic Commerce & Supply Chain System, Chongqing Technology and Business University, Chongqing 400067, China)

Abstract

High accuracy in water demand predictions is an important basis for the rational allocation of city water resources and forms the basis for sustainable urban development. The shortage of water resources in Chongqing, the youngest central municipality in Southwest China, has significantly increased with the population growth and rapid economic development. In this paper, a new grey water-forecasting model (GWFM) was built based on the data characteristics of water consumption. The parameter estimation and error checking methods of the GWFM model were investigated. Then, the GWFM model was employed to simulate the water demands of Chongqing from 2009 to 2015 and forecast it in 2016. The simulation and prediction errors of the GWFM model was checked, and the results show the GWFM model exhibits better simulation and prediction precisions than those of the classical Grey Model with one variable and single order equation GM(1,1) for short and the frequently-used Discrete Grey Model with one variable and single order equation, DGM(1,1) for short. Finally, the water demand in Chongqing from 2017 to 2022 was forecasted, and some corresponding control measures and recommendations were provided based on the prediction results to ensure a viable water supply and promote the sustainable development of the Chongqing economy.

Suggested Citation

  • Hua’an Wu & Bo Zeng & Meng Zhou, 2017. "Forecasting the Water Demand in Chongqing, China Using a Grey Prediction Model and Recommendations for the Sustainable Development of Urban Water Consumption," IJERPH, MDPI, vol. 14(11), pages 1-12, November.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:11:p:1386-:d:118902
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    References listed on IDEAS

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    1. Lan Yu & Soon Keat Tan & Lloyd H. C. Chua, 2017. "Online Ensemble Modeling for Real Time Water Level Forecasts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(4), pages 1105-1119, March.
    2. Chang, Tsung-Sheng & Ku, Cheng-Yuan & Fu, Hsin-Pin, 2013. "Grey theory analysis of online population and online game industry revenue in Taiwan," Technological Forecasting and Social Change, Elsevier, vol. 80(1), pages 175-185.
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    Cited by:

    1. Ning Zhang & Zaiwu Gong & Kedong Yin & Yuhong Wang, 2018. "Special Issue “Decision Models in Green Growth and Sustainable Development”," IJERPH, MDPI, vol. 15(6), pages 1-8, May.
    2. Xiang Li & Jiang Zhu & Tao Liu & Xiangdong Yin & Jiangchun Yao & Hao Jiang & Bing Bu & Jianlong Yan & Yixuan Li & Zhangcheng Chen, 2023. "Quota and Space Allocations of New Urban Land Supported by Urban Growth Simulations: A Case Study of Guangzhou City, China," Land, MDPI, vol. 12(6), pages 1-21, June.
    3. Yu-Feng Zhao & Ming-Huan Shou & Zheng-Xin Wang, 2020. "Prediction of the Number of Patients Infected with COVID-19 Based on Rolling Grey Verhulst Models," IJERPH, MDPI, vol. 17(12), pages 1-20, June.
    4. Zhenhui Huang & Wei Wei & Ying Han & Shuangying Ding & Ke Tang, 2022. "The Coupling Coordination Evolutionary Analysis of Tourism-Ecological Environment-Public Service for the Yellow River Basin of China," IJERPH, MDPI, vol. 19(15), pages 1-23, July.

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