College of Rongzhi, Chongqing Technology and Business University, Chongqing 401320, China.
Chongqing Key Laboratory of Electronic Commerce & Supply Chain System, Chongqing Technology and Business University, Chongqing 400067, China.
Int J Environ Res Public Health. 2017 Nov 15;14(11):1386. doi: 10.3390/ijerph14111386.
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.
高精度的需水预测是城市水资源合理配置的重要基础，也是可持续城市发展的基础。作为中国西南部最年轻的中央直辖市，重庆的水资源短缺随着人口增长和经济快速发展而显著增加。在本文中，基于用水量数据特点，建立了一种新的灰色需水预测模型（GWFM）。研究了 GWFM 模型的参数估计和误差检验方法。然后，采用 GWFM 模型对重庆 2009-2015 年的需水量进行模拟，并对 2016 年进行预测。对 GWFM 模型的模拟和预测误差进行了检验，结果表明，GWFM 模型的模拟和预测精度均优于经典单变量一阶方程灰色模型（GM(1,1)）和常用的单变量一阶离散灰色模型（DGM(1,1)）。最后，对重庆 2017-2022 年的需水量进行了预测，并根据预测结果提出了相应的控制措施和建议，以确保供水的可持续性，促进重庆经济的可持续发展。
