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Abstract
Water-energy nexus has been a popular topic of rese arch in recent years. The relationships between the demand for water resources and energy are intense and closely connected in urban areas. The primary, secondary, and tertiary industry gross domestic product (GDP), the total population, the urban population, annual precipitation, agricultural and industrial water consumption, tap water supply, the total discharge of industrial wastewater, the daily sewage treatment capacity, total and domestic electricity consumption, and the consumption of coal in industrial enterprises above the designed size were chosen as input indicators. A feedforward artificial neural network model (ANN) based on a back-propagation algorithm with two hidden layers was constructed to combine urban water resources with energy demand. This model used historical data from 1991 to 2016 from Wuxi City, eastern China. Furthermore, a multiple linear regression model (MLR) was introduced for comparison with the ANN. The results show the following: (a) The mean relative error values of the forecast and historical urban water-energy demands are 1.58 % and 2.71%, respectively; (b) The predicted water-energy demand value for 2020 is 4.843 billion cubic meters and 47.561 million tons of standard coal equivalent; (c) The predicted water-energy demand value in the year 2030 is 5.887 billion cubic meters and 60.355 million tons of standard coal equivalent; (d) Compared with the MLR, the ANN performed better in fitting training data, which achieved a more satisfactory accuracy and may provide a reference for urban water-energy supply planning decisions.
Highlights
Water and energy are basic natural and strategic resources, and they form the material basis for the survival of human society and provide an important guarantee for the sustainable development of the national economy
In the study of water demand forecasting, Cengiz Koç forecasted the water demand of the Bodrum Peninsula for the 3 to 40 years of the tourism season based on the local population statistics [7]
The study only analyzed the impacts of population size and structure of water demand, and it did not take into account the constraints of other economic factors on water use
Summary
Water and energy are basic natural and strategic resources, and they form the material basis for the survival of human society and provide an important guarantee for the sustainable development of the national economy. With intensified global climate change, population growth, and rapid economic and social development, the comprehensive forecast of water and energy demand in urban areas is of great significance for policy planning. In the study of water demand forecasting, Cengiz Koç forecasted the water demand of the Bodrum Peninsula for the 3 to 40 years of the tourism season based on the local population statistics [7]. The study only analyzed the impacts of population size and structure of water demand, and it did not take into account the constraints of other economic factors on water use. Rathnayaka established Australian urban households as water terminals, divided residential end-use water into different types, established the urban residential end-use water demand model, Water 2018, 10, 385; doi:10.3390/w10040385 www.mdpi.com/journal/water
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