Dynamic assessment and forecast of urban water ecological footprint based on exponential smoothing analysis. (10th September 2018)

• Record Type: Journal Article
• Authors: Su, Yin; Gao, Weijun; Guan, Dongjie; Su, Weici
• Is Part Of: Journal of cleaner production. Volume 195(2018)
• Page Start: 354
• Page End: 364
• Publication Date: 2018-09-10
• Subjects: Water ecological footprint -- Water ecological carrying capacity -- Water ecological footprint accounts -- Exponential smoothing model; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2018.05.184
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Water resources are essential for production and life of human beings, as well as urban economy and social development. At present, shortage of water resource has been emerging one of the urgent problems that many cities in China are facing due to rapid urbanization. In this work, water ecological footprint method has been applied to demonstrate how the sustainable utilization of water resources can be realized. According to the basic principle and calculation model of water ecological footprint, the water ecological footprint (WEF) and water ecological carrying capacity (WEC) in a period of 2004–2015 in Beijing, Shanghai, Tianjin, and Chongqing were analyzed. Then, the water ecological footprints per capita were predicted with the quadratic exponential smoothing in 2020 and 2025, respectively. The results show that the total WEF in these cities except for Shanghai increased from 2004 to 2015. The productive WEF was the primary consumption account in the total WEF accounts of the four cities. In 2015, the productive WEFs of Beijing, Shanghai, Tianjin, and Chongqing accounted for 54.46%, 82.61%, 75.04%, and 80.03% of total WEF amounts, respectively. At the same time, the proportion of the WEF of tertiary industry in Beijing was as high as 50.14% in the productive WEF accounts. The biggest proportion of the WEF of secondary industry was 59.14% and 53.14% in Shanghai and Chongqing, respectively. In Tianjin, the WEF of primary industry was the biggest proportion, accounting for 65.03%. In terms of the WEF per capita, we also found that the water ecological surplus per capita for Tianjin occurred only in 2012 indicating serious water ecological deficit in the other years. While the water ecological deficit per capita occurred in Shanghai before 2014 and exited in Beijing in the whole study period, which suggested that water resource utilization was not sustainable. However, the WEC per capita in Chongqing was bigger than the WEF per capita during 2004–2015, contributing to the water ecological surplus per capita in Chongqing. That is to say, the sustainable utilization of water resources in Chongqing was rational. It is evidenced that such changes of the total WEF are closely related to the productive WEF. We thus suggest that the productive structure associated with the distribution of water resources in different cities should be manipulated towards improving the WEC, reducing the WEF and fix regional water imbalance for further promoting the sustainable development of the overall socio-economy.