Journal of East China Normal University(Natural Sc
CAO Kun, LIU Su-xia
Based on the ecological footprint model and the carrying capacities of water resources from 2001 to 2013 in Beijing, the ecological footprint and the carrying capacities in Shanghai at the same year were calculated and the current situation was analyzed. Furthermore, using the techniques of Support Vector Regression (SVR) in machine learning, the ecological footprints in Shanghai from 2014 to 2016 were predicted, and the possible influencing factors were discussed. The results show that the ecological footprints of water from 2001 to 2010 keep steady, while from 2011 to 2013 there are significant reductions
compared with previous years. The status of water resources from 2001 to 2013 have been characterized by ecological deficit, and the annual average of difference of water resources ecological pressure index is −3.083 11, which demonstrates that the local water resources cannot be self-sufficient, so as to need transit water resources to meet the needs of normal production and living. In spite of the industrial structure in the optimization and economic benefits of water resources in improving, the ecological footprint of ten thousand yuan GDP and ten thousand yuan industrial GDP in Shanghai is on the decline, and the average
is higher than Beijing, and therefore there is still improve space. The predicted results show that the ecological footprint from 2014 to 2016 will present a rising trend every year. The situation of water crisis will be increasingly serious, thus measures of protection of water resources and promoting the sustainable development should be put into effect.
water ecological footprint,
Support Vector Regression,
CAO Kun, LIU Su-xia. Analysis and SVR predication of water resources ecological footprint in Shanghai[J]. Journal of East China Normal University(Natural Sc, doi: 10.3969/j.issn.1000-5641.2016.04.016.
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