Abstract
After the 2008 Wenchuan earthquake, secondary geological disasters occurred frequently and caused huge economic losses in the upper reaches of Min River. In this paper, 2003–2012 GDP data of the upper Min River were divided into two states: no disaster (2003–2007) and disaster (2008–2012). With the support of Excel and Matlab7.0 software, the data were, respectively, used to construct no disaster GM (1,1) model and disaster GM (1,1) model. Then two forecasting models were compared to establish grey forecasting–difference comparison model on the regional economic effects of natural disasters (including Wenchuan earthquake and secondary mountain hazards) and presumably analysed the influence degree and its recovery. Conclusions are drawn as follows: (1) The variation of 2003–2012 GDP in the upper reaches of Min River is shown as inclined “N”, so regional economy is affected by natural disasters significantly; (2) Using non-disaster or disaster of grey forecasting model to speculate 2008–2012 GDP and test c, p value, the results show the “good” rating that indicates the model can be used for pcrct rediction of regional GDP; (3) It obtains the I value from using grey forecasting-difference comparison model that shows a irregular “几” font variation around the 2008 year; (4) The development of natural disasters has different effects on regional economic recovery. The upper reaches of Min River can be restored to the level of non-disaster in 2014–2015. And the recovery time of these counties is that:Wenchuan County in 2015–2016, Li County in 2011–2012, Mao County in 2020–2021, Songpan Country in 2015–2016, Heishui County cannot be restored. The research results can serve as a guide and reference for the post-disaster of the regional social and economic development, overall planning and sustainability.
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Acknowledgments
The study was financially supported by the National Natural Science Foundation of China (Grant No. 41371185 and 41101164) and MOE (Ministry of Education in China) Special task project of Humanities and Social Sciences (Research on the cultivation of Engineering Science and technology personnel) (Grant No. 15JDGC019).
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Miao, C., Ding, M. Analysis of influence of natural disaster on the economy and prediction of recovery time based on grey forecasting–difference comparison model: a case study in the upper Min River. Nat Hazards 85, 1135–1150 (2017). https://doi.org/10.1007/s11069-016-2625-1
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DOI: https://doi.org/10.1007/s11069-016-2625-1