Integrated risk zoning of drought and waterlogging disasters based on fuzzy comprehensive evaluation in Anhui Province, China

This study presents a methodology for risk analysis, assessment, combination, and regionalization of integrated drought and waterlogging disasters in Anhui Province, which is supported by geographical information systems (GIS) and technique of natural disaster risk assessment from the viewpoints of climatology, geography, disaster science, environmental science, and so on. Along with the global warming, the occurrences of water-related disasters become more frequent and serious. It is necessary to determine the mode of spatial distribution of water-related disaster risk. Based on the principle of natural disaster risk, natural conditions, and socioeconomic situation, drought and waterlogging disaster risk index, which combined hazard, exposure, vulnerability, and restorability, was developed by using combined weights, entropy, and fuzzy comprehensive evaluation method. Drought and waterlogging disaster risk zoning map was made out by using GIS spatial analysis technique and gridding GIS technique. It was used for comparing the relative risk of economic and life losses in different grids of Anhui Province. It can also be used to compare the situation of different levels of drought and waterlogging disaster combination risk in a similar place. The result shows that the northwestern and central parts of Anhui Province possess higher risk, while the southwestern and northeastern parts possess lower risk. The information obtained from statistical offices and remote sensing data in relation to results compiled were statistically evaluated. The results obtained from this study are specifically intended to support local and national governmental agencies on water-related disaster management.

[1]  G. Obasi,et al.  WMO's Role in the International Decade for Natural Disaster Reduction , 1994 .

[2]  Zhao Yanxia.  Preliminary Analysis on the Demand and Review of Progress in the Field of Meteorological Drought Research , 2012 .

[3]  Qi Zhang,et al.  Dynamic risk prediction based on discriminant analysis for maize drought disaster , 2013, Natural Hazards.

[4]  Okada Norio,et al.  Integrated natural disaster risk management:comprehensive and integrated model and Chinese strategy choice , 2006 .

[5]  Xuehui Ren,et al.  Integrated risk assessment of flood disaster based on improved set pair analysis and the variable fuzzy set theory in central Liaoning Province, China , 2014, Natural Hazards.

[6]  G. Ge.  Research on Multi-scale Superposed Drought Index and Its Classification Based on Standardized Precipitation Index , 2013 .

[7]  D. Wilhite,et al.  CHAPfER2UNDERSTANDING THE DROUGHT PHENOMENON:THE ROLE OF DEFINITIONS , 1985 .

[8]  N. Okada,et al.  Damage Evaluation of Agro-meteorological Hazards in the Maize-Growing Region of Songliao Plain, China: Case Study of Lishu County of Jilin Province , 2004 .

[9]  T. McKee,et al.  THE RELATIONSHIP OF DROUGHT FREQUENCY AND DURATION TO TIME SCALES , 1993 .

[10]  N. Guttman.  ACCEPTING THE STANDARDIZED PRECIPITATION INDEX: A CALCULATION ALGORITHM 1 , 1999 .

[11]  D. Wilhite,et al.  Monitoring the 1996 Drought Using the Standardized Precipitation Index , 1999 .

[12]  N. Guttman.  COMPARING THE PALMER DROUGHT INDEX AND THE STANDARDIZED PRECIPITATION INDEX 1 , 1998 .

[13]  Yuan Wen.  COMPARISON BETWEEN STANDARDIZED PRECIPITATION INDEX AND Z-INDEX IN CHINA , 2004 .

[14]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[15]  D. Yan,et al.  Extreme precipitation events identified using detrended fluctuation analysis (DFA) in Anhui, China , 2014, Theoretical and Applied Climatology.