Abstract
The risk analysis of flood and drought disasters and the study of their influencing factors enhance our understanding of the temporal and spatial variation law of disasters and help identify the main factors affecting disasters. This paper uses the provincial administrative region of China as the research area. The proportion of the disaster area represents the degree of the disaster. The statistical distribution of the proportions was optimized from 10 alternative distributions based on a KS test, and the disaster risk was analyzed. Thirty-five indicators were selected from nature, agriculture and the social economy as alternative factors. The main factors affecting flood and drought disasters were selected by Pearson, Spearman and Kendall correlation coefficient test. The results demonstrated that the distribution of floods and drought is right-skewed, and the gamma distribution is the best statistical distribution for fitting disasters. In terms of time, the risk of flood and drought disasters in all regions showed a downward trend. Economic development and the enhancement of the ability to resist disasters were the main reasons for the change in disasters. Spatially, the areas with high drought risk were mainly distributed in Northeast and North China, and the areas with high flood risk were mainly distributed in the south, especially in Hubei, Hunan, Jiangxi and Anhui. The distribution of floods and drought disasters was consistent with the distribution characteristics of precipitation and water resources in China. Among the natural factors, precipitation was the main factor causing changes in floods and drought disasters. Among the agricultural and socioeconomic factors, the indicators reflecting the disaster resistance ability and regional economic development level were closely related to flood and drought disasters. The research results have reference significance for disaster classification, disaster formation mechanisms and flood and drought resistance.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ahmadalipour A, Moradkhani H, Castelletti A, Magliocca N (2019) Future drought risk in Africa: integrating vulnerability, climate change, and population growth. Sci Total Environ 662:672–686. https://doi.org/10.1016/j.scitotenv.2019.01.278
Cai T, Li XY, Ding X, Wang J, Zhan J (2019) Flood risk assessment based on hydrodynamic model and fuzzy comprehensive evaluation with GIS technique. Int J Disaster Risk Reduct 35:12. https://doi.org/10.1016/j.ijdrr.2019.101077
Chen HL, Liang ZY, Liu Y, Jiang QS, Xie SG (2018) Effects of drought and flood on crop production in China across 1949–2015: spatial heterogeneity analysis with Bayesian hierarchical modeling. Nat Hazards 92:525–541. https://doi.org/10.1007/s11069-018-3216-0
Chen WZ, Zhu D, Huang CJ, Ciais P, Yao YT, Friedlingstein P, Sitch S, Haverd V, Jain AK, Kato E, Kautz M, Lienert S, Lombardozzi D, Poulter B, Tia HQ, Vuichard N, Walker AP, Zeng N (2019a) Negative extreme events in gross primary productivity and their drivers in China during the past three decades. Agric for Meteorol 275:47–58. https://doi.org/10.1016/j.agrformet.2019.05.002
Chen X, Li FW, Wang YX, Feng P, Yang RZ (2019b) Evolution properties between meteorological, agricultural and hydrological droughts and their related driving factors in the Luanhe River basin, China. Hydrol Res 50:1096–1119. https://doi.org/10.2166/nh.2019.141
Farhangfar S, Bannayan M, Khazaei HR, Baygi MM (2015) Vulnerability assessment of wheat and maize production affected by drought and climate change. Int J Disaster Risk Reduct. https://doi.org/10.1016/j.ijdrr.2015.03.006
Fontaine MM, Steinemann AC (2009) Assessing vulnerability to natural hazards: impact-based method and application to drought in Washington State. Nat Hazard Rev 10:11–18. https://doi.org/10.1061/(ASCE)1527-6988(2009)10:1(11)
Forbes C, Evans M, Hastings N, Peacock B (2011) Statistical distributions. Wiley
Fu Q, Zhou ZQ, Li TX, Liu D, Hou RJ, Cui S, Yan PR (2018) Spatiotemporal characteristics of droughts and floods in northeastern China and their impacts on agriculture. Stoch Environ Res Risk Assess 32:2913–2931. https://doi.org/10.1007/s00477-018-1543-z
Grubler A (2014) IPCC fifth assessment report. Weather 68:310
Guo H, Bao A, Liu T, Ndayisaba F, Jiang L, Kurban A, De Maeyer P (2018) Spatial and temporal characteristics of droughts in Central Asia during 1966–2015. Sci Total Environ 624:1523–1538. https://doi.org/10.1016/j.scitotenv.2017.12.120
Jia JX, Wang XY, Hersi NAM, Zhao W, Liu YH (2019) Flood-risk zoning based on analytic hierarchy process and fuzzy variable set theory. Nat Hazard Rev 20:8. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000329
Luh J, Christenson EC, Toregozhina A, Holcomb DA, Witsil T, Hamrick LR, Ojomo E, Bartram J (2015) Vulnerability assessment for loss of access to drinking water due to extreme weather events. Clim Change 133:665–679. https://doi.org/10.1007/s10584-015-1493-0
McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. In: Proceedings of the 8th conference on applied climatology. American Meteorological Society, Boston, pp 179–183
Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391:204–216. https://doi.org/10.1016/j.jhydrol.2010.07.012
Modarres R, Sarhadi A, Burn DH (2016) Changes of extreme drought and flood events in Iran. Glob Planet Change 144:67–81. https://doi.org/10.1016/j.gloplacha.2016.07.008
Murthy CS, Laxman B, Sai MVRS (2015) Geospatial analysis of agricultural drought vulnerability using a composite index based on exposure, sensitivity and adaptive capacity. Int J Disaster Risk Reduct 12:163–171. https://doi.org/10.1016/j.ijdrr.2015.01.004
Narasimhan B, Srinivasan R (2005) Development and evaluation of Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) for agricultural drought monitoring. Agric for Meteorol 133:69–88. https://doi.org/10.1016/j.agrformet.2005.07.012
Palmer W (1965) Meteorological drought. US department of Commerce Weather Bureau Research Paper, pp 45–58
Parsons DJ, Rey D, Tanguy M, Holman IP (2019) Regional variations in the link between drought indices and reported agricultural impacts of drought. Agric Syst 173:119–129. https://doi.org/10.1016/j.agsy.2019.02.015
Pei W, Fu Q, Liu D, Li TX, Cheng K, Cui S (2018) Spatiotemporal analysis of the agricultural drought risk in Heilongjiang Province, China. Theor Appl Climatol 133:151–164. https://doi.org/10.1007/s00704-017-2182-x
Pei W, Fu Q, Liu D, Li T (2019) A drought index for Rainfed agriculture: The Standardized Precipitation Crop Evapotranspiration Index (SPCEI). Hydrol Process 33:803–815. https://doi.org/10.1002/hyp.13365
Prabnakorn S, Maskey S, Suryadi FX, de Fraiture C (2019) Assessment of drought hazard, exposure, vulnerability, and risk for rice cultivation in the Mun River Basin in Thailand. Nat Hazards 97:891–911. https://doi.org/10.1007/s11069-019-03681-6
Qian XJ, Liang L, Shen Q, Sun Q, Zhang LP, Liu ZX, Zhao SH, Qin ZH (2016) Drought trends based on the VCI and its correlation with climate factors in the agricultural areas of China from 1982 to 2010. Environ Monit Assess 188:13. https://doi.org/10.1007/s10661-016-5657-9
Rosenthal R (1968) An application of the Kolmogorov–Smirnov test for normality with estimated mean and variance. Psychol Rep 22:570. https://doi.org/10.2466/pr0.1968.22.2.570
Shao WY, Kam J (2020) Retrospective and prospective evaluations of drought and flood. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2020.141155
Shen Q, Liang L, Luo X, Li YJ, Zhang LP (2017) Analysis of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China from 1982 to 2010. Environ Monit Assess 189:14. https://doi.org/10.1007/s10661-017-6187-9
Simelton E, Fraser EDG, Termansen M, Forster PM, Dougill AJ (2009) Typologies of crop-drought vulnerability: an empirical analysis of the socio-economic factors that influence the sensitivity and resilience to drought of three major food crops in China (1961–2001). Environ Sci Policy 12:438–452. https://doi.org/10.1016/j.envsci.2008.11.005
Tanago IG, Urquijo J, Blauhut V, Villarroya F, De Stefano L (2016) Learning from experience: a systematic review of assessments of vulnerability to drought. Nat Hazards 80:951–973. https://doi.org/10.1007/s11069-015-2006-1
Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23:1696–1718. https://doi.org/10.1175/2009JCLI2909.1
Wijitkosum S (2018) Fuzzy AHP for drought risk assessment in Lam Ta Kong Watershed, the North-eastern Region of Thailand. Soil Water Res 13:218–225. https://doi.org/10.17221/158/2017-SWR
Wilhite DA, Sivakumar MVK, Pulwarty R (2014) Managing drought risk in a changing climate: the role of national drought policy. Weather Clim Extremes 3:4–13. https://doi.org/10.1016/j.wace.2014.01.002
Williamson R (2013) IPCC releases fifth assessment report. Carbon Manag 4:583
Wu D, Yan DH, Yang GY, Wang XG, Xiao WH, Zhang HT (2013) Assessment on agricultural drought vulnerability in the Yellow River basin based on a fuzzy clustering iterative model. Nat Hazards 67:919–936. https://doi.org/10.1007/s11069-013-0617-y
Xiao YH (2017) A fast algorithm for two-dimensional Kolmogorov–Smirnov two sample tests. Comput Stat Data Anal 105:53–58. https://doi.org/10.1016/j.csda.2016.07.014
Xiao D, Haicheng L, Yang D (2017) Evaluation method of grain reduction caused by droughts and floods and empirical analysis of China grain reduction. J Catastrophol 32:26–31. https://doi.org/10.3969/j.issn.1000-811X.2017.02.005
Xu HF, Xu KX, Yang YJ (2021) Risk assessment model of agricultural drought disaster based on grey matter-element analysis theory. Nat Hazards 107:2693–2707. https://doi.org/10.1007/s11069-021-04681-1
Yan DH, Han DM, Wang G, Yuan Y, Hu Y, Fang HY (2014) The evolution analysis of flood and drought in Huai River Basin of China based on monthly precipitation characteristics. Nat Hazards 73:849–858. https://doi.org/10.1007/s11069-014-1109-4
Yang HC, Wang HX, Fu GB, Yan HM, Zhao PP, Ma MH (2017) A modified soil water deficit index (MSWDI) for agricultural drought monitoring: case study of Songnen Plain, China. Agric Water Manag 194:125–138. https://doi.org/10.1016/j.agwat.2017.07.022
Yang J, Pei Y, Zhang YW, Ge QS (2018a) Risk assessment of precipitation extremes in northern Xinjiang, China. Theor Appl Climatol 132:823–834. https://doi.org/10.1007/s00704-017-2115-8
Yang P, Xia J, Zhang Y, Zhan C, Qiao Y (2018b) Comprehensive assessment of drought risk in the arid region of Northwest China based on the global palmer drought severity index gridded data. Sci Total Environ 627:951–962. https://doi.org/10.1016/j.scitotenv.2018.01.234
Yuan Y, Yan DH, Yuan Z, Yin J, Zhao ZN (2019) Spatial Distribution of Precipitation in Huang–Huai–Hai River Basin between 1961 to 2016, China. Int J Environ Res Public Health 16:11. https://doi.org/10.3390/ijerph16183404
Zhang JY, Chen YB (2019) Risk assessment of flood disaster induced by typhoon rainstorms in Guangdong Province. China Sustain. https://doi.org/10.3390/su11102738
Zhang Q, Gu XH, Singh VP, Kong DD, Chen XH (2015) Spatiotemporal behavior of floods and droughts and their impacts on agriculture in China. Glob Planet Change 131:63–72. https://doi.org/10.1016/j.gloplacha.2015.05.007
Zuo D, Cai S, Xu Z, Peng D, Kan G, Sun W, Pang B, Yang H (2019) Assessment of meteorological and agricultural droughts using in-situ observations and remote sensing data. Agric Water Manag 222:125–138. https://doi.org/10.1016/j.agwat.2019.05.046
Acknowledgements
This research was supported by funds from the National Natural Science Foundation of China (No. 52009019) and the Natural Science Foundation of Heilongjiang Province (No. LH2019E012).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflicts of interest for this work.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Pei, W., Tian, C., Fu, Q. et al. Risk analysis and influencing factors of drought and flood disasters in China. Nat Hazards 110, 1599–1620 (2022). https://doi.org/10.1007/s11069-021-05004-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11069-021-05004-0