Skip to main content

Advertisement

Log in

Innovative trend analysis of main agriculture natural hazards in China during 1989–2014

  • Original Paper
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

China is a country where the agricultural areas are frequently affected by natural hazards, and comprehending the change trends of natural hazards is of great significance to sustainable development in agriculture. Innovative trend analysis (ITA) is a new and important trend detection method. In this study, the ITA method was used to analyze five kinds of natural hazards in agricultural areas of China during 1989–2014: wind and hail, forest fire, drought, flood, and freezing hazard. The ITA method was compared with two traditional trend analysis methods, i.e., the Mann–Kendall (M–K) test and linear regression analysis (LRA). The results showed that the areas affected by wind and hail, forest fire, drought, and flood in China are showing significant decreasing trends (p < 0.01 or p < 0.05), whereas the areas affected by freezing hazard are showing significant increasing trends. Using the LRA and M–K test methods, 40 and 51 time series with significant trends (p < 0.01 or p < 0.05) were detected, respectively, while ITA was able to successfully detect 138 significant trends (p < 0.01 or p < 0.05), including 89 time series that did not show significant trends when using the LRA or M–K tests. The time series surveyed indicated that the ITA method is superior to the two traditional analysis methods, and it is able to detect the hidden trends in time series. In addition, based on the analysis of the spatial distribution of the ITA data, the areas affected by wind and hail, forest fire, drought, and flood are showing significant decreasing trends in Southwest and East China (p < 0.01 or p < 0.05), whereas in the North China and part of Central China, there are significant increasing trends for these four natural hazards (p < 0.01 or p < 0.05). In most part of North, Central (p < 0.01 or p < 0.05), Northwest (p < 0.01 or p < 0.05), and South (p < 0.01) China, freezing hazard is increasing significantly, and it is showing a significant decreasing trend only in East and Northeast China (p < 0.01).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Ay M, Kisi O (2015) Investigation of trend analysis of monthly total precipitation by an innovative method. Theor Appl Climatol 120:617–629

    Article  Google Scholar 

  • Chang Y, Dong J (2011) Present situation and development trend of China’s agrometeorological disaster assessment. Heilongjiang Sci Technol Inf 6:20

    Google Scholar 

  • Cui L, Wang L, Lai Z, Tian Q, Liu W, Li J (2017) Innovative trend analysis of annual and seasonal air temperature and rainfall in the Yangtze river basin, china during 1960–2015. J Atmos Solar Terr Phys 164:48–59

    Article  Google Scholar 

  • Du X, Jin X, Yang X, Yang X, Xiang X, Zhou Y (2015) Spatial-temporal pattern changes of main agriculture natural disasters in china during 1990–2011. J Geogr Sci 25(4):387–398

    Article  Google Scholar 

  • Gao Y, Zhan H, Chen W, Jiao J (2013) Study on the impact of natural disasters on agriculture in China. J Catastrophol 28(3):79–84

    Google Scholar 

  • Hirabayashi Y, Mahendran R, Koirala S, Konoshima L, Yamazaki D, Watanabe S, Kim H, Kanae S (2013) Global flood risk under climate change. Nat Clim Change 3(9):816–821

    Article  Google Scholar 

  • Iglesias A, Mougou R, Moneo M et al (2011) Towards adaptation of agriculture to climate change in the Mediterranean. Reg Environ Change 11(1):159–166

    Article  Google Scholar 

  • Islam A, Mitra D, Dewan A, Akhter SH (2016) Coastal multi-hazard vulnerability assessment along the Ganges deltaic coast of Bangladesh: a geospatial approach. Ocean Coast Manag 127:1–15

    Article  Google Scholar 

  • Kendall MG (1970) Rank correlation methods, 4th edn. Griffin, London

    Google Scholar 

  • Kim S, Shin Y, Kim H et al (2013) Impacts of typhoon and heavy rain disasters on mortality and infectious diarrhea hospitalization in South Korea. Int J Environ Health Res 23(5):365–376

    Article  Google Scholar 

  • Lei XU, Qiao Z, Jing Z, Liang Z, Wei S, Jin YX (2017) Extreme meteorological disaster effects on grain production in Jilin province, China. J Integr Agric 16(2):486–496

    Article  Google Scholar 

  • Liao J, Su Y, Zewei F, Li M (2008) Analysis on the effects of agricultural natural disasters on the agricultural economy in Guizhou in the past 54 years. J Anhui Agric Sci 25:11114–11117

    Google Scholar 

  • Liu JG, Diamond J (2005) China’s environment in a globalizing world. Nature 435(7046):1179–1186

    Article  Google Scholar 

  • Maaskant B, Jonkman SN, Bouwer LM (2009) Future risk of flooding: an analysis of changes in potential loss of life in South Holland (The Netherlands). Environ Sci Policy 12(2):157–169

    Article  Google Scholar 

  • Mann HB (1945) Nonparametric test against trend. Econometrica 13:245–259

    Article  Google Scholar 

  • Markus M, Demissie M, Short MB, Verma S, Cooke RA (2014) Sensitivity analysis of annual nitrate loads and the corresponding trends in the lower Illinois River. J Hydrol Eng 19(3):533–543

    Article  Google Scholar 

  • McMichael AJ, Woodruff RE, Hales S (2006) Climate change and human health: present and future risks. Lancet 367(9513):859–869

    Article  Google Scholar 

  • Morrissey SA, Reser JP (2007) Natural disasters, climate change and mental health considerations for rural Australia. Aust J Rural Health 15(2):120–125

    Article  Google Scholar 

  • Ni JR, Sun LY, Li T et al (2010) Assessment of flooding impacts in terms of sustainability in mainland China. J Environ Manag 91(10):1930–1942

    Article  Google Scholar 

  • Olive DJ (1980) Linear regression analysis. Technometrics 22:130

    Article  Google Scholar 

  • Onyutha C (2015) Identification of sub-trends from hydrometeorological series. Stoch Environ Res Risk Assess 30(1):189–205

    Article  Google Scholar 

  • Pei W, Fu Q, Liu D et al (2018) Spatiotemporal analysis of the agricultural drought risk in Heilongjiang Province, China. Theor Appl Climatol 133(1–2):151–164

    Article  Google Scholar 

  • Şen Z (2012) Innovative trend analysis methodology. J Hydrol Eng 17:1042–1046

    Article  Google Scholar 

  • Şen Z (2014) Trend identification simulation and application. J Hydrol Eng 19:635–642

    Article  Google Scholar 

  • Şen Z (2015) Innovative trend significance test and applications. Theor Appl Climatol 127(3–4):1–9

    Google Scholar 

  • Sivakumar MVK (2006) Climate prediction and agriculture current status and future challenges. Climate Res 33(1):3–17

    Article  Google Scholar 

  • Suder G, Gillingham DW (2007) Paradigms and paradoxes of agricultural risk governance. Int J Risk Assess Manag 7(3):444–457

    Article  Google Scholar 

  • Tian G, Lin Z (2016) Research on impact of meteorological disasters on food production: taking Fujian province for example. J Catastrophol 1:148–152

    Google Scholar 

  • Wang XF, Li MS (2012) Analysis on decoupling relationship between natural disasters and grain production in China. J Catastrophol 27(1):94–97 (in Chinese)

    Google Scholar 

  • Wilhelmi OV, Wilhite DA (2002) Assessing vulnerability to agricultural drought: a Nebraska case study. Nat Hazards 25(1):37–58

    Article  Google Scholar 

  • Wu H, Qian H (2016) Innovative trend analysis of annual and seasonal rainfall and extreme values in Shanxi, China, since the 1950s. Int J Climatol 37(5):2582–2592

    Article  Google Scholar 

  • Wu X, Wang Z, Zhou X, Zeng Z, Lai C, Chen X (2017) Variability of annual peak flows in the Beijiang river basin, south china, and possible underlying causes. Hydrol Res 48(2):442–454

    Article  Google Scholar 

  • Xiao FJ, Xiao ZN (2010) Characteristics of tropical cyclones in China and their impacts analysis. Nat Hazards 54(3):827–837

    Article  Google Scholar 

  • Xu L, Wang H, Ma X, Chen J, Ma J (2013) Study on framework and adaptive strategies of drought disaster risk management in Yunnan province. Areal Res Dev 32(2):103–108

    Google Scholar 

  • Zhang D, Wang G, Zhou H (2011) Assessment on Agricultural drought risk based on variable fuzzy sets model. Chin Geogr Sci 21(2):167–175

    Article  Google Scholar 

  • Zhao J (1995) Physical geography of China, 3rd edn. Higher Education Press, Beijing (in Chinese)

    Google Scholar 

  • Zhou Y, Li N, Wu WX et al (2013) Exploring the characteristics of major natural disasters in China and their impacts during the past decades. Nat Hazards 69(1):829–843

    Article  Google Scholar 

  • Zhou Z, Wang L, Lin A, Zhang M, Niu Z (2018) Innovative trend analysis of solar radiation in china during 1962–2015. Renew Energy 119:675–689

    Article  Google Scholar 

Download references

Acknowledgements

This research was financially supported by the National Natural Science Foundation of China (Grant No. 41571400) and the National Key Research and Development Program of China (Grant No. 2018YFD0300905). The paper was also supported by the Open Research Fund Program of Anhui Province Key Lab of Farmland Ecological Conservation and Pollution Prevention, and in part by the Anhui Key Laboratory of Smart City and Geographical Condition Monitoring under Grant 2016-K-01Z. The authors would also like to thank the reviewers for their constructive suggestions and comments.

Author information

Authors and Affiliations

Authors

Contributions

JL and WW conceived and designed the methodology of innovative trend analysis of the main natural hazards in agricultural areas. XY advised on the methods applied in the study, HJ, RG, HW, JH, and YJ performed the experimental analyses. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Junli Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, J., Wu, W., Ye, X. et al. Innovative trend analysis of main agriculture natural hazards in China during 1989–2014. Nat Hazards 95, 677–720 (2019). https://doi.org/10.1007/s11069-018-3514-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-018-3514-6

Keywords

Navigation