Abstract
Shandong Province, the main grain-producing area in China, has ranked first in China in terms of total agricultural output value for many years. However, droughts with high frequency and long duration have been hindering local agricultural production. This paper aims to assess the risk of drought disasters in Shandong Province. Firstly, based on the natural disaster system theory, an agricultural drought disaster risk assessment model is developed. This model is applied to assess the agricultural drought hazard, exposure, vulnerability, emergency response and recovery capability, and agricultural drought disaster risk from 2012 to 2020. Secondly, risk uncertainty is analyzed through the evolution of risk over the past years. Finally, the accuracy of the risk assessment is verified through agricultural drought-related losses. The results show that: (1) The risk assessment results are in good agreement with the actual drought losses. (2) From the spatial scale, the high-risk areas of agricultural drought disasters were mainly located in the western part of Shandong Province. High-hazard areas of drought were located in eastern Shandong Province, and areas with high agricultural exposure and vulnerability were concentrated in the western part of the province, and the emergency response and recovery capacity of Rizhao and Zaozhuang was low. (3) From the time scale, there was high uncertainty of agricultural drought disaster risk in Dongying, Qingdao, and Heze in 2012–2020, all of which had reached a high-risk level of agricultural drought disaster several times. The agricultural exposure in Dongying, the agricultural vulnerability in Heze, and the emergency response and recovery capacity in Heze and Linyi all showed an increasing trend. The interannual variation characteristics and spatial zoning of agricultural drought risk are explored, and it is instructive for risk decision-makers to better develop drought response measures and improve drought resilience.
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References
Ahammed S, Homsi R, Khan N, Shahid S, Shiru M, Mohsenipour M, Ahmed K, Nawaz N, Alias N, Yuzir A (2020) Assessment of changing pattern of crop water stress in Bangladesh. Environ Dev Sustain 22:4619–4637. https://doi.org/10.1007/s10668-019-00400-w
Bahrami M, Bazrkar S, Zarei A (2021) Spatiotemporal investigation of drought pattern in Iran via statistical analysis and GIS technique. Theor Appl Climatol 143:1113–1128. https://doi.org/10.1007/s00704-020-03480-1
Bhunia P, Das P, Maiti R (2020) Meteorological drought study through spi in three drought prone districts of west Bengal, India. Earth Syst Environ 4:43–55. https://doi.org/10.1007/s41748-019-00137-6
Bi S, Qiu X, Wang G, Gong Y, Wang L, Xu M (2021) Spatial distribution characteristics of drought disasters in Hunan province of China from 1644 to 1911 based on EOF and REOF methods. Environ Earth Sci 80:1–11. https://doi.org/10.1007/s12665-021-09867-1
Chen M, Ning S, ** J, Cui Y, Wu C, Zhou Y (2020) Risk assessment of agricultural drought disaster on the Huaibei plain of China based on the improved connection number and entropy information diffusion method. Water-Sui 12:1089. https://doi.org/10.3390/w12041089
China Banking and Insurance Regulatory Commission (2012−2020) Yearbook of China’s Insurance 2013−2021. China Insurance Yearbook Club, Bei**g (in Chinese)
Chu H, Venevsky S, Wu C, Wang M (2019) NDVI-based vegetation dynamics and its response to climate changes at amur-Heilongjiang river basin from 1982 to 2015. Sci Total Environ 650:2051–2062. https://doi.org/10.1016/j.scitotenv.2018.09.115
Dabanli I (2018) Drought hazard, vulnerability, and risk assessment in turkey. Arab J Geosci 11:1–12. https://doi.org/10.1007/s12517-018-3867-x
Dracup J, Lee K, Paulson E (1980) On the definition of droughts. Water Resour Manag 16:297–302. https://doi.org/10.1029/WR016i002p00297
Duan Y, **ong J, Cheng W, Wang N, Li Y, He Y, Liu J, He W, Yang G (2021) Flood vulnerability assessment using the triangular fuzzy number-based analytic hierarchy process and support vector machine model for the belt and road region. Nat Hazards. https://doi.org/10.1007/s11069-021-04946-9
Guo H, Chen J, Pan C (2021) Assessment on agricultural drought vulnerability and spatial heterogeneity study in China. Int J Env Res Pub He 18:4449. https://doi.org/10.3390/ijerph18094449
Hagenlocher M, Meza I, Anderson C, Min A, Renaud F, Walz Y, Siebert S, Sebesvari Z (2019) Drought vulnerability and risk assessments: state of the art, persistent gaps, and research agenda. Environ Res Lett 14:083002. https://doi.org/10.1088/1748-9326/ab225d
Hoque M, Pradhan B, Ahmed N, Sohel M (2021) Agricultural drought risk assessment of northern new south Wales, Australia using geospatial techniques. Sci Total Environ 756:143600. https://doi.org/10.1016/j.scitotenv.2020.143600
Jia J, Han L, Liu Y, He N, Zhang Q, Wan X, Zhang Y, Hu J (2016) Drought risk analysis of maize under climate change based on natural disaster system theory in southwest China. Acta Ecol Sin 36:340–349. https://doi.org/10.1016/j.chnaes.2016.06.001
Karimi M, Melesse A, Khosravi K, Mamuye M, Zhang J (2019) Analysis and prediction of meteorological drought using SPI index and Arima model in the Karkheh river basin, Iran. In: Extreme hydrology and climate variability. Elsevier, pp 343–353. https://doi.org/10.1016/B978-0-12-815998-9.00026-9
Krishnan A, Kasim M, Hamid R, Ghazali M (2021) A modified critic method to estimate the objective weights of decision criteria. Symmetry 13:973. https://doi.org/10.3390/sym13060973
Lesk C, Rowhani P, Ramankutty N (2016) Influence of extreme weather disasters on global crop production. Nature 529:84–87. https://doi.org/10.1038/nature16467
Li X, Du J, Long H, Sun G (2019) Characteristics and risk analysis of hydrological disaster events from 1949 to 2015 in Urumqi, China. Theor Appl Climatol 137:745–754. https://doi.org/10.1007/s00704-018-2630-2
Li K, Tong Z, Liu X, Zhang J, Tong S (2020) Quantitative assessment and driving force analysis of vegetation drought risk to climate change: methodology and application in northeast China. Agric For Meteorol 282:107865. https://doi.org/10.1016/j.agrformet.2019.107865
Liu X, Pan Y, Zhu X, Yang T, Bai J, Sun Z (2018) Drought evolution and its impact on the crop yield in the north China plain. J Hydrol 564:984–996. https://doi.org/10.1016/j.jhydrol.2018.07.077
Liu Y, You M, Zhu J, Wang F, Ran R (2019) Integrated risk assessment for agricultural drought and flood disasters based on entropy information diffusion theory in the middle and lower reaches of the Yangtze River, China. Int J Disast Risk Reduct 38:101. https://doi.org/10.1016/j.ijdrr.2019.101194
Liu Q, Zhang S, Zhang H, Bai Y, Zhang J (2020) Monitoring drought using composite drought indices based on remote sensing. Sci Total Environ 711:134585. https://doi.org/10.1016/j.scitotenv.2019.134585
Luo D, Ye L, Sun D (2020) Risk evaluation of agricultural drought disaster using a grey cloud clustering model in Henan Province, China. Int J Disast Risk Reduct 49:101759. https://doi.org/10.1016/j.ijdrr.2020.101759
Merigo J (2011) A unified model between the weighted average and the induced OWA operator. Expert Syst Appl 38(9):11560–11572. https://doi.org/10.1016/j.eswa.2011.03.034
Musei S, Nyaga J, Dubow A (2021) Spei-based spatial and temporal evaluation of drought in Somalia. J Arid Environ 184:104296. https://doi.org/10.1016/j.jaridenv.2020.104296
Nie Y, Tan Y, Deng Y, Yu J (2020) Suitability evaluation of typical drought index in soil moisture retrieval and monitoring based on optical images. Remote Sens Basel 12:2587. https://doi.org/10.3390/rs12162587
Palchaudhuri M, Biswas S (2016) Application of AHP with GIS in drought risk assessment for Puruliya district, India. Nat Hazards 84:1905–1920. https://doi.org/10.1007/s11069-016-2526-3
Qu Y, Lv J, Su Z, Sun H, Ma M (2018) Research review and perspective of drought mitigation. J Hydraul Eng 49:115–125 (in Chinese)
Sahana V, Mondal A, Sreekumar P (2021) Drought vulnerability and risk assessment in India: sensitivity analysis and comparison of aggregation techniques. J Environ Manage 299:113689. https://doi.org/10.1016/j.jenvman.2021.113689
Shandong Bureau of Statistics (2012−2020) Shandong Statistical Yearbook 2013−2021. China Statistics Press, Bei**g (in Chinese)
Shukla S, Wood A (2008) Use of a standardized runoff index for characterizing hydrologic drought. Geophys Res Lett. https://doi.org/10.1029/2007GL032487
Simelton E, Fraser E, Termansen M, Benton T, Gosling S, South A, Arnell N, Challinor A, Dougill A, Forster P (2012) The socioeconomics of food crop production and climate change vulnerability: a global scale quantitative analysis of how grain crops are sensitive to drought. Food Secur 4:163–179. https://doi.org/10.1007/s12571-012-0173-4
Sun R, Gao G, Gong Z, Wu J (2020) A review of risk analysis methods for natural disasters. Nat Hazards 100:571–593. https://doi.org/10.1007/s11069-019-03826-7
The Ministry of Water Resources of the People’s Republic of China (2012‒2020) China Water and Drought Disaster Bulletin. China Cartographic Publishing House, Bei**g (in Chinese)
Vicente-Serrano S, Begueria S, López-Moreno J (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
Wang H, Chen Y, Pan Y, Li W (2015) Spatial and temporal variability of drought in the arid region of China and its relationships to teleconnection indices. J Hydrol 523:283–296. https://doi.org/10.1016/j.jhydrol.2015.01.055
Wang H, Pan Y, Chen Y (2017) Comparison of three drought indices and their evolutionary characteristics in the arid region of northwestern China. Atmos Sci Lett 18:132–139. https://doi.org/10.1002/asl.735
Wang Q, Liu Y, Zhang Y, Tong L, Li X, Li J, Sun Z (2019) Assessment of spatial agglomeration of agricultural drought disaster in China from 1978 to 2016. Sci Rep-Uk 9(1–8):3. https://doi.org/10.1038/s41598-019-51042-x
Xu Y, Li Z, Wang L (2020) Temporal-spatial differences in and influencing factors of agricultural eco-efficiency in Shandong province, China. Cienc Rural. https://doi.org/10.1590/0103-8478cr20190818
Yan H, Wang S, Wang J, Lu H, Guo A, Zhu Z, Myneni R, Shugart H (2016) Assessing spatiotemporal variation of drought in China and its impact on agriculture during 1982–2011 by using PDSI indices and agriculture drought survey data. J Geophys Res Atmos 121:2283–2298. https://doi.org/10.1002/2015JD024285
Yang P, Huang X, Peng L, Zheng Z, Wu X, **ng C (2021) Safety evaluation of major hazard installations based on regional disaster system theory. J Loss Prevent Proc 69:104346. https://doi.org/10.1016/j.jlp.2020.104346
Yang W, Zhang L, Gao Y (2022) Agricultural drought disaster characteristics and return period analysis in three Northeastern provinces. J Arid Land Res Environ 36(10):133–141
Yang W, Zhang L, Yang Z (2023) Spatiotemporal characteristics of droughts and floods in Shandong Province, China and their relationship with food loss. Chin Geogr Sci 33:304–319. https://doi.org/10.1007/s11769-023-1338-0
Yao T, Zhao Q, Li X, Shen Z, Ran P, Wu W (2021) Spatiotemporal variations of multi-scale drought in Shandong Province from 1961 to 2017. Water Supply 21(2):525–541. https://doi.org/10.2166/ws.2020.332
Yevjevich V (1967) Objective approach to definitions and investigations of continental hydrologic droughts, An. Ph.D. thesis. Colorado State University. Libraries.
Yi F, Li C, Feng Y (2018) Two precautions of entropy-weighting model in drought-risk assessment. Nat Hazards 93:339–347. https://doi.org/10.1007/s11069-018-3303-2
Zarei A, Moghimi M, Koohi E (2021) Sensitivity assessment to the occurrence of different types of droughts using GIS and AHP techniques. Water Resour Manag 35:3593–3615. https://doi.org/10.1007/s11269-021-02906-3
Zeng Z, Wu W, Li Z, Zhou Y, Guo Y, Huang H (2019) Agricultural drought risk assessment in southwest China. Water 11:1064. https://doi.org/10.3390/w11051064
Zhang Z, Zhang Y, Sun Z, Zheng J, Liu E, Feng L, Feng C, Si P, Bai W, Cai Q, Yang N, Werf W, Zhang L (2019) Plastic film cover during the fallow season preceding sowing increases yield and water use efficiency of rain-fed spring maize in a semi-arid climate. Agric Water Manage 212:203–210. https://doi.org/10.1016/j.agwat.2018.09.001
Zhang L, Wang Y, Chen Y, Bai Y, Zhang Q (2020a) Drought risk assessment in central Asia using a probabilistic copula function approach. Water 12:421. https://doi.org/10.3390/w12020421
Zhang Q, Yao Y, Li Y, Huang J, Ma Z, Wang Z, Wang S, Wang Y, Zhang Y (2020b) Causes and changes of drought in China: research progress and prospects. J Meteorol Res 34:460–481. https://doi.org/10.1007/s13351-020-9829-8
Zhang L, Liang C, Li T, Yang W (2022) A two-stage EDM method based on KU-CBR with the incomplete linguistic intuitionistic fuzzy preference relations. Comput Ind Eng 172:108552. https://doi.org/10.1016/j.cie.2022.108552
Zhao Y, Yang N, Wei Y, Hu B, Cao Q, Tong K, Liang Y (2019) Eight hundred years of drought and flood disasters and precipitation sequence reconstruction in Wuzhou city, southwest China. Water 11:219. https://doi.org/10.3390/w11020219
Zhou X, Wang P, Tansey K, Zhang S, Li H, Wang L (2020) Develo** a fused vegetation temperature condition index for drought monitoring at field scales using sentinel-2 and Modis imagery. Comput Electron Agric 168:105144. https://doi.org/10.1016/j.compag.2019.105144
Zhu X, Xu K, Liu Y, Guo R, Chen L (2021) Assessing the vulnerability and risk of maize to drought in China based on the Aquacrop model. Agric Syst 189:103040. https://doi.org/10.1016/j.agsy.2020.103040
Zuo D, Cai S, Xu Z, Li F, Sun W, Yang X, Kan G, Liu P (2018) Spatiotemporal patterns of drought at various time scales in Shandong province of eastern China. Theor Appl Climatol 131:271–284. https://doi.org/10.1007/s00704-016-1969-5
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This work was supported by the National Social Science Foundation of China (19CGL045).
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The National Social Science Foundation of China (19CGL045).
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WY contributed to conceptualization, methodology, modeling, and writing-original draft. LZ contributed to funding acquisition, supervision, and writing—review and editing. CL contributed to validation, and writing—review and editing.
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Yang, W., Zhang, L. & Liang, C. Agricultural drought disaster risk assessment in Shandong Province, China. Nat Hazards 118, 1515–1534 (2023). https://doi.org/10.1007/s11069-023-06057-z
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DOI: https://doi.org/10.1007/s11069-023-06057-z