IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i4p3786-d1073414.html
   My bibliography  Save this article

A New Agricultural Drought Disaster Risk Assessment Framework: Coupled a Copula Function to Select Return Periods and the Jensen Model to Calculate Yield Loss

Author

Listed:
  • Hongjun Lei

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Jie Yu

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Hongwei Pan

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Jie Li

    (China Machinery Industry International Cooperation Co., Ltd., Zhengzhou 450018, China)

  • Shah Jahan Leghari

    (College of Land Science and Technology, China Agricultural University, Beijing 100193, China)

  • Chongju Shang

    (Guizhou Water Conservancy Research Institute, Guiyang 550002, China)

  • Zheyuan Xiao

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Cuicui Jin

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Lili Shi

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

Abstract

China is one of the regions with the most frequent drought disasters and serious social and economic losses. Agricultural drought is the most serious natural disaster. Due to climate change, the regional agricultural drought risk assessment has always been the focus of the academic circle. This study takes Zunyi City as an example, which is the most typical city of karst landform development. The monthly precipitation data set of ground meteorological observation stations in Zunyi City from 1956 to 2020 was selected, and the drought characteristic variables were extracted by the coupled use of the precipitation anomaly percentage ( Pa ) index and the theory of runs. A copula function was applied to establish the joint distribution model of characteristic variables, obtaining the drought frequency and drought return periods. Combined with the Jensen model, the agricultural drought loss rate under different drought return periods in the target year (2020) was calculated and evaluated. The results showed that the Gumbel-Hougaard copula function was suitable for the joint distribution of drought joint variables in Zunyi City. From 1956 to 2020, fewer droughts occurred in Zhengan and Wuchuan, and the most droughts took place in Fenggang, Meitan, and Yuqing. The average drought duration in each county was about 1.5 months, and the average drought severity was about 0.35 in spatial distribution. Crop loss rate caused by drought increased and the affected area expanded with the increase of drought return periods (5, 10, 20, 50, and 100 years) in temporal distribution. Meanwhile, the drought disaster was most drastic in the eastern region, followed by the south, north, west, and central area. The results were highly consistent with the historical drought in Zunyi City, which verified the validity of the model. This study could provide scientific knowledge for drought resistance and reasonable mitigation programing for the security of the regional agricultural production and the sustainability of social and economic development.

Suggested Citation

  • Hongjun Lei & Jie Yu & Hongwei Pan & Jie Li & Shah Jahan Leghari & Chongju Shang & Zheyuan Xiao & Cuicui Jin & Lili Shi, 2023. "A New Agricultural Drought Disaster Risk Assessment Framework: Coupled a Copula Function to Select Return Periods and the Jensen Model to Calculate Yield Loss," Sustainability, MDPI, vol. 15(4), pages 1-16, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3786-:d:1073414
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/4/3786/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/4/3786/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Schmitt, Jonas & Offermann, Frank & Söder, Mareike & Frühauf, Cathleen & Finger, Robert, 2022. "Extreme weather events cause significant crop yield losses at the farm level in German agriculture," Food Policy, Elsevier, vol. 112(C).
    2. Rina Wu & Jiquan Zhang & Yuhai Bao & Enliang Guo, 2019. "Run Theory and Copula-Based Drought Risk Analysis for Songnen Grassland in Northeastern China," Sustainability, MDPI, vol. 11(21), pages 1-17, October.
    3. Nakabuye, Hope Njuki & Rudnick, Daran & DeJonge, Kendall C. & Lo, Tsz Him & Heeren, Derek & Qiao, Xin & Franz, Trenton E. & Katimbo, Abia & Duan, Jiaming, 2022. "Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment," Agricultural Water Management, Elsevier, vol. 274(C).
    4. Xiaojing Liu & Jiquan Zhang & Donglai Ma & Yulong Bao & Zhijun Tong & Xingpeng Liu, 2013. "Dynamic risk assessment of drought disaster for maize based on integrating multi-sources data in the region of the northwest of Liaoning Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(3), pages 1393-1409, February.
    5. Poulomi Ganguli & M. Reddy, 2012. "Risk Assessment of Droughts in Gujarat Using Bivariate Copulas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(11), pages 3301-3327, September.
    6. Jinyu Zhang & Kang Gao & Yong Li & Qiaosen Zhang, 2022. "Maximum Likelihood Estimation Methods for Copula Models," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 99-124, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaodi Fu & Xiaoyan He & Liuqian Ding, 2023. "Stochastic Flood Simulation Method Combining Flood Intensity and Morphological Indicators," Sustainability, MDPI, vol. 15(18), pages 1-25, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ziqiang Xing & Denghua Yan & Cheng Zhang & Gang Wang & Dongdong Zhang, 2015. "Spatial Characterization and Bivariate Frequency Analysis of Precipitation and Runoff in the Upper Huai River Basin, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3291-3304, July.
    2. Mansoor Ahmed & Ghulam Hussain Dars & Suhail Ahmed & Nir Y. Krakauer, 2023. "Analyzing drought trends over Sindh Province, Pakistan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 119(1), pages 643-661, October.
    3. Fatih Tosunoglu & Ibrahim Can, 2016. "Application of copulas for regional bivariate frequency analysis of meteorological droughts in Turkey," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(3), pages 1457-1477, July.
    4. Qiu, Lei & Wang, Xiaoyang & Wei, Jia, 2023. "Energy security and energy management: The role of extreme natural events," Innovation and Green Development, Elsevier, vol. 2(2).
    5. D. Chiru Naik & Sagar Rohidas Chavan & P. Sonali, 2023. "Incorporating the climate oscillations in the computation of meteorological drought over India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(3), pages 2617-2646, July.
    6. Wittwer, Raphaël A. & Klaus, Valentin H. & Miranda Oliveira, Emily & Sun, Qing & Liu, Yujie & Gilgen, Anna K. & Buchmann, Nina & van der Heijden, Marcel G.A., 2023. "Limited capability of organic farming and conservation tillage to enhance agroecosystem resilience to severe drought," Agricultural Systems, Elsevier, vol. 211(C).
    7. Rina Wu & Jiquan Zhang & Yuhai Bao & Enliang Guo, 2019. "Run Theory and Copula-Based Drought Risk Analysis for Songnen Grassland in Northeastern China," Sustainability, MDPI, vol. 11(21), pages 1-17, October.
    8. Zahra Fahimirad & Nazanin Shahkarami, 2021. "The Impact of Climate Change on Hydro-Meteorological Droughts Using Copula Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 3969-3993, September.
    9. Wencun Zhou & Zhengjia Liu & Sisi Wang, 2023. "Spatiotemporal Dynamics of the Cropland Area and Its Response to Increasing Regional Extreme Weather Events in the Farming-Pastoral Ecotone of Northern China during 1992–2020," Sustainability, MDPI, vol. 15(18), pages 1-28, September.
    10. Riao, Dao & Guga, Suri & Bao, Yongbin & Liu, Xingping & Tong, Zhijun & Zhang, Jiquan, 2023. "Non-overlap of suitable areas of agro-climatic resources and main planting areas is the main reason for potato drought disaster in Inner Mongolia, China," Agricultural Water Management, Elsevier, vol. 275(C).
    11. Huicong Jia & Donghua Pan & Jing-ai Wang & Wan-chang Zhang, 2016. "Risk mapping of integrated natural disasters in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(3), pages 2023-2035, February.
    12. Huili Chen & Zhongyao Liang & Yong Liu & Qingsong Jiang & Shuguang Xie, 2018. "Effects of drought and flood on crop production in China across 1949–2015: spatial heterogeneity analysis with Bayesian hierarchical modeling," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(1), pages 525-541, May.
    13. Yu Xiaobing & Li Chenliang & Huo Tongzhao & Ji Zhonghui, 2021. "Information diffusion theory-based approach for the risk assessment of meteorological disasters in the Yangtze River Basin," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(3), pages 2337-2362, July.
    14. Robert Finger, 2023. "Digital innovations for sustainable and resilient agricultural systems," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(4), pages 1277-1309.
    15. Feng, Xudong & Bi, Shaojie & Li, Hongjun & Qi, Yongqing & Chen, Suying & Shao, Liwei, 2024. "Soil moisture forecasting for precision irrigation management using real-time electricity consumption records," Agricultural Water Management, Elsevier, vol. 291(C).
    16. Junfei Chen & Menghua Deng & Lu Xia & Huimin Wang, 2017. "Risk Assessment of Drought, Based on IDM-VFS in the Nanpan River Basin, Yunnan Province, China," Sustainability, MDPI, vol. 9(7), pages 1-16, June.
    17. Piyush Dahal & Nicky Shree Shrestha & Madan Lall Shrestha & Nir Y. Krakauer & Jeeban Panthi & Soni M. Pradhanang & Ajay Jha & Tarendra Lakhankar, 2016. "Drought risk assessment in central Nepal: temporal and spatial analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(3), pages 1913-1932, February.
    18. L. Vergni & F. Todisco & F. Mannocchi, 2015. "Analysis of agricultural drought characteristics through a two-dimensional copula," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2819-2835, June.
    19. Dai, Meng & Huang, Shengzhi & Huang, Qiang & Leng, Guoyong & Guo, Yi & Wang, Lu & Fang, Wei & Li, Pei & Zheng, Xudong, 2020. "Assessing agricultural drought risk and its dynamic evolution characteristics," Agricultural Water Management, Elsevier, vol. 231(C).
    20. Löw, Philipp & Osterburg, Bernhard, 2024. "Evaluation of nitrogen balances and nitrogen use efficiencies on farm level of the German agricultural sector," Agricultural Systems, Elsevier, vol. 213(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3786-:d:1073414. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.