Dynamic assessment and prediction of potato disaster loss risk in Gansu Province, China

被引:0
|
作者
Fang, Feng [1 ]
Wang, Jing [2 ]
Jia, Jianying [1 ]
Yin, Fei [1 ]
Huang, Pengcheng [1 ]
Wang, Dawei [1 ]
机构
[1] Lanzhou Reg Climate Ctr, Lanzhou 730020, Peoples R China
[2] Lanzhou Inst Arid Meteorol, Lanzhou 730020, Peoples R China
基金
中国国家自然科学基金;
关键词
Potato; Meteorological disaster loss; Dynamic risk assessment; Risk prediction; Interpolation-EMD-SVM; MULTIOBJECTIVE OPTIMIZATION; EVOLUTION; STRATEGY; SAMPLE;
D O I
10.1016/j.ecolind.2024.112626
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Meteorological disasters occur frequently, and Gansu Province is a sensitive area for food production. Potatoes are a major crop in this province. As a result, executing risk zoning and risk prediction for potato production is quite important. However, in existing risk assessment and prediction research, the dynamic nature of risks and improving the accuracy of risk prediction are urgent scientific issues that must be addressed. Weighting, spatial econometric analysis, climate diagnosis technology, and machine learning models were used to provide a refined spatiotemporal evolution of potato disaster risk in China's Gansu Province, as well as predict future potato production risk. The findings indicate that there are significant interdecadal fluctuations in the potato disaster loss, which has decreased considerably since 2000. The average yield decrease rate in the 1980s, 1990s, 2000s, and 2010s was -13.9%, -15.4%, -9.1%, and -7.3%, respectively, and the county percentage susceptible to severe yield loss was 26.1%, 39.1%, 22.9%, and 12.9%. Second, most counties' potato production falls within the medium-low or low risk region. Eastern and southern Gansu are particularly vulnerable to catastrophic calamities. High risk counties are primarily clustered in Qingyang and Longnan, whereas low risk counties are concentrated in Wuwei and Gannan. Third, high risk locations have altered, and the migration trajectory of the risk indicator's barycenter shows significant differences in direction and distance. The comprehensive risk moves in a southeast-west-northern direction, but the distance is short. Overall, disaster losses in most counties are decreasing, and future trends will be similar with previous patterns. The Interpolation-EMD-SVM scheme greatly increases the accuracy of the disaster loss risk prediction. The technology and methods provide a scientific foundation for accurately assessing risk dynamic characteristics, managing regional disaster risks, and preventing and mitigating disasters.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] Seismic Hazard Assessment for the Tianshui Urban Area, Gansu Province, China
    Wang, Zhenming
    Butler, David T., III
    Woolery, Edward W.
    Wang, Lanmin
    INTERNATIONAL JOURNAL OF GEOPHYSICS, 2012, 2012
  • [32] Epidemiological investigation of hyperuricemia and analysis of risk factors in the Gansu province of China
    Liu, Jia
    Liu, Jing
    Quan, Jin-Xin
    Tian, Limin
    Zhang, Qi
    DIABETES-METABOLISM RESEARCH AND REVIEWS, 2014, 30 : 23 - 24
  • [33] Statistical landslide susceptibility assessment in a dynamic environment: A case study for Lanzhou City, Gansu Province, NW China
    Torizin, Jewgenij
    Wang, Li-chao
    Fuchs, Michael
    Tong, Bin
    Balzer, Dirk
    Wan, Li-qin
    Kuhn, Dirk
    Li, Ang
    Chen, Liang
    JOURNAL OF MOUNTAIN SCIENCE, 2018, 15 (06) : 1299 - 1318
  • [34] Epidemiological investigation of obesity and analysis of risk factors in Gansu province, China
    Liu, Jia
    Zhang, Qi
    Liu, Juxiang
    Quan, Jinxin
    Liu, Jing
    DIABETES-METABOLISM RESEARCH AND REVIEWS, 2015, 31 : 72 - 73
  • [35] Statistical landslide susceptibility assessment in a dynamic environment: A case study for Lanzhou City, Gansu Province, NW China
    TORIZIN Jewgenij
    WANG Li-chao
    FUCHS Michael
    TONG Bin
    BALZER Dirk
    WAN Li-qin
    KUHN Dirk
    LI Ang
    CHEN Liang
    JournalofMountainScience, 2018, 15 (06) : 1299 - 1318
  • [36] Statistical landslide susceptibility assessment in a dynamic environment: A case study for Lanzhou City, Gansu Province, NW China
    Jewgenij Torizin
    Li-chao Wang
    Michael Fuchs
    Bin Tong
    Dirk Balzer
    Li-qin Wan
    Dirk Kuhn
    Ang Li
    Liang Chen
    Journal of Mountain Science, 2018, 15 : 1299 - 1318
  • [37] Previous pulmonary diseases and risk of lung cancer in Gansu Province, China
    Brenner, AV
    Wang, ZY
    Kleinerman, RA
    Wang, LD
    Zhang, SZ
    Metayer, C
    Chen, K
    Lei, SW
    Cui, HX
    Lubin, JH
    INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2001, 30 (01) : 118 - 124
  • [38] Health and Economic Loss Assessment of PM2.5 Pollution during 2015-2017 in Gansu Province, China
    Liao, Qin
    Jin, Wangqiang
    Tao, Yan
    Qu, Jiansheng
    Li, Yong
    Niu, Yibo
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2020, 17 (09)
  • [39] Simulation of the stability and dynamic characteristics of Nanshan landslide in Zhouqu of Gansu province, China
    Wang, Xiongshi
    Liu, Dongfei
    Tian, Liming
    Ma, Jinzhu
    ADVANCES IN ENERGY SCIENCE AND EQUIPMENT ENGINEERING, 2015, : 741 - 746
  • [40] Risk Assessment and Control for Geohazards at Multiple Scales: An Insight from the West Han River of Gansu Province in China
    Ye, Zhennan
    Tian, Yuntao
    Li, Hao
    Shao, Changqing
    Gao, Youlong
    Wang, Gaofeng
    WATER, 2024, 16 (13)