Agricultural drought risk assessment in Southern Plateau and Hills using multi threshold run theory

被引:4
|
作者
Palagiri, Hussain [1 ]
Pal, Manali [1 ]
机构
[1] NIT Warangal, Dept Civil Engn, Warangal 506004, India
关键词
Agricultural drought; ESACCI SM; Standardised Soil Moisture Index (SSMI); Standardised Precipitation Evapotranspiration; Run Theory; RIVER; INDIA; CHINA;
D O I
10.1016/j.rineng.2024.102022
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Agricultural drought in this study is characterized and assessed using the Standardized Soil Moisture Index (SSMI). Employing run theory with three thresholds, SSMI identifies grid-wise drought events, quantifying them in terms of peak, frequency, duration and intensity. To evaluate SSMI's performance in assessing drought risk, a comparison is made with the Standardized Precipitation Evapotranspiration Index (SPEI). Spatially, frequency aligns with duration for both indices, indicating regions with longer drought events also experience more frequent occurrences. Meteorological droughts in SPH from 1991 to 2020 are found to be more intense, frequent, longer-lasting, but less severe. Spatially heterogeneous drought events are identified by both indices, with SSMI proving a reliable indicator of drought risk, similar to SPEI. Archimedean copula functions reveal high joint occurrences of various drought characteristics, suggesting significant correlations. The results show that the joint occurrences of duration and peak, intensity and frequency, and duration and peak are all high. This insight is crucial for enhancing drought risk management and developing more effective warning systems.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] An operational agricultural drought risk assessment model for Nebraska, USA
    Wu, H
    Wilhite, DA
    NATURAL HAZARDS, 2004, 33 (01) : 1 - 21
  • [22] Drought monitoring and agricultural drought loss risk assessment based on multisource information fusion
    Manman Zhang
    Dang Luo
    Yongqiang Su
    Natural Hazards, 2022, 111 : 775 - 801
  • [23] Drought monitoring and agricultural drought loss risk assessment based on multisource information fusion
    Zhang, Manman
    Luo, Dang
    Su, Yongqiang
    NATURAL HAZARDS, 2022, 111 (01) : 775 - 801
  • [24] Dynamic agricultural drought risk assessment for maize using weather generator and APSIM crop models
    Yaxu Wang
    Juan Lv
    Hongquan Sun
    Huiqiang Zuo
    Hui Gao
    Yanping Qu
    Zhicheng Su
    Xiaojing Yang
    Jianming Yin
    Natural Hazards, 2022, 114 : 3083 - 3100
  • [25] Dynamic agricultural drought risk assessment for maize using weather generator and APSIM crop models
    Wang, Yaxu
    Lv, Juan
    Sun, Hongquan
    Zuo, Huiqiang
    Gao, Hui
    Qu, Yanping
    Su, Zhicheng
    Yang, Xiaojing
    Yin, Jianming
    NATURAL HAZARDS, 2022, 114 (03) : 3083 - 3100
  • [26] Agricultural drought risk assessment of Northern New South Wales, Australia using geospatial techniques
    Hoque, Muhammad Al-Amin
    Pradhan, Biswajeet
    Ahmed, Naser
    Sohel, Md Shawkat Islam
    SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 756 (756)
  • [27] Drought risk assessment and prediction using artificial intelligence over the southern Maharashtra state of India
    Singh, T. P.
    Nandimath, Pooja
    Kumbhar, Vidya
    Das, Sandipan
    Barne, Prathamesh
    MODELING EARTH SYSTEMS AND ENVIRONMENT, 2021, 7 (03) : 2005 - 2013
  • [28] Drought risk assessment and prediction using artificial intelligence over the southern Maharashtra state of India
    T. P. Singh
    Pooja Nandimath
    Vidya Kumbhar
    Sandipan Das
    Prathamesh Barne
    Modeling Earth Systems and Environment, 2021, 7 : 2005 - 2013
  • [29] Flood and drought risk assessment for agricultural areas (Tagus Estuary, Portugal)
    Freire, Paula
    Rodrigues, Marta
    Fortunato, Andre B.
    Freitas, Alberto
    NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2021, 21 (08) : 2503 - 2521
  • [30] Assessment on Agricultural Drought Risk Based on Variable Fuzzy Sets Model
    ZHANG Dan WANG Guoli ZHOU Huicheng Faculty of Infrastructure Engineering Dalian University of Technology Dalian China Water Conservancy and Hydropower Science Research Institute of Liaoning Province Shenyang China
    Chinese Geographical Science, 2011, (02) : 167 - 175