Characterizing agricultural drought in the Karamoja subregion of Uganda with meteorological and satellite-based indices

被引:0
|
作者
Catherine Nakalembe
机构
[1] University of Maryland,Department of Geographical Sciences
来源
Natural Hazards | 2018年 / 91卷
关键词
Agricultural drought; NDVI; SPI; Remote sensing; Karamoja; East Africa;
D O I
暂无
中图分类号
学科分类号
摘要
Karamoja is notoriously food insecure and has been in need of food aid for most years during the last two decades. One of the main factors causing food insecurity is drought. Reliable, area-wide, long-term data for detecting and monitoring drought conditions are critical for timely, life-saving interventions and the long-term development of the region, yet such data are sparse or unavailable. Due to advances in satellite remote sensing, characterizing drought in data-sparse regions like Karamoja has become possible. This study characterizes agricultural drought in Karamoja to enable a comprehensive understanding of drought, concomitantly evaluating the suitability of NDVI-based drought monitoring. We found that in comparison with the existing data, NDVI data currently provide the best, consistent, and spatially explicit information for operational drought monitoring in Karamoja. Results indicate that the most extreme agricultural drought in recent years occurred in 2009 followed by 2004 and 2002 and suggest that in Karamoja, moderate to severe droughts (e.g., 2008) often have the same impact on crops and human needs (e.g., food aid) as extreme droughts (e.g., 2009). We present in a proof-of-concept frame, a method to estimate the number of people needing food assistance and the population likely to fall under the integrated food security phase classification (IPC) Phase 3 (crisis) due to drought severity. Our model indicates that 90.7% of the variation in the number of people needing aid can be explained by NDVI data and NDVI data can augment these estimates. We conclude that the biggest drivers of food insecurity are the cultivation of crops on marginal land with insignificant inputs, the lack of irrigation and previous systematic incapacitation of livestock (pastoral) alternatives through government programming. Further research is needed to bridge empirical results with social–economic studies on drought impacts on communities in the region to better understand additional factors that will need to be addressed to ensure livelihood resilience.
引用
收藏
页码:837 / 862
页数:25
相关论文
共 50 条
  • [31] Applicability of long-term satellite-based precipitation products for drought indices considering global warming
    Bai, Xiaoyan
    Shen, Wen
    Wu, Xiaoqing
    Wang, Peng
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2020, 255 (255)
  • [32] Assessing Meteorological and Agricultural Drought in Chitral Kabul River Basin Using Multiple Drought Indices
    Baig, Muhammad Hasan Ali
    Abid, Muhammad
    Khan, Muhammad Roman
    Jiao, Wenzhe
    Amin, Muhammad
    Adnan, Shahzada
    REMOTE SENSING, 2020, 12 (09)
  • [33] Yield prediction models for some wheat varieties with satellite-based drought indices and machine learning algorithms
    Akcapinar, Muhammed Cem
    Cakmak, Belgin
    IRRIGATION AND DRAINAGE, 2025, 74 (01) : 237 - 250
  • [34] Monitoring the Spring 2021 Drought Event in Taiwan Using Multiple Satellite-Based Vegetation and Water Indices
    Chou, Chien-Ben
    Weng, Min-Chuan
    Huang, Huei-Ping
    Chang, Yu-Cheng
    Chang, Ho-Chin
    Yeh, Tzu-Ying
    ATMOSPHERE, 2022, 13 (09)
  • [35] Satellite-based vegetation health indices as a criteria for insuring against drought-related yield losses
    Bokusheva, R.
    Kogan, F.
    Vitkovskaya, I.
    Conradt, S.
    Batyrbayeva, M.
    AGRICULTURAL AND FOREST METEOROLOGY, 2016, 220 : 200 - 206
  • [36] Machine learning algorithms for merging satellite-based precipitation products and their application on meteorological drought monitoring over Kenya
    Ghosh, Suravi
    Lu, Jianzhong
    Das, Priyanko
    Zhang, Zhenke
    CLIMATE DYNAMICS, 2024, 62 (01) : 141 - 163
  • [37] Modeling drought impact occurrence based on meteorological drought indices in Europe
    Stagge, James H.
    Kohn, Irene
    Tallaksen, Lena M.
    Stahl, Kerstin
    JOURNAL OF HYDROLOGY, 2015, 530 : 37 - 50
  • [38] Meteorological Drought Analysis in the Lower Mekong Basin Using Satellite-Based Long-Term CHIRPS Product
    Guo, Hao
    Bao, Anming
    Liu, Tie
    Ndayisaba, Felix
    He, Daming
    Kurban, Alishir
    De Maeyer, Philippe
    SUSTAINABILITY, 2017, 9 (06)
  • [39] SATELLITE-BASED DROUGHT MONITORING IN KENYA IN AN OPERATIONAL SETTING
    Klisch, A.
    Atzberger, C.
    Luminari, L.
    36TH INTERNATIONAL SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT, 2015, 47 (W3): : 433 - 439
  • [40] Machine learning algorithms for merging satellite-based precipitation products and their application on meteorological drought monitoring over Kenya
    Suravi Ghosh
    Jianzhong Lu
    Priyanko Das
    Zhenke Zhang
    Climate Dynamics, 2024, 62 : 141 - 163