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Spatio-temporal analysis of drought and return periods over the East African region using Standardized Precipitation Index from 1920 to 2016

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Listed:
  • Kalisa, Wilson
  • Zhang, Jiahua
  • Igbawua, Tertsea
  • Ujoh, Fanan
  • Ebohon, Obas John
  • Namugize, Jean Nepomuscene
  • Yao, Fengmei

Abstract

East African region is susceptible to drought due to high variation in monthly precipitation. Studying drought at regional scale is vital since droughts are considered a ‘creeping’ disaster by nature with devasting and extended impact often requiring long periods to reverse the recorded damages. This study assessed drought exceedance and return years over East Africa from 1920 to 2016 using Climate Research Unit (CRU) precipitation data records. Meteorological drought, where precipitation is the central quantity of interest, was adopted in the work. Standardize Precipitation Index (SPI) was used to study long term meteorological droughts and also to assess drought magnitude, frequency, exceedance probability and return years using Joint Probability Density Function (JPDF). Also, Mann-Kendall trend analysis was applied to precipitation and SPI to investigate the trend changes. Results showed that years with high drought magnitude ranged from 1920−22, 1926−29, 1942−46 and 1947−51 with values corresponding to 2.2, 3.2, 3.4 and 2.6, respectively while years with low drought magnitude ranged from 1930−31, 1988−89 and 2001−02 with values as 0.2, 0.12 and 0.15, respectively. The longest droughts occurred from 1926−29, 1937−41, 1942−46, 1947−51, 1952−56, and 1958−61 with values in years as 3, 4, 4, 4, 4, and 3 years, respectively, while the shortest droughts occurred in time period of 1 year and ranged from 1930−31, 1964−65, 1979−80, 1981−82, 1983−84, 1988−89, 1991−92, 1993−94, 1996−97 and 2001−02. Also, it was demonstrated that probability of drought occurrence is high when severity is low and such droughts occur at short time intervals and not all severest drought took longer periods. The SPI trends indicate high positive (negative) pixels above (below) the zero-trend mark, indicating that drought prevails in both low and high elevation areas up to 2000 m. There was no direct link between ENSO and drought but arguably the association of drought in most El Niño and La Niña years suggests that the impact of ENSO cannot be ruled out since peak ENSO events occur during October to March periods which coincides with the short (SON) and long (MAM) rainy seasons of East Africa. The study is particularly relevant in being able to depict continuous and synoptic drought condition all over East Africa, providing vital information to farmers and policy makers, using very cost-effective method.

Suggested Citation

  • Kalisa, Wilson & Zhang, Jiahua & Igbawua, Tertsea & Ujoh, Fanan & Ebohon, Obas John & Namugize, Jean Nepomuscene & Yao, Fengmei, 2020. "Spatio-temporal analysis of drought and return periods over the East African region using Standardized Precipitation Index from 1920 to 2016," Agricultural Water Management, Elsevier, vol. 237(C).
  • Handle: RePEc:eee:agiwat:v:237:y:2020:i:c:s0378377420301748
    DOI: 10.1016/j.agwat.2020.106195
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    References listed on IDEAS

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    1. Muhammad Athar Haroon & Jiahua Zhang & Fengmei Yao, 2016. "Drought monitoring and performance evaluation of MODIS-based drought severity index (DSI) over 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. 84(2), pages 1349-1366, November.
    2. von Grebmer, Klaus & Bernstein, Jill & Nabarro, David & Prasai, Nilam & Amin, Shazia & Yohannes, Yisehac & Sonntag, Andrea & Patterson, Fraser, 2016. "2016 Global hunger index: Getting to zero hunger," IFPRI books, International Food Policy Research Institute (IFPRI), number 978-0-89629-226-0.
    3. von Grebmer, Klaus & Bernstein, Jill & Nabarro, David & Prasai, Nilam & Amin, Shazia & Yohannes, Yisehac & Sonntag, Andrea & Patterson, Fraser, 2016. "Synopsis: 2016 Global hunger index: Getting to zero hunger," IFPRI synopses 978-0-89629-228-4, International Food Policy Research Institute (IFPRI).
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    Cited by:

    1. Samantaray, Alok Kumar & Ramadas, Meenu & Panda, Rabindra Kumar, 2022. "Changes in drought characteristics based on rainfall pattern drought index and the CMIP6 multi-model ensemble," Agricultural Water Management, Elsevier, vol. 266(C).
    2. Veysel Gumus & Oguz Simsek & Yavuz Avsaroglu & Berivan Agun, 2021. "Spatio‐temporal trend analysis of drought in the GAP Region, 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. 109(2), pages 1759-1776, November.
    3. Wilson Kalisa & Tertsea Igbawua & Fanan Ujoh & Igbalumun S. Aondoakaa & Jean Nepomuscene Namugize & Jiahua Zhang, 2021. "Spatio-temporal variability of dry and wet conditions over East Africa from 1982 to 2015 using quantile regression model," 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. 106(3), pages 2047-2076, April.
    4. Cai, Siyang & Zuo, Depeng & Wang, Huixiao & Xu, Zongxue & Wang, GuoQing & Yang, Hong, 2023. "Assessment of agricultural drought based on multi-source remote sensing data in a major grain producing area of Northwest China," Agricultural Water Management, Elsevier, vol. 278(C).
    5. Li, Yifei & Huang, Shengzhi & Wang, Hanye & Zheng, Xudong & Huang, Qiang & Deng, Mingjiang & Peng, Jian, 2022. "High-resolution propagation time from meteorological to agricultural drought at multiple levels and spatiotemporal scales," Agricultural Water Management, Elsevier, vol. 262(C).
    6. da Silva, Antonio Samuel Alves & Stosic, Tatijana & Arsenić, Ilija & Menezes, Rômulo Simões Cezar & Stosic, Borko, 2023. "Multifractal analysis of standardized precipitation index in Northeast Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    7. Junju Zhou & Haitao Tang & Yu Qiu & Zhaonan Guo & Chuyu Luo & Xue Wang & Wei Shi & Dongxia Zhang & Chunli Wang & Xuemei Yang & Chunfang Liu & Wei Wei, 2023. "Spatio-Temporal Changes and Influencing Factors of Meteorological Dry-Wet in Northern China during 1960–2019," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    8. Cao, Meng & Chen, Min & Liu, Ji & Liu, Yanli, 2022. "Assessing the performance of satellite soil moisture on agricultural drought monitoring in the North China Plain," Agricultural Water Management, Elsevier, vol. 263(C).

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