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Evaluating the standardized and threshold based drought indices for historical drought detection in the Great Ruaha River Basin, Tanzania

Author

Listed:
  • Erasto Benedict Mukama

    (Vrije Universiteit Brussel
    Sokoine University of Agriculture)

  • Estifanos Addisu Yimer

    (Vrije Universiteit Brussel)

  • Winfred Baptist Mbungu

    (Sokoine University of Agriculture)

  • Stefaan Dondeyne

    (Vrije Universiteit Brussel
    Ghent University
    University de Liège)

  • Ann Griensven

    (Vrije Universiteit Brussel
    IHE Delft Institute for Water Education)

Abstract

Drought poses significant threats to humans and ecosystems, underscoring the need for robust and efficient monitoring systems for informed decision making and adaptive management. This study assessed the effectiveness of five indices in detecting historical droughts and low-flow periods in the upper and lower sub-basins of the Great Ruaha River Basin, Tanzania using hydrometeorological data (1981–2022). Historical droughts were obtained from government reports and scientific literature. The indices included the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Precipitation Actual Evapotranspiration Index (SPAEI), Standardized Streamflow Index (SSI) and Water Scarcity Index (WSI). The standardized indices were calculated using basin monthly precipitation, evapotranspiration and discharge data at 3-, 6-, and 12-month timescales while the WSI was used to define low-flows based on a threshold of 0.001 m3/s, computed from the 10th percentile of daily discharge data. Drought characteristics were investigated using the run theory approach. The SPI captured 70–90% of historical droughts, SPEI identified 80–90%, SPAEI detected 50–60%, while SSI, and WSI each identified 80%. The SPI, SPEI and SSI classified majority of these events as severe while SPAEI identified them as moderate. The WSI was the most effective in detecting low flows, whereas all the standardized indices performed poorly. Between 1981 and 1989, discharge never fell below 0.001 m3/s. However, from 1990, lower discharges occurred almost every year, indicating a major shift in the hydrological system. Based on our research findings, we recommend using the SPI, SPEI, SSI and WSI for drought monitoring and more specific, the WSI for low flow analysis. Therefore, by using appropriate drought indices, water managers can achieve sustainable management of droughts and water resources in the basin.

Suggested Citation

  • Erasto Benedict Mukama & Estifanos Addisu Yimer & Winfred Baptist Mbungu & Stefaan Dondeyne & Ann Griensven, 2025. "Evaluating the standardized and threshold based drought indices for historical drought detection in the Great Ruaha River Basin, Tanzania," 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. 121(10), pages 12243-12273, June.
    • Handle: RePEc:spr:nathaz:v:121:y:2025:i:10:d:10.1007_s11069-025-07279-z
    DOI: 10.1007/s11069-025-07279-z
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    1. Dong-Dong Zhang & Deng-Hua Yan & Fan Lu & Yi-Cheng Wang & Jing Feng, 2015. "Copula-based risk assessment of drought in Yunnan 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. 75(3), pages 2199-2220, February.
    2. England, Matthew I., 2019. "Contested waterscapes: Irrigation and hydropower in the Great Ruaha River Basin, Tanzania," Agricultural Water Management, Elsevier, vol. 213(C), pages 1084-1095.
    3. Pan, Ying & Zhu, Yonghua & Lü, Haishen & Yagci, Ali Levent & Fu, Xiaolei & Liu, En & Xu, Haiting & Ding, Zhenzhou & Liu, Ruoyu, 2023. "Accuracy of agricultural drought indices and analysis of agricultural drought characteristics in China between 2000 and 2019," Agricultural Water Management, Elsevier, vol. 283(C).
    4. Soumyashree Dixit & K. V. Jayakumar, 2022. "A Non-stationary and Probabilistic Approach for Drought Characterization Using Trivariate and Pairwise Copula Construction (PCC) Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1217-1236, March.
    5. Javad Bazrafshan & Majid Cheraghalizadeh & Kokab Shahgholian, 2022. "Development of a Non-stationary Standardized Precipitation Evapotranspiration Index (NSPEI) for Drought Monitoring in a Changing Climate," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(10), pages 3523-3543, August.
    6. Kristian Näschen & Bernd Diekkrüger & Mariele Evers & Britta Höllermann & Stefanie Steinbach & Frank Thonfeld, 2019. "The Impact of Land Use/Land Cover Change (LULCC) on Water Resources in a Tropical Catchment in Tanzania under Different Climate Change Scenarios," Sustainability, MDPI, vol. 11(24), pages 1-28, December.
    7. Yang, Beibei & Cui, Qian & Meng, Yizhuo & Zhang, Zhen & Hong, Zhiming & Hu, Fengmin & Li, Junjie & Tao, Chongxin & Wang, Zhe & Zhang, Wen, 2023. "Combined multivariate drought index for drought assessment in China from 2003 to 2020," Agricultural Water Management, Elsevier, vol. 281(C).
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