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Moving from drought hazard to impact forecasts

Author

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  • Samuel J. Sutanto

    (Wageningen University and Research)

  • Melati Weert

    (Wageningen University and Research)

  • Niko Wanders

    (Utrecht University)

  • Veit Blauhut

    (University of Freiburg)

  • Henny A. J. Lanen

    (Wageningen University and Research)

Abstract

Present-day drought early warning systems provide the end-users information on the ongoing and forecasted drought hazard (e.g. river flow deficit). However, information on the forecasted drought impacts, which is a prerequisite for drought management, is still missing. Here we present the first study assessing the feasibility of forecasting drought impacts, using machine-learning to relate forecasted hydro-meteorological drought indices to reported drought impacts. Results show that models, which were built with more than 50 months of reported drought impacts, are able to forecast drought impacts a few months ahead. This study highlights the importance of drought impact databases for developing drought impact functions. Our findings recommend that institutions that provide operational drought early warnings should not only forecast drought hazard, but also impacts after developing an impact database.

Suggested Citation

  • Samuel J. Sutanto & Melati Weert & Niko Wanders & Veit Blauhut & Henny A. J. Lanen, 2019. "Moving from drought hazard to impact forecasts," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-12840-z
    DOI: 10.1038/s41467-019-12840-z
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    Cited by:

    1. Tsun-Hua Yang & Wen-Cheng Liu, 2020. "A General Overview of the Risk-Reduction Strategies for Floods and Droughts," Sustainability, MDPI, vol. 12(7), pages 1-20, March.

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