Moving from drought hazard to impact forecasts

Samuel J. Sutanto (), Melati Weert, Niko Wanders, Veit Blauhut and Henny A. J. Lanen
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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

Nature Communications, 2019, vol. 10, issue 1, 1-7

Abstract: 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.

Date: 2019
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DOI: 10.1038/s41467-019-12840-z

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