Articles | Volume 20, issue 6
Nat. Hazards Earth Syst. Sci., 20, 1595–1608, 2020
https://doi.org/10.5194/nhess-20-1595-2020

Special issue: Recent advances in drought and water scarcity monitoring,...

Nat. Hazards Earth Syst. Sci., 20, 1595–1608, 2020
https://doi.org/10.5194/nhess-20-1595-2020

Research article 04 Jun 2020

Research article | 04 Jun 2020

Skill of large-scale seasonal drought impact forecasts

Samuel J. Sutanto et al.

Data sets

Supporting data for 'Skill of large-scale seasonal drought impact forecasts' S. J. Sutanto and M. van der Weert https://doi.org/10.4121/uuid:4c6f7f0f-e402-4b6c-a2a2-711bcd224e1f

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Short summary
Present-day drought early warning systems only provide information on drought hazard forecasts. Here, we have developed drought impact functions to forecast drought impacts up to 7 months ahead using machine learning techniques, logistic regression, and random forest. Our results show that random forest produces a higher-impact forecasting skill than logistic regression. For German county levels, drought impacts can be forecasted up to 4 months ahead using random forest.
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