Moving from drought hazard to impact forecasts

oleh: Samuel J. Sutanto, Melati van der Weert, Niko Wanders, Veit Blauhut, Henny A. J. Van Lanen

Format: Article
Diterbitkan: Nature Portfolio 2019-10-01

Deskripsi

There still lacks a forecast system that inform end-users regarding the drought impacts, which will be however important for drought management. Here the authors assess the feasibility of forecasting drought impacts using machine-learning and confirm that models, which were built with sufficient amount of reported drought impacts in a certain sector, are able to forecast drought impacts a few months ahead.