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The Maturation of AI in Drought Science: A Review of Trends, Pitfalls, and Priorities

Abstract Machine learning (ML) has emerged as a key tool in drought research, with applications growing rapidly over the past 20 years. While several reviews have described specific ML methods and their use in forecasting and monitoring, a comprehensive assessment of trends, gaps, and emerging chall...

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Kaydedildi:
Asıl Yazarlar: Guido Ascenso, Matteo Giuliani, Jorge Pérez‐Aracil, Sancho Salcedo‐Sanz, Claudia Bertini, Paolo Bonetti, Gustau Camps‐Valls, Miguel Ángel Fernández Torres, Andrea Ficchì, Nora Linscheid, Martina Merlo, Giulio Palcic, Markus Reichstein, Marcello Restelli, Andrea Toreti, Eliot Walt, Andrea Castelletti
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: Wiley 2026-04-01
Seri Bilgileri:Water Resources Research
Konular:
machine learning
drought
explainable AI
reproducibility
trends
Online Erişim:https://doi.org/10.1029/2025WR041828
Etiketler: Etiketle
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