A Paradigm Shift in Drought Forecasting: First Application of Bayesian Concept Drift-Enhanced Hidden Markov Models for Probabilistic Climate Risk Mapping in Northwestern Algeria

Authors

DOI:

https://doi.org/10.36253/ijam-3944

Keywords:

climate change, Hidden Markov Model, Non-Stationarity, Bayesian Concept Drift, Agrometeorology,, Algeria

Abstract

Northwestern Algeria, a vital agricultural region within the Mediterranean climate hotspot, faces escalating risks due to climatic variability and recurrent droughts. Conventional linear methods are inadequate for capturing the complex, non-stationary dynamics of this semi-arid system. This study introduces an innovative framework integrating a Non-Stationary Hidden Markov Model (NSHMM), Bayesian Concept Drift detection, and CUSUM changepoint analysis. Analyzing 35 years (1990-2024) of daily meteorological data, we identified four distinct climate regimes. Results reveal profound non-stationarity: the frequency of the extreme 'Hot & Very Dry' regime increased by 45% since the 1990s, while its persistence rose by 14%. The Bayesian analysis quantifies three major structural drifts with scores reaching 0.80, indicating abrupt climate reorganization. These findings are corroborated by 113 changepoints and a significant teleconnection with the North Atlantic Oscillation (r = 0.58, p < 0.01). Critically, these shifts remain undetected by conventional trend analysis (Mann-Kendall p = 0.16), underscoring the necessity of non-stationary methodologies. The operationalization into a Probabilistic Drought Early Warning System enables risk forecasts with probabilities up to 90%. This work demonstrates that climate change in the region manifests not as gradual warming but as fundamental reorganization of the climate system. 

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Published

2026-06-04

How to Cite

Kaci, M., Martínez-Ruiz, E., & O’Connel, J. T. (2026). A Paradigm Shift in Drought Forecasting: First Application of Bayesian Concept Drift-Enhanced Hidden Markov Models for Probabilistic Climate Risk Mapping in Northwestern Algeria. Italian Journal of Agrometeorology. https://doi.org/10.36253/ijam-3944

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