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MTA FENNTARTHATÓ FEJLŐDÉS ÉS
TECHNOLÓGIÁK NEMZETI PROGRAM

SUSTAINABLE TECHNOLOGIES SUBPROGRAM

Decoding precipitation regimes and cyclicity across contrasting climate zones using machine learning and transformation techniques: Insights from Egypt and the Kurdistan Region, Iraq


Csaba Ilyés, Musaab A.A. Mohammed, Mohamed Hamdy Eid, Sarkhel H. Mohammed, László Bozó, Meeran A. Omer, Péter Szűcs

Researchers from the Institute of Water Resources and Environmental Management at the University of Miskolc developed an integrated machine learning and spectral-analysis framework to investigate long-term precipitation variability across two climatically contrasting regions: the Kurdistan Region of northern Iraq and Egypt. The study analyzed monthly precipitation records from 16 meteorological stations covering periods of up to eight decades (1941–2024).

The findings of the research provided insights into hydroclimatic variability in water-stressed environments and offered important benchmarks for climate adaptation, water-resource management, drought preparedness, reservoir operation, and groundwater recharge planning in arid and semi-arid regions facing increasing climate uncertainty.

Tovább a cikkhez: Environmental Challenges