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Vol. 127, No. 4 * Pages 421–504 * October - December 2023


Journal of the Hungarrian Meteorological Service

Special issue: Application of advanced methods used for specific environmental purposes

Guest Editor: Kálmán Kovács

letöltés [pdf: 2891 KB]
Contribution of data-driven methods to risk reduction and climate change adaptation in Hungary and beyond
Edina Birinyi, Boglárka O. Lakatos, Márta Belényesi, Dániel Kristóf, Zsolt Hetesi, László Mrekva, and Gábor Mikus
DOI:10.28974/idojaras.2023.4.1 (pp. 421–446)
 PDF (7695 KB)   |   Abstract

Among a series of tangible phenomena related to climate change and ecosystem degradation, the severe drought damage that occurred in 2022 urges in particular a thoughtful and long-term concept to tackle and mitigate the effects of similar events. To develop this concept, in addition to taking stock of scientific results so far, it is crucial to establish the basis for mutually supportive cooperation between the sectors concerned, including agriculture, water management, and nature conservation.
As confirmed by scientific knowledge, the continuous deterioration of the landscape's water retention and evapotranspiration capacity is associated with weakening the climate regulating function and the degradation of agricultural production conditions. Accordingly, the task is not to find new resources and interventions ensuring the continuation of current landscape use; the real goal is to find the landscape use (farming methods and water use) that will ensure sustainable human livelihoods and environmental conditions.
All the tools and knowledge are available for the first steps and subsequent ongoing monitoring and refinement of a precautionary and prevention-based approach to support all levels of ecosystem services. With continuous professional dialogue and implementation of established and new methods, several goals can be achieved simultaneously, such as the integration of economic trends into the approach, the revitalization of Hungarian landscape culture, and hence the preservation of the rural workforce.


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