Geomatics and Environmental Engineering, vol. 20, no. 3

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Vol. 20 No. 3 (2026): Geomatics and Environmental Engineering

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Submitted
Oct 15, 2025
Accepted
Mar 5, 2026
Published
Apr 30, 2026
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This work is licensed under a Creative Commons Attribution 4.0 International License.

Drought Assessment and Forecasting according to the Köppen–Geiger Climate Classification Using GRACE and MERRA Observations

https://doi.org/10.7494/geom.2026.20.3.105
Monika Biryło
University of Warmia and Mazury in Olsztyn, Faculty of Geoengineering, Olsztyn, Poland
https://orcid.org/0000-0002-8006-288X

Corresponding Author(s) : Monika Biryło

monika.sienkiewicz@uwm.edu.pl

Geomatics and Environmental Engineering, Vol. 20 No. 3 (2026): Geomatics and Environmental Engineering

Abstract

Prolonged and recurrent droughts are a problem of the 21st century. Agriculture, grazing, fires, logging, and mining make soil susceptible to permanent degradation. However, well-managed land can recover from long drought cycles. Because drought is increasingly affecting larger areas, continuous monitoring and risk assessment are essential. Satellite-based models provide global observations of the Earth and enable their assessment using indices, thereby supporting the classification of the examined areas. In this study, the Combined Climatological Deviation Index (CCDI) and the Water Storage Deficit Index (WSDI) were calculated to evaluate drought sensitivity in Europe, within its climatic zones according to the Köppen–Geiger classification. Based on the research, it was concluded that almost all areas show a tendency towards drying, and the predictions indicate that the current drought conditions and their pace will continue. The CCDI and WSDI are very useful in studies of drought in Europe.

Keywords

total water storage precipitation drought WSDI CCDI
Biryło, M. (2026). Drought Assessment and Forecasting according to the Köppen–Geiger Climate Classification Using GRACE and MERRA Observations. Geomatics and Environmental Engineering, 20(3), 105–133. https://doi.org/10.7494/geom.2026.20.3.105
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