Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Zeitschriften |
| DOI | 10.1038/s41597-026-07750-x |
Lizenz  |
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| Titel (primär) | A global dataset of spatiotemporal drought events from reanalysis and hydrological model data for 1980–2024 |
| Autor | Štovíček, V.; Hanel, M.; Kumar, R.
; Moravec, V.; Markonis, Y.; Cammalleri, C.; Řehoř, J.; Trnka, M.; Rakovec, O. |
| Quelle | Scientific Data |
| Erscheinungsjahr | 2026 |
| Department | CHS |
| Sprache | englisch |
| Topic | T5 Future Landscapes |
| Supplements | Supplement 1 |
| Abstract | We present a
global dataset of spatiotemporally clustered drought events for
1980–2024, derived from daily precipitation, potential
evapotranspiration, soil moisture, and surface runoff data. Drought
conditions were consistently defined using a 10th percentile threshold
and clustered in space and time using a three–dimensional implementation
of the Density–Based Spatial Clustering of Applications with Noise
(DBSCAN) algorithm. The dataset represents droughts as coherent
spatiotemporal events rather than isolated grid–cell anomalies. For each
drought event, it provides detailed metadata on spatial extent,
temporal duration, severity, and centroid position. By applying a
consistent event–detection framework across atmospheric forcing,
root–zone soil moisture, and runoff response, the dataset supports
systematic analysis of global drought dynamics and compound extremes.
The dataset is openly available at https://doi.org/10.5281/zenodo.18292641 providing a reusable resource for climate, hydrology, and hazard research. |
| Štovíček, V., Hanel, M., Kumar, R., Moravec, V., Markonis, Y., Cammalleri, C., Řehoř, J., Trnka, M., Rakovec, O. (2026): A global dataset of spatiotemporal drought events from reanalysis and hydrological model data for 1980–2024 Sci. Data 10.1038/s41597-026-07750-x |
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