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Event peak flow dataset for spatial counterfactual events, Germany

Authors
/persons/resource/dung

Nguyen,  D.
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/bmerz

Merz,  B.
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Guse,  Björn
External Organizations;

/persons/resource/lihan

Han,  Li
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/guan

Guan,  Xiaoxiang
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Rakovec,  Oldrich
External Organizations;

Samaniego,  Luis
External Organizations;

Ahrens,  Bodo
External Organizations;

/persons/resource/vorogus

Vorogushyn,  S.
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

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Citation

Nguyen, D., Merz, B., Guse, B., Han, L., Guan, X., Rakovec, O., Samaniego, L., Ahrens, B., Vorogushyn, S. (2024): Event peak flow dataset for spatial counterfactual events, Germany.
https://doi.org/10.5880/GFZ.4.4.2024.002


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5025321
Abstract
This dataset comprises event peak flows, representing extreme floods at 516 stations in Germany. The data generation process involves several key steps. Initially, observed rainfall events associated with 10 historical flood disasters from 1950 to 2021 are undergone spatial shifts. These shifts involve three distances (20, 50, and 100 km) and eight directions (North, Northeast, East, Southeast, South, Southwest, West, Northwest), resulting in 24 counterfactual precipitation events. Including the factual (no shift) event, a total of 25 distinct shifting events are considered. Subsequently, these shifted fields are used as atmospheric forcing for a mesoscale hydrological model (mHM) set up and calibrated for the entire Germany. The model produces daily stream flows across its domain, from which the event peak flows are derived. This dataset is expected to provide a valuable resource for analyzing and modeling the dynamics extreme flood events in Germany.