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We propose a formal classification scheme for streamflow droughts in humid-temperature climate regions. The classification scheme relies on an existing drought typology and assigns events to one of eight drought types - each characterized by a set of compounding drivers - using information about seasonality, precipitation deficits and snow availability. To ensure generalizability, the classification scheme uses globally available data i.e. observed streamflow from the Global Runoff Database and hydro-meteorological time series from the ERA5-Land reanalysis including temperature, precipitation, and snow-water-equivalent (SWE). Hydrological drought types include rainfall deficit droughts, which are exclusively caused by a prolonged lack of rainfall and possibly aggravated by high evapotranspiration; rain-to-snow-season droughts, caused by a rainfall deficit in the rain season continuing into the snow season; wet-to-dry season droughts caused by a rainfall deficit in the rain season that continues into the dry season; cold-snow-season droughts, caused by abnormally low temperatures in the snow season; warm-snow-season droughts, caused by abnormally high temperatures in the snow season; snowmelt droughts, caused by a lack of snowmelt discharge in snow-influenced basins; glaciermelt droughts, caused by a lack of glaciermelt; and composite droughts, caused by a number of drought generation mechanisms.
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Hydrological drought classification in Europe
Authors: Manuela Brunner
Owners: Manuela Brunner
Last update: 26.09.2022
This dataset provides input data and an R-script to run the drought classification scheme proposed by Brunner et al. 2022 (Water Resources Research) for 817 catchments in Europe.
Dataset components:
(1) Shapefile of 817 GRDC catchment outlets (GRDC 2019): GRDC_points.shp
Metadata information was derived from GRDC
(2) Shapefile of 817 catchment shapes with information on catchment characteristics derived from the GSIM data base and ERA5Land data: GRDC_shapes.shp
Metadata information derived from GSIM database (Do et al. 2018) and ERA5Land (Munoz-Sabater et al. 2021).
(3) R-script implementing the drought classification scheme: drought_typology.R
(4) Data needed to classify drought events for the 817 catchments:
(a) Streamflow droughts extracted from GRDC time series
(b) Precipitation deficits extracted from ERA5Land-derived precipitation time series
(c) Snow-Water-Equivalent (SWE) anomalies and time series
(d) Temperature time series
Related publications:
Brunner, M. I., Van Loon, A. F., & Stahl, K. (2022). Moderate and severe hydrological droughts in Europe differ in their hydro-meteorological drivers. Water Resources Research, 58, e2022WR032871. https://doi.org/10.1029/2022WR032871
Do, H. X., Gudmundsson, L., Leonard, M., & Westra, S. (2018).The Global Streamflow Indices and Metadata Archive - Part 1: Station catalog and catchment boundary. PANGAEA. Retrieved from https://doi.org/10.1594/PANGAEA.887477doi: 10.1594/PANGAEA.887477
GRDC (2019). Global runoff data centre. Retrieved from https://www.bafg.de/GRDC/EN/02srvcs/21tmsrs/riverdischargenode.html
Munoz-Sabater, J., Dutra, E., Agust ́ı-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., ... (2021) ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth System Science Data, 13, 4894349–4383. doi: 10.5194/essd-13-4349-2021
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using remote data access protocols such as OPeNDAP. Other data services may be made available in the future to
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