ABSTRACT:

Streamflow regime classes identified for the 671 stations in the CAMELS dataset (United States) using functional data analysis: (1) intermittent regime, (2) strong winter regime, (3) weak winter regime, (4) melt regime, and (5) New Year's regime. The textfile contains a table with the USGS gauge ID of each catchment in the CAMELS dataset and their regime class (1-5). More information on the CAMELS dataset can be found in Newman et al. (2015) and Addor et al. (2017). A detailed description on how the regime classes were derived can be found in Brunner et al. (2020).

Addor, N., A. J. Newman, N. Mizukami, and M. P. Clark (2017), The CAMELS data set: Catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21(10), 5293–5313, doi:10.5194/hess-21-5293-2017.
Brunner, M. I., A. Newman, L. A. Melsen, and A. Wood (2020), Functional streamflow regime classes in the United States and their future changes, Hydrol. Earth Syst. Sci. Discuss., under review.
Newman, A. J. et al. (2015), Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: Data set characteristics and assessment of regional variability in hydrologic model performance, Hydrol. Earth Syst. Sci., 19(1), 209–223, doi:10.5194/hess-19-209-2015.

ABSTRACT:

This resource provides (1) stochastic continuous streamflow simulations for the 671 catchments in the CAMELS dataset by Addor et al. (2017), (2) peak-over-threshold events extracted from the observed and stochastically simulated series for different flood thresholds, and (3) an R-script to calculate regional flood hazard probabilities using the susceptibility index proposed by Brunner et al. (2020). It accompanies the manuscript How probable is widespread flooding in the United States by Brunner et al. (2020).

Brunner, M. I., Papalexiou, S., Clark, M. P., & Gilleland, E. (2020). How probable is widespread flooding in the UnitedStates? Water Resources Research, 56,e2020WR028096. https://doi.org/10.1029/2020WR028096.

ABSTRACT:

I here present a spatial set of natural-regulated catchment pairs to study the effect of reservoir regulation on local and regional flood and drought characteristics in the United States.
This data set is composed of the following components:
1) List of catchment pairs (paired_catch_list.txt) containing the USGS IDS of the 114 paired natural ('nat_id') and regulated ('reg_id') gauge.
2) Folder with shapefiles of gauge locations and catchment boundaries of natural and regulated catchments (folder shapefiles).
3) Folder with streamflow time series corresponding to the natural and regulated gauges
4) Folder with extracted mean drought and flood characteristics for the natural and regulated gauges

The dataset accompanies the article 'Reservoir regulation affects droughts and floods at local and regional scales' by Brunner 2021 published in ERL: https://iopscience.iop.org/article/10.1088/1748-9326/ac36f6

ABSTRACT:

This dataset provides streamflow and hydro-meteorological time series (temperature, evapotranspiration, precipitation, snow-water-equivalent (SWE), and snowmelt) for 937 catchments in Central and Northern Europe for the period 1969-2011.

ABSTRACT:

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.

ABSTRACT:

Streamflow, precipitation, and potential evapotranspiration time series for 5015 catchments from different large-sample datasets: 720 gauges in Central Europe from the LamaH dataset (Klingler et al. 2021), 2683 gauges in the United States from the streamflow and basin characteristics dataset by Dudley et al. 2018 (Dudley18), 208 gauges in Australia from the CAMELS-AUS dataset (Fowler et al. 2021), 109 gauges in Chile from the CAMELS-CL dataset (Alvarez et al. 2018), 576 catchments in Great Britain from the CAMELS-GB dataset (Coxon et al. 2020), and 733 catchments in Brazil from the Catchments Attributes for Brazil (CABra) dataset (Almagro et al. 2021).

ABSTRACT:

This dataset provides flood events and flood types for the period 1981–2012 for a selection of 863 catchments in Europe, which are part of the Global Runoff Data Centre database (GRDC) and are uninfluenced by large dams. It accompanies an analysis by Brunner and Fischer (2022), which assesses how spatial flood connectedness varies by flood generation process using a flood event classification scheme distinguishing between three rainfall-driven and two snowmelt-influenced flood types.
The flood types were determined using the classification scheme by Fischer et al. 2019, which separates between three rainfall-induced flood types and two snowmelt-influenced types:
R1: flood events with high flood peaks and small volumes, associated with heavy rainfall of high intensity
R2: flood events with moderate peak and volume, associated with medium-duration rainfall of uniform intensity
R3: flood events with large volume, associated with long, successive rainfall events
S1: rain-on-snow floods, where rainfall falls on a snow cover, i.e. associated with high amounts of rainfall but less snow melt compared to snow melt floods
S2: snow melt floods, where the snow cover melts, i.e. associated with a high amount of snow melt but no or only a small amount of rainfall

ABSTRACT:

This dataset provides daily streamflow for 827 catchments in the Central Alps for the period 1970-2017.
In addition, it provides daily hydro-meteorological time series for the following variables: precipitation, temperature, and snow-water-equivalent derived from gridded ERA5-Land data.This dataset accompanies the manuscript by Brunner et al. (2023) and is needed to reproduce their results.

Brunner, M. I., Götte, J., Schlemper, C., & Van Loon, A. F. (2023). Hydrological drought generation processes and severity are changing in the Alps. Geophysical Research Letters, 50, e2022GL101776. https://doi.org/10.1029/2022GL101776

ABSTRACT:

This dataset accompanies a manuscript by Brunner and Gilleland under consideration for publication in Earth's Future: 'Future changes in floods, droughts, and their extents in the Alps: a sensitivity analysis with a non-stationary stochastic streamflow generator'.
It provides daily streamflow, temperature, and precipitation data for 925 nearly natural catchments in the Alps for the period 1981-2016 and a shapefile with information on catchment locations, areas, and elevations.

ABSTRACT:

This dataset contains drought events of groundwater (GW), streamflow (Q), precipitation (P) and P-ET (PET) for 70 catchments in the Central Alps retrieved with a variable threshold method from daily time series over the period 1989-2017. It accompanies the paper by Brunner and Chartier-Rescan submitted to GRL.