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ZENODO
Dataset . 2026
License: CC BY NC
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY NC
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY NC
Data sources: Datacite
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CAMELS-PL: hydro-meteorological time series and landscape attributes for 354 catchments in Poland

Authors: Brzezińska, Wiktoria; Dolich, Alexander; Perz, Adam Edmund; Maharjan, Ashim; Loritz, Ralf; Wrzesiński, Dariusz;

CAMELS-PL: hydro-meteorological time series and landscape attributes for 354 catchments in Poland

Abstract

Description: CAMELS-PL provides a comprehensive collection of hydro-meteorological time series and catchment attributes for 354 streamflow gauges across Poland. The hydrological time series (discharge and water level) span from 1 November 1950 to 31 October 2024; the meteorological time series derived from E-OBS v31.0e span from 1 January 1951 to 31 December 2024; the meteorological time series derived from G2DC-PL span from 1 January 1951 to 31 December 2019; and the benchmark model simulations (LSTM and HBV) cover the full modelled period from 1 January 1951 to 31 October 2024. All time series are in daily resolution. The static catchment attributes include information about topography, climate, hydrology, soils, and land cover derived from both the European CORINE Land Cover 2018 dataset and the national BDOT10k topographic database. Catchment boundaries and gauging station locations are provided as shapefiles and GeoPackage files and were obtained from IMGW-PIB. Additionally, the dataset includes discharge simulations from a regionally trained Long Short-Term Memory (LSTM) network and a locally calibrated conceptual HBV model, providing benchmark data for future hydrological modelling studies in Poland. Information about the code and methods for generating CAMELS-PL can be found here: https://github.com/bigapple233-cmyk/Hy2DL/tree/CAMELS-PL Disclaimer: English: Discharge, water level time series, and catchment boundary data included in CAMELS-PL were obtained from the Institute of Meteorology and Water Management — National Research Institute (IMGW-PIB). For terms of use, please refer to: https://danepubliczne.imgw.pl Changelog v1.0.0 Initial release of CAMELS-PL, the version of the dataset described by the CAMELS-PL data description paper (submitted). Includes daily hydrological time series for 354 catchments across Poland (1 November 1950 – 31 October 2024). Includes daily meteorological time series derived from E-OBS v31.0e for 354 catchments across Poland (1 January 1951 – 31 December 2024). Includes catchment attributes covering topography, climate, hydrology, soils, CORINE land cover, and BDOT10k national land cover. Includes simulated discharge time series and benchmark results from a regional LSTM model (5 ensemble members) and a locally calibrated HBV model (5 calibration seeds using the DREAM algorithm). Includes HBV model parameter sets and LSTM model training epoch files for all ensemble members. Includes supplementary meteorological time series from the G2DC-PL+ gridded dataset for 354 catchments across Poland (1 January 1951 – 31 December 2019).

Keywords

Topography, Soil, Streamflow, Precipitation, Rainfall-Runoff Modelling, Benchmark dataset

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average