Articles | Volume 17, issue 11
https://doi.org/10.5194/essd-17-5745-2025
https://doi.org/10.5194/essd-17-5745-2025
Data description paper
 | 
03 Nov 2025
Data description paper |  | 03 Nov 2025

CAMELS-NZ: hydrometeorological time series and landscape attributes for New Zealand

Sameen Bushra, Jeniya Shakya, Céline Cattoën, Svenja Fischer, and Markus Pahlow

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Cited articles

Adams, C. J. and Ramsay, W. R. H.: Archean and Paleoproterozoic zircons in Paleozoic sandstones in southern New Zealand: evidence for remnant Nuna supercontinent and Ur continent rocks within Zealandia, Australian Journal of Earth Sciences, 69, 1061–1081, https://doi.org/10.1080/08120099.2022.2091039, 2022. 
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017. a, b, c, d, e, f
Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F.: GloFAS – global ensemble streamflow forecasting and flood early warning, Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, 2013. a
Almagro, A., Oliveira, P. T. S., Meira Neto, A. A., Roy, T., and Troch, P.: CABra: a novel large-sample dataset for Brazilian catchments, Hydrol. Earth Syst. Sci., 25, 3105–3135, https://doi.org/10.5194/hess-25-3105-2021, 2021. a
Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Puelma, C., Cortes, G., Garreaud, R., McPhee, J., and Ayala, A.: The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset, Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018, 2018. a, b, c
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To support comparative hydrology and climate impact research, we present a large-sample dataset with hourly and daily streamflow and hydrometeorological data from 369 catchments across Aotearoa New Zealand. It includes detailed catchment attributes and represents diverse hydrological regimes. This open-access resource enables model evaluation and international comparisons and helps fill a key regional gap in global hydrological data.
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