Articles | Volume 14, issue 9
https://doi.org/10.5194/essd-14-4035-2022
https://doi.org/10.5194/essd-14-4035-2022
Data description paper
 | 
06 Sep 2022
Data description paper |  | 06 Sep 2022

A 500-year annual runoff reconstruction for 14 selected European catchments

Sadaf Nasreen, Markéta Součková, Mijael Rodrigo Vargas Godoy, Ujjwal Singh, Yannis Markonis, Rohini Kumar, Oldrich Rakovec, and Martin Hanel

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Cited articles

Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., Kudlur, M., Levenberg, J., Monga, R., Moorea, S., Murray, D. G., Steiner, B., Tucker, P., Vasudevan, V., Warden, P., Wicke, M., Yu, Y., Zheng, X., and Google brain: Tensorflow: A system for large-scale machine learning, in: 12th {USENIX} symposium on operating systems design and implementation ({OSDI} 16, 2–4 November 2016, Savannah, GA, USA, pp. 265–283, 2016. a, b
Armstrong, M. S., Kiem, A. S., and Vance, T. R.: Comparing instrumental, palaeoclimate, and projected rainfall data: Implications for water resources management and hydrological modelling, Journal of Hydrology: Regional Studies, 31, 100728, https://doi.org/10.1016/j.ejrh.2020.100728, 2020. a
Arnold, T. B.: kerasR: R interface to the keras deep learning library, Journal of Open Source Software, 2, 296, https://doi.org/10.21105/joss.00296, 2017. a, b
Ayzel, G., Kurochkina, L., and Zhuravlev, S.: The influence of regional hydrometric data incorporation on the accuracy of gridded reconstruction of monthly runoff, Hydrol. Sci. J., 0, https://doi.org/10.1080/02626667.2020.1762886, 1–12, 2020. a
Boch, R. and Spötl, C.: Reconstructing palaeoprecipitation from an active cave flowstone, J. Quaternary Sci., 26, 675–687, 2011. a
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This article presents a 500-year reconstructed annual runoff dataset for several European catchments. Several data-driven and hydrological models were used to derive the runoff series using reconstructed precipitation and temperature and a set of proxy data. The simulated runoff was validated using independent observed runoff data and documentary evidence. The validation revealed a good fit between the observed and reconstructed series for 14 catchments, which are available for further analysis.
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