Articles | Volume 27, issue 18
https://doi.org/10.5194/hess-27-3375-2023
https://doi.org/10.5194/hess-27-3375-2023
Research article
 | 
22 Sep 2023
Research article |  | 22 Sep 2023

On the visual detection of non-natural records in streamflow time series: challenges and impacts

Laurent Strohmenger, Eric Sauquet, Claire Bernard, Jérémie Bonneau, Flora Branger, Amélie Bresson, Pierre Brigode, Rémy Buzier, Olivier Delaigue, Alexandre Devers, Guillaume Evin, Maïté Fournier, Shu-Chen Hsu, Sandra Lanini, Alban de Lavenne, Thibault Lemaitre-Basset, Claire Magand, Guilherme Mendoza Guimarães, Max Mentha, Simon Munier, Charles Perrin, Tristan Podechard, Léo Rouchy, Malak Sadki, Myriam Soutif-Bellenger, François Tilmant, Yves Tramblay, Anne-Lise Véron, Jean-Philippe Vidal, and Guillaume Thirel

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Cited articles

Alexandrov, G., Ames, D., Bellocchi, G., Bruen, M., Crout, N., Erechtchoukova, M., Hildebrandt, A., Hoffman, F., Jackisch, C., and Khaiter, P.: Technical assessment and evaluation of environmental models and software, Environ. Model. Softw., 26, 328–336, https://doi.org/10.1016/j.envsoft.2010.08.004, 2011. a
Andréassian, V., Hall, A., Chahinian, N., and Schaake, J.: Introduction and synthesis: Why should hydrologists work on a large number of basin data sets?, Large sample basin experiments for hydrological parametrization: results of the models parameter experiment – MOPEX, IAHS Red Books Series no 307, IAHS Press, Wallingford, https://hal.inrae.fr/hal-02588687 (last access: 1 June 2023), 2006. a
Ayzel, G. and Heistermann, M.: The effect of calibration data length on the performance of a conceptual hydrological model versus LSTM and GRU: A case study for six basins from the CAMELS dataset, Comput. Geosci., 149, 104708, https://doi.org/10.1016/j.cageo.2021.104708, 2021. a
Barthel, R., Haaf, E., Nygren, M., and Giese, M.: Systematic visual analysis of groundwater hydrographs: potential benefits and challenges, Hydrogeol. J., 30, 359–378, https://doi.org/10.1007/s10040-021-02433-w, 2022. a, b, c
Beven, K. and Westerberg, I.: On red herrings and real herrings: disinformation and information in hydrological inference, Hydrol. Process., 25, 1676–1680, https://doi.org/10.1002/hyp.7963, 2011. a, b
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Short summary
We present the results of a large visual inspection campaign of 674 streamflow time series in France. The objective was to detect non-natural records resulting from instrument failure or anthropogenic influences, such as hydroelectric power generation or reservoir management. We conclude that the identification of flaws in flow time series is highly dependent on the objectives and skills of individual evaluators, and we raise the need for better practices for data cleaning.
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