Articles | Volume 27, issue 2
https://doi.org/10.5194/hess-27-349-2023
https://doi.org/10.5194/hess-27-349-2023
Technical note
 | 
18 Jan 2023
Technical note |  | 18 Jan 2023

Technical note: A procedure to clean, decompose, and aggregate time series

François Ritter

Related subject area

Subject: Ecohydrology | Techniques and Approaches: Uncertainty analysis
Technical note: On uncertainties in plant water isotopic composition following extraction by cryogenic vacuum distillation
Haoyu Diao, Philipp Schuler, Gregory R. Goldsmith, Rolf T. W. Siegwolf, Matthias Saurer, and Marco M. Lehmann
Hydrol. Earth Syst. Sci., 26, 5835–5847, https://doi.org/10.5194/hess-26-5835-2022,https://doi.org/10.5194/hess-26-5835-2022, 2022
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Macroinvertebrate habitat requirements in rivers: overestimation of environmental flow calculations in incised rivers
Renata Kędzior, Małgorzata Kłonowska-Olejnik, Elżbieta Dumnicka, Agnieszka Woś, Maciej Wyrębek, Leszek Książek, Jerzy Grela, Paweł Madej, and Tomasz Skalski
Hydrol. Earth Syst. Sci., 26, 4109–4124, https://doi.org/10.5194/hess-26-4109-2022,https://doi.org/10.5194/hess-26-4109-2022, 2022
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Impacts of non-ideality and the thermodynamic pressure work term pΔv on the surface energy balance
William J. Massman
Hydrol. Earth Syst. Sci., 24, 967–975, https://doi.org/10.5194/hess-24-967-2020,https://doi.org/10.5194/hess-24-967-2020, 2020
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How to predict hydrological effects of local land use change: how the vegetation parameterisation for short rotation coppices influences model results
F. Richter, C. Döring, M. Jansen, O. Panferov, U. Spank, and C. Bernhofer
Hydrol. Earth Syst. Sci., 19, 3457–3474, https://doi.org/10.5194/hess-19-3457-2015,https://doi.org/10.5194/hess-19-3457-2015, 2015
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Modelling irrigated maize with a combination of coupled-model simulation and uncertainty analysis, in the northwest of China
Y. Li, W. Kinzelbach, J. Zhou, G. D. Cheng, and X. Li
Hydrol. Earth Syst. Sci., 16, 1465–1480, https://doi.org/10.5194/hess-16-1465-2012,https://doi.org/10.5194/hess-16-1465-2012, 2012

Cited articles

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Short summary
This study offers a method to clean time series – data recorded at specific time intervals (hours, months, etc.). It cuts time series into small pieces (called bins) and rejects bins without enough data. Errors in each bin are then flagged with a popular method called the box plot rule, which has been improved in this study. Finally, each bin can be averaged to produce a new time series with less noise, fewer gaps, and fewer errors. This procedure can be generalized to any discipline.