EGU21-9877
https://doi.org/10.5194/egusphere-egu21-9877
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Rescue of groundwater level time series: how to identify and treat errors

Jānis Bikše, Inga Retike, Andis Kalvāns, Aija Dēliņa, Alise Babre, Konrāds Popovs, Marta Jemeļjanova, Artjoms Zelenkevičs, Artūrs Baikovs, and Zanita Avotniece
Jānis Bikše et al.
  • University of Latvia, Faculty of Geography and Earth Sciences, Riga, Latvia (janis.bikse@lu.lv)

Groundwater level time series are the basis for various groundwater-related studies. The most valuable are long term, gapless and evenly spatially distributed datasets. However, most historical datasets have been acquired during a long-term period by various operators and database maintainers, using different data collection methods (manual measurements or automatic data loggers) and usually contain gaps and errors, that can originate both from measurement process and data processing. The easiest way is to eliminate the time series with obvious errors from further analysis, but then most of the valuable dataset may be lost, decreasing spatial and time coverage. Some gaps can be easily replaced by traditional methods (e.g. by mean values), but filling longer observation gaps (missing months, years) is complicated and often leads to false results. Thus, an effort should be made to retain as much as possible actual observation data.

In this study we present (1) most typical data errors found in long-term groundwater level monitoring datasets, (2) provide techniques to visually identify such errors and finally, (3) propose best ways of how to treat such errors. The approach also includes confidence levels for identification and decision-making process. The aim of the study was to pre-treat groundwater level time series obtained from the national monitoring network in Latvia for further use in groundwater drought modelling studies.

This research is funded by the Latvian Council of Science, project “Spatial and temporal prediction of groundwater drought with mixed models for multilayer sedimentary basin under climate change”, project No. lzp-2019/1-0165.

How to cite: Bikše, J., Retike, I., Kalvāns, A., Dēliņa, A., Babre, A., Popovs, K., Jemeļjanova, M., Zelenkevičs, A., Baikovs, A., and Avotniece, Z.: Rescue of groundwater level time series: how to identify and treat errors, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9877, https://doi.org/10.5194/egusphere-egu21-9877, 2021.

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