EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Temporal water table dynamics derived from optical satellite data

Iuliia Burdun1, Michel Bechtold2, Mika Aurela3, Gabrielle De Lannoy2, Ankur R. Desai4, Elyn Humphreys5, Santtu Kareksela6, Viacheslav Komisarenko7,8, Maarit Liimatainen9,10, Hannu Marttila9, Kari Minkkinen11, Mats B. Nilsson12, Paavo Ojanen10,11, Sini-Selina Salko1, Eeva-Stiina Tuittila13, Evelyn Uuemaa7, and Miina Rautiainen1
Iuliia Burdun et al.
  • 1Aalto University, School of Engineering, Department of Built Environment, Espoo, Finland (
  • 2KU Leuven, Heverlee, Belgium
  • 3Finnish Meteorological Institute, Helsinki, Finland
  • 4University of Wisconsin-Madison, Madison, USA
  • 5Carleton University, Department of Geography & Environmental Studies, Ottawa, Canada
  • 6Metsähallitus, Jyväskylä, Finland
  • 7University of Tartu, Tartu, Estonia
  • 8Ghent University, Ghent, Belgium
  • 9University of Oulu, Oulu, Finland
  • 10Natural Resources Institute Finland, Oulu, Finland
  • 11University of Helsinki, Department of Forest Sciences, Helsinki, Finland
  • 12Swedish University of Agricultural Sciences, Umeå, Sweden
  • 13University of Eastern Finland, School of Forest Sciences, Joensuu, Finland

Water table constitutes a master control of the general biogeochemistry in northern peatlands. The performance of peatland simulations in global ecosystem models is strongly hampered by the accuracy of the water table predictions. We examined the applicability of the Optical TRApezoid Model (OPTRAM) to monitor the temporal fluctuations in water table over 53 intact, restored, and drained northern peatlands in Finland, Estonia, Sweden, Canada, and the USA from 2018 through 2021. Various OPTRAM were computed based on Sentinel-2 data with the Google Earth Engine cloud platform. We found that (i) the choice of vegetation index utilised in OPTRAM does not significantly affect OPTRAM performance; (ii) the tree cover density is a significant factor controlling the sensitivity of OPTRAM to water table dynamics; (iii) the relationship between water table and OPTRAM often disappears for deep water tables. Based on an anomaly analysis, we further found that OPTRAM seems to be in particular suitable to monitor long-term (i.e., interannual) water table variability while the performance for short-term changes (e.g., response to individual rain events) was lower. Overall, our results support the application of OPTRAM to monitor water table dynamics in intact and restored northern peatlands with low tree cover density when the water table is shallow to moderately deep.

How to cite: Burdun, I., Bechtold, M., Aurela, M., De Lannoy, G., Desai, A. R., Humphreys, E., Kareksela, S., Komisarenko, V., Liimatainen, M., Marttila, H., Minkkinen, K., Nilsson, M. B., Ojanen, P., Salko, S.-S., Tuittila, E.-S., Uuemaa, E., and Rautiainen, M.: Temporal water table dynamics derived from optical satellite data, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4279,, 2023.