4.4 Review

Continuous and high-frequency measurements in limnology: history, applications, and future challenges

Journal

ENVIRONMENTAL REVIEWS
Volume 24, Issue 1, Pages 52-62

Publisher

CANADIAN SCIENCE PUBLISHING
DOI: 10.1139/er-2015-0030

Keywords

lake metabolism; temporal variability; spatial variability; extreme events; hydrodynamics

Funding

  1. Estonian Ministry of Education and Research [PUT777]
  2. Estonian Science Foundation [ETF8729, ETF9102]
  3. EU through European Regional Development Fund, program Environmental Conservation and Environmental Technology R&D Programme project VeeOBS [3.2.0802.11-0043]
  4. MARS project (Managing Aquatic ecosystems and water Resources under multiple Stress) - 7th EU Framework Programme, Theme 6 (Environment including Climate Change) [603378]
  5. [SF0170011s08]
  6. [IUT 21-2]

Ask authors/readers for more resources

Over the past 15 years, an increasing number of studies in limnology have been using data from high-frequency measurements (HFM). This new technology offers scientists a chance to investigate lakes at time scales that were not possible earlier and in places where regular sampling would be complicated or even dangerous. This has allowed capturing the effects of episodic or extreme events, such as typhoons on lakes. In the present paper we review the various fields of limnology, such as monitoring, studying highly dynamic processes, lake metabolism studies, and budget calculations, where HFM has been applied, and which have benefitted most from the application. Our meta-analysis showed that more than half of the high-frequency studies from lakes were made in North America and Europe. The main field of application has been lake ecology (monitoring, lake metabolism) followed by physical limnology. Water temperature and dissolved oxygen have been the most universal and commonly measured parameters and we review the various study purposes for which these measurements have been used. Although a considerable challenge for the future, our review highlights that broadening the spatial scale of HFM would substantially broaden the applicability of these data across a spectrum of different fields.

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