4.7 Article

Modelling primary production in shallow well mixed lakes based on MERIS satellite data

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 163, Issue -, Pages 253-261

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2015.03.023

Keywords

Primary production; Remote sensing; Modelling; Lakes; Peipsi; Vortsjarv; MERIS

Funding

  1. Environmental Conservation and Environmental Technology R&D Programme project VeeOBS [3.2.0802.11-0043]
  2. Estonian Ministry of Education and Research target funding project [SF180009As11]
  3. Estonian Science Foundation [ETF9102]
  4. [IUT 21-2]

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Lakes play an important role in the global carbon cycle. Hence, data on seasonal and spatial variations of phytoplankton primary production (PP) is needed to estimate their ecological state. However, considerable difficulties arise when investigating the spatial and temporal variations of productivity in inland waters. Traditional in situ sampling approaches cannot provide the necessary data over large lakes or for lakes over large geographic regions. A solution can be to combine modelling with satellite data, by using different satellite products as inputs for a primary production model. The objective of this study is to evaluate and validate a lake primary production model based on satellite products. For that purpose we compared PP(sat) with PP(in situ) in two large, shallow, well mixed, and eutrophic Estonian lakes. A semi-empirical phytoplankton primary production model, derived by us earlier, was used. It allows estimating the values of phytoplankton primary production for lakes over large geographic areas. The primary production model operated well using MERIS products as input data. Our results show that spatial variability in primary production cannot be neglected in large lakes. Combining satellite data with model calculations allows monitoring of the state of lakes in space and time, providing a new perspective for lake primary production studies. (C) 2015 Elsevier Inc. All rights reserved.

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