Model-based data analysis of the effect of winter mixing on primary production in a lake under reoligotrophication

Shubham Krishna, Hugo N. Ulloa, Onur Kerimoglu, Camille Minaudo, Orlane Anneville and Alfred Wüest

Ecological Modelling, 2021, vol. 440, issue C

Abstract: Nutrient loading, in combination with climate change are important drivers of primary productivity in lakes. Understanding and forecasting future changes in primary production (PP) in response to local and global forcing are major challenges for developing sustainable lake management. The objective of this study is to understand and characterize the mechanisms underlying the large differences in observed PP rates and nutrient concentrations between two consecutive years (2012 and 2013) in Lake Geneva, Switzerland. For this purpose, we apply a one-dimensional (1D) physical–biogeochemical model system. The Framework of Aquatic Biogeochemical models (FABM) interface is used to couple the General Ocean Turbulence Model (GOTM) with a biogeochemical model, the Ecological Regional Ocean Model (ERGOM). We calibrated GOTM, by adjusting physical parameters, with the observed temperature profiles. A model calibration method is implemented to minimize model-data misfits and to optimize the biological parameters related to phytoplankton growth dynamics.

Keywords: Nutrient; Carbon fixation; Phytoplankton classes; Coupled models; Colimitation; Deep mixing; Model calibration (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:440:y:2021:i:c:s0304380020304634

DOI: 10.1016/j.ecolmodel.2020.109401

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