How morphology shapes the parameter sensitivity of lake ecosystem models

Andersen T. K. , Bolding K., Nielsen A., Bruggeman J., Jeppesen E., Trolle D.

ENVIRONMENTAL MODELLING & SOFTWARE, vol.136, 2021 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 136
  • Publication Date: 2021
  • Doi Number: 10.1016/j.envsoft.2020.104945
  • Journal Indexes: Science Citation Index Expanded, Scopus, Academic Search Premier, PASCAL, Aerospace Database, Applied Science & Technology Source, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Biotechnology Research Abstracts, CAB Abstracts, Communication Abstracts, Compendex, Computer & Applied Sciences, Environment Index, Geobase, Greenfile, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Global sensitivity analysis, Lake ecosystem modelling, Process-based modelling, Moment-independent sensitivity method, Variance-based sensitivity method, FABM-PCLake, OF-THE-ART, SHALLOW LAKES, WATER-QUALITY, CLIMATE-CHANGE, DEEP LAKE, STATE, PHOSPHORUS, IDENTIFIABILITY, ZOOPLANKTON, CALIBRATION


A global sensitivity analysis of a lake ecosystem model (GOTM-FABM-PCLake) was undertaken to test the impacts of lake morphology on parameter sensitivity in three different lakes. The analysis was facilitated by the Parallel Sensitivity and Auto-Calibration tool (parsac) and included a screening step with the density-based Borgonovo's method followed by in-depth analysis with both Borgonovo's and the variance-based Sobol' methods. The Borgonovo's method proved efficient in ranking the most influential parameters and its results were corroborated by the Sobol' method. For total phosphorus and total nitrogen, parameters related to the benthic-pelagic coupling and phytoplankton, were particularly important for the shallower lakes, whereas the most important parameters for total nitrogen were related mainly to the benthic-pelagic coupling in the deepest lake. For chlorophyll a, phytoplankton and zooplankton parameters were most influential. We conclude that lake morphology shapes the parameter sensitivity of lake ecosystem models.