loading page

Using System-Inspired Metrics to Improve Water Quality Prediction in Stratified Lakes
  • +3
  • Kamilla Kurucz,
  • Cayelan C Carey,
  • Peisheng Huang,
  • Eduardo R De Sousa,
  • Jeremy T White,
  • Matthew R Hipsey
Kamilla Kurucz
Centre for Water and Spatial Science, UWA School of Agriculture and Environment, The University of Western Australia

Corresponding Author:[email protected]

Author Profile
Cayelan C Carey
Department of Biological Sciences, Virginia Tech
Peisheng Huang
Centre for Water and Spatial Science, UWA School of Agriculture and Environment, The University of Western Australia
Eduardo R De Sousa
INTERA Inc
Jeremy T White
INTERA Inc
Matthew R Hipsey
Centre for Water and Spatial Science, UWA School of Agriculture and Environment, The University of Western Australia

Abstract

Despite the growing use of Aquatic Ecosystem Models (AEMs) for lake modelling, there is currently no widely applicable framework for their configuration, calibration, and evaluation. Calibration is generally based on direct data comparison of observed vs. modelled state variables using standard statistical techniques, however, this approach may not give a complete picture of the model’s ability to capture system-scale behaviour that is not easily perceivable in observations, but which may be important for resource management. The aim of this study is to compare the performance of ‘naïve’ calibration and a ‘system-inspired’ calibration, an approach that augments the standard state-based calibration with a range of system-inspired metrics (e.g., thermocline depth, metalimnetic oxygen minima), to increase the coherence between the simulated and natural ecosystems. A coupled physical-biogeochemical model was applied to a focal site to simulate two key state-variables: water temperature and dissolved oxygen. The model was calibrated according to the new system-inspired modelling convention, using formal calibration techniques. There was an improvement in the simulation using parameters optimised on the additional metrics, which helped to reduce uncertainty predicting aspects of the system relevant to reservoir management, such as the occurrence of the metalimnetic oxygen minima. Extending the use of system-inspired metrics when calibrating models has the potential to improve model fidelity for capturing more complex ecosystem dynamics.
10 Jul 2024Submitted to ESS Open Archive
17 Jul 2024Published in ESS Open Archive