2020 journal article
Parameter uncertainty drives important incongruities between simulated chlorophyll-a and phytoplankton functional group dynamics in a mechanistic management model
ENVIRONMENTAL MODELLING & SOFTWARE, 129.
UN Sustainable Development Goal Categories
6. Clean Water and Sanitation
(Web of Science; OpenAlex)
13. Climate Action
(Web of Science)
15. Life on Land
(Web of Science)
Source: Web Of Science
Added: June 29, 2020
Mechanistic phytoplankton functional group (PFG) models are used to develop water quality targets designed to mitigate cyanobacteria blooms, but it remains unclear whether PFG models adequately simulate cyanobacteria dynamics as most are evaluated against observations of chlorophyll-a instead of PFG biomass. To address this challenge, we analyzed an application of CE-QUAL-ICM, a 3D mechanistic PFG model used by water managers and modelers. Global Sensitivity Analysis was employed to assess the sensitivity of modeled chlorophyll-a, cyanobacteria biomass, and eukaryotic phytoplankton biomass to 42 uncertain input factors in CE-QUAL-ICM's PFG growth and loss functions. Results revealed that parameterization of CE-QUAL-ICM captured bloom variation but underpredicted bloom peaks, and simulated chlorophyll-a with greater skill than PFG biomass. Additionally, when run across realistic ranges of PFG parameter values, model outputs were highly sensitive to chlorophyll-to-carbon ratios and phosphorus uptake parameters, indicating that these factors should be the focus of targeted parameterization efforts.