Parameter uncertainty drives important incongruities between simulated chlorophyll-a and phytoplankton functional group dynamics in a mechanistic management model. (July 2020)

• Record Type: Journal Article
• Authors: Nelson, Natalie G.; Muñoz-Carpena, Rafael; Phlips, Edward
• Is Part Of: Environmental modelling & software. Volume 129(2020)
• Publication Date: 2020-07
• Subjects: Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2020.104708
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: 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. Highlights: 42 PFG growth equation parameters were evaluated with Global Sensitivity Analysis. Outputs were most sensitive to chlorophyll-to-carbon and phosphorus uptake factors. Parameterization targeting chlorophyll- a may not capture underlying PFG dynamics.