Modeling phytoplankton community in reservoirs. A comparison between taxonomic and functional groups-based models

Area of Science:

• Environmental Science
• Limnology
• Water Quality Modeling

Background:

• Phytoplankton community structure significantly impacts reservoir water quality.
• Accurate modeling of phytoplankton dynamics is crucial for water resource management.
• Existing models vary in their representation of phytoplankton communities.

Purpose of the Study:

• To formulate and compare two mechanistic water quality models differing in phytoplankton representation.
• To assess model performance using parameter estimation and validation.
• To evaluate the impact of nutrient loading scenarios on phytoplankton dynamics.

Main Methods:

• Developed a Taxonomic group model and a Functional group model for phytoplankton.
• Employed constrained parameter estimation within an equation-oriented framework.
• Validated models using data from Paso de las Piedras Reservoir, Argentina.

Main Results:

• Phytoplankton morpho-functional groups demonstrated a closer representation of species growth requirements.
• The Functional group model exhibited enhanced performance compared to the Taxonomic group model.
• Model simulations predicted increased phytoplankton dynamics under elevated nutrient loading scenarios.

Conclusions:

• The Functional group model provides a more accurate representation of phytoplankton communities for water quality assessment.
• This modeling approach is valuable for predicting the effects of environmental changes, such as nutrient enrichment.
• Findings support improved water resource management strategies for drinking water supply reservoirs.