Markensten et al NYWEA 2008 Upstate Freshwater Institute

Markensten et al. NYWEA 2008 Upstate Freshwater Institute Simulating multiple functional groups of phytoplankton in Cannonsville Reservoir Hampus Markensten 1, Don Pierson 2, Emmet M. Owens 1, Susan M. O'Donnell 1 and Steven W. Effler 1. Email: hm@upstatefreshwater. org 1) Upstate Freshwater Institute Syracuse, USA 2) Department of Environmental Protection (DEP) NYC, USA

Cannonsville reservoir Markensten et al. NYWEA 2008 Upstate Freshwater Institute • Second largest reservoir serving New York City with drinking water. • Mesotrophic with a retention time of 2. 6 years and a storage capacity of 373*106 m 3 of water (98. 5 billion gallons).

Background Markensten et al. NYWEA 2008 Upstate Freshwater Institute • In the past Cannonsville experienced high average chlorophyll concentrations and frequent phytoplankton blooms. • Cyanobacteria often dominate in summer and autumn e. g. Aphanizomenon, Anabaena and Microcystis. • A one dimensional (1 D) lake model that simulates temperature, hydrodynamics, nutrient dynamics and total phytoplankton biomass has previously been developed by the Upstate Freshwater Institute (UFI) (Doerr et al, 1998) and applied to the reservoir. DOERR, S. M. , E. M. OWENS, R. K. GELDA, M. T. AUER & S. W. EFFLER. 1998. Development and testing of a nutrient-phytoplankton model for Cannonsville Reservoir. Lake and Reservoir Management 14. : 301 -321.

Overview of UFI 1 D reservoir water quality model Markensten et al. NYWEA 2008 Upstate Freshwater Institute

Objectives Markensten et al. NYWEA 2008 Upstate Freshwater Institute • A need to predict the occurrence of bloom forming phytoplankton. • Solution: Merge the existing 1 D reservoir water quality model, which includes a good description of hydrodynamic and chemistry, with a model focused on the dynamics of phytoplankton groups. • Compare the model performance before and after merging the two models.

• PROTECH (phytoplankton response to environmental change) is a model developed by Colin Reynolds in UK that focuses on the phytoplankton biology. • Phytoplankton can respond to changes in nutrient, light and temperature by vertical movements to reach the most favorable depth. • Phytoplankton growth rates are calculated from size and volume relationships that affect nutrient uptake light harvesting and temperature dependence. • Eight different functional groups of phytoplankton are simulated that differ in their surface area/volume, capability to fix nitrogen, use silica and regulate their buoyancy Markensten et al. NYWEA 2008 Upstate Freshwater Institute

Markensten et al. NYWEA 2008 Upstate Freshwater Institute Size and Shape Influences • Growth • Temperature adaptation • Light absorption • Grazing • Passive movement (up or down) • Nutrient uptake not explicitly affected

Markensten et al. NYWEA 2008 Upstate Freshwater Institute

What is different in PROTECH? • Morphological relationships describe growth: r 20 Markensten et al. NYWEA 2008 Upstate Freshwater Institute Reynolds (1989)

Markensten et al. NYWEA 2008 Upstate Freshwater Institute Temperature-sensitivity of growth rate (rθ) as a function of s/v (Reynolds in Sommer 1989)

Light effect on phytoplankton growth Markensten et al. NYWEA 2008 Upstate Freshwater Institute (Reynolds in Sommer 1989)

Markensten et al. NYWEA 2008 Upstate Freshwater Institute Overview of the hybrid 1 D model including phytoplankton functional groups

Markensten et al. NYWEA 2008 Upstate Freshwater Institute Feature UFI ver 4. 1 UFI PROTECH hybrid Representation of phytoplankton Carbon-based; constant stoichiometry; single (lumped) algae class Carbon-based; constant stoichiometry; multiple (eight) algae classes (PROTECH) Nutrients N, P, Si. Zooplankton Specified from measurements. Modeled. Suspended Solids FSS; VSS=Detritus + Algal material. Phytoplankton Settling Always downward at specified rate. Some phytoplankton may move up or down. Resuspension Wave-driven resuspension in Complete resuspension of deposited littoral areas; flux computed algal particulates (Algal C) in mixed from critical stress layer relationship. Deposition At rate determined by settling velocity. Sediment Release, Diagenesis Specified release rate of SRP Release of SRP, NH 3 and Si from (via TRP) and NH 3; no phytoplankton at same rate as in the transformation of deposited water column (respiration). organic material. Below mixed layer: determined by settling velocity. In mixed layer: no deposition.

Phytoplankton Functional Groups Markensten et al. NYWEA 2008 Upstate Freshwater Institute • • • Large Filamentous diatoms - Aulacoseira Small diatoms – Stephanodiscus Small Flagellates – Cryptomonas Rhodomonas Large Flagellates - Ceratium Large non N fixing cyanobacteria - Microcystis Large N fixing cyanobacteria - Anabaena Aphanizomenon

Model Calibration Markensten et al. NYWEA 2008 Upstate Freshwater Institute • The phytoplankton model was not tuned to local conditions – Alometric coefficients influencing phytoplankton growth are those given by Reynolds. • Minimal tuning of the sub-models describing hydrodynamics and nutrient kinetics. Expectations • To simulate realistic seasonal patterns of chlorophyll and functional group biomass. • To simulate inter annual variations in phytoplankton biomass

Markensten et al. NYWEA 2008 Upstate Freshwater Institute Results Comparison of Measured and Modeled Data 1998 Hydrothermal Model Measured PROTECH

Markensten et al. NYWEA 2008 Upstate Freshwater Institute Measured PROTECH hybrid 1 D UFI 1 D

Comparing hybrid model results with measurements Markensten et al. NYWEA 2008 Upstate Freshwater Institute

Comparing hybrid model results with measurements Markensten et al. NYWEA 2008 Upstate Freshwater Institute

Conclusions Markensten et al. NYWEA 2008 Upstate Freshwater Institute • Both models perform well in predicting chlorophyll on an annual scale, and also realistically simulated seasonal patterns in chlorophyll. • The PROTECH hybrid model successfully simulated occurrence of major functional groups in the Cannonsville Reservoir. • The model is a valuable tool for predicting seasonal variability in chlorophyll and phytoplankton functional groups • Evaluation of the model using other reservoirs and longer time series of data is underway.

Cannonsville Isopleths 1966 - 1990 Markensten et al. NYWEA 2008 Upstate Freshwater Institute Water Temperature (C) Delta Change based on Chlorophyll ECAM A 2 2081 -2300 a (mg m-3) Baseline Chlorophyll a (mg m-3)

Markensten et al. NYWEA 2008 Upstate Freshwater Institute