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Simulating multiple functional groups of phytoplankton in Cannonsville Reservoir

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

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Simulating multiple functional groups of phytoplankton in Cannonsville Reservoir

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  1. Simulating multiple functional groups of phytoplankton in Cannonsville Reservoir • Hampus Markensten1, Don Pierson2, Emmet M. Owens1, Susan M. O'Donnell1 and Steven W. Effler1. • Email: hm@upstatefreshwater.org • 1) Upstate Freshwater Institute • Syracuse, USA • 2) Department of Environmental Protection (DEP) • NYC, USA

  2. Cannonsville reservoir • 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  m3 of water (98.5 billion gallons).

  3. Background • 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 (1D) 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.

  4. Overview of UFI 1D reservoir water quality model

  5. Objectives • A need to predict the occurrence of bloom forming phytoplankton. • Solution: Merge the existing 1D 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.

  6. 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

  7. Size and Shape Influences • Growth • Temperature adaptation • Light absorption • Grazing • Passive movement (up or down) • Nutrient uptake not explicitly affected

  8. What is different in PROTECH? • Morphological relationships describe growth: r20 Reynolds (1989)

  9. Temperature-sensitivity of growth rate (rθ) as a function of s/v (Reynolds in Sommer 1989)

  10. Light effect on phytoplankton growth (Reynolds in Sommer 1989)

  11. Overview of the hybrid 1D model including phytoplankton functional groups

  12. Phytoplankton Functional Groups • 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

  13. Expectations Model Calibration • 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. • To simulate realistic seasonal patterns of chlorophyll and functional group biomass. • To simulate inter annual variations in phytoplankton biomass

  14. Results Comparison of Measured and Modeled Data 1998 Hydrothermal Model Measured PROTECH

  15. Measured PROTECH- hybrid1D UFI 1D

  16. Comparing hybrid model results with measurements

  17. Comparing hybrid model results with measurements

  18. Conclusions • 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.

  19. Water Temperature (C) Chlorophyll a (mg m-3) Cannonsville Isopleths 1966 - 1990 Delta Change based on ECAM A2 2081-2300 Chlorophyll a (mg m-3) Baseline

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