Ecological Forecasting for the Great Lakes

Regional Data Exchange WorkshopUniversity at Buffalo

May 15, 2008

Joseph AtkinsonGreat Lakes ProgramUniversity at Buffalo

Use of models in management/decision makingIn

crea

sing

util

ity

Data

Information

Knowledge and understanding

Decision making

Increasing resource and knowledge requirements

Modeling

Analysis and visualization

Synthesis and forecasting

Adaptive management

Management/modeling Issues• Water quantity and flows (hydrologic model)

– Hydropower, shipping, recreational boating – Controls at Lake Superior and Lake Ontario– Diversions – Changes in habitat (wetlands), fisheries

• Pollution, eutrophication (hydrodynamic, nutrients)– Algal blooms and HABs

• Invasive species (ecological model)• Persistent toxic chemicals (water quality model)

– Organics, metals, etc.; bioaccumulation– Contaminated sediments (IJC areas of concern)

(sediment transport model)• Climate change (multiple concerns, models)

Focus on integrated modeling approaches

Other issues/features• International waters• Closed basin circulation• Coastal flows, upwelling and downwelling• River/lake interactions• Vertical suspended solids structure (benthic

nepheloid layer)– Cycling of organics

• Vertical and horizontal (thermal bar) stratification

• Water/sediment interactions• Atmospheric deposition and exchange• Point and non-point source loads

What is a model?• Idealized representation of the real system

– Conceptual– Simple analytical– Physical

– Mathematical (numerical)

– Expressed in terms of “governing equations”• Differential equations describing conservation statements

(mass, momentum, energy, etc.)– Constitutive relations (equation of state, coefficients)– Incorporate approximations --- “all models are wrong”

• Scale and resolution (time and space)• Processes to be considered• Numerical approximations (computer solutions)

Light

Nutrients

Temperature

Grazing, mortality

Algal biomass kCtd

Cd

t

C

What are models used for?

• Integrate and synthesize data– ex: water level regulation in Lake Ontario

• Simulate the “real world”– Demonstrate understanding of system

• Allow experimentation, evaluation of “what if” scenarios

• Convey results – Graphics, tables, etc.– Management support, options, risk

Model application

Problem statement

CalibrationConfirmation

(system understanding)

Conceptual frameworkManagement, scientific questions

Processes to consider,Resolution

Model formulation

Scenarios(test management

options)

Solution method

Risk and uncertainty

iteration

Data

Examples

• Algal bloom monitoring and modeling (MERHAB)

• Source locations and resource sheds

• Integrated coastal ecosystem model

• New York Ocean and Great Lakes Ecosystem Conservation

• Sediment transport

Hydrodynamic and particle tracking tools

• Three-dimensional hydrodynamic model (Princeton Ocean Model, POM)

• Uses actual or historic meteorological data– Forecasting based on actual, current conditions

• Current applications using surface velocity field– Any level can be used

• POM produces velocity and diffusion fields

Hydrodynamic and particle tracking tools (con’d)

• Lagrangian (particle tracking) approach – Random walk algorithm– Conservative, passively transported particles

(like a water molecule)

• Gridless model, but interpolates from POM grid values

Random walk algorithm

Deterministic component = real velocity + pseudo velocity;Stochastic component = random walk based on diffusivity

tDzt

x

Duxx x

xnn

21In x direction,

(similar for y direction)

Iterative approach used to account for changes in velocity and diffusivity values at initial and final location

Particle movement = deterministic component + stochastic component

deterministic stochastic

Application to Lake Erie

• Forward and backward tracking

• August and May conditions– General circulation– Source areas

• One-day, one-week and one-month resource shed simulations

• Connection with watershed model

“Particles” move with predicted water flow

General circulation Point release (bloom tracking)

Forward tracking

Source regions - Western Basin Lake Erie

“Long-term” vision - MERHAB-LGL project

(Monitoring and Event Response for Harmful Algal Blooms)

• Provide predictions of algal bloom growth and movement, with certainty estimates, to predict potential impacts in Great Lakes basin

– “Early warning system”/management tool– Focus on Lakes Erie and Ontario

Approach

• Run hydrodynamic model (POM) continuously– Maintain initial conditions for forecast runs

• Click on map of lake, or enter location (web based application)

• Run hydrodynamic model for desired forecast period (several days to several weeks)

– Historical or forecast meteorological data – Produce velocity and diffusivity fields

• Run particle tracking/population model– Different modes possible:

o Multiple “particles”o Backtracking

User interface

Database

(MySQL)

Input module

Hydrodynamic model

(POM)

Data sources

(NOAA/NWS)

Run/Forecast module

Execution module

Output module

Particle tracking model

(PTM)

Basic system arrangement (web-based modeling interface):

Resource sheds - overview

• Resource sheds in coastal waters (Great Lakes)– Motivation– What are they?

• Hydrodynamic and particle tracking tools

• Application to Lake Erie

• Integration with watershed model

Motivation

• Determine source of materials (resources) to a particular area– Zebra mussels– Algae blooms

• Understand physical “connectivity” among different areas of the lake

What are they?(how are they calculated?)

• Particle tracking, used in combination with hydrodynamic model, to illustrate circulation and flow patterns– backtracking

• “Single release” – all locations from which materials originate at a common time– One day, one week, one month, etc.

• Pathlines – full trajectories over time period of interest

• “Continuous release” - particle positions plotted for continuous release to “fill in” all locations that may be contributing to a location of interest during the chosen time period

One-day backtracks (August)

One-week

One-week (May)

One-month

Density plots

Example Resource Shed Distributions Defined with Particle BacktrackingExample Resource Shed Distributions Defined with Particle Backtracking(in Western & Central Lake Erie)(in Western & Central Lake Erie)

1 day1 day

1 week1 week

2 weeks2 weeks

3 weeks3 weeks

1 month1 month

Central Basin Site 311 August 31Central Basin Site 311 August 31

00

maxmax

Example Resource Shed Distributions Defined with Particle BacktrackingExample Resource Shed Distributions Defined with Particle Backtracking(in Western & Central Lake Erie)(in Western & Central Lake Erie)

1 day1 day

1 week1 week

2 weeks2 weeks

3 weeks3 weeks

1 month1 month

Western Basin Site 835 August 31Western Basin Site 835 August 31

00

maxmax

General components – coastal ecosystem model

(intensive monitoring study in Lake Ontario summer 2008)

• Want to test “biological filtering”, or “near-shore shunt” hypothesis

• Include interactions with shore and with open water

• Combined physical/chemical/biological structure• Synthesize data, evaluate system responses to

various stressors, provide predictive capabilities (hypothesis testing)

Considerations

• Define state variables

• Desired temporal and spatial resolution– Nested model?– Same resolution for all components?

• Data availability

• Match watershed model(s) with lake model

• Time period of simulation

Data needs

• Meteorological (wind speed and direction, air temp., dew point, etc.)

• Point, non-point sources– Flows, temperatures, concentrations, ….

• Benthic conditions– Sediment, algae, ….

• In-lake currents and temperatures, concentrations, ….

• Desired level of detail in time and space

Possible approaches (model team)

• Existing models:– POM (hydrodynamic)– Saginaw Bay model (food web interactions,

bioaccumulation)– Particle tracking– LOTOX (water quality)– Delft/Elcom (hydrodynamics, water quality)– Cladophora growth– Watershed (?) – SWAT, other– Others (?)

• Canada/US – 3 focus areas each (proposed)

Proposed model

Coastal zone ecosystem model

Watershed,hydrological

Hydrodynamics

Particle tracking

Sediment transport

Ecological (nutrients, lower food web)

Chemical fate and transport

Cladophora growth

Input data:Geometry, bathymetry, topographyLand use, soil typeInitial conditionsMeteorology

Output:Tributary flows, loadingsLake circulation, water temperature, bottom shearP concentrations, biomass

Simple 2 - box model

inflows outflows

transport

Near-shore region

Off-shore region

“Basic” model• Mass balance for near-shore (NS) region:

or

• Mass balance for off-shore (OS) region:

or

NSNSNSOSNSexNSinNSNS VCkCCQQCQC

dt

VCd

OSOSOSOSNSexOSOS VCkCCQ

dt

VCd

NS

OSexinNSNS

NS

exNS

V

CQQCCk

V

QQ

dt

dC

NSOS

exOSOS

OS

exOS CV

QCk

V

Q

dt

dC

Sample results

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

0 10 20 30 40 50

Time (days)

C (

mg

/l)

C_NS C_OS

Conclusions

• We’re ready