Integrated Ecological Assessment February 28, 2006 Long-Term Plan Annual Update Carl Fitz Recovery Model Development and

Integrated Ecological Assessment http://www.sfwmd.gov/org/wrp/elm

February 28, 2006Long-Term Plan Annual Update

Carl Fitz

Recovery Model Development and Calibration


Integrated Ecological Assessment:Status of the

Everglades Landscape Model

Model Applications Support Unit,

Hydrologic and Environmental Systems Modeling Department

1.00 92.00 183.00 274.00 365.004.94

5.72

6.501

1

112

2

2

2

3

3

3 3


ELM and the Long-Term Plan

“predict recovery of existing P gradients...” “predict changes in P gradients as result of

perturbation...” “predict changes in P gradients in response to new

inputs...” predict effects of STA “by-pass” flows or “changed

discharge points” compare “with-project to future-without” to assess

benefits does not directly assess “need for additional STAs or

BMPs” evaluate “regional system changes in P gradients”...

due to management actions


Presentation:

1. What is ELM?

2. How can it be applied?

3. How well does it work?

4. Is it ready for external review?


ELM Goals:

• Integrate hydrology, biology, and nutrient cycling in spatially

explicit, dynamic simulations

• Provide a framework for collaborative field research and other

modeling efforts

• Understand and predict the long-term, relative responses of the

landscape to different management scenarios

Develop a modeling tool for integrated ecological assessment

of water management scenarios for Everglades restoration


ELM Objectives: Specific Performance Measures

Measures

Phosphorus: concentration in surface water

Phosphorus: accumulation in ecosystem

...Other ecosystem measures with model updates

Scales

Temporal: Annual trends over decadal time periods

Spatial: 1-km resolution gradients across tens of km


ELM Design: Integrating ecological interactions

1. Boxes change in response to each other

2. Arrows denote simple model “mechanisms” of WHY things change

3. Using simple “WHYs”, model is not restricted to statistical “fits” of past behavior

4. Thus, apply understanding to predict future recovery, restoration


ELM Design: Overview

Hydrology• Requires daily flow data through water control structures

(observed, or from model such as SFWMM)

• ELM distributes water & nutrients across marshes and canals

Water Quality• Dynamics of primary phosphorus mechanisms in marshes

• Changing soils and plants greatly affect marsh water quality

Ecology• Theory: Considers theories of basic ecosystem structure and

function

• Practice: Simple-ecosystem interactions (i.e. the WHYs) capture the long term ecological gradients



Presentation:

1. What is ELM?





(hypothetical example)

Historical scenario, 1981-2000: • actual flows • actual (historical) phosphorus inflow concentrations

Hypothetical scenario, 1981-2000: • actual flows• 10 ppb phosphorus inflow concentrations

Use model to indicate the likely spatial reduction in phosphorus impacts across the Greater Everglades, with lower inflow phosphorus concentrations

Example Application:What might have happened if clean water had entered

the Everglades in the past?


Example Application:What might have happened if clean water had entered

the Everglades in the past?


Example Application: project alternative comparisons

Everglades gradient

FL

OW

2 km

4 km

6 km

8 km

STA 3/4 outflow


Example Application

CERP 2050wProj simulation: 5 scenarios,

with STA outflow concentrations ranging from 10 to 30 ppb

FL

OW

2 km

4 km

6 km

8 km

STA 3/4 outflow

Evaluate Everglades gradient downstream of STA 3/4 outflow

AtmosphericLoad


Presentation:

1. What is ELM?





How well does ELM work?

Water Quality: Regional analysis of

phosphorus (TP)

concentration in

surface water

median bias of

predictions in marsh

= 1 ppb of TP



Water Quality: Matching gradients of

TP concentration

in surface water

TP in Marsh Surface WaterWCA-2A Transects, 1994 - 2000

0

10

20

30

40

50

60

70

80

90

0 2 4 6 8 10 12 14 16

Distance from canal (km)

Me

an

TP

co

nc

. (p

pb

)

Simulated: F transect

Observed: F transect

Simulated: E transect

Observed: E transect



Ecology: Matching gradients ofecosystem phosphorus accumulation rate

Ecology:Matching gradients ofsoil peat accretion rate

P Accumulation in EcosystemWCA-2A Transects, 1981-2000

0

100

200

300

400

500

600

700

0 2 4 6 8 10 12 14 16


Ra

te (

mg

/m^

2/y

r)

Simulated F transect

Simulated E transect

Observed (Robbins 2004, approx.values & locations)

Peat accretionWCA-2A Transects, 1981-2000

0

2

4

6

8

10

12

0 2 4 6 8 10 12 14 16


Pe

at

ac

cre

tio

n (

mm

/yr)

Simulated: F transect

Simulated: E transect

Observed (Reddy et al.)


Ecology:

Patterns of other

ecological variables



Hydrology• Regional calibration/validation performance comparable to

SFWMM

Water Quality• Effectively predict long term trends in phosphorus gradients

• 1 ppb = median bias of TP concentration in marsh surface water, across region over a 20 year period

Ecology• Effectively predict long term trends in ecological gradients:

• Long-term phosphorus accumulation gradient is good match to observed

• Other gradients and patterns of important ecological variables evaluated for consistency with available data


Presentation:

1. What is ELM?





Documentation & Review

Existing Documentation• Description of Everglades, objectives and conceptual model

• Verbal, mathematical, and graphical description of algorithms

• All source code functions & variables documented (Doxygen)

• All input data documented, including “metadata”

• Numerical & graphical summaries of calibration/validation

• Comprehensive sensitivity analysis, aspects of uncertainty

• User’s Guide

Peer Review• Peer-reviewed science publications, 1996 - 2003

• Multi-agency review by CERP RECOVER Team, 2002

• Independent peer review, upcoming(?)


Value of ELMThe model is capable of the following applications:

CERP “predict average annual water column (or soil) phosphorus

concentrations in a spatial pattern...”

EFA/Long-Term Plan “predict recovery of existing P gradients...” “predict changes in P gradients as result of perturbation...” “predict changes in P gradients in response to new inputs...” predict effects of STA “by-pass” flows or “changed discharge

points” compare “with-project to future-without” to assess benefits

Operations compare “P gradient changes”...due to LO... “diversion to

WCAs” evaluate “regional system changes in P gradients”... due to

management actions


Supplementary slides follow

The end


Ecological

Processes


Ecological

Processes

Documents

Integrated Ecological Assessment February 28, 2006 Long-Term Plan Annual Update Carl Fitz Recovery Model Development and