virtual experiment © oregon state university models as a communication tool for hja scientists...

Virtual Experiment

© Oregon State University

Models as a communication tool for HJA scientists

Kellie Vache and Jeff McDonnell

Dept of Forest Engineering

HJA Science Hour

Virtual Experiment

© Oregon State University

Outline

A rationale for modeling in LTER 5

The STELLA concept

Going beyond STELLA (visualization, more complex models, other languages, etc

Conclusions

Virtual Experiment

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A rationale for modeling

in LTER 5

Virtual Experiment

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LTER 5

How do land use, natural disturbances, and climate change affect three key sets of ecosystem services: carbon and nutrient dynamics, biodiversity, and hydrology?

our component areas: (1) climate, (2) hydrology, (3) disturbance, (4) ecophysiology, (5) carbon and nutrient dynamics, (6) biodiversity, and (7) stream-forest interactions.

A major goal will be to test predictive rules (i.e., hypotheses) regulating temporal behaviors.

Virtual Experiment

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LTER 20-yr review 2002

Recommendation 4. Ecological research by LTER scientists involving multiple disciplines, dimensions and scales should be organized a priori by hypotheses and theory, and tested by predictive models across broader and broader phenomena.

Virtual Experiment

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Why should we consider models?

We have a stated desire and need to integrate across the bio-geo-hydro interface

Our group discussions are often left rather open ended

We tend to get caught up in the details of our particular field or area of interest

We have difficulty with each other’s jargon and terminology

Virtual Experiment

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Another issue

We may all visit and look at thesame spot on the landscape, but may view it very differently based on our disciplinary focus

Virtual Experiment

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Sapflow! DOC, DOC, DON!DON!

StreamRouting!

Soil depth!

Lateral flow!!!

Our dominant processes bias

Virtual Experiment

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Sapflow

DOC flushing

Lateral flow

Soil depth

Stream routing

Watershed Function

Virtual Experiment

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Sapflow

DOC flushing

Lateral flow

Soil depth

Stream routing

Watershed Function

Virtual Experiment

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Representing content

in biogeochem

Representing content

in geomorph

Representing contentin hydrology

Representing contentin plant phys

General HJA system

representation

BiogeochemContent Represented

GeomporhContent

Represented

Plant Content Represented

Plant Content Represented

Virtual Experiment

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A STELLA PRIMER

Virtual Experiment

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What is STELLA?

A visual modeling environment Simulations developed through ‘dragging and dropping’ of a

standard set of modeling components

OR

A software tool designed to simulate dynamic systems.

OR

A tool to develop and solve systems of ordinary differential equations

Virtual Experiment

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Density independent population growth Described mathematically as a differential equation:

Can be solved for population through integration:

A STELLA Example

rNdt

dN

Where N = population size and r = birth rate

rtt eNN 0 Where N0 = initial population size

and Nt = population at any time t

0250005000075000

100000

0 10 20 30 40

Time

Po

pu

lati

on

Plugging into a spreadsheet

Virtual Experiment

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RUN STELLA HERE

Virtual Experiment

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A STELLA Rainfall/Runoff Model

So il

Discharge

Degree of Saturation

kS low

Po ro sity

Depth To B edrock

~

Rain

Rain Rate

Virtual Experiment

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STELLA discussions thusfar

ET1~

throughfall

m1

K1

soil1

Ks1

soil2

soilmoisture1

soilmoisture2

K2

m2

Ks2

soil3

flux

C3

C4

flux4

soilmoisture3

DOC1

DOC4

flux2

DOC conc2

DOC2

flux3

DOC3

C2

Ks3

Ohorizon

sorption2

sorption1

C1

sorption3

K3

m3 soil4

soilmoisture4m4

Ks4

K4

sorption4

DOC conc3

DOC conc4

ET2

ET3

ET4

PET2

PET1

PET3

PET4

~PET

flux5

DOC1 conc1

Virtual Experiment

© Oregon State University

Some initial results

Dirt plot simulations

0

20

40

60

80

100

120

140

2/9/99 5/20/99 8/28/99 12/6/99 3/15/00 6/23/00 10/1/00 1/9/01 4/19/01

A_measured DOC 10 cm

predicted DOC 0-10 cm

B_measured DOC 10 cm

C_measured DOC 10 cm

D_measured DOC 10 cm

E_measured DOC 10 cm

Virtual Experiment

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Going beyond STELLA

Virtual Experiment

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Limitations of the STELLA Approach

As a model becomes more complex, the STELLA environment becomes quite clunky

Spatial distribution of boxes is difficult

Direct incorporation of GIS data not feasible

Limited output potential

Virtual Experiment

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Grid-based hydrologic models (eg. DHSVM) move water laterally and vertically, but each grid cell is, in fact, cast as a 1 dimensional lumped model

A complicated STELLA-like simulation

Lettenmaier, 2002

Beyond STELLA – A brief example

Individual STELLA–like boxes!

Important processes could be explored as a STELLA model

Subsequent allocation and solution of many boxes, potentially using a GIS based grid, might then occur in a more fully featured language

Virtual Experiment

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A distributed model that began with STELLA explorations

•Data originated as 50 m gridded DEM

•Simple assumptions about soil depth, porosity, rainfall distribution, etc.

•DHSVM like routing structure

•Simple models of ET, drainage, etc.

•Map color represents depth to water table

Virtual Experiment

© Oregon State University

A distributed model that began with STELLA explorations

•Data originated as 50 m gridded DEM

•Simple assumptions about soil depth, porosity, rainfall distribution, etc.

•DHSVM like routing structure

•Simple models of ET, drainage, etc.

•Map color represents depth to water table

Virtual Experiment

© Oregon State University

Conclusions

Virtual Experiment

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Conclusions

While we will likely each continue to use detailed, process-specific models, a “group model” could be something we consider within LTER 5

We all take ownership in its development and construction

We use it to identify and explore disciplinary interfaces

A modeler could then incorporate this ‘simple’ model into a more sophisticated modeling environment

Virtual Experiment

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Hypotheses that might be tested with a model

McDonnell Group Focus: What are potential effects of rainfall distribution on the accumulation

and movement of water in the system? How might spatially variable depth to bedrock effect water

movement? Can the model simulate residence time? How does it compare to

Kevin McGuire’s measurement based estimates? What does this say about the model?

How does the model split old water vs. new water?

HJA Group Focus: What are the potential effects of stand age or species change on

hydrologic response? How do paired catchment studies reflect the larger lookout creek

basin? How might geomorphology interact with hydrology? What are the potential meso-scale effects of wildfire?

Virtual Experiment

© Oregon State University