Imagining how models and modelers advance understanding of … · 2016-10-19 · Mike Healy: Workshop on linking hydrodynamics and ecosystem models. • Need decision analysis models

Imagining how models and modelers advance understanding of

the SFE

Chris EnrightDelta Science Program

April 24, 2013

Main ideas

• Modeling is not about answers—it’s about insight, learning, and better questions

• We don’t have a modeling problem, rather it’s a sociology problem

• Modeling helps‐‐– contend with complexity– cope with non‐stationarity– “glue” between disciplines

THeat Content

Heat LossRate (Btu/min)

sink

Mass of Coffee

Coffee TempAir Temp

TempDifference

Mug insulation

Why model?• The Delta is a complex, connected, changing system

Courtesy RMA

Changes—intentional and unintentional—have Delta‐scaleconsequences for restorations and conveyance

Why model?• The Delta is a complex, connected, changing system• The future is non‐stationary. Nothing will hold still

June06

Breach occursJuly 8, 2006

Blacklock Stage ‐‐ June 18, 2006 to September 1, 2006

July06 Aug06 Sept06

Why model?• The Delta is a complex, connected, changing system• The future is non‐stationary. Nothing will hold still• “Answers” becoming increasingly provisional

June06

Breach occursJuly 8, 2006

Blacklock Stage ‐‐ June 18, 2006 to September 1, 2006

July06 Aug06 Sept06

Why model?• The Delta is a complex, connected, changing system• The future is non‐stationary. Nothing will hold still• “Answers” becoming increasingly provisional• Signal‐to‐noise is THE science issue for the future

Why model?• The Delta is a complex, connected, changing system• The future is non‐stationary. Nothing will hold still• “Answers” becoming increasingly provisional• Signal‐to‐noise is THE science issue for the future• Models are complexity holders, not answer givers

Why model?• The Delta is a complex, connected, changing system• The future is non‐stationary. Nothing will hold still• “Answers” becoming increasingly provisional• Signal‐to‐noise is THE science issue for the future• Models are complexity holders, not answer givers• Modeling is cheap

– We should run novel ideas to ground– “What if’s” should be routine– Probe sensitivity and uncertainty

Courtesy Stuart Siegel

1. Modeling is not about answers—it’s about insight and better questions

A complex system

Insight from a complex system: cooling coffee

T

Heat Content


sink

Cooling Coffee


Management question:How long until I can drink it?

Cooling Coffee

T

Heat Content


sink


Cooling CoffeeToo hot

Drinkable

Room Temp


T

Heat Content


sink

Time



Drinkable

Room Temp


T

Heat Content


sink

Time



Drinkable

Room Temp


T

Heat Content


sink

TimeAnswer?



Room Temp


T

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sink

This model is wrong. Temp can go arbitrarily low.Needs other processes. May be somewhat useful though.

Drinkable

TimeAnswer?


Cooling Coffee

T

Heat Content


sink

Mass of Coffee

Coffee TempAir Temp

TempDifference

Mug insulation

Mug shape

Too hot

Room Temp

Drinkable

Time


Cooling Coffee

T

Heat Content


sink

Mass of Coffee

Coffee TempAir Temp

TempDifference

Mug insulation

Mug shape

Too hot

Room Temp

Answer?Time

Drinkable


Cooling Coffee

T

Heat Content


sink

Mass of Coffee

Coffee TempAir Temp

TempDifference

Mug insulation

Mug shape

Too hot

Room Temp

Time

Drinkable

Answer?

Insight: • The process is non‐linear


Cooling Coffee

T

Heat Content


sink

Mass of Coffee

Coffee TempAir Temp

TempDifference

Mug insulation

Mug shape

Too hot

Room Temp

Answer?Time

Drinkable

Insight: • The process is non‐linear• I can influence the response


Cooling Coffee

T

Heat Content


sink

Mass of Coffee

Coffee TempAir Temp

TempDifference

Mug insulation

Mug shape

Too hot

Room Temp

Time

Drinkable

Enjoy it!

Insight: • The process is non‐linear• I can influence the response• “Drinkable” isn’t one moment


Cooling Coffee

T

Heat Content


sink

Mass of Coffee

Coffee TempAir Temp

TempDifference

Mug insulation

Mug shape

Too hot

Room Temp

Insight: • The process is non‐linear• I can influence the response• “Drinkable” isn’t one moment Better question:

Maximize enjoyment time!Time

Drinkable

Enjoy it!


Cooling Coffee

T

Heat Content


sink

Mass of Coffee

Coffee TempAir Temp

TempDifference

Mug insulation

Mug shape

Too hot

Room Temp

TimeBetter but…

Drinkable


Maximize enjoyment time!


Cooling Coffee

T

Heat Content


sink

Mass of Coffee

Coffee TempAir Temp

TempDifference

Mug insulation

Mug shape

Too hot

Room Temp

TimeWay Better!

Drinkable


Maximize enjoyment time!

Flow Pattern

Delta currentsSediment supplyor whatever…

Turbidityor whatever…

HabitatQuantity

HabitatQuality

Delta Flows!

T sink

Delta Flow

SpeciesResponse

Insight from a complex system: Delta flowsOcean or Export

You pick!

Management question:“How much flow do fish need?”

Flow Pattern


Turbidityor whatever…

HabitatQuantity

HabitatQuality

Delta Flows!

T sink

Delta Flow

SpeciesResponse


You pick!

Better question:“How can we influence the system trajectory with flowsand connections to increase native species resilience?”


Turbidityor whatever…Delta Flows!

T sink

Delta Flow

SpeciesResponse


You pick!

Time

Models hold complexity: • Alternative trajectories• Response sensitivity (insight)• Indicate uncertainty

Flow Pattern

HabitatQuantity

HabitatQuality



T sink

Delta Flow

SpeciesResponse


You pick!

Time


Flow Pattern

HabitatQuantity

HabitatQuality



T sink

Delta Flow

SpeciesResponse


You pick!

Time


Flow Pattern

HabitatQuantity

HabitatQuality

2. Not a modeling problem, a sociology problem

• Models are mature and improving• Compute power is less limiting• We should improve the modeling model• The issue is how we work together

– We should ask “what if” routinely– Models are insight drivers if we use ‘em that way

Sociology of system knowledge

• Nobody really knows what they want from “the modeling” at first…

• ...so interdisciplinary interaction is key:CASCaDE links models of climate‐>

hydrology‐> hydrodynamics‐> sediment‐> geomorphology‐>

phytoplankton‐> bivalves‐> contaminants‐> marsh accretion‐> fish

Delta Science Plan:“Modeling community”

• How do we organize data, tools, and people to gain modeling insight in support of Bay‐Delta problem solving?

Data Models

People(many disciplines)

Insight

A modeling community links scientists and modelers

• Continuous conceptual model• Formulate hypotheses• Choose parsimonious modeling

tools• Formulate the modeling

approach • Get the thing to work

• Post‐process for question‐relevant high‐level outputs

• ANALYSIS—“so what,” “what did we learn,” ask a better question

multidisciplinary debate multidisciplinary debatetechnical debate

technical multidisciplinary collaborationTechnical warrior work—Takes timetechnical work iteration

multidisciplinary debate

Do it again…

A modeling community links scientists and modelers

• Continuous conceptual model• Formulate hypotheses• Choose parsimonious modeling

tools• Formulate the modeling

approach • Get the thing to work

• Post‐process for question‐relevant high‐level outputs

• ANALYSIS—“so what,” “what did we learn,” ask a better question

multidisciplinary debate multidisciplinary debatetechnical debate

technical multidisciplinarycollaborationTechnical warrior work—Takes timetechnical work iteration

multidisciplinary debate

Do it again…

Modeling recommendations

National Research Council• RPA assessment “…lack of life‐cycle model with outputs that match scale of actions.”

• BDCP Effect Analysis “(Use) integrated models including life‐cycle models.”


IEP Science Advisory Group• “…get interdisciplinary researchers to work together on integrated models.”


Mike Healy: Workshop on linking hydrodynamics and ecosystem models.

• Need decision analysis models (e.g. Delta EFT; Bay‐Delta EDT).

• Establish a Science Center to … coordinate data management, model development, and training in the use of models


Modeling Community Letter to CALFED• Invest is common data, model engines, visualization, interoperability…

• “We recommend …a collaborative, integrated program dedicated to advancing Delta modeling capabilities”


Independent modeling team (SWRCB)• Change will occur—preparation is needed• Integrated understanding requires integrated models

• Invest in long‐term model development• Organize policy‐making to better employ modeling results


CWEMF at Sudwerk last night—• Supporting the Delta Science Plan

Modeling centers are common

• Interagency Modeling Center (Everglades)• Center for Integrated Modeling (Gulf of Mexico)• Ecosystem Modeling Program (NOAA Chesapeake)• National Wetlands Research Center (USGS)• Resource Ecology and Ecosystem Modeling (NOAA Alaska)

• Conservation Biology Institute• Joint Ecosystem Modeling Laboratory (Florida USGS)• NOAA Fisheries Science Centers

What you would know upon visiting the nascent B‐D Modeling Center

• Culture of independence and excellence• Interdisciplinary interaction is valued• Incubating great ideas• Works on policy‐relevant problem solving• Communicates to managers and policy makers• Builds modeling capacity—a real career path

3. The modeling issues for the future‐‐ technical ‐‐

• Sequencing and landscape‐scaling restoration– Shallow, high friction, flow and transport (in vegetation);– Tidal energy dissipation– Sediment transport—channel response– Geomorphic change trajectories

• Residence time (flushing, age, exposure) • Food web• Top down—bottom up• Life‐history and behavior• Model interoperability—process cascade and feedback• Real‐time forecasting and data assimilation• Geochemical cycling

3. The modeling issues for the future‐‐ sociological ‐‐

• Build capacity—should be a career path• Models can facilitate trust building• Remove obstacles to collaboration• Routine “what if” and “gaming”—scientists, stakeholders, and policy makers

• Bring models into the room• Modeling community needs a focal point—a modeling center of excellence

Thank you

CASCaDE teamSWRCB Expert PanelSteve CulbersonJon BurauAnke Mueller‐SolgerWalter BourezJohn DeGeorgeRichard RachieleLenny GrimaldoPeter Goodwin

“Modeling Community”

• Most of what we need to understand is at disciplinary boundaries

• Modeling should be the “glue” between the science disciplines

• What is the “geometry” of interaction?• How do we build capacity?

Van Sickle Island‐‐2000 acres

100’ Breach

Thank you RMA

Van Sickle Island‐‐2000 acres

5000’ Breach

-6.50

-11.32 -0.64

-8.61

-9.48

-10.35 -6.65

-6.74

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-22.54

-7.47

0.03

-0.71

-8.61

-11.54

-0.10

-0.61

-20.22

-27.57

12.87 4.68

3.92 5.55

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Change from Base EC(%)

September 1, 2002 14.05

13.93 1.04

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10.74 7.10

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9.90

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4.30 6.73 3.40

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Change from Base EC(%)

September 1, 1992

September 1, 1992

All else equal: 7000 ac

restoration

Northern Suisun Marsh (away from the Bay)

Southern Suisun Marsh (on the Bay)

Salinity decreases5‐15% in Delta

Salinity increases5‐15% in Delta

Courtesy RMA

Future is now

• Exponential growth of compute power.• Massively parallel supercomputing and the next

• Expect “what‐if” results now.generation of atmospheric models

Van Sickle Is Levee BreachEffect on Stage and Salinity

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July 1992 Simulation


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Van Sickle IslandLevee Breach2000 acres

July 1992 Simulation


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July 1992 Simulation Van Sickle Breach


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Stage



Nurse Slough restoration:Induced regional bed shear stress

Base

NurseDifferenceNurse ‐ Base

05 Jun 0100

05 Jun 0100

W a t e r S u r f a c e E l e v a t i o n a t S - 2 1 S u n r i s e C l u b i n S u i s u n M a r s h N o v e m b e r 1 9 9 8 - N o v e m b e r 2 0 0 0

- 3

- 2

- 1

0

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1 1 / 1 / 9 8 1 / 3 0 / 9 9 4 / 3 0 / 9 9 7 / 2 9 / 9 9 1 0 / 2 7 / 9 9 1 / 2 5 / 0 0 4 / 2 4 / 0 0 7 / 2 3 / 0 0 1 0 / 2 1 / 0 0

Sta

ge (f

t, N

GV

D)

S u n r i s e C l u b f l o o d e d

Chadbourne Slough Levee Breach Suisun Marsh

Tidal Range Reduction Due to Levee Breach

9.14.9

3.0 2.0

5.96.5

1.6

1.21.31.3

1.4

2.62.1

1.21.00.5

‐0.5‐0.1

‐0.6

‐0.3

‐0.4

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0.00.0 0.0 0.0

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+10%

+5%

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‐5%

Regional Salinity Impact of Sunrise Club Levee Breach

Average of DSM1 and DSM2 Simulation of July 2000

Percentage ChangeSunrise Club

‐0.1

1. Breaches damp tidal energy

Tidal Trapping may occur wherever standing waves and progressive waves are proximate.

|max'||max'|''huhuSSD

Standing Waves

ProgressiveWaves

Examples of Insight from modeling

• PTM used to estimate steelhead migration rate. Data later showed they go faster—not an answer, insight into behavior.

•

Uniquely available from models tie together what if baseline

• Residence time (exposure, flushing, age)• Particle history (amenable to productivity calculation)• Eulerian and Lagrangian excursion (stationary and dynamic habitat overlap model)

• Tidal range• Salinity gradient• Stage/current phasing (wave progressivity)• ubar/u’ (physical behavior cues, non‐flood sediment cues)

• Most importantly: change in these quantities within the scope of SWRCB power.

Documents

Imagining how models and modelers advance understanding of … · 2016-10-19 · Mike Healy: Workshop on linking hydrodynamics and ecosystem models. • Need decision analysis models