Making better decisions for aquatic resources in the Anthropocene

Adam Terando

Mitch Eaton

Dept. of Interior Southeast Climate Science Center

Department of Interior Climate Science Center Network

DOI Secretarial Order 3289: Producing actionable science that helps individuals and organizations understand and adapt to global change.

Department of Interior Climate Science Center Network

SECSC vision for science that “adds up”

Characterize and understand the effects of climate change on fish, wildlife, and habitat

Provide research-based information to support landscape scale adaptive management decisions

Actionable Science @ DOI SE Climate Science Ctr. Implementing a decision-oriented project portfolio

Formal problem deconstruction

The Decision Analytic Approach

1. Problem Framing

• Decision maker(s) & stakeholders• Values/objectives • Risk Attitudes• Alternative Actions

2. Consequences • Predictive Models

3. Identify Preferred Action

• Optimization• Trade-off analysis

Formal problem deconstruction

The Decision Analytic Approach

1. Problem Framing

• Decision maker(s) & stakeholders• Values/objectives • Risk Attitudes• Alternative Actions

2. Consequences • Predictive Models

3. Identify Preferred Action

• Optimization• Trade-off analysis

CONSIDERATION OF

NON-STATIONARY DYNAMICS

Sea-level rise and water resource managementCONSIDERATION OF NON-STATIONARY DYNAMICS IN DECISION-MAKING

USGS

How do we manage a coastal wetland impoundment that must satisfy multiple competing objectives and address a changing climate?

OUR HYPOTHETICAL

How do we manage a coastal wetland impoundment that must satisfy multiple competing objectives and address a changing climate?

OUR HYPOTHETICAL

How do we manage a coastal wetland impoundment that must satisfy multiple competing objectives and address a changing climate?

OUR HYPOTHETICAL

THE NEW REALITY

IPCC AR4 200711

USGCRP – Draft NCA 2013

Already Seeing Big Changes12

USGCRP – Draft NCA 201313

Warmer climate means a wetter atmosphere

Wat

er v

apor

pre

ssur

e (m

b)

Temperature

Saturation vapor pressurees

16

Larger percentage of precipitation has come in form of intense single day events.

Extreme One-Day Precipitation Events, Contiguous 48 States

Effects of Climate ChangeHeavy Precipitation

17

Drought

Burke et al. 2006Chelcy Miniat, USDA Forest Service18

River Discharge -An Example of Complex Interactions

tn.gov

19

Leuzinger and Korner 2010, GCBLabat et al. 2004, AWRGedney et al. 2006, Nature

Streamflow

Simple Water Balance

Input – Output = Loss

Precipitation – Streamflow = Evapotranspiration

River discharge across the globe has been increasingat a rate of 4% for each 1°C increase in global temperature.

Chelcy Miniat, USDA Forest Service20

Franks and Beerling 2009, PNAS

Evapotranspiration: Changes in Forest Leaves

With increasing size and decreasing density, stomatal conductance and transpirationalwater loss are reduced.

Chelcy Miniat, USDA Forest Service21

Franks and Beerling 2009, PNAS

Evapotranspiration: Changes in Forest Leaves

Which means, discharge (i.e. streamflow) must increase.

Chelcy Miniat, USDA Forest Service

Simple Water Balance

Input – Output = Loss

Precipitation – Streamflow = Evapotranspiration

22

Water availability could be a key concern

USGCRP – Draft NCA 201323

Formal problem deconstruction

The Decision Analytic Approach

1. Problem Framing

• Decision maker(s) & stakeholders• Values/objectives • Risk Attitudes• Alternative Actions

2. Consequences • Predictive Models

3. Identify Preferred Action

• Optimization• Trade-off analysis

Downscaling

“the process of making the link between the state some variable representing the large space and the state of some variable representing a much smaller space.” Benestad (2008)

Pros – globally consistent, physically consistent, many parameters modeled,

Cons – computationally expensive, affected by errors in a GCM, must approximate the things that occur at a finer resolution (clouds, precipitation)

Statistical Dynamic

Pros – incorporate historical information, computationally inexpensive, flexibly crafted for specific purposes

Cons – assumes statistical relationships will be valid in the future, require a long observational record, affected by the errors in a GCM

Based on statistical relationships between regional and global scale

Based on physical relationships similar to those in the Global Climate Models

DOWNSCALING

SERAP - HayhoeCLAREnCE10

Statistically DownscaledCCSM3A1FI Emissions Scenario

Dynamically DownscaledCCSM3A2 Emissions Scenario

Change in Average Total Precipitation

Puerto RicoMean Annual Precipitation

Puerto RicoMean Annual Precipitation

GCMs can’t resolve island

100 KM

Resolving Terrain is critical

2 KM

Formal problem deconstruction

The Decision Analytic Approach

1. Problem Framing

• Decision maker(s) & stakeholders• Values/objectives • Risk Attitudes• Alternative Actions

2. Consequences • Predictive Models

3. Identify Preferred Action

• Optimization• Trade-off analysis

Formal Adaptive Management

System Model

Monitoring

System Model*

Learning Adapt

Action SHARPER

Human use (agriculture and drinking water) and wildlife habitat

Maximize outflow for agricultural use Maintain minimum threshold of habitat for endangered sp.

Spring decision for water release

WHICH HYPOTHESIS WILL BE CLOSEST TO THE ONE TRUE OBSERVED STATE?

FUTURE WATER DEMAND

DEALING WITH UNCERTAINTY

Martin et al., Climatic Change, 2011

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Evidence (observations) of which state is reality increases with time.

Martin et al., Climatic Change, 2011

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Adjust actions accordingly.

LEARN

Martin et al., Climatic Change, 2011

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ADAPT

LEARN

Martin et al., Climatic Change, 2011

SMALL DIFFERENCES IN OCCUPANCY

THRESHOLD

Martin et al., Climatic Change, 2011

LARGE DIFFERENCES IN WATER RELEASE

Martin et al., Climatic Change, 2011

LOWER VALUE IF CLIMATE CHANGE IGNORED

Irrigation levels (at)

Water Units

Year

Site Occupancy

Proportion Occupied

Year

Martin et al., Climatic Change, 2011

LOWER VALUE IF CLIMATE CHANGE IGNORED

Irrigation levels (at)

Water Units

Year

Site Occupancy

Proportion Occupied

Year

Forced water closures

Threshold violations

Martin et al., Climatic Change, 2011