Topics

Topics

• What Chesapeake Bay models are available • Quick description of CBP models• Model – Data interactions• How are models used in planning• New interesting results

– Climate change effects– Possible future landscapes

• Possible Model – Data Interactions

Environmental Models

• Uses– Fill in gaps in data – Hindcast (calibration)

• Spatial• Temporal• Functional

– Prediction – Forecast – Scenario• Answer what-if? questions

• Chesapeake-related open source modeling effort gaining some momentum

• Several versions of Bay models available

• More watershed models in development

http://ccmp.chesapeake.org/CCMP/models.php

Place of Models in Chesapeake Bay Program Decision Structure

Monitoring

ResearchModeling

Managers

Analysis

Ecosystem

Decision Support System

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Area of Criteria Exceedence

Area of AllowableCriteria

Exceedence

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ExceedenceData

Watershed Model

Bay Model

CriteriaAssessmentProcedures

Effects

Allocations

Airshed Model

Land UseChange Model

COAST

Annual or Monthly:

Land Use AcreageConservation PracticesFertilizerManureAtmospheric DepositionPoint SourcesSeptic Loads

Hourly Values:

RainfallSnowfallTemperatureEvapotranspirationWindSolar RadiationDewpointCloud Cover

Daily output comparedTo observations

Quick overview of watershed model Calibration

HSPF

Snapshot:


Hourly Values:


“Average AnnualFlow-Adjusted Loads”

Quick Overview of Watershed Model Scenarios

Hourly output is summed over 10 years of hydrology to compare against other management scenariosHSPF

Each segment consists of separately-modeled land uses

• High Density Pervious Urban• High Density Impervious Urban• Low Density Pervious Urban• Low Density Impervious Urban• Construction• Extractive • Forest• Disturbed Forest• Natural Grass

• Composite Crop with Manure (high till)

• Composite Crop with Manure (low till)

• Composite Crop without Manure

• Alfalfa• Nursery• Pasture• Degraded Stream bank• Animal Feeding Operations• Hay with Nutrients• Hay without Nutrients

Phase 5 Rivers, Segments, and Flow Calibration Stations

• Ensures even treatment across jurisdictions

• Fully documented calibration strategy

• Repeatable

• Makes Calibration Feasible

• Enables uncertainty analysis

Automated Calibration

How do we calibrate?

River Reach

Reasonable values of sediment, nitrogen, and phosphorus

Observations of flow, sediment, nitrogen, and phosphorus

Land variableWDM

Final TextOutput

METWDM

Land Input File Generator

1


1

2

6

ATDEPWDM

Vegetative coverPlowing times


FertilizerManure

Legume fixationCrop uptake targets

ProcessParameter

FilesModel Structure

Files

Calibration of hydrology

Final TextOutput

River variableWDM

METWDM

ATDEPWDM

PSWDM

River Input File Generator

5

6

4

Model StructureFiles

ExternalTransferModule 3

OptimizationRoutine

Land variableWDM

Final TextOutput

METWDM


1


1

2

6

ATDEPWDM



FertilizerManure

Legume fixationCrop uptake targets

ProcessParameter


Files

Calibration of land nutrients and sediment

OptimizationRoutine

Compare to literature values

Calibration of River Water Quality

Final TextOutput

River variableWDM

METWDM

ATDEPWDM

PSWDM

River Input File Generator

5

6

4

ProcessParameter


Files

OptimizationRoutine

Snapshot:


Hourly Values:


“Average AnnualFlow-Adjusted Loads”

Use of the Watershed model in Decision Making

Hourly output is summed over 10 years of hydrology to compare against other management scenariosHSPF

From the Chesapeake Bay Commission Report: Cost-Effective Strategies for the Bay

December, 2004

Nitrogen Load Indicator

Watershed model indicator of source sector for nitrogen loads to the Bay

Pollutant Reduction

Efforts

AllocationsExample

Section 1: What Do We Want to Achieve

Impaired Water

Note: Representation of 303(d) listed waters for nutrient and/or sediment water quality impairments for illustrative purposes only. For exact 303(d) listings contact EPA (http://www.epa.gov/owow/tmdl/). Unimpaired Water

Chesapeake Bay and Tidal TributaryNutrient and/or Sediment Impaired Waterbodies

Decision Support System

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ExceedenceData

Watershed Model

Bay Model

CriteriaAssessmentProcedures

Effects

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Airshed Model

Land UseChange Model

COAST

Nitrogen Pollution vs. Cost

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Judging Progress

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Nitrogen Load

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The Great Divide

Tier3

Drastic Option

Lower Potomac Estuary - Dissolved Oxygen - Deep Water

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Absolute Effect Normalized by load

Eff

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MD Western Shore

Patuxent

Potomac

Rappahannock

York

James

MD Eastern Shore

VA Eastern Shore

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Nitrogen Load

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Effect of Geographic Targeting

Tier3

Drastic Option

Effect of Geographic Targeting

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Nitrogen Load

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Drastic Option Efficient Option

Allocating Maximum Loads for Nutrient and Sediment Pollution

Susquehanna

VA Eastern Shore

Upper Eastern ShoreRapp

York

Potomac

James

Pax

Upper Western Shore


Maryland

Delaware

New York

District of Columbia

Virginia

West Virginia

Pennsylvania


Then running many scenarios to determine a reasonable plan for each area meet their nutrient goals

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TN TP SED

2010 Goal Reduction to meet goal 1985-2000 reduction

Climate change story

Estimated Climate Change Effects in the Chesapeake Region

In our region, temperatures are estimated to increase with a high degree of certainty, and precipitation to increase especially at higher rainfall events with a moderate degree of certainty.

How this effects flow in the watershed hangs in a hydrologic balance between precipitation and evapotranspiration.

About half the annual Chesapeake watershed precipitation inputs are lost by evapotranspiration.

Observed Temperature and Precipitation Trends (1901-1998)

Mean Annual Temperature

Red = increaseBlue = decrease

Green = increaseBrown = decrease

Annual Precipitation Total

Looking back over the observed record for the last century.

Source: Karl and Knight, 1998

Observed trends in precipitation by size class (percent per century, 1910-1996)

National Average

Global Climate Models (GCMs) Used

Seven Global Climate Models were used from the CARA analysis. These GCMs “differ in their output for a number of reasons, including spatial resolution in the atmosphere and ocean, treatments of land hydrology, and treatments of sea ice.” They are:

• CCCM – Canadian Centre for Climate Modeling and Analysis• CSIRO - Australia’s Commonwealth Scientific and Industrial

Research Organization • ECHM - German High Performance Computing Centre for Climate

and Earth System Research • GFDL - Geophysical Fluid Dynamics Laboratory• HDCM - Hadley Centre for Climate Prediction and Research• NCAR - National Center for Atmospheric Research• CCSR - Univ. of Tokyo, Center for Climate System Research/

National Institute for Environmental Studies

http://www.cara.psu.edu/climate/models_details.asp

http://www.cara.psu.edu/climate/models_details.asp

Two emission scenarios from the UN’s Intergovernmental Panel on Climate Change (IPCC) were used.

A2 emission scenario - A very heterogeneous world of economic growth where the underlying theme is self-reliance and preservation of local identities. Fertility patterns across regions converge slowly, which results in continuously increasing population. Economic development is primarily regionally oriented and per capita economic growth and technological change are more fragmented and slower than other storylines.

B2 emission scenario - A world in which the emphasis is on local solutions to economic, social, and environmental sustainability. It is a world with continuously increasing global population, but at a lower rate than A2, and with intermediate levels of economic development, and technological change. While the scenario is oriented toward environmental protection and social equality, it focuses on local and regional levels.

Projected CO2 concentrations using IPCC “SRES” storylines

uniform multiplier

flash upper 30

flash upper 10

Rationale for Different Methods of Modifying Precipitation

Climate Scenarios

• 7 models• 2 futures• = 14 scenarios for each precip method

• 3 precipitation methods– Chose high, medium, and low effect for each precip

method

• 9 bay-wide scenarios

}

Phosphorus Changes in Loads to the Chesapeake Bay

-12.0%

-10.0%

-8.0%

-6.0%

-4.0%

-2.0%

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2.0%

4.0%

6.0%

8.0%

10.0%

Flash 10 High Flash 10medium

Flash 10 Low Flash 30 High Flash 30medium

Flash 30 Low UniformMultiplier High

UniformMultiplierMedium

UniformMultiplier Low

Modeled Climate Effects on Bay Loading - Susquehanna

-6.8%-3.7%

-10.2%

-2.8%

-40%

-20%

0%

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80%

FLOW TOTN TOTP TSSX

Per

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m B

ase

Modeled Climate Effects on Bay Loading - Patuxent

-8.0%-1.9% -1.3%

10.9%

-40%

-20%

0%

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120%

FLOW TOTN TOTP TSSX

Per

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m B

ase

Modeled Climate Effects on Bay Loading - James

-4.2%-0.5% -1.5%

5.2%

-40%

-20%

0%

20%

40%

60%

80%

100%

120%

FLOW TOTN TOTP TSSX

Per

cen

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ge

fro

m B

ase

Modeled Climate Effects on Bay Loading - Total Watershed

-6.0%-1.6% -2.1%

4.9%

-40%

-20%

0%

20%

40%

60%

80%

100%

FLOW TOTN TOTP TSSX

Per

cen

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m B

ase

CBP Management Under A Changing Climate

Planning for long-term Bay restoration may involve the consideration of new questions:

• What are the potential impacts of climate change on water quality and living resources?

• How will our tributary strategies and other management actions perform under changing climatic conditions?

• What are the implications for water resources, such as water supply and flood control measures.

Model data interactions

• Direct calibration

• Models identify monitoring priorities spatially, temporally, and functionally

• Data analyses and empirical models (estimator, sparrow) can give a separate estimate of hindcast

M models

Data

e models

calibration

calibration

prio

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prio

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comparisons

Empirical vs mechanistic

• Empirical– Known accuracy– Limited to spatial/temporal range and scale of

the data

• Mechanistic– Can predict beyond the data– Unknown accuracy generally

2002 Chesapeake Bay Sediment

SPARROW

Load = B0 * {sources}

* B1 * {loss mechanisms}

Comparison of coefficients

• Sediment by acre– Construction : Agriculture : Forest

• Sparrow 1000 : 60 : 1• HSPF literature 1000 : 30 : 3

• Sediment total contribution– Urban : Ag : Forest : Stream

• Sparrow 26 : 62 : 5 : 7• HSPF 13 : 45 : 12 : 30

Checking model against estimator

• Load

• Trend

TN: USGS Estimator Model and P5 WSM

1.E+05

1.E+06

1.E+07

1.E+08

1.E+09N

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Estimator Load

WSM

Flow adjusted trend for TN through 2002

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James Rappa Appom Pamun Matta Susq Potm Patux Choptank

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Estimator

WSM

Integrating models with Data

• Chesapeake Bay Environmental Observatory

Models

User

Middleware

Data

Questions to Discuss

• Innovative uses of models

• How to integrate models and data– Intermediate empirical models– Model analysis of monitoring networks– Cyberinfrastructure– Hybrids (nudged models)

Topics

Documents

Transcript of Topics