Stockholm Environment Institute

Natural Heritage Institute

CABY Watershed Modeling with WEAP

CABY Planning MeetingMay 6 2006David Purkey and David Yates

Application of WEAP to the American River Basin

Catchment Delineation

• Based on six digit hydrologic units (HUC6).

• HUCs were subdivided if necessary to calculate inflows to key reservoirs.

• In addition to 56 catchments in the American River Basin, the Camp Creek and Sly Park Creek catchments were added to compute inflow to Jenkinson Lake.

American River Basin

Major Streams in Basin

Model Catchments

Catchment Characterization

• Land was categorized using the SSURGO soils and the CALVEG vegetation databases.– Soils were classified as shallow or deep.

– Vegetation was classified as trees, shrubs, bare, urban, grassland, or wet.

• Resulting classifications were– Deep trees

– Shallow trees

– Deep shrubs

– Etc.

Modeled Rivers

Modeled Reservoirs

Aloha

Hell Hole

Loon Lake

Echo

French Meadows

Caples & SilverFolsom

Union Valley

Ice House

Sly Park

Stumpy Mdw

Modeled Transfers

Climate Data

• DAYMET.org (Univ. Montana & NCAR) – Daily, 1-km gridded data were mapped o the

centroids of each suib-catchment– Precipitation, temperature, humidity, and wind.

• Data were developed using observed climate data and terrain models.

Middle Fork Project

Upper American Project

El Dorado Irrigation District

Calibration Results

North Fork American at North Fork Dam

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Climate Change (and other) Scenarios in WEAP

Probabilistic assessment of regional climate change

A Bayesian approach that combines predictions from multiple AOGCM output (21 models)

Probabilistic representation of temperature/precipitation change, at regional scales, incorporating natural variability

Reconciles projections from different AOGCMs

BIAS and CONVERGENCE criteria:

Reward models that perform well in reproducing current climate/

discount models that show a large bias

Reward models that form a consensus/downweight extreme

Projections

Avoids the Problems of being “Married” to individual GCM!!

Climate Scenarios- Probabilistic Projections

A1B Seasonal Changes for Northern California from 21 AOGCMs

Precipitation

Winter Spring Summer Fall

Winter- equal likelihood of more or less precip.; no strong long term trend

Spring, Summer Fall- more likelihood of less precip.

Climate Scenarios- Probabilistic Projections

Temperature

Winter Spring Summer Fall

A1B Seasonal Changes for Northern California from 21 AOGCMs

Early 21st Century warming of 0.8C

Natural variability could mask early 21st century anthropogenic warming.

Climate Scenarios - Probabilistic Projections

• These probabilistic projections are useful, for getting a “feel” for the climatic range suggested by AOGCM models.

• BUT.. How do we use this information given impact assessment needs?

• Impact assessment models need “REAL DATA” .. E.g. Climate time series, such as temperature, precipitation, wind, humidity, etc.

This is the downscaling process…

Single Climate Scenario Instance Moderate Warming and Drying

1011121314151617181920

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Hist Avg PcpHist Avg. Tmp

Yates et al. 2003, A K-nn algorithm for generating regional climate scenarios, WRR

Climate Scenarios- Probabilistic Projections

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Avg Temp Alder_C A1B Wm Dry_5

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Monthly Avg. Temperature for Alder Creek - 2010 to 2030

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Monthly Total Precipitation Data for Alder Creek – 2010 to 2030

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Total ppt Alder_C A1B Wm Wet_1

North and Middle Forks

French Meadows

Hell Hole

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Climate Change and Hydropower for the main projects

An ensemble of climate projections and their impacts on hydropower

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Headline: Even Wet scenarios suggest a decline in production with given operating rules.

Project Storage

Total Avg. Weekly Storage (UARP)

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Total Avg. Weekly Storage- Middle Fork Project

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North Fork Water Temps- Unmanaged Watershed

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Middle Fork Water Temps – Managed Watershed

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