Lecture 15: Flood Mitigation and Forecast ModelingLecture 15: Flood Mitigation and Forecast Modeling. Key Questions. 1. What is a 100-year flood inundation map? 2. What is a levee

Lecture 15: Flood Mitigation and Forecast ModelingKey Questions1. What is a 100-year flood inundation map?

2. What is a levee and a setback levee?

3. How are land acquisition, insurance, emergency response used to mitigate a flood

4. How is streamflow forecasting used to mitigate a flood?

5. What is the difference between weather and climate?

6. What has caused the climate to change in the last 100 years?

7. How will future climate impact snow andstreamflow in the Nooksack basin?

Niigata Japan, 1964 liquefaction

Nooksack River

100-year Floodplain Map

Mitigation: 100 Year Flood Map

Mitigation: Structural Techniques

1. Levees are engineered embankments designed to contain the river

Mitigation: Structural Techniques

Levees are designed to contain floods along most of the lower Nooksack (floods that range from 5 to 100 year return periods)

levee

Mitigation: Setbacks Levees

The Soldiers Home Setback Levee on the Puyallup River near Orting.

Mitigation: Structural Techniques

2. Dams can store and slowly release water

storage capacity

monitored release

Δ

=

Mitigation: Land Acquisition

Mitigation: Nooksack River

Mitigation: Insurance

Mitigation: Emergency Response

Mitigation: Forecast Modeling

Modeling the effects of climate change forecasts on streamflow in the Nooksack River basin

Climate versus Weather

Weather: short-term, local variations in atmospheric conditions (one monthly average represents weather)

Average January temperatures at the Clearbrook weather station.

Climate versus Weather

Climate: long-term average weather conditions (30 years or longer)(collection of monthly values represents climate)

Average January temperatures at the Clearbrook weather station.

What does the trend line indicate?

http://www.globalwarmingart.com/wiki/File:1000_Year_Temperature_Comparison_png#Description

Reconstructed temperatures for the past 2000 years

http://www.globalwarmingart.com/wiki/File:1000_Year_Temperature_Comparison_png#Description

Measured temperatures for the past 200 years

n = 3146

97% of active, publishing climatologists think human activities have changed the climate

Greenhouse Gases

Greenhouse Effect: CO2 and other greenhouse gases trap radiated heat from the Earth and increase the temperature

http://www.esrl.noaa.gov/gmd/outreach/carbon_toolkit/basics.html

Anthropogenic (human) causes for increased CO2

Burning of fossil fuels

Deforestation

CO2 source

trees are a CO2 sink

http://www.epa.gov/climatechange/

South Cascade Glacier

1960

1928 2000

One of three benchmark Glaciers that have been established in a USGS glacier monitoring program

South Cascade Glacier

One of three benchmark Glaciers that have been established in a USGS glacier monitoring program

Mote et al. (2008)Averaged sea level at stable tide gauge sites

Futuristic CO2 Emission Scenarios

General Circulation Models (GCM)

Emission Scenarios

About 40 institutions world wide run GMCs

Modeled Temperature Predictions based on different CO2 emission scenarios

GCM: NASA’s GISS model

Modeling the effects of climate change forecasts on streamflow in the Nooksack River basin

Goal of ResearchTo predict impact of climate change on snowpack and streamflow in the Nooksack River basin

The Nooksack River is a snow dominated basin that is sensitive to temperature changes

Discharge at North Cedarville, WAWater Year 2009 (Oct 2008 – Sept 2009)

spring peak due to snowmelt

Time

Hydrograph

Time

Hydrograph

snow packno snowpack so rain falls on exposed bedrock and thin, wet soils and produces a high peak

more volume but less peaked

HydrographHydrograph

Approach

Predicted climate data

Predict Future:

Snow Water Equivalent (SWE)

Streamflow

Peak FlowsHydrology model

DHSVM

Spatial characteristics of

the Nooksack River basin

Data processing

Methods

1. Hydrologic Model Set-up, Calibration, & Validation

2. Downscaling & Validation of Climate Change Forecasts

3. Hydrologic Modeling

Methods: DHSVMDistributed Hydrology Soil Vegetation Model

DHSVM calculates a water and energy budget on each grid cell for each time step

inputs - outputs = change in storage

The DHSVM also predicts snow accumulation and melt

Methods: DHSVM

Spatial Input• DEM

• Watershed Boundary

• Stream Network

• Soil Thickness

• Soil Type

• Landcover

Methods: DHSVM

Meteorological Input• Temperature

• Precipitation

• Wind Speed

• Relative Humidity

• Shortwave Radiation

• Longwave Radiation

North Shore Weather Station, Lake Whatcom

DHSVM: Streamflow Calibration

Photo: USGS

Calibration – adjustment of model parameters to mimic an observed dataset

USGS Stream gauge at Cedarville

DHSVM: Calibration

Initial Simulation

After Calibration

010

000

3000

0

Nooksack River, WY 06-07

Date

Dai

ly M

ean

Stre

amflo

w (c

fs)

1Jan2006 2Jul2006 1Jan2007 2Jul2007

Cedarville - observedCedarville - simulated

010

000

3000

0

Nooksack River, WY 06-07

Date

Dai

ly M

ean

Stre

amflo

w (c

fs)

1Jan2006 2Jul2006 1Jan2007 2Jul2007

Cedarville - observedCedarville - simulated

DHSVM: Calibration & Validation

Validation – comparison of simulated data with observed data for a time period not included in the calibration

010

000

2000

030

000

4000

050

000

Nooksack River, WY 06-09

Date

Dai

ly M

ean

Stre

amflo

w (c

fs)

1Jan2006 1Jan2007 1Jan2008 1Jan2009

Cedarville - observedCedarville - simulated

calibration validation

DHSVM: SWE Calibration

Photo: NRCS

Calibration – adjustment of model parameters to mimic an observed dataset

Snotel Stations

DHSVM: Calibration & Validation

01

23

4

Wells Creek Snotel (NF), WY 06-09

Date

Dai

ly M

ean

SW

E (m

)

1Jan2006 1Jan2007 1Jan2008 1Jan2009

observedsimulated

01

23

4

Middle Fork Snotel, WY 06-09

Date

Dai

ly M

ean

SW

E (m

)

1Jan2006 1Jan2007 1Jan2008 1Jan2009

observedsimulated

Methods

1. Hydrologic Model Set-up, Calibration, & Validation

2. Downscaling & Validation of Climate Change Forecasts

3. Hydrologic Modeling

IPCC 2001

Emissions Scenarios

Methods: Climate Change Forecasts

2040s Changes in Temperature and PrecipitationMote and others, 2005

Three General Circulation Models (GCMs) :

1. IPSL_CM4_A2Institut Pierre Simon Laplace (with A2)

2. Echam5_A2Max Planck Institute for Meteorology (with A2)

3. GISS_ER_B1Goddard Institute for Space Studies (with B1)

GCM scale of 100s km regional scale of 10s km local station

Methods: GCM Downscaling

CIG, 2010

Monthly time scale

Methods: GCM Downscaling

April Mean Temperature

Mean Temperature (C)

Freq

uenc

y

7 8 9 10 11 12

02

46

810

6 7 8 9 10 11 12

0.0

0.2

0.4

0.6

0.8

1.0

April eCDF

Mean Temperature (C)

Non

-Exc

eeda

nce

Pro

babi

lity

Abbotsford, 1950-1999

Empirical Cumulative Distribution Functions (eCDF)

Methods: GCM Downscaling

6 8 10 12 14

0.0

0.2

0.4

0.6

0.8

1.0

April eCDFs

Mean Temperature (C)

Non

-Exc

eeda

nce

Pro

babi

lity

Abbotsford, 1950-19992050s GISS Forecast, 2035-2065

Shift 50-year historical time series based on 31-year

forecast period

Result: 50-year forecast

6 8 10 12 14

0.0

0.2

0.4

0.6

0.8

1.0

April eCDFs

Mean Temperature (C)

Non

-Exc

eeda

nce

Pro

babi

lity

Abbotsford, 1950-1999GISS Forecast, 2035-2065Combined 2050s Forecast

Methods: GCM Downscaling

Each forecast is based on the Abbotsford time series

0 100 200 300 400 500 600

-10

010

2030

Monthly Mean Temperature, 1950-1999

Month

Tem

pera

ture

(C)

AbbotsfordGISS_B1 2050 Forecast

Methods: GCM Downscaling

Each forecast is based on the Abbotsford time series

0 100 200 300 400 500 600

-10

010

2030

Monthly Mean Temperature, 1950-1999

Month

Tem

pera

ture

(C)

AbbotsfordGISS_B1 2050 Forecast

Methods: Validation of Downscaling

1 2 3 4 5 6 7 8 9 10 11 12

-10

010

20

Monthly Mean Temperature, 1950-1999

Month

Tem

pera

ture

(C)

-10

010

20-1

00

1020

-10

010

20

AbbotsfordGISS_B1Echam_A2IPSL_A2

12

34

56

7

median

outlier

25th – 75th percentiles

minimum

Methods: Local Forecasts

1 2 3 4 5 6 7 8 9 10 11 12

-10

010

2030

Monthly Mean Temperature - 2050

Month

Tem

pera

ture

(C)

-10

010

2030

-10

010

2030

-10

010

2030

AbbotsfordGISS_B1ECHAM_A2IPSL_A2

Methods: Local Forecasts

1 2 3 4 5 6 7 8 9 10 11 12

010

020

030

040

050

060

0

Total Monthly Precipitation - 2050

Month

Pre

cipi

tatio

n (m

m)

010

020

030

040

050

060

00

100

200

300

400

500

600

010

020

030

040

050

060

0 AbbotsfordGISS_B1ECHAM_A2IPSL_A2

Methods: Processing of Forecasts

1. Apply monthly ΔT to daily Abbotsford data

2. Disaggregate daily data to a 3-hour time step

3. Derive other 3-hour meteorological input from temperature and precipitation

• Shortwave Radiation

• Longwave Radiation

• Windspeed

• Relative Humidity

Methods

1. Hydrologic Model Set-up, Calibration, & Validation

2. Downscaling & Validation of Climate Change Forecasts

3. Hydrologic Modeling

Approach

Predicted climate data

Predict Future:

Snow Water Equivalent (SWE)

Streamflow

Peak FlowsHydrology model

DHSVM

Spatial characteristics of

the Nooksack River basin

Data processing

Results: SWE

1 2 3 4 5 6 7 8 9 10 11 12

01

23

45

Monthly Mean SWE at MF Snotel - IPSL_A2

Month

SWE(

m)

1950-19992000202520502075

1 2 3 4 5 6 7 8 9 10 11 12

01

23

45

Monthly Mean SWE at MF Snotel - GISS_B1

Month

SWE(

m)

1950-19992000202520502075

Results: SWE

2 4 6 8 10 12

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Monthly Mean SWE at MF Snotel - GISS_B1

Month

SWE

(m)

1950-19992000202520502075

2 4 6 8 10 12

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Monthly Mean SWE at MF Snotel - IPSL_A2

Month

SWE

(m)

1950-19992000202520502075

Results: Streamflow

1 2 3 4 5 6 7 8 9 10 11 12

050

0010

000

1500

020

000

Monthly Median Streamflow - IPSL_A2

Month

Stre

amflo

w (c

fs)

1950-19992000202520502075

1 2 3 4 5 6 7 8 9 10 11 12

050

0010

000

1500

020

000

Monthly Median Streamflow - GISS_B1

Month

Stre

amflo

w (c

fs)

1950-19992000202520502075

Results: Streamflow

2 4 6 8 10 12

020

0060

0010

000

Monthly Median Streamflow - IPSL_A2

Month

Stre

amflo

w (c

fs)

1950-19992000202520502075

2 4 6 8 10 12

020

0060

0010

000

Monthly Median Streamflow - GISS_B1

Month

Stre

amflo

w (c

fs)

1950-19992000202520502075

Results: Peak Flow Events

0e+0

04e

+04

8e+0

4

Annual Peak Flows (WY 1951-1999) - IPSL_A2

Stre

amflo

w (c

fs)

Ferndale-observedCedarville-simulated2000202520502075

0e+0

04e

+04

8e+0

4Annual Peak Flows (WY 1951-1999) - GISS_B1

Stre

amflo

w (c

fs)

Ferndale-observedCedarville-simulated2000202520502075

Results: Peak Flow Events

IPSL_A2 2000

Month

Freq

uenc

y

0 2 4 6 8 10

010

2030

40

IPSL_A2 2025

Month

Freq

uenc

y

0 2 4 6 8 10

010

2030

40

IPSL_A2 2050

Month

Freq

uenc

y

0 2 4 6 8 10

010

2030

40

IPSL_A2 2075

Month

Freq

uenc

y

0 2 4 6 8 10

010

2030

40

Simulated Peaks Above 30,000 cfs

Forecast Period

Freq

uenc

y

2000 2025 2050 2075

020

4060

8010

0

GISS_B1Echam_A2IPSL_A2

Temperature or Precipitation?

• Predicted increases in temperature and precipitation

• More agreement on temperature trends

• Previous regional studies indicate that temperature is the driving factor in changes to SWE(Hamlet et al., 2005, Mote et al., 2005, Mote et al., 2008)

1 2 3 4 5 6 7 8 9 10 11 12

-10

010

2030

Monthly Mean Temperature - 2075

Month

Tem

pera

ture

(C)

-10

010

2030

-10

010

2030

-10

010

2030

AbbotsfordGISS_B1ECHAM_A2IPSL_A2

1 2 3 4 5 6 7 8 9 10 11 12

010

020

030

040

050

060

0

Total Monthly Precipitation - 2075

Month

Pre

cipi

tatio

n (m

m)

010

020

030

040

050

060

00

100

200

300

400

500

600

010

020

030

040

050

060

0 AbbotsfordGISS_B1ECHAM_A2IPSL_A2

Conclusions

• SWE will decrease

• Timing of peak SWE and of the spring melt peak in the hydrograph will move earlier in the year

• Winter streamflow will increase, summer streamflow will decrease

• Peak flow events will increase in magnitude and frequency

• Extent of change depends on temperature change

Photo: John Scurlock