alan f. hamlet dennis p. lettenmaier
DESCRIPTION
Effects of Land Cover, Topography, and Climate on Pacific Northwest Flooding and Flood Forecasting. JISAO Center for Science in the Earth System Climate Impacts Group and Department of Civil and Environmental Engineering University of Washington January, 2004. - PowerPoint PPT PresentationTRANSCRIPT
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Alan F. HamletDennis P. Lettenmaier
JISAO Center for Science in the Earth System Climate Impacts Group
and Department of Civil and Environmental EngineeringUniversity of Washington
January, 2004
Effects of Land Cover, Topography, and Climate on Pacific Northwest Flooding and Flood Forecasting
http://www.hydro.washington.edu/Lettenmaier/Presentations/2004/hamlet_coastal_management_jan_2004.ppt
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Hydroclimatology of the Pacific Northwest
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Annual PNW Precipitation (mm)
Elevation (m)
The Dalles
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WinterPrecipitation
SummerPrecipitation
(mm)
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0.0
0.5
1.0
1.5
2.0
2.5
3.0
10 11 12 1 2 3 4 5 6 7 8 9
Month
No
rmal
ized
Str
eam
flow
SnowDominated
Transient Snow
Rain Dominated
Hydrologic Characteristics of PNW Rivers
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Temperature warms,precipitation unaltered:
•Streamflow timing is altered• Annual volume stays about the same
Precipitation increases,temperature unaltered:
•Streamflow timing stays about the same•Annual volume is altered
Sensitivity of Snowmelt and Transient Riversto Changes in Temperature and Precipitation
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
19
73
19
73
19
73
19
73
19
73
19
73
19
74
19
74
19
74
19
74
19
74
19
74
Water Year
Flo
w (
cfs
)
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
19
73
19
73
19
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19
73
19
73
19
73
19
74
19
74
19
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19
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19
74
19
74
Water Year
Flo
w (
cfs
)
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Characteristics of Flooding Events West and East of the Cascades
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Coastal and Transient Snow Basins(West of the Cascades)
Flooding frequently occurs in Nov-Dec when intense rain storms with temperatures above freezing are most likely.
In so-called “Rain on Snow” events that produce severe flooding, the presence of snow is actually not the major driver. Instead, intense and sustained precipitation over enlarged basin areas (due to warm temperatures) with fully saturated soils produce the major component of the runoff in the largest events.
In moderate flooding events, snow melt and precipitation tend to be more comparable in their contribution to peak streamflows and antecedent snowpack is more important.
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Cold Warm
Effective basin area contributing direct runoff to the river channel system increases in warm winter storm events.
Skagit River Basin
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Snow Melt Dominant Basins (East of the Cascades)
Flooding mostly occurs in spring when snow melt peaks.
Severe flooding can result from extraordinarily heavy snowpacks over large spatial areas (e.g. WY 1997), rapid snowmelt due to extremely warm or clear weather, or from a combination of sustained snow melt and heavy precipitation (e.g. the Vanport Flood in 1948).
Moderate snowmelt floods can have much longer duration in comparison with flooding produced by individual rain storms.
Note that huge snowpacks do not necessarily produce severe flooding in spring (e.g. WY 1999).
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Effects of Land Cover on Flooding in the Pacific Northwest
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Urbanization (increased impervious surfaces and removal of active soil storage during development)
•Altered streamflows:Increased magnitude and “flashiness” of peak flowsMore rapid recession and lower base flows in late summer
•Stream channel erosion and instability
•Capacity problems in storm water drainage systems
•Ecological problems due to erosion, scouring, or increased nutrient and sediment loadings
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Source: Booth D.B., 2000, Forest Cover, Impervious-Surface Area, and the Mitigation of Urbanization Impacts in King County, WAhttp://depts.washington.edu/cwws/Research/Reports/forest.pdf
Typical Effects of Urbanization on a Small Watershed Des Moines Creek
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Effects of Logging and Road Networks
•Loss of forest canopy increases total snow accumulation
•Increased exposure to wind and solar radiation increases melt rates
•Road building and culverts alter natural drainage networks creating “pipes” to the stream channel which increase peak flows during moderate flooding events
•Loss of vegetation can produce larger sediment loads or trigger debris flows
•Effects of logging and road building are roughly additive.
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Source: Storck, P., 2000, Trees, Snow and Flooding: An Investigation of Forest Canopy Effects on Snow Accumulation and Melt at the Plot and Watershed Scales in the Pacific Northwest, Water Resources Series Technical Report No. 161, Dept of CEE, University of Washington
Effects of Forest Canopy on Snow Accumulation
Loss of canopy increases the snow water equivalent and increases the rate of melt.
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Sources: Storck, P., 2000, Trees, Snow and Flooding: An Investigation of Forest Canopy Effects on Snow Accumulation and Melt at the Plot and Watershed Scales in the Pacific Northwest, Water Resources Series Technical Report No. 161, Dept of CEE, University of WashingtonBowling, L.C., P. Storck and D.P. Lettenmaier, 2000, Hydrologic effects of logging in Western Washington, United States, Water Resources Research, 36 (11), 3223-3240
Modeling studies (Storck 2000) and comparative analysis of observations in paired catchments (Bowling et al. 2000) show that large scale clearcutting results in increased flood peaks on the order of 10% for small basins in the transient snow zone of the Cascades.
Effects of Harvest Strategies on Magnitude of Flood Peaks
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Bowling, L.C. and Lettenmaier, D.P., 1997, Evaluation of the Effects of Forest Roads on Streamflow in Hard and Ware Creeks, Washington, Water Resources Series Technical Report No. 155, Dept of CEE, University of Washington
Bowling and Lettenmaier (1997) estimated that the 10-yr flood peak increased ~10% in two small transient snow basins due to road networks alone.
Roads and logging together were estimated to increase the 10-yr flood peak on the order of 20% in the same two small transient snow basins.
Effects of Roads Networks on Peak Flows
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Effects of Climate Variability on Flooding in the Pacific Northwest
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A history of the PDOwarm
coolwarm
A history of ENSO
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Pacific Decadal Oscillation El Niño Southern Oscillation
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150000
200000
250000
300000
350000
400000
450000
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0
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0
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0
195
0
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0
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0
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0
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0
200
0
Ap
r-S
ept F
low
(cfs
)
Effects of the PDO and ENSO on Columbia River Summer Streamflows
Cool CoolWarm Warm
PDO
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150000
200000
250000
300000
350000
400000
450000
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Probability of Exceedence
Flo
w (
cfs)
WarmPDO/WarmENSO
WarmPDO/ENSONeut
WarmPDO/CoolENSO
CoolPDO/WarmENSO
CoolPDO/ENSONeut
CoolPDO/CoolENSO
Naturalized Summer Streamflow at The Dalles
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Selection Criteria:
•Unregulated Streams
•Daily Flow Records
•Records 57-65 Years Long
Pacific Northwest Streamflow Records Selected for Flood Analysis
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Daily Flow Data w/ Threshold (1986-1996)Dungeness R near Sequim, WA
0
1000
2000
3000
4000
5000
6000
10
/1/8
5
3/1
9/8
6
9/4
/86
2/2
1/8
7
8/9
/87
1/2
4/8
8
7/1
1/8
8
12
/27
/88
6/1
4/8
9
11
/30
/89
5/1
8/9
0
11
/3/9
0
4/2
1/9
1
10
/7/9
1
3/2
4/9
2
9/9
/92
2/2
5/9
3
8/1
3/9
3
1/2
9/9
4
7/1
7/9
4
1/2
/95
6/2
0/9
5
12
/6/9
5
5/2
3/9
6
Date
Flo
w (
cfs
)
daily flow
threshold
Daily Flow Data w/ Threshold (Oct.1,1990-Nov.30,1990)Dungeness R near Sequim, WA
0
1000
2000
3000
4000
5000
6000
10
/1/9
0
10
/4/9
0
10
/7/9
0
10
/10
/90
10
/13
/90
10
/16
/90
10
/19
/90
10
/22
/90
10
/25
/90
10
/28
/90
10
/31
/90
11
/3/9
0
11
/6/9
0
11
/9/9
0
11
/12
/90
11
/15
/90
11
/18
/90
11
/21
/90
11
/24
/90
11
/27
/90
11
/30
/90
Date
Flo
w (
cfs
)
daily flow
thresholdData Processing Methods
•Determine mean annual flood for each basin
•Set threshold and reset value
•Determine number of peaks above threshold for each climate category
•Estimate probability of event above threshold for each basin and climate category
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Transient Snow Basins
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
EwPw EnPw EcPw EwPc EnPc EcPc
Climate Category
Pro
ba
bili
ty o
f F
loo
d E
ve
nt
Ab
ov
e
Th
res
ho
ld
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Snow-Dominant Basins
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
EwPw EnPw EcPw EwPc EnPc EcPc
Climate Category
Pro
ba
bili
ty o
f F
loo
d E
ve
nt
Ab
ov
e
Th
res
ho
ld
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Effects of Climate Change on the Pacific Northwest
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Precipitation Fraction, 2020s
0.5
0.75
1
1.25
1.5
1.75
J F M A M J J A S O N D
Frac
tion
hadCM2
hadCM3
PCM3
ECHAM4
mean
Delta T, 2020s
-1
0
1
2
3
4
5
J F M A M J J A S O N D
De
gre
es
C
hadCM2
hadCM3
PCM3
ECHAM4
mean
Delta T, 2040s
-1
0
1
2
3
4
5
J F M A M J J A S O N D
De
gre
es
C
hadCM2
hadCM3
PCM3
ECHAM4
mean
Precipitation Fraction, 2040s
0.5
0.75
1
1.25
1.5
1.75
J F M A M J J A S O N D
Fra
ctio
n
hadCM2
hadCM3
PCM3
ECHAM4
mean
Four Delta Method Climate Change Scenarios for the PNW
~ + 1.7 C ~ + 2.5 C
Somewhat wetter winters and perhaps somewhat dryer summers
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ColSimReservoir
Model
VICHydrology Model
Changes in Mean Temperature and
Precipitation or Bias Corrected Output
from GCMs
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Current Climate 2020s 2040s
Snow Water Equivalent (mm)
VIC Simulations of April 1 Average Snow Water Equivalentfor Composite Scenarios (average of four GCM scenarios)
The main impact: less snow
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Regulated Flow
Historic Naturalized Flow
Estimated Range of Naturalized FlowWith 2040’s Warming
Naturalized Flow for Historic and Global Warming ScenariosCompared to Effects of Regulation at 1990 Level Development
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0
1000
2000
3000
4000
5000
6000
7000
8000
900010
/1
10/2
9
11/2
6
12/2
4
1/21
2/18
3/18
4/15
5/13
6/10 7/8
8/5
9/2
Date
Infl
ow
(ac
re-f
t) Simulated 20thCentury Climate
2020s ClimateChange Scenario
2040s ClimateChange Scenario
Effects to the Cedar River (Seattle Water Supply)for “Middle-of-the-Road” Scenarios
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Observed Climate Change:
Trends in Temperature, Precipitation, Snowpack, and Streamflow
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Area-weighted Regional Avg=1.5 F/century
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Annual Precipitation TrendsFrom HCN stations
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Relative Trends in April 1 Snow Water Equivalent 1916-1997
Relative Trend %/yrRelative Trend %/yr
Ele
vatio
n (m
)
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Trends in Annual Streamflow at The Dalles from 1858-1998 are strongly downward.
0
50000
100000
150000
200000
250000
300000
350000
1858
1868
1878
1888
1898
1908
1918
1928
1938
1948
1958
1968
1978
1988
1998
An
nu
al M
ean
Flo
w (
cfs)
Annual
5 yr mean
10 yr mean
Linear (Annual)
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Some Conclusions Regarding Planning, Project Design
Specifications, and Flood Forecasting
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“Past Performance is not a Good Measure of Future Performance.”
Estimates of flood probability distributions and design specifications (e.g. the “100 year” or “1% likelihood” flood) are a complex function of land surface characteristics, interannual and decadal scale climate variability, long-term climate variations (such as global warming), and water management policies, all of which are non-stationary in time.
For convenience, estimates of flood design specifications have traditionally been based on fixed periods of the historic record.
In the case of expensive or long-lived structures or for planning processes that should be robust to climate variability and climate change, the use of the historic record for flood estimation is problematic both because of relatively small sample size and changing conditions over time.
Note that in the case non-stationary conditions over time, longer streamflow records do not necessarily improve estimates of flood frequencies.
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Problems with Forecasting Applications Based on Statistical Relationships
Many operational streamflow forecasting applications are currently based on statistical relationships between weather or climate forecasts, snowpack measurements, and streamflow.
When land cover of the basin or climate conditions change, the skill of these forecasts can be impaired. Such problems cannot be resolved in the short term because there is no training data available for the altered conditions.
These problems have serious implications both for short term flood forecasting applications and forecasts used for water management at seasonal time scales.
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Current or Projected Land Surface
Conditions
Current or Projected Meteorological Data
Hydrologic Model
Updated or ProjectedStreamflowTime Series
Design CriteriaForecasts
Planning Scenarios
Use of dynamic models can improve estimates of hydrologic design specifications and short-term and seasonal streamflow forecasts.