Transcript document

Connecting Flooding
and Climatic Variability:
What are the
Missing Links?
Katie Hirschboeck
CUAHSI 2nd Biennial Science Meeting
Water Across Interfaces
18-21 July 2010
Is this evidence of climate change?
Annual Flood Series
Or this? . . . .
Annual Flood Series
These two
flood series
are from
neighboring
watersheds:
While increasing trends in extreme
precipitation in the United States and elsewhere have been observed,
(e.g., Groisman et al. 2001, Meehl et al. 2000)
. . . it is unclear whether similar trends have
occurred in extreme flooding.
Some studies have not seen any systematic
trends in peak streamflow; others have found
trends in some watersheds but not others. . .
(e.g., Lettenmaier et al. (1994), Lins & Slack (1999),
Douglas et al. (2000), Jain & Lall (2000), Kundzewicz &
Robson (2000, 2004), McCabe & Wolock (2002), Miller
& Piechota (2008), Villarini et al. (2009) . . . more!)
FLOOD HAZARD MANAGERS:
have been constrained in developing ways
to incorporate climate change information
operationally due to:
-- existing flood management policy
and practices
-- the short-term, localized, and
weather-based nature of the flooding
process itself
-- lack of a cohesive climate-based
explanation for observed variability . . .
with or without trends.
What’s needed . . . .
Information presented in an operationally
useful format for flood managers which
describes how changes in the large-scale
climatic “drivers” of hydrometeorological
extremes will manifest themselves in
flooding variability in
SPECIFIC WATERSHEDS 
5 Insights on Ways to Identify
Flood-Climate Linkages That Might
Otherwise Be Missed
1. Expanded understanding of climate
2. Process-sensitive “bottom-up”
approach
3. Peaks-above base vs. annual maxima
4. Regions of flood sensitivity to climate
5. Storm type, hierarchy, and basin scale
ARE WE THINKING ABOUT
CLIMATE IN THE BEST WAY ?
“Climate is what you expect,
weather is what you get.”
Robert A. Heinlein
“Indices”
“Normals”
HYDROMETEOROLOGY
 Weather, short time scales
 Local / regional spatial scales
 Forecasts, real-time warnings
vs.
HYDROCLIMATOLOGY
 Seasonal / long-term perspective
 Site-specific and regional synthesis of
flood-causing weather scenarios
 Regional linkages/differences identified
 Entire flood history context 
benchmarks for future events
HOW CAN WE THINK ABOUT
CLIMATE DIFFERENTLY ?
#1 Our understanding of
climate / climate variability
should be expanded beyond
statistical definitions to
include mechanistic, eventbased, weather components.
Synoptic Climatology—
as defined by Harman
& Winkler (1997):
Macroscale
Synoptic scale
“The study of
Mesoscale
climate from the
viewpoint of its
constituent weather
Storm
components or events
scale
and the way in which these
components are related to
atmospheric circulation at all scales.”
Meteorological &
climatological
flood-producing
mechanisms
operate at
varying temporal
and spatial scales
Circulation Pattern
 Storm type
 Hydrograph
The type of storm
(and its atmospheric
drivers) can
both influence
the shape of
the hydrograph and
the magnitude &
persistence of the
flood peak
Summer
convective event
Synoptic-scale
event
(typically cool season)
Tropical storm or
other extreme event
MIGHT THIS BE A WAY TO ADDRESS
THE NONSTATIONARITY ISSUE?
# 2 This expanded understanding
of climate can be linked to
flooding both deterministically
and probabilistically through a
process-sensitive “bottom
up” approach in which
individual peaks are grouped
according to their flood-causing
storm types and circulation
patterns.
Re-Examining the “iid”
Assumption
It all started with a newspaper ad . . .
THE FFA
“FLOOD PROCESSOR”
With expanded feed tube
– for entering all kinds
of flood data
including steel chopping,
slicing & grating blades
– for removing unique physical
characteristics, climatic
information, and outliers
plus plastic mixing blade
– to mix the flood
types together
The Standard iid Assumption for FFA
Flood Frequency
Analysis assumes
stationarity & “iid”
“ iid ” assumption: independently, identically distributed
Alternative Conceptual Framework:
Timevarying
means
Timevarying
variances
Mixed
frequency
distributions
may arise from:
• storm types
Both
• synoptic patterns
• ENSO, etc.
teleconnections
SOURCE: Hirschboeck, 1988 (inspired by Kisiel 1969)
• multi-decadal
circulation regimes
FLOOD HYDROCLIMATOLOGY
is the analysis of flood events within the
context of their history of variation
- in magnitude, frequency, seasonality
- over a relatively long period of time
- analyzed within the spatial framework
of changing combinations of
meteorological causative mechanisms
Hirschboeck, 1988
Flood Hydroclimatology Approach
 “ Bottom–Up ” Approach
(surface-to-atmosphere)
 Observed Gage Record
 Meteorological / Mechanistic /
Circulation-Linked
 Flood Hydroclimatology
Framework / Link
to Flood Distribution
3 EXAMPLES: Flood Hydroclimatology in AZ
Sample
Distributions of
Peaks-above-Base
(Partial Duration
Series) events:
Are there
climatically
controlled
mixed
populations
within?
Santa Cruz River at Tucson
Peak flows separated into
3 hydroclimatic subgroups
All Peaks
Tropical
storm
Winter
Sumer
Synoptic
Convective
Hirschboeck et .al. 2000
What does this time series look
like when classified
hydroclimatically?
What kinds of storms produced
the biggest floods?
Hydroclimatically classified time series . . .
Santa Cruz at Tucson
52700 (cfs)
50000
45000
C onv e ctiv e
Discharge in (cfs)
40000
Tropical S torm
35000
S y noptic
30000
25000
20000
15000
10000
5000
0
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
W ater Year
1970
1975
1980
1985
1990
1995
2000
Verde River below Tangle Ck
Peak flows separated into
3 hydroclimatic subgroups
Tropical
storm
All Peaks
Sumer
Convective
Winter
Synoptic
Hirschboeck et .al. 2000
Historical Flood
Sample frequency curve defined by
plotting observed flood magnitudes vs
their empirical probability plotting
positions, separated by flood type
Probability
analysis
based on
hydroclimatically
separated
flood series
Alila & Mtiraoui 2002
Empirical plotting positions
computed separately for
each hydroclimatic type
Annual flood
peaks only:
Thinking Beyond the Standard iid
Assumption for FFA . . . .
Based on these results
we can re-envision the
underlying probability
distribution function for
Arizona floods to be
not this . . . .
. . . but this:
Alternative Model to Explain How
Flood Magnitudes Vary over Time
Schematic for Arizona floods based
on different storm types
Varying mean and standard deviations
due to different causal mechanisms
HOW MIGHT CLIMATE
CHANGE AFFECT THESE
DISTRIBUTIONS?
Change in Frequency or
Intensity of Tropical Storms?
Some Important FloodGenerating Tropical
Storms
Tropical storm
Octave Oct 1983
Latitudinal Shifts in
Winter Storm Track?
Roosevelt Dam
Jan 1993
Sabino Creek
July 2006
Winter flooding
on Rillito in Tucson
More Intense Summer
Monsoon?
THE BOTTOM-UP
APPROACH . . .
TRADITIONAL DOWNSCALING:
Interpolation of GCM
results computed at
large spatial scale fields
to higher resolution,
smaller spatial scale
fields,
and eventually
to watershed processes
at the surface.
Hirschboeck 2003 “Respecting the Drainage Divide”
Water Resources Update UCOWR
“Scaling up from local data
is as important as scaling
down from globally forced
regional models.”
— Pulwarty, 2003
PROPOSED COMPLEMENTARY APPROACH:
RATIONALE FOR
PROCESS-SENSITIVE UPSCALING:
Attention to climatic driving forces & causes:
-- storm type seasonality
-- atmospheric circulation patterns
with respect to:
-- basin size
-- watershed boundary / drainage divide
-- geographic setting (moisture sources, etc.)
. . . can provide a basis for a cross-scale linkage
of GLOBAL climate variability
with LOCAL hydrologic variations
at the individual basin scale . . .
• Process-sensitive upscaling . . .
can define relationships that may not be
detected via precipitation downscaling
• Allows the imprint of a drainage basin’s
characteristic mode of interacting with
precipitation in a given storm type to be
incorporated into the statistics of the flow
event’s probability distribution as it is
“scaled up” and linked to model output
and /or a larger scale flow-generating
circulation pattern
CAN WE GET MORE OUT OF THE
RECORDS WE HAVE?
#3 A deeper understanding of
flood-climate linkages can be
obtained by examining all
observed flood peaks at a
given gauge (e.g., the peaksabove-base record), not just
the annual flood series.
Lins & Slack
(2005):
Increasing
trends
observed
primarily in
low –
moderate
flow quantiles
EXAMPLE: Some years have many
partial peaks, others few . . .
Interannual variability in #’s of partial peaks
La Niña years
El Niño years
Climate variability may manifest
itself in a shift to more frequent,
smaller floods in a given year
. . . which would be missed in
the annual series or a selection
of the most extreme floods.
CAN WE TARGET OUR
EXPLORATION MORE
STRATEGICALLY REGIONALLY?
#4 Watersheds located in transition
zones between climate regions,
or at the margins of influence by
a specific storm type are likely to
exhibit the greatest sensitivity to
climatic variability.
Precipitable Water Vapor & Moisture Pathways
Jan
Jul
Apr
Oct
Hirschboeck, 1991, Climate and floods, in USGS WSP 2375
always baroclinic
seasonal
always barotropic
seasonal
always baroclinic
Modified from: Hayden, B.P. (1988) Flood
Climates, Chapter 1 in: Baker, V.R.; Kochel, R.C.
and Patton, P.C., (eds). FLOOD GEOMORPHPLOGY
Map of “Flood Climates”
Hayden, B.P. (1988) Flood Climates, Chapter 1 in:
Baker, V.R.; Kochel, R.C. and Patton, P.C., (eds).
FLOOD GEOMORPHPLOGY
ARE THERE UNTAPPED CLIMATERELATED EXPLANATIONS FOR
WATERSHED RESPONSE,
PARTITIONING, & SCALING THEORY?
#5 The dominant flood-producing
storm type can vary with basin
size, elevation, and orographic
influence, resulting in a varied
response to climatic variability
depending on a basin’s scale and
hierarchical position.
Response to weather & climate varies
with basin size (e.g. convective events
are more important flood producers in
small drainage basins)
Huge opportunity to sort out the
interplay between basin scale,
hierarchical position, predominant
flood-producing storm type and
basin response . . .
See presentations of:
Jim Smith
Witold Krajewski
Mark Raleigh
Jessica Lundquist
Stephen Shaw
and others!
In closing . . .
How can we address some
of the missing links that
connect flooding
and climatic variability?
Move beyond the
“Flood Processor!
1. Expand mechanistic understanding of
climate
2. Use a process-sensitive “bottom-up”
approach
3. Take full advantage of peaks-above
base records
4. Target regions of flood sensitivity to
climate
5. Link all of the above to watershed
characteristcs . . . . and . . .
. . . let the rivers “speak for themselves”
about how they respond to climate !
Santa Cruz River at Tucson, Arizona