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Italian Journal of Engineering Geology and Environment - Book www.ijege.uniroma1.it © 2011 Casa Editrice Università La Sapienza
855
DOI: 10.4408/IJEGE.2011-03.B-093
IMPLEMENTATION OF POST-FIRE DEBRIS-FLOW HAZARD
ASSESSMENTS ALONG DRAINAGE NETWORKS,
SOUTHERN CALIFORNIA, U.S.A.
J
osePH
E. GARTNER
(*)
, s
usan
H. CANNON
(*)
& P
aul
M. SANTI
(**)
(*)
U.S. Geological Survey
(**)
Colorado School of Mines
intermountain western USA (s
tevens
et alii, 2008;
C
annon
et alii, 2010). These multi-variate models
estimate probabilities and volumes of debris flows us-
ing combinations of predictive variables that describe
the extent and severity of fire within a drainage basin,
the drainage basin morphology and soil characteris-
tics, and storm rainfall characteristics. These models
are specific to particular geographic regions and fire
regimes. Some models can be used to estimate debris-
flow susceptibility within the first few years follow-
ing a fire (e.g. G
aRtneR
et alii, 2008; C
annon
et alii,
2009; 2010), and some models define time-dependent
factors to quantify the diminishing effect of fire on de-
bris-flow susceptibility, allowing the model to be ap-
plied over a range of timescales following a fire (e.g.,
G
atwood
et alii, 2000; G
aRtneR
et alii, 2009).
The multi-variate, debris-flow susceptibility mod-
els are presently implemented in a geographic infor-
mation system (GIS) by identifying specific drainage
basin outlets, and then extracting the measures of
the model input variables for the drainage basin ar-
eas upstream from the drainage basin outlets. These
measures, along with specified design storm rainfall
conditions, are then used to estimate the probability
and volume of debris flow for each identified drainage
basin outlet (Fig. 1). Although this approach can be
used to identify debris-flow susceptibility for specific
locations, it provides only a single estimate for each
drainage basin, and thus does not reflect the range of
debris-flow hazards that may exist upstream of the
ABSTRACT
Burned watersheds in Southern California stee-
plands can be particularly susceptible to debris flow.
Rapid assessments of potential debris-flow hazards
following a fire are necessary to provide timely infor-
mation to the public, land managers, and emergency-
response agencies about locations most prone to debris-
flow impact. Here we present a method to implement
a set of existing debris-flow susceptibility models
along a drainage network using input variables that are
quantified for the contributing drainage basin areas to
each grid cell along a drainage network. This method
accounts for the spatially variable properties within
contributing drainage basin areas as debris flows travel
through the drainage network. Applying the models
along drainage networks, rather than to an entire drain-
age basin, provides hazard assessments that identify the
potential impacts within the primary channels of a wa-
tershed, where destructive debris flows may both erode
and deposit large volumes of material.
K
ey
words
: debris-flow susceptibility, post-fire erosion, drai-
nage networks, continuous variables
INTRODUCTION
Empirical models that provide estimates of the
probability and magnitude of post-fire debris flows
are currently used to assess hazards from recently
burned drainage basins in southern California (e.g.
C
annon
et alii, 2009; C
annon
et alii, 2010), and the
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J.E. GARTNER, S.H. CANNON & P.M. SANTI
856
5th International Conference on Debris-Flow Hazards Mitigation: Mechanics, Prediction and Assessment Padua, Italy - 14-17 June 2011
able grids are then used as input to the susceptibility
models to generate estimates of debris-flow probabil-
ity and volume for each grid cell along the drainage
network. Ranked output from the debris-flow volume
and probability models are added together to generate
a combined relative debris-flow hazard ranking.
The application of debris-flow susceptibility
models along drainage networks allows for a spatially
specific assessment of potential debris-flow suscepti-
bilities within a burned area. Maps that identify haz-
ardous locations within the drainage network may be
used to help guide post-fire debris flow mitigation
plans and plan emergency evacuation routes. Fur-
ther, such an application provides a means to estimate
how debris-flow volumes change as they travel down
drainage networks.
In this paper, we describe the basis and form of
existing debris-flow susceptibility models, followed
by a discussion of the process used to generate the
continuous variable grids used as data input to the
models. We then present results of an assessment for
a hypothetical drainage basin. Within this basin, we
identify several locations within the drainage network
where estimates of debris-flow probability, debris-
flow volume, and combined relative debris-flow haz-
ard ranking could be beneficial. This example dem-
onstrates how the continuous variable approach for
applying debris-flow susceptibility models provides
spatially specific information on debris-flow suscep-
tibilities within a burned drainage basin.
As more data becomes available and the understand-
ing of post-fire debris-flow processes increases, the em-
drainage basin outlet. Debris-flow impacts within a
drainage basin will be greatest in the channels through
which a debris flow travels, eroding and depositing
material, and on the fan below the drainage basin
outlet where material is deposited. In addition, if as-
sessments of debris-flow probability and volume are
needed for multiple locations along a channel, then
the process of identifying each drainage basin outlet,
delineating drainage basins, and obtaining measures
for the input variables used in the models is labor in-
tensive and time-consuming. Last, this approach iden-
tifies debris-flow hazards only in flow-accumulating
terrain, so that hazards in inter-basin areas are not as-
sessed, as in Fig. 1.
OBJECTIVES AND APPROACH
We present a new method for implementing de-
bris-flow susceptibility models that better characteriz-
es potential hazards within recently burned areas than
the present drainage-basin wide approach. With this
new method, termed the continuous variable method,
we generate sets of continuous variable grids to im-
plement the debris-flow susceptibility models along
the drainage network. The continuous variable grids
provide measures of the model input variables for
each grid cell along a drainage network based on the
upstream conditions (Fig. 2). These continuous vari-
Fig. 1 - Map showing results from a drainage-basin wide
approach for implementing a model for estimating
post-fire debris-flow volumes. This map shows es-
timated debris-flow volumes expected at drainage
basin outlets (open circles) as a function of model
input variables obtained for each drainage basin.
Debris-flow volumes at additional locations (solid
circles), for example, at road crossings within the
drainage basin, are not identified. The gray area
represents the inter-basin area for which hazard
information is also not obtained
Fig. 2 - Schematic illustration of the continuous variable
method, where grids of continuous variables are
defined for each contributing area to each grid cell
along the drainage network. The size of each con-
tributing area increases with distance downstream
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IMPLEMENTATION OF POST-FIRE DEBRIS-FLOW HAZARD ASSESSMENTS ALONG DRAINAGE NETWORKS, SOUTHERN CALIFORNIA,
Italian Journal of Engineering Geology and Environment - Book www.ijege.uniroma1.it © 2011 Casa Editrice Università La Sapienza
857
deposited in debris-retention basins, and range be-
tween 300 and 1,000,000 m
3
(G
aRtneR
et alii, 2008;
C
annon
et alii, 2010). Independent variables associat-
ed with each volume measurement include the drain-
age basin relief, the length of the longest flow path
within the drainage basin, the drainage basin area with
gradients greater than or equal to 30 percent, several
measures of soil physical properties, the basin area
burned at high, moderate, and low severity, total trig-
gering storm rainfall, storm duration, and measures of
peak rainfall intensity at different durations. The data
used to define the independent variables include 10-m
resolution DEMs and burn severity grids, 1:250,000
scale soil maps, and tipping bucket rain gage data col-
lected in the field
Multiple linear regression analyses of the databases
were used to generate models that relate debris-flow
volume to a set of predictor variables with the form;
where α are coefficients and x are variables, and i is
the number of variables used in the model (H
elsen
&
H
iRsCH
, 2002). The variables selected in the analyses
provide the best model for a given dataset based on
multiple linear regression statistics (adjusted r
2
, re-
sidual standard error, etc.) and the ability to predict
debris-flow volume from an independent test dataset
(G
aRtneR
et alii, 2008). In general, each model in-
cludes at least one variable that characterizes the ef-
fects of drainage basin morphology, soil properties,
burn severity, and storm rainfall on debris-flow vol-
ume. The volume model presented in C
annon
et alii
(2010) has an R
2
of 0.83 and a residual standard error
of 0.90. In addition, the model predicted 87 percent
of debris flow volumes from a test dataset to within
an order of magnitude.
MODELS FOR ESTIMATING DEBRIS-FLOw
PROBABILITY
Models that predict the spatial probability of
debris-flow occurrence were developed using lo-
gistic multiple regression analyses of databases that
link observations of debris-flow presence or absence
with independent variables similar to those described
above (R
uPeRt
et alii, 2008; C
annon
et alii, 2010).
The probability of debris flow (P) is characterized as:
pirical debris-flow susceptibility models are frequently
updated. As a result, the predictive variables in the mod-
els, and their coefficients, may change. In this paper we
provide a framework to implement a generic set of de-
bris-flow susceptibility models along drainage networks
using continuous variable grids so that the approach will
be applicable to both existing and future models.
BACKGROUND
Existing models for characterizing post-fire, de-
bris-flow susceptibility have been generated from da-
tabases consisting of measures of debris-flow volumes
and observations of debris-flow occurrence as the de-
pendent variables, and independent variables that char-
acterize drainage basin morphology, soil conditions,
the extent and severity of the fire, and storm rainfall
conditions (e.g., G
aRtneR
et alii, 2008; R
uPeRt
et alii,
2008; G
aRtneR
et alii, 2009; C
annon
et alii, 2010).
Each measure of debris-flow volume or observation of
debris flow is associated with both a single drainage ba-
sin for which the independent variables are defined and
a single storm rainfall event.
The databases used to generate the debris-flow
susceptibility models include information compiled
from drainage basins with areas between 0.01 km
2
to
30 km
2
(G
aRtneR
et alii, 2005; G
aRtneR
et alii, 2008;
R
uPeRt
et alii, 2008; G
aRtneR
et alii, 2009; C
annon
et
alii, 2010). Measurements of debris-flow volume and
observations of debris-flow occurrence were made
along drainage networks at channel confluences or
road crossings, at the mouth of the drainage basin, or
at locations along first order channels where single de-
bris-flow paths were identified (G
aRtneR
et alii, 2008;
s
anti
et alii, 2008). Because these measurements and
observations were made at positions throughout drain-
age networks with drainage basin areas between 0.01
and 30 km
2
, we consider the models to be applicable
to any location along a drainage network within this
range of basin areas. Increased erosion due to wildfire
is most pronounced within the first two to three years
following a fire and so these models are temporally
applicable to this time period (C
annon
et alii, 2010).
MODELS FOR ESTIMATING DEBRIS-FLOw
VOLUMES
Debris-flow volumes were measured either as the
amount of material removed from the main channels
within a drainage basin, or as the amount of material
(1)
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J.E. GARTNER, S.H. CANNON & P.M. SANTI
858
5th International Conference on Debris-Flow Hazards Mitigation: Mechanics, Prediction and Assessment Padua, Italy - 14-17 June 2011
terized by both a high probability of occurrence and a
large estimated volume of material. The least hazard-
ous basins are characterized by both low probabilities
and the smallest volumes. In between these extremes
are basins that are characterized by a combination of
either relatively low probabilities and larger volume
estimates or high probabilities and smaller volume
estimates. Due to the different combinations of low
to high debris-flow volumes and probabilities, C
an
-
non
et alii (2010) suggested that, for a given basin, the
debris-flow volume and probability rankings be added
together to generate a “combined relative debris flow
hazard ranking”, with the lowest values representing
the least hazardous basins, and the highest values rep-
resenting the most hazardous basins. These two sug-
gestions are followed in this paper to provide a single
hazard assessment in addition to the individual debris-
flow volume and probability estimates.
METHODS
To implement debris-flow susceptibility models
along drainage networks, a set of continuous variable
grids are generated that provide measures of each of
the necessary independent variables for each grid cell
in a DEM. Independent variables used in the debris-
flow susceptibility models can be divided into four
categories: 1) measures of the drainage basin area that
meet a particular criteria (e.g., drainage basin area
with gradients greater than or equal to 30 percent), 2)
measures of the percentage of the drainage basin area
that meet a particular criteria (e.g., the percentage of
the drainage basin area burned at moderate and high
severity), 3) measures of average values of the drain-
age basin area (e.g., average gradient of the drainage
basin area), and 4) measures of the drainage basin
morphology (e.g., drainage basin relief, ruggedness,
and length of the longest flow path within the drain-
age basin). Each of these different types of variables
can be determined for each grid cell located along the
drainage network using DEMs, binary grids, integer
grids (e.g., a gradient or burn severity grid) and hy-
drology algorithms available in a GIS.
A flow-direction grid is generated from a DEM
using an eight direction flow model (J
enson
&
d
ominGue
, 1988) wherein each cell is coded to indi-
cate the direction water will travel from the cell based
on the greatest elevation change between adjacent grid
cells. This grid is used to generate a flow-accumula-
where
In this case, β are logistic regression coefficients,
x are values for the predictor variables, and i is the
number of variables in the model (H
osmeR
& l
eme
-
sHow
, 2000). The variables selected in the analyses
provide the best model for a given dataset based on
logistic regression statistics (R
uPeRt
et alii, 2008;
C
annon
et alii, 2010). As above, each model in-
cludes at least one variable that characterizes the ef-
fects of drainage basin morphology, soil properties,
burn severity, and storm rainfall conditions on the
probability of debris-flow generation.
The best probability model is identified using
m
C
f
adden
s
ρ
2
, which is a similar measure to R
2
used
in linear regression but with acceptable values rang-
ing from 0.2 to 0.4. Additionally, model sensitivity
can be evaluated based on the percent of debris flow
occurrences correctly identified with a probability
greater than 50 percent. The probability model de-
veloped by C
annon
et alii (2010) has a m
C
f
adden
s
ρ
2
of 0.35 and a model sensitivity of 44 percent.
COMBINED RELATIVE DEBRIS-FLOw HA-
ZARD RANkING
Because of uncertainties associated with the de-
bris-flow volume and probability estimates, C
annon
et alii (2010) recommended that, rather than present-
ing estimates with several significant figures, each
estimated debris-flow volume and probability be as-
signed to a class rank between 1 and 4. Estimated
debris-flow volumes less than 1000 m
3
are assigned
a class rank of 1, volumes between 1001 and 10,000
m
3
are assigned to class 2, volumes between 10,001
and 100,000 m
3
are assigned to class 3, and volumes
greater than 100,000 m
3
are assigned to class 4.
Further, estimates of debris-flow probabilities less
than 25 percent are assigned to class 1, probabilities
between 26 and 50 percent are assigned to class 2,
probabilities between 51 and 75 percent are assigned
to class three, and probabilities between 76 to 100
percent are assigned to class four.
Debris-flow hazards from a given basin can be
considered as the combination of both probability and
volume, with the most hazardous basins being charac-
(2)
3
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IMPLEMENTATION OF POST-FIRE DEBRIS-FLOW HAZARD ASSESSMENTS ALONG DRAINAGE NETWORKS, SOUTHERN CALIFORNIA,
Italian Journal of Engineering Geology and Environment - Book www.ijege.uniroma1.it © 2011 Casa Editrice Università La Sapienza
859
created by weighting a flow-accumulation command
with an integer grid (e.g., a gradient grid) and then
dividing the output by a drainage basin area grid. This
action divides the sum of the upstream values of the
integer grid by the contributing drainage basin area.
GRIDS wITH MEASURES OF THE DRAINAGE
BASIN MORPHOLOGY
Generating continuous variable grids that charac-
terize drainage basin morphology (e.g. drainage basin
ruggedness, drainage basin relief, and the length of
the longest flow path within a drainage basin) require
specific hydrology algorithms. The flow-length hy-
drology tool in the spatial analyst of ArcGIS (ESRI,
2008), with the upstream option, can be used to create
a grid that represents the distance of the longest flow
path within a drainage basin. A grid that represents
the upstream relief can be determined using the Riv-
ertools program (R
ivix
, 2001). The relief grid is used
to calculate drainage basin ruggedness by dividing
the relief grid by the square root of a drainage basin
area grid (m
elton
, 1965). Other software may be used
to generate these continuous variable grids, however
the outputs should mimic the grids generated here to
avoid introducing error into the model results.
CALCULATING DEBRIS-FLOw PROBABILI-
TIES AND VOLUMES USING MAP ALGEBRA
Once the necessary continuous variable grids
for the variables used in the debris-flow susceptibil-
ity models have been generated, map algebra (ESRI,
2008) is used to calculate debris-flow volumes and
probabilities along the drainage network. Each con-
tinuous variable grid is used as the input variables in
the map algebra expression, and the outputs are grids
with cell values equal to the predicted debris-flow
volume and probability, and combined relative debris-
flow hazard ranking. These outputs are multiplied by
a binary grid representing the applicable drainage
network (between 0.01 and 30 km
2)
so that volume,
probability, and combined relative hazard ranking are
estimated only along the drainage network.
EXAMPLE OF A CONTINUOUS VARIA-
BLE BASED HAZARD ASSESSMENT
Here we apply the debris-flow susceptibility
models to a hypothetical watershed to illustrate their
implementation in a continuous variable framework.
tion grid, which provides measures of the number of
grid cells that flow into each grid cell. The flow ac-
cumulation grid can be weighted with another grid to
create a grid where the value of each grid cell equals
the upstream sum of values from the weight grid.
The flow-accumulation grid is multiplied by the
grid cell area (e.g., 100 m
2
for a 10-m DEM), to gen-
erate a drainage basin area grid where each grid cell
contains a measure of the contributing drainage basin
area. The drainage network for a given area (Fig. 2)
is then defined by converting the drainage basin area
grid to a binary grid; values of one are assigned to
those grid cells with drainage basin areas between
0.01 km
2
and 30 km
2
and values of zero are assigned
to grid cells with values outside of this range.
In this paper we use ArcGIS (ESRI, 2008) and
Rivertools (R
ivix
, 2001) software to implement the
debris flow susceptibility models. Other software and
hydrology algorithms may be used to implement the
susceptibility models, however, this may potentially
introduce error into the results.
GRIDS FOR MEASURES OF THE DRAINAGE
BASIN AREA THAT MEET A PARTICULAR CRI-
TERIA
To generate grids with measures of basin area that
meet a particular criteria (e.g., drainage basin area
with gradients greater than or equal to 30 percent),
the flow-accumulation command is weighted with a
binary grid with cell values equal to one for locations
that meet the specific criteria and then multiplied by
the grid cell area.
GRIDS wITH MEASURES OF THE PERCEN-
TAGE OF THE DRAINAGE BASIN AREA THAT
MEET A PARTICULAR CRITERIA
Grids with measures of the percentage of the
drainage basin area that meet particular criteria are
generated using a flow-accumulation command
weighted with a binary grid that represents the unique
criteria with values of one, dividing the output grid
by a drainage basin area grid, and then multiplying
this output grid by 100 to calculate a percentage value.
GRIDS FOR MEASURES OF THE AVERAGE
VALUES OF THE DRAINAGE BASIN AREA
A grid of average values for the drainage basin
area (e.g., the average drainage basin gradient) is
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J.E. GARTNER, S.H. CANNON & P.M. SANTI
860
5th International Conference on Debris-Flow Hazards Mitigation: Mechanics, Prediction and Assessment Padua, Italy - 14-17 June 2011
The watershed contains several locations where infor-
mation on expected debris-flow hazards could be ben-
eficial, including roads that cross the main channels.
Debris-flow probabilities, volumes, and combined rel-
ative debris-flow hazard rankings are calculated along
the drainage network, including the locations where
the roads intersect the drainages. This example dem-
onstrates how a land manager might use the debris-
flow susceptibility models to identify locations where
debris-flows impacts will be greatest. This informa-
tion could be used for many applications; to identify
the type of equipment needed to remove the material,
to size culverts and debris-retention structures, and to
determine if portions of the road are safe for travel
during evacuations.
DEBRIS-FLOw VOLUME MODEL
For this example, we use a model for estimating
the volume of debris-flow material expected along the
drainage network as a function of the drainage basin
area burned at all severities, the length of the longest
flow path within a drainage basin, the drainage basin
relief, and the peak 60-minute storm rainfall inten-
sity The drainage basin area burned at all severities
is generated as described previously by weighting a
flow-accumulation command with a grid that repre-
sents burned grid cells with values of one, and zero
for unburned. This grid is multiplied by the area of
each grid cell (1×10
-4
km
2)
to determine the upstream
area burned at all severities in square kilometers. The
length of the longest flow path within a drainage ba-
sin is determined using the flow-length command in
ArcGIS spatial analysis, hydrology toolbox with the
upstream option chosen (ESRI, 2008). The input for
this command is a flow-direction grid, and the output
is divided by 1000 to convert to units of kilometers.
The drainage basin relief is determined using the re-
lief command in Rivertools (R
ivix
, 2001).
These grids are used as the inputs for the debris-
flow volume model using single output map alge-
bra. A value of 10 mm/hr was chosen for a peak
60-minute rainfall intensity based on values used in
a recent hazard assessment in southern California
(C
annon
et alii, 2009). The resulting grid from the
map algebra represents the estimated debris-flow
volume for each grid cell within the burned drainage
network (Fig. 3).
DEBRIS-FLOw PROBABILITY MODEL
In this example, debris-flow probability is calcu-
lated as a function of the percentage of drainage basin
area with gradients greater than or equal to 30 percent,
drainage basin ruggedness, the percentage of drainage
basin area burned at moderate and high severity, the
average clay content and liquid limit of soils within
the drainage basin, and average storm rainfall intensity
As described above, the continuous variable grid
for the percentage of the drainage basin area with gra-
dients greater than or equal to 30 percent is generated
using the flow-accumulation command, weighted with
a binary grid consisting of values of one for gradients
greater than 30 percent and values of zero for gradients
less than 30 percent. The output of this command is
then divided by a non-weighted, flow-accumulation
grid and multiplied by 100 to determine the percent-
age of the drainage basin area with gradients greater
than or equal to 30 percent. The grid with measures
for drainage basin ruggedness is determined by divid-
ing the relief grid, generated using Rivertools (R
ivix
,
2001), by the square root of a drainage basin area grid.
The grids representing the average clay content and
liquid limit of soils within the drainage basin are gen-
erated using flow-accumulation commands weighted
with grids representing clay content and liquid limit
derived from the USSOILS database (s
CHwaRz
& a
l
-
exandeR
, 1995). The outputs of these operations are
divided by a drainage basin area grid and multiplied by
100 to calculate percent values. A value of 10 mm/hr
is chosen for an average storm rainfall intensity based
Fig. 3 - Potential debris-flow volumes calculated along a
hypothetical burned drainage network in response
to a 10 mm of rain in 1 hour. Debris-flow volumes
increase with distance downstream and increasing
drainage basin area
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IMPLEMENTATION OF POST-FIRE DEBRIS-FLOW HAZARD ASSESSMENTS ALONG DRAINAGE NETWORKS, SOUTHERN CALIFORNIA,
Italian Journal of Engineering Geology and Environment - Book www.ijege.uniroma1.it © 2011 Casa Editrice Università La Sapienza
861
fied along the drainage network provides a single map
output that identifies the locations most susceptible to
debris-flow impacts.
The example application provided here dem-
onstrates how debris-flow susceptibilities may vary
at different locations along a drainage network in a
burned area. The application of an existing model for
post-fire debris-flow volume indicates that volumes
will generally increase with distance down the drain-
age network, reflecting the addition of material from
sequentially larger drainage basin areas, and more im-
portantly, longer channel lengths (s
anti
et alii, 2008).
This application characterizes the process whereby
debris flows originating in lower-order portions of the
drainage network will progressively increase in vol-
ume as they travel downstream. The rate of volume
increase is a function of basin morphology, the extent
and severity of the burned area, soil physical proper-
ties, and storm rainfall.
Estimates of the probability of post-fire debris
flows indicate that debris-flow probabilities can both in-
crease and decrease along the drainage network, reflect-
ing changing conditions within drainage basin areas.
Specifically, an area that is unburned or burned at low
on a recent hazard assessment for southern California
(C
annon
et alii, 2009). These grids and average storm
rainfall estimate are used as the inputs to the model
which is processed using map algebra (ESRI, 2008).
The resulting grid from the map algebra represents
the debris-flow probability at each grid cell along the
burned drainage network (Fig. 4)..
COMBINED RELATIVE DEBRIS-FLOw HA-
ZARD RANkING
Combined relative debris-flow hazard rankings
for the drainage network were calculated as the sum of
ranked values of the estimated debris-flow volume and
probability. These values ranged between 2 and 5 (Tab.
1). In addition, combined relative debris-flow hazard
rankings were calculated for each of the locations of
interest indicated on Figure 5 (Tab. 1).
DISCUSSION AND CONCLUSIONS
Applying existing empirical debris-flow hazard
assessment models along drainage networks pro-
vides additional information to basin-wide hazard
assessments. This new method estimates debris-flow
volumes and probabilities at all locations along the
drainage network, where debris-flow impacts are most
likely to be most significant. Implementation of this
approach also eliminates the need to manually iden-
tify specific drainage basin outlets of interest, thus de-
creasing the time needed to generate emergency post-
fire debris-flow hazard assessments. In addition, the
combined relative debris-flow hazard ranking identi-
Fig. 4 - Debris-flow probabilities estimated along a
burned drainage network in response to 10 mm of
rain in one hour. Probabilities can both increase
and decrease along the drainage network, reflect-
ing changing conditions within contributing areas
Fig. 5 - Combined relative debris-flow hazard rankings
calculated along a burned drainage basin net-
work. Rankings can both increase and decrease
along a drainage network, reflecting changes in
probability estimates associated with changing
conditions within drainage basin areas
Tab. 1 - Debris-flow susceptibilities for locations of inter-
est within a burned drainage basin
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J.E. GARTNER, S.H. CANNON & P.M. SANTI
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5th International Conference on Debris-Flow Hazards Mitigation: Mechanics, Prediction and Assessment Padua, Italy - 14-17 June 2011
ments. In addition, the maps show that roads crossing
the upper reaches of the drainage are more suitable for
an evacuation route, as opposed to the road that passes
through locations 3 through 6.
The continuous variable approach presented here
optimizes the predictive capability of debris-flow sus-
ceptibility models and provides more spatially specific
information on potential debris-flow hazards following
wildfire. Future research on how topography affects
debris-flow processes of channel incision, transport and
deposition will better identify where debris-flow inci-
sion and transport give way to debris-flow deposition.
ACKNOWLEDGEMENTS
The authors would like to thank U.S. Geological
Survey colleagues Jonathan McKenna and Jonathan
Godt, and the two anonymous reviewers of the 5
th
De-
bris Flow Hazards and Mitigation Conference Interna-
tional Review Committee for their helpful comments
on this paper.
severity between locations 4 and 7 on Figure 3 results
in a channel reach where debris-flow probability esti-
mates decrease with distance downstream. The lower
probability estimates result from the mitigating effects
of unburned areas, and areas burned at low severity
within the drainage basin. Similarly, the channel above
location 3 on Figure 4 shows probabilities that increase
and then decrease with distance downstream due to the
effects of the drainage network passing through an area
of lower gradients. These changes in debris-flow prob-
abilities are also reflected in the map showing the com-
bined relative debris-flow hazard ranking.
Maps generated using this approach can be used
to identify hazardous locations within the drainage
network, guide post-fire debris-flow hazard mitiga-
tion plans, and plan emergency evacuation routes. For
example, these maps indicate that debris-flow impacts
will be greatest at locations 1, 2, and 6, and the least at
locations 7 and 4, thus providing information on where
to focus post-fire channel erosion mitigation treat-
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Statistics