A CASE STUDY OF SHALLOW LANDSLIDE OCCURRENCE AND MAGNITUDEFREQUENCY DUE TO RAINFALL EVENTS AFTER EARTHQUAKES IN
NORTHWESTERN CALIFORNIA
by
Cheryl A. Hayhurst
A Thesis
Presented to
The Faculty of Humboldt State University
In Partial Fulfillment
Of the Requirements for the Degree
Masters of Science
In Natural Resources: Watershed Management
December, 2006
A CASE STUDY OF SHALLOW LANDSLIDE OCCURRENCE AND MAGNITUDEFREQUENCY DUE TO RAINFALL EVENTS AFTER EARTHQUAKES IN
NORTHWESTERN CALIFORNIA
By
Cheryl A. Hayhurst
Approved by the Master’s Thesis Committee:
________________________________________________________________________
E. George Robison, Major Professor
Date
________________________________________________________________________
William Bigg, Committee Member
Date
________________________________________________________________________
Mark Hemphill-Haley, Committee Member
Date
________________________________________________________________________
Coordinator, Natural Resources Graduate Program
Date
________________________________________________________________________
Natural Resources Graduate Program Number
________________________________________________________________________
Donna E. Schafer, Dean for Research and Graduate Studies
Date
ABSTRACT
A CASE STUDY OF SHALLOW LANDSLIDE OCCURRENCE AND MAGNITUDEFREQUENCY DUE TO RAINFALL EVENTS AFTER EARTHQUAKES IN
NORTHWESTERN CALIFORNIA
Cheryl A. Hayhurst
This project is a case study to examine trends in shallow, rapid landslide
occurrence and magnitude-frequency in Humboldt County, California. It attempts to
identify a trend of increasing landslide occurrence and magnitude-frequency correlated to
large seismic events (magnitude [M] six and greater) followed by significant rain events
yielding high antecedent soil moisture conditions with Antecedent Precipitation Index
values greater than 10 centimeters.
Shallow landslides were observed through aerial photographs for three
earthquakes that occurred in 1954, 1980, and 1992. For each earthquake, non earthquake
“control”, earthquake “control”, and earthquake/rainfall event related “treatment” study
years were selected for observation. Earthquake event selection was based on aerial
photograph coverage, precipitation events producing an Antecedent Precipitation Index
value greater than 10 centimeters, and earthquakes magnitude six or greater. Recently
harvested areas were selected in order to provide uniformity of land management
practices and also to allow for the maximum observance of landslides, which are often
not seen under a full canopy.
The occurrence and magnitude-frequency rates of shallow, rapid landslides were
found to increase after an earthquake (magnitude six or greater) followed by a
precipitation event with an Antecedent Precipitation Index value greater than 10
iii
centimeters than when compared to landslide occurrence and magnitude-frequency rates
related to high precipitation events only.
iv
ACKNOWLEDGEMENTS
Funding for this project was provided by Scotia Pacific, L.L.C. I would like to
express sincere gratitude to my committee members Dr. Bill Bigg, Dr. Mark HemphillHaley, and Dr. E. George Robison for all of their time and expertise. Special thanks to
John Oswald for the original project idea along with the ScoPac Geology Department for
their time, advice, and the experience of a lifetime. I would also like to thank my
husband, Nick, for providing endless support throughout this process.
v
TABLE OF CONTENTS
Page
ABSTRACT....................................................................................................................... iii
ACKNOWLEDGEMENTS................................................................................................ v
TABLE OF CONTENTS................................................................................................... vi
LIST OF TABLES............................................................................................................ vii
LIST OF FIGURES ......................................................................................................... viii
LIST OF APPENDICES.................................................................................................... ix
INTRODUCTION .............................................................................................................. 1
STUDY AREA ................................................................................................................... 6
MATERIALS AND METHODS...................................................................................... 11
Antecedent Precipitation Index Method ....................................................................... 11
Seismic Investigation .................................................................................................... 17
Earthquake Event Selection .......................................................................................... 17
Landslide Inventory ...................................................................................................... 22
Landslide Magnitude-Frequency Analysis ................................................................... 23
RESULTS ......................................................................................................................... 25
DISCUSSION ................................................................................................................... 37
REFERENCES ................................................................................................................. 42
vi
LIST OF TABLES
Table
Page
1
Summary of size and location of individual study areas for each earthquake event,
Humboldt County, California.. ................................................................................9
2
Antecedent Precipitation Index values greater than 10 centimeters for the period
of record between December 1, 1940 and January 1, 2000. ..................................14
3
Summary of earthquake events with a 50% landslide exceedence probability
radius determined by applying the model Wilson and Keefer developed in 1985 to
determine the aerial extent of landsliding as it relates to earthquake magnitude. .19
4
Sum of landslide occurrence and area for each stage (control and study year) for
each earthquake event, Humboldt County, California...........................................26
5
Summary of percentage changes in landslide counts and area between the control
year and the study year for each earthquake event. ...............................................28
6
Summary of landslide occurrence and area by stage within the individual study
areas for each earthquake event. ............................................................................30
7
Summary of percentage changes in landslide occurrence and area for the
individual study areas between control and study years for each earthquake event.31
vii
LIST OF FIGURES
Figure
Page
1
Location of fourteen study sites within Pacific Lumber Company’s aerial
photograph coverage area in Humboldt County, California... .................................7
2
Graph showing the relationship between earthquake magnitude and the maximum
distance of disrupted slides from the earthquake epicenter for 2% (P=2), 50%
(P=0), and 98% (P=2) landslide exceedence probabilities (adapted from Wilson
and Keefer 1985)....................................................................................................18
3
Aerial extent radius of 50 percent landslide exceedence probability in kilometers
(Table 4) for each earthquake based on earthquake magnitude, Humboldt County,
California. Aerial extent radius determined by application of the method defined
by Wilson and Keefer (1985).................................................................................20
4
Landslide area-frequency distributions for each control and study year: 1954,
1980, and 1992 data sets. A power law trend line is drawn through the study
years. . ...................................................................................................................34
5
Landslide area-frequency distribution for the 1980 earthquake event with a power
law trend line placed through the most robust portion of the data from the study
year (1984). ............................................................................................................36
viii
LIST OF APPENDICES
Appendix
A
Page
Calculated Antecedent Precipitation Index values (in inches) during the period of
record from December 1940 through December 1999 in five year intervals. .......47
ix
INTRODUCTION
Shallow rapid landslides are a significant concern in terms of public safety and
infrastructure and as a source of potential water pollution. Shallow landslide initiation is
strongly related to precipitation with saturated soil conditions and earthquakes. What is
not well understood is the relative effect of combined recent earthquakes and saturated
soil conditions in initiating landslides, especially shallow rapid landslides. This case
study evaluates the potential change in occurrence and area-frequency distribution of
shallow, rapid landslides due to periodic large environmental triggers such as rainfall and
earthquakes, specifically the combination of the two. For this case study, I created an
inventory of shallow, rapid landslides in fourteen study areas using aerial photographs of
various vintages. The fourteen study areas had been recently harvested and were
observed through a time period bracketing three earthquakes in the years 1954
(magnitude 6.5), 1980 (magnitude 7.2), and 1992 (magnitude 7.1). Landslides were
observed in association with the following conditions:
1) After a rain event that occurred prior to the earthquake (in order to provide a
control for the rain events);
2) After the earthquake (in order to provide a control for the earthquake); and
3) After a rain event that occurred after the earthquake.
The hypothesis tested in this case study is that the occurrence and magnitude-frequency
distribution of shallow, rapid landslides will increase for a precipitation event that is
1
2
preceded by a relatively large magnitude earthquake (magnitude six or greater) in
comparison to the control years.
Landslides are the common term indicating the movement of soil or bedrock
down slope. Landslides can include slow processes such as creep or fast processes as in
the case of debris flows. World-wide, fast moving landslides are the cause of loss of life
and property damage and, as a result, are often studied for the purpose of creating hazard
maps that try to estimate the probability of the occurrence of landslides. Aside from the
large and devastating landslides that do cause damage and harm, they are also important
in terms of water quality. Landslides, especially debris slides and debris flows, can enter
a stream channel or river and cause excess sedimentation that persists over long periods
of time. This excess sediment can diminish water quality for beneficial uses such as
drinking water supply and aquatic habitat.
Landslides occur in northwestern California, possibly due to poorly consolidated
sedimentary bedrock, steep topography, ground shaking due to earthquakes, large
amounts of annual rainfall, or some combination thereof. Many northwestern California
streams and rivers, including the watersheds evaluated in this study, are listed on the
Environmental Protection Agency’s (USEPA) Clean Water Act Section 303(d) List of
Water Quality Limited Segment for Sedimentation/Siltation (California State Water
Resources Control Board 2002). Total Maximum Daily Loads, established by the Clean
Water Act in Section 303, are calculations of the maximum amount of a particular
3
pollutant that can be received by a water body and still meet water quality standards set
by States, Territories, and Tribes for particular beneficial uses for that water body.
Total Maximum Daily Load calculations contain background values for the
specific pollutants and once developed, a regulatory agency may be charged with
enforcement of those Total Maximum Daily Loads for land owners within the watersheds
of the impaired water bodies (California State Water Resources Control Board 2002).
Sediment Total Maximum Daily Loads can be important to land managers conducting
activities on their land such as timber harvesting or cattle ranching which can cause the
de-stabilization of soils or bedrock and can lead to landslides that may impact streams
and rivers.
Along with Total Maximum Daily Loads, sediment budgets are often created for
watersheds in order to quantify the rates of sediment production, transport, and discharge
of sediment. Landslides are an important sediment transport mechanism in watersheds
and long term study of their magnitude and frequency rates must be conducted to create a
sediment budget (Dietrich et al. 1982, Lehre 1982, Reid and Dunne 1996). Long term
studies are necessary to account for typical watershed conditions and also allow for the
capture of rare and extreme events that may cause an increase in the magnitude and
frequency of landslides such as large rain events and earthquakes.
Rainfall and earthquakes are two widely studied natural processes that trigger
landslides and both processes occur in northwestern California. Rainfall-induced
landslides have been widely studied. They commonly begin due to increased pore
4
pressure in saturated ground conditions (Ziemer 1984, Anderson and Sitar 1995, Crozier
1999, Dai and Lee 2001, Casadel et al. 2003, Jakob and Weatherly 2003, Coe et al. 2004,
Dhakal and Sidle 2004, Onda et al. 2004). Fedora (1987) developed an Antecedent
Precipitation Index that functions under the assumption that the effect of a given
precipitation event on soil saturation will decay through time. Ziemer and Albright
(1987) also developed an Antecedent Precipitation equation for predicting peak flows in
subsurface soil pipes. The Antecedent Precipitation Index method is useful in
determining the antecedent soil moisture conditions that exist in the study region from
previous storms which can be a better indicator of landslide potential than looking at the
intensity and duration of individual rain events. In northwestern California, similar
intensity rainstorms will have a different effect if occurring at the end of the summer
season when it has not rained for some time and the soil is dry versus an occurrence in
the winter after a series of rain events when soils are already saturated. The Antecedent
Precipitation Index method will also ensure that the precipitation events used in the study
have a similar effect on soil conditions.
Earthquake-induced landslides have been the subject of recent studies (Wilson
and Keefer 1985, Pearce and Watson 1986, Dadson et al. 2004). Earthquakes trigger
landslides when ground motions reach the critical acceleration, which is the minimum
acceleration required to overcome a slope’s resistance to sliding (Wilson and Keefer
1985). Wilson and Keefer (1985) developed a method for estimating the aerial extent of
earthquake-induced landslides based on earthquake magnitude. The model, developed by
5
Wilson and Keefer (1985), is an empirical relation for the severity of seismic shaking as a
function of earthquake magnitude and the distance from the seismic source, producing a
rating curve for earthquake magnitude and distance from the epicenter. I employed this
technique for the current study as a tool to refine specific study sites based on the
probability that landsliding that might occur in a particular area as the result of an
earthquake event.
Northwestern California provides an ideal location for this study because the area
is seismically active, receives a lot of rainfall, and has steep terrain. However, there are
several limitations. The first limitation is the lack of aerial photograph coverage.
Coverage is not available for all years, therefore, a true landslide frequency cannot be
calculated. Additionally, small landslides may not be discernable in aerial photographs
and can under represent the occurrence of smaller landslides. This study is focuses on
larger and less frequent natural events. As a result, there are not many events
represented. Also, rainfall data were obtained from only one rain gauge located within
the study region. These data were applied uniformly to the entire region. Rain does not
fall with uniform amount and intensity over an entire watershed so the precipitation data
can only be considered approximate for the conditions within the study area. This study
assumes the landslides observed occurred in colluvium and were not bedrock failures. I
also assumed that vegetation in the study areas consisted of redwood (Sequoia
sempervirens) and Douglas-fir (Pseudotsuga menziesii) which can provide implications
for the effect of root strength.
STUDY AREA
This study was conducted in Humboldt County, California, in forested lands
owned by Scotia Pacific, LLC (Figure 1). The region consists of portions of Freshwater
Creek, Elk River, Van Duzen River, Yager Creek, and lower Eel River Watersheds.
These watersheds lie on the western slope of the California Coast Range and typically
maintain a maritime climate and average annual precipitation of approximately 124
centimeters (Western Regional Climate Center 2006)
Within the study area, a subset of fourteen smaller study sites was selected based
on aerial photograph availability and timber harvest activity discernable from aerial
photographs (Figure 1). The study areas are former timber harvest sites. Recently
harvested areas were selected to provide uniform land management characteristics and
because the removal of the canopy allowed for observation of landslides that otherwise
might not have been detected under a full canopy. Robison et al. (1999) determined,
during a landslide inventory in Oregon, that aerial photo observation of landslides is
higher in areas recently harvested (0-9 years old) than mature forests (greater than 100
years old). In their study, 50 percent of ground-based measured landslides were detected
in recently harvested areas compared to only five percent in mature forests. In addition to
uniform land management and increased aerial photograph observance, using recently
harvested areas provides similar starting conditions for the study sites. Recently
harvested areas also have a decreased likelihood of further ground disturbance due to
return of ground-based
6
7
Figure 1. Location of fourteen study sites within Pacific Lumber Company’s aerial
photograph coverage area in Humboldt County, California.
8
equipment within the timeframe of this study. Table 1 summarizes the fourteen study
sites. The fourteen study sites occur in areas dominated by redwood and secondarily by
Douglas-fir.
The geology underlying the study sites consist of the Franciscan Complex
(including the Coastal terrane and the Yager terrane) and the Wildcat Group. The
Coastal belt is divided into structural terranes separated by low to moderately dipping,
fault zones (McLaughlin et al. 2000). The Coastal terrane (Paleocene to Late Eocene) is
highly disrupted by fracturing, shearing, and folding and consists of sandstone, mudstone,
and conglomerate with sandstone-rich rocks occurring in the eastern portion of the
terrane and mélange in western exposures (Blake et al. 1988). The Yager terrane
(Paleocene to Late Eocene) of the Franciscan Complex is lithologically, structurally, and
chronologically more homogeneous than the Coastal terrane and consists of well-bedded,
moderately to slightly sheared, and highly folded mudstone and sandstone (Blake et al.
1988). The Yager terrane is also described as massive indurated sandstone with
interbedded sandstone-conglomerate, siltstone and conglomerates and is typically fine
grained, well bedded, and highly sheared in places (Kelsey and Allwardt 1987, Kilbourne
1985a, b, Spittler 1983a).
The Wildcat Group is Miocene to Pleistocene in age and consists of primarily
moderately to poorly indurated, folded, massive to poorly bedded marine sedimentary
rocks including sandstone, siltstone, mudstone, shale and conglomerate (Kelsey and
Allwardt 1987). The Wildcat Group is broken into five members. Three of the members
of the Wildcat Group dominate the bedrock of the fourteen study areas.
9
Table 1. Summary of size and location of individual study areas for each earthquake
event, Humboldt County, California.
Earthquake Event
Study Area
1954
Lake Creek 1
1980
1992
Area
(Square
Kilometers)
0.3
United States Geological
Survey 7.5-Minute
Quadrangle Map
McWhinney Creek
Lake Creek 2
0.9 McWhinney Creek
Root Creek
1.0 Redcrest
S. F. Elk
2.6 McWhinney Creek
Yager Creek
2.3 Hydesville and Owl Creek
Eel River
12.6 Myers Flat and Weott
Hely Creek
9.7 Owl Creek and Redcrest
Root Creek
7.0 Redcrest
Sammy Creek
3.3 Scotia and Redcrest
Bridge Creek
0.8 Redcrest
Eel River
1.2 Redcrest
Little Freshwater Creek
2.3 McWhinney Creek
Shively Creek
1.3 Redcrest
Tank Gulch
0.5 Scotia
10
The three members include the Carlotta Formation, the Rio Dell Formation, and Scotia
Bluffs Formation. The Carlotta Formation is a non-marine conglomerate, sandstone, and
claystone of Middle to Late Pleistocene age that is partially indurated and mildly folded
(Kilbourne 1985a, b). The Rio Dell Formation, Pliocene to Pleistocene, is a compact,
massive mudstone that is partially indurated and folded and has alternating sandstone and
mudstone beds (Kilbourne 1985a, b). The Scotia Bluffs sandstone is a shallow marine,
massive, very compact, fine grained sandstone that is Pliocene to Pleistocene in age
(Kilbourne 1985a, b). In many places within the study areas, previous workers were
unable to differentiate members of the Wildcat Group and thus these rocks are mapped as
Undifferentiated Wildcat Group. This undivided geologic unit possesses characteristics
of all of the members of the Wildcat Group.
MATERIALS AND METHODS
I used five techniques to refine the study area, select precipitation and earthquake
events, and for analysis. The techniques include an analysis of antecedent soil moisture
conditions using Fedora’s Antecedent Precipitation Index (Fedora 1987), the Wilson and
Keefer method for predicting the aerial extent of landsliding (Wilson and Keefer 1985),
aerial photographic landslide inventory, earthquake event selection, and a landslide
magnitude-frequency analysis. The Antecedent Precipitation Index (Fedora 1987) and
Wilson and Keefer (1985) methods are primarily used to provide temporal and spatial
constraints for the study by determining which precipitation and earthquake events to
investigate with the aerial photographs and where landsliding was likely to occur for a
given earthquake event.
Antecedent Precipitation Index Method
Fedora’s (1987) Antecedent Precipitation Index equation was chosen for use in
this study because the recession coefficient could be calculated. The calculation for the
recession coefficient is also dependent on watershed size. Fedora (1987) provided two
recession coefficient equations, one for large watersheds and one for small watersheds.
The equation for small watersheds is used for this study. Fedora’s modified equation for
determining the Antecedent Precipitation Index (Fedora 1987), allows for the use of any
time interval of precipitation observations and is given as:
11
12
APIt = API(t –
t)
* C(a) +Pt
APIt = Antecedent Precipitation Index at time t (inches)
t
= Time interval of precipitation observations (hours)
C(a) = Recession coefficient (dimensionless)
Pt
= Precipitation volume during one t ending at time t (inches)
The recession coefficient is determined through the following equation:
C(a) = C(b)(
t(a)/ t(b))
C(a) = Recession coefficient based on time interval t(a)
C(b) = Recession coefficient based on time interval t(b)
Determined from C = 0.925 +7.93E(-3*Ln(a));
a = watershed area (square miles)
t(a) = Time interval of precipitation observations
t(b) = Time interval used to derive recession coefficient C(b)
For this study, daily Antecedent Precipitation Index values were produced using
daily precipitation values recorded by a rain gage located in Scotia, Humboldt County,
California. The rain gage (Coop ID # 048045) is part of the National Weather Service’s
Cooperative Station Network and lies at 40.5 meters above sea level (National Climate
Data Center [NCDC] 2004). The daily precipitation data was taken from the U.S.
Department of Commerce National Climatic Data Center and included sixty four years of
data from December 1940 through December 2003 (National Climate Data Center 2004).
13
The recession coefficient value (C) to use in the Antecedent Precipitation Index
equation was determined to be 0.897961 by calculating an average watershed area for
zero order basins within the broad study region. The average area (0.03305 square miles
or 0.0856 square kilometers) for the zero order basins was determined by obtaining the
areas of one hundred zero order basins randomly selected within the study region. Zeroorder basin areas, or colluvial hollows, were used because they tend to be the origination
areas for shallow, rapid landslides (Dietrich et al. 1982, Lehre 1982, Swanson et al. 1987,
Benda and Dunne 1997, and Montgomery et al. 2000).
With the recession coefficient (C) calculated, the modified Antecedent
Precipitation Index calculation was applied to the daily precipitation values to produce
daily Antecedent Precipitation Index values for over sixty four years of recorded data.
Results were graphed (Appendix A) and precipitation events producing Antecedent
Precipitation Index values over 10.16 centimeters (four inches) were selected as potential
candidates for this study. An Antecedent Precipitation Index value greater than 10.16
centimeters (four inches) was selected because on average during the period of record
(1940 to 2003) these events occurred approximately every three and a half years. This
time span provided sufficient time between each earthquake and precipitation event to
allow for aerial photographic capture without observing the influence of a similar event.
Cafferata and Spittler (1998) determined a similar precipitation value for landslide
initiation threshold at 11.94 centimeters (4.70 inches) over a three-day period in the
Caspar Creek watershed. Table 2 presents the precipitation events with Antecedent
14
Table 2. Antecedent Precipitation Index values greater than 10 centimeters for the period
of record between December 1, 1940 and January 1, 2000.
December 4, 1945
Antecedent Precipitation
Index Value (centimeters)
11.5
October 29, 1950
12.5
December 5, 1952
11.3
December 22, 1955
15.4
January 8, 1959
11.7
February 15, 1959
12.9
December 22, 1964
14.7
January 29, 1966
10.8
December 24, 1968
12.4
November 10, 1971
10.5
January 16, 1974
12.4
March 18, 1975
10.6
October 25, 1979
11.2
November 17, 1981
10.2
January 26, 1983
10.7
January 8, 1995
11.7
January 10, 1995
11.6
March 9, 1995
11.4
Date
15
Table 2. Antecedent Precipitation Index values greater than ten centimeters for the period
of record between December 1, 1940 and January 1, 2000 (continued).
Date
December 9, 1996
Antecedent Precipitation
Index Value (centimeters)
11.7
January 1, 1997
14.5
December 16, 2002
10.7
December 28, 2002
11.5
16
Precipitation Index values greater than 10.16 centimeters. The specific precipitation
events selected for this study were chosen based on results of the earthquake catalogue
and availability of aerial photograph coverage for the period of time involved. The
selected precipitation events are discussed under Earthquake Event Selection in the
following sections.
Seismic Investigation
The purpose of the seismic investigation is to identify key earthquake events and
define the study region based on a range of areas that exceed the fifty percent probability
for a landslide to occur due to a specific earthquake event. The seismic investigation
consists of two parts. Development of an earthquake catalogue and employing the
method developed by Wilson and Keefer (1985) to predict the aerial limits of earthquakeinduced landsliding for the fifty percent landslide exceedence probability.
The earthquake catalogue was compiled using information from the United States
Geological Survey (USGS) National Earthquake Information Center (National
Earthquake Information Center 2005). A database search was conducted within an area
defined by 39° to 42.5° and -122° to -125.5° for earthquakes with magnitudes greater
than 5.0 between the years 1930 and 2003. Wilson and Keefer (1985) determined that
the smallest events to cause disrupted slides and falls, coherent slides, and lateral spreads
or flows are of magnitudes (M) 4.0, 4.5, and 5.0, respectively. The catalog time frame is
restricted due to the availability of aerial photograph coverage from 1948 to 2003. The
17
aerial range of the study encompasses a large portion of the northern coast of California
which is necessary in order to assess the effects of large magnitude earthquakes that may
have occurred outside the study region.
The method defined by Wilson and Keefer (1985) to predict the aerial extent of
landsliding was applied to each event in the catalogue. I used a rating curve that
correlates earthquake magnitude to distance from the epicenter for a 50 percent landslide
exceedence probability area (Figure 2). The result was that nine earthquakes occurred
with magnitudes large enough to produce an area of fifty percent landslide exceedence
probability surrounding the earthquake epicenter (Table 3).
Earthquake Event Selection
Specific events of interest were selected based on when the precipitation and
earthquake events occurred in relation to each other and whether aerial photographs were
available for those events.
Three earthquake events were determined to be suitable for study: 1954
(Magnitude 6.5), 1980 (Magnitude 7.2), and 1992 (Magnitude 7.1). Three earthquakes
occurred in 1992 within two days of magnitudes 7.1, 6.6 and 6.6, however, the two
smaller magnitude earthquakes occurred offshore and most of the study area falls outside
of the influence of the 50 percent landslide exceedence probability. For the purposes of
this study I only consider the larger magnitude event in 1992. Figure 3 shows the area of
18
Figure 2. Graph showing the relationship between earthquake magnitude and the
maximum distance of disrupted slides from the earthquake epicenter for 2%
(P=2), 50% (P=0), and 98% (P=2) landslide exceedence probabilities (adapted
from Wilson and Keefer 1985).
19
Table 3. Summary of earthquake events with a 50% landslide exceedence probability
radius determined by applying the model Wilson and Keefer developed in 1985 to
determine the aerial extent of landsliding as it relates to earthquake magnitude.
Earthquake
ID
EQ1
Date
Latitude
Longitude
Magnitude P = 0
(kilometers)
6.5
45
12/21/1954
40.7800
-123.8700
EQ2
6/7/1975
40.5700
-124.1400
5.7
14
EQ3
11/8/1980
41.1200
-124.2500
7.2
120
EQ4
7/31/1987
40.4200
-124.4100
6.0
23
EQ5
8/17/1991
40.2400
-124.3500
6.2
33
EQ6
4/25/1992
40.3700
-124.3200
7.1
92
EQ7
4/26/1992
40.4200
-124.6000
6.6
48
EQ8
4/26/1992
40.3800
-124.5700
6.6
48
EQ9
1/22/1997
40.2700
-124.3900
5.7
14
Notes: P=0 (Fifty percent landslide exceedence probability
radius) (from National Earthquake Information Center 2005).
20
Figure 3. Aerial extent radius of 50 percent landslide exceedence probability in
kilometers (Table 4) for each earthquake based on earthquake magnitude,
Humboldt County, California. Aerial extent radius determined by application of
the method defined by Wilson and Keefer (1985).
21
50 percent landslide occurrence potential for each of the three selected earthquakes based
on the Wilson and Keefer (1985) method for predicting the aerial extent of landsliding.
For the 1954 earthquake, aerial photos were examined for the years 1954 (before the
earthquake, control year) and 1962/1963 (after the earthquake and associated
precipitation event, study year). Precipitation events producing Antecedent Precipitation
Index values greater than 10 centimeters occurred in 1950 and 1953, within five years
prior to the earthquake, and also in 1956, two years after the earthquake. No earthquakes
exhibiting a large enough magnitude to achieve a 50 percent exceedence probability area
occurred between 1930 and 1954. There were also no relevant earthquakes between 1954
and 1963.
Aerial photo landslide examination for the 1980 earthquake included the
following years: 1978 (before the earthquake, control year), 1981 (after the earthquake
and before the second precipitation event, control year), and 1984 (after the earthquake
and associated precipitation event, study year). The 1981 aerial photo set provides two
control years which separate out the rainfall-induced landslides and the earthquakeinduced landslides. Having a control for the earthquake-induced landslide is important
because it provides a separate rate of occurrence between the earthquake-induced
landslides and those caused by both the earthquake and the following rain event. A
precipitation event occurred in 1975, five years prior to the earthquake, and in 1982 and
1983, three years after the earthquake.
22
For the 1992 earthquake, a control set was not available due to approximately
nine years without a precipitation event large enough to produce an Antecedent
Precipitation Index value greater than 10 centimeters (four inches). The first available
precipitation event occurred in 1983 and that event was already in use for the 1980
earthquake data set. Instead, aerial photographs were available in 1994 (after the
earthquake, but before the precipitation event) and in 1997, after the earthquake and
precipitation event that occurred in 1997.
In general, the relevant precipitation events occurred within five years of the
earthquake both before and after providing temporal constraints for drastic environmental
changes in study area characteristics. Aerial photograph coverage for each event was
typically within six years of the event occurring.
The resulting earthquake events considered during this study provide two
occurrences of rainfall-induced landslide control sets (before the earthquake) and two
occurrences of earthquake-induced landslide control sets (following the earthquake and
prior to the next relevant rain event).
Landslide Inventory
I evaluated individual landslides within each study area using a mirror
stereoscope and aerial photographs sets. The following aerial photographs were used:
1954 (California Department of Natural Resources 1954), 1962/1963 (Humboldt County
Assessor 1962/1963), 1978 (Scotia Pacific Geology Archives 1978), 1981 (Cascade
23
Aerial Maps and Surveying 1981), 1984 (Scotia Pacific Geology Archives 1984), 1994
(Cascade Aerial Maps and Surveying 1994), and 1997 (WAC, Inc 1997). I identified
landslides in aerial photos as locations of increased albedo compared to surrounding
areas. Aerial photographs are often used to construct landslide catalogues (Pearce and
Watson 1986, Hovius et al. 1997, Reid 1998, Robison et al. 1999, Hovius et al. 2000,
Guzzetti et al. 2002, Martin et al. 2002, Wills and McCrink 2002, Brardinoni et al. 2003,
and Dadson et al. 2004). The approximate length and width was measured for each
landslide to calculate a landslide area. By following the same harvest areas through time,
hillslope conditions such as geology, slope gradient, and management are kept uniform. I
considered land management as uniform during the observation period with the
assumption that re-entry to the study site did not occur after the harvest activity and
causing additional ground disturbance. One characteristic that changes through time is
the vegetation because the area starts out recently harvested and then is in a period of
regrowth.
Landslide Magnitude-Frequency Analysis
Magnitude-frequency analyses are often done to determine temporal and spatial
rates of landsliding in order to assess landslide hazards and produce landslide frequency
and probability curves (Hovius et al. 1997, 2000, Dai and Lee 2001, Guzzetti et al. 2002,
and Martin et al. 2002). Using the area data collected during the landslide inventory, an
area-frequency distribution curve was produced by calculating the frequency of landslide
24
area within bins corresponding to the area of the smallest observed landslides and then
calculating the cumulative frequency of the landslides. The area-frequency distribution
curve was plotted on a log-log graph using the cumulative frequency and the landslide
area bins.
RESULTS
Data were analyzed by looking at 1) changes in landslide size and occurrence, 2)
percentage change in landslide size and occurrence, 3) size of the landslides with respect
to landslide area, and 4) analysis of magnitude-frequency. Data were analyzed by
examining the total landscape effect and in addition to the individual study areas.
When looking at the data set as a whole for each earthquake, both the number of
landslides and the area of the landslides increased in each case from the control year to
the study year (Table 4). Results support the hypothesis that the number and area of
landslides increased when de-stabilized colluvial hollows experience high antecedent
moisture conditions when compared to the non-earthquake precipitation control and the
earthquake control. The study year in each data set occurred after an earthquake
followed by a precipitation event with an Antecedent Precipitation Index value greater
than ten centimeters. It is possible that the increase in slide area and occurrence observed
in the study year is due to observing previous failures and not isolating only failures that
occurred both after the earthquake and the precipitation event. It is interesting to see,
however, that with respect to the 1980 earthquake set, there was a decrease in both the
observed number of landslides and slide areas from the precipitation control year and the
following earthquake control year. This indicates that
25
26
Table 4. Sum of landslide occurrence and area for each stage (control and study year) for
each earthquake event, Humboldt County, California.
Earthquake
Year
1954
1980
1992
Photo
Year
1954
(control
year)
1963
(study
year)
1978
(control
year)
1981
(control
year)
1984
(study
year)
1994
(control
year)
1997
(study
year)
Sum of
Individual
Slide Areas
(square
meters)
Average Slide
Area per Slide
(square meters)
13
4,702
362
7.07
21
30,723
1,463
32.59
213
109,349
513
32.59
163
61,310
376
32.59
322
221,935
689
5.36
19
12,709
669
5.36
77
52,067
676
Total Study
Area
(square
kilometers)
Total
Number
of Slides
7.07
27
the observation of previous failures is not causing the increase in the total landslides
observed in successive years.
It is interesting to observe the average individual slide area for the control and
study years. This value may indicate a change in the slide mechanism between the
control and study years. For example, an increase in the number of slides with a
consistent slide area per slide between control and study year may indicate the failures
are of a similar type such as shallow landslides. An increase in the slide area per slide
can indicate a change in the slide mechanism to perhaps larger, more deep-seated
failures. It appears the individual slide area generally remained consistent, within
approximately 200 square meters, consistent between control and study years with the
exception of the 1954 data set, in which the average individual slide area increased by
approximately 1,100 square meters (Table 4). Table 5 presents the data from Table 4 in
terms of a percentage change between the control year and study year. The percentage
change was positive in each case showing an increase in both number of slides and slide
areas. The largest percentage change in the number of landslides occurred between 1994
and 1997 at 305 percent (Table 5). The largest percent change in slide area occurred
between 1954 and 1963 at 553 percent (Table 5). This suggests that larger slides may
have occurred during this time period as compared to other earthquake data sets,
especially because it is not accompanied by the largest increase in the number of slides.
28
Table 5. Summary of percentage changes in landslide counts and area between the
control year and the study year for each earthquake event.
Earthquake
Year
Control
Photo Year
Study
Photo Year
Percentage
Change in
Slide Numbers
From Control
Year
1954
1954
1963
62
Percentage
Change in
Slide Area
(square meters)
From Control
Value
553
1980
1978
1984
51
103
1981
1984
98
147
1994
1997
305
310
1992
29
Another way I examined the data was to segregate data into the individual study
areas. Table 6 shows the number of slides and the slide areas for each study area in the
data sets at each stage (control and study year). In the majority of the individual study
areas, landslide count and landslide area increased between the control and study years.
Exceptions to the increase are found in the 1954 earthquake data set in Lake Creek 1,
Lake Creek 2, and Root Creek (Table 6). Lake Creek 1 experienced one additional
landslide in the study year than in the control year, but the landslide area decreased
slightly (11 square meters) between the study year and the control year. This decrease
may be due to smaller landslides occurring in the study year or increased vegetative cover
preventing observation. Lake Creek 2 did not experience any landsliding in either the
control or study year. Root Creek experienced the same number of landslides in both the
control and the study years. The landslide area in Root Creek did increase in the study
year over the control year even though the number of landslides remained the same. This
may be indicative of either a reactivation of a previously mapped landslide or occurrence
of larger landslides during the control year.
The percentage changes in landslide counts and landslide areas for the individual
study areas are presented in Table 7. The percentage changes in landslide counts, with
the exception of Lake Creek 2 and Root Creek in the 1954 data set, ranged from six
percent to 625 percent. The 1992 earthquake data set experienced the greatest percent
change in landslide counts between the control year and the study year with all of the
increases
Eel River
Hely Creek
Root Creek
Sammy Creek
Total
1980
Bridge Creek
Eel River
Little Freshwater
Creek
Shively Creek
Tank Gulch
Total
Notes: NA = Not available
Lake Creek 1
Lake Creek 2
Root Creek
S. F. Elk
Yager Creek
Total
1954
1992
Basin
Earthquake Year
N/A
N/A
N/A
N/A
N/A
2.3
1.3
0.5
6.11
85
80
21
27
213
0.8
1.2
12.6
9.7
7.0
3.3
32.58
5
4
3
19
0
7
79
N/A
16
68
163
13
29
15
77
3
17
112
85
52
73
322
N/A
N/A
N/A
N/A
N/A
4,6179
38,712
5,492
18,967
109,349
2,902
807
2,213
12,709
0
6,787
39,393
N/A
3,026
18,891
61,310
10,558
16,732
6,942
52,067
2428
15,408
53,954
101306.1
28,334
38,342
221,939
Number of Slides
Slide Area (square meters)
Study
Post
Post
Area
Before
Post
Before
Post
(km2) Earthquake Earthquake Earthquake Earthquake Earthquake Earthquake
& Storm
& Storm
4
N/A
5
1,524
N/A
1,511
0.3
0.9
0
N/A
0
0
N/A
0
1.0
7
N/A
7
2,471
N/A
6,367
2.6
0
N/A
3
0
N/A
602
2.3
2
N/A
6
708
N/A
22,242
7.07
13
N/A
21
4,702
N/A
30,723
Table 6. Summary of landslide occurrence and area by stage within the individual study areas for each earthquake event.
30
31
Table 7. Summary of percentage changes in landslide occurrence and area for the
individual study areas between control and study years for each earthquake event.
Earthquake
Year
Basin
1954
Lake Creek 1
1954
1963
25
Percentage
Change in
Slide Area
(square
meters) From
Control
Value
-1
Lake Creek 2
1954
1963
0
0
Root Creek
1954
1963
0
158
S. F. Elk
1954
1963
*
*
Yager Creek
1954
1963
200
3041
Eel River
1978
1984
32
17
1981
1984
42
37
1978
1984
6
162
1981
1984
NA
NA
1978
1984
148
416
1981
1984
225
836
1978
1984
170
102
1981
1984
7
103
1994
1997
*
*
1980
Hely Creek
Root Creek
Sammy Creek
1992
Bridge Creek
Control
Photo
Year
Study
Photo Year
Percentage
Change in Slide
Numbers From
Control Year
32
Table 7. Summary of percentage changes in landslide occurrence and size for individual
study areas between control and study years for each earthquake event
(continued).
Earthquake
Year
1992
(continued)
Basin
Eel River
Little
Freshwater
Creek
Shively Creek
Tank Gulch
1994
1997
143
Percentage
Change in
Slide Area
(square
meters) From
Control
Value
127
1994
1997
160
264
1994
1997
625
1973
1994
1997
400
214
Control
Photo
Year
Study
Photo
Year
Percentage
Change in Slide
Numbers From
Control Year
* = Percent change could not be calculated due to an initial value of
zero.
NA = Not available
33
greater than 100 percent. None of the study areas experienced a decrease in landslide
counts between the control year and the study year.
Percentage changes in landslide areas were also nearly all positive, with the
exception of Lake Creek 1, which experienced a decrease in landslide area, and Lake
Creek 2 where no landslides occurred in either the control or study years. The positive
percentage changes in landslide areas ranged from 17 percent (Eel River in the 1980
earthquake set) to 3,041 percent (Yager Creek in the 1954 earthquake set). The negative
percentage change in landslide area experienced in Lake Creek 1 in the 1954 data set was
only a one percent reduction in landslide area, the smallest percentage change observed in
the data set.
South Fork Elk River in the 1954 data set and Bridge Creek in the 1992 data set
could not have percentage changes calculated because they both did not have any
landslides in the control year and then did have landslides in the study year, however,
there was a net increase in landslides at both locations.
Cumulative frequencies for each year were calculated for landslide area results of
the landslide inventory and plotted as an area-frequency distribution (Figure 4). In
general, the area-frequency distribution is greater for the study years compared to the
control years in both the small magnitude events and through the most robust portion of
the area-frequency distribution curve. The trend does not remain consistent for the large
magnitude events. This may indicate that the large magnitude events are controlled by
factors other than those associated with the smaller landslide events. The most robust
34
1954
Cumulative Frequency
(N (m 2)-1 yr-1)
1000
1954
1963
100
Power (1963)
y = 198.65x -0.5044
R2 = 0.9458
10
1
1
10
1000
10000
1980
1000
Cumulative Frequency
(N (m 2)-1 yr-1)
100
Area (m2)
1978
1981
100
1984
Power (1984)
y = 239674x -1.2679
R2 = 0.887
10
1
1
10
1000
10000
1992
1000
Cumulative Frequency
(N (m 2)-1 yr-1)
100
Area (m2)
1994
1997
100
Power (1997)
y = 6564x -0.9149
R2 = 0.8974
10
1
1
10
100
Area (m2)
1000
10000
Figure 4. Landslide area-frequency distributions for each control and study year: 1954,
1980, and 1992 data sets. A power law trend line is drawn through the study
years.
35
portion of the data generally occurs between approximately 200 square meters and 2,000
square meters for each data set.
Figure 5 shows the area-frequency distribution for the 1980 earthquake data set.
This event was associated with the most data and also provided control years for both the
precipitation and the earthquake events. Only the most robust portion of the landslide
area data from 1984 was graphed to show the increase in the strength of the power curve.
It changed from an R2 of 0.89 (Figure 4), where the power curve was best fit through all
the data, to an R2 of 0.98 (Figure 5) when fitted through the main part of the data.
36
1980
Cumulative Frequency
(N (m 2)-1 yr-1)
1000
1978
1981
100
1984
Power (1984)
10
y = 2E+06x -1.5519
R2 = 0.983
1
1
10
100
1000
10000
2
Area (m )
Figure 5. Landslide area-frequency distribution for the 1980 earthquake event with a
power law trend line placed through the most robust portion of the data from the
study year (1984).
DISCUSSION
The purpose of this case study is to test for a general increase in landslide
occurrence and magnitude-frequency after a large seismic event followed by a large
precipitation event coinciding with high antecedent soil moisture when compared to
control years having similar events, although not combined. My hypothesis at the outset
of this study was that there would be an increase in landslide occurrence and magnitudefrequency under this set of conditions. The data indicate there is a general increase in
both occurrence of the number of landslides and the magnitude-frequency of landslides
after an earthquake followed by a large precipitation event. These results are consistent
with Dadson et al. (2004) who found an increase in landslide occurrences mapped in
Taiwan after a typhoon following an earthquake compared to the number of landslides
mapped just after the earthquake and after a typhoon that occurred several years before
the earthquake.
An important consideration of the results of this study is that the study years
occurred approximately nine years, six years, and three years after the initial harvest for
the 1954, 1980, and 1992 data sets, respectively. These time frames, especially for the
1954 data set, occur at the weakest time for relative root reinforcement for residual root
systems and new root growth (Ziemer 1981). In 1981, Ziemer found relative root
reinforcement to be at its lowest, at approximately 20 percent, at 10 years after harvest
for clear cut harvests. Further research could determine if the cycle of natural hazards
examined in this study would have the same results regardless of the type of harvest.
37
38
Interestingly, the largest percentage change in the number of landslides occurred
in the 1992 set (Figure 4, Table 5). In Figure 4, the area-frequency distribution curves
between 1994 (control year) and 1997 (study year) have a larger distance between them
than any of the other data sets. Compared to the other data sets, the 1992 data set should
have the strongest relative root reinforcement strength because it was only approximately
three years between the initial harvest and the study year. Additionally, the large increase
in the number of landslides observed during this time period occurred most recently
compared to the other data sets. The large increases seen in 1992 may be due to spatial
variations in antecedent soil moisture conditions because only one rain gage station was
used in the calculation of the Antecedent Precipitation Index. Rainfall may have been
more intense or lasted longer in the study areas farther from that rain gage. An additional
consideration for 1992 is that there were three earthquakes with magnitudes greater that
six (M6) within two days in 1992. The additional earthquakes might have increased the
effect of de-stabilization of colluvial hollows as compared to the 1954 and 1980 single
earthquake event data sets.
I also believed it was important to examine, along with root reinforcement
influences, any differences in rainfall amounts or Antecedent Precipitation Index values
that might cause differences between the data sets. Cafferata and Spittler (1998)
identified one, three, and 10 day rainfall thresholds for initiating landslides in Caspar
Creek (north-central coast of California) at 4.88 centimeters (1.92 inches), 11.94
centimeters (4.70 inches), and 20.09 centimeters (7.91 inches), respectively. I targeted
39
twelve rainfall events for this study (Table 2). Of these twelve, seven had one day
rainfall totals between 9.91 and 11.30 centimeters (3.90 and 4.45 inches, respectively),
well above the one day rainfall threshold identified by Cafferata and Spittler (1998).
Four of the targeted rainfall events had three day rainfall totals between 18.08 and 25.37
centimeters (7.12 and 9.99 inches, respectively) that were greater than the threshold
identified by Cafferata and Spittler (1998) and one storm had a five day rainfall total of
40.11 centimeters (15.79 inches).
Looking at the most significant rain events, in terms of rainfall totals and
Antecedent Precipitation Index values allows for direct comparison of the precipitation
controls. For the 1954 earthquake event, the rain event producing the highest Antecedent
Precipitation Index (12.4 centimeters) for the control year analysis occurred on October
29, 1950. It had a three day rainfall amount of 25.37 centimeters (9.99 inches). The rain
event with the highest Antecedent Precipitation Index (14.7 centimeters) for the study
year had a one day rain total of 10.74 centimeters (4.23 inches). The Antecedent
Precipitation Index values for these two rain events are relatively similar even though the
actual rainfall amounts were more than double the amount in the study year compared to
the control year. The 1980 earthquake data set yielded rain events with very similar
Antecedent Precipitation Index values and one day rainfall totals for the pre-earthquake
control (January 1, 1974), post-earthquake control (November 17, 1981), and the study
year (January 26, 1983). The January 16, 1974 rainfall event had an Antecedent
Precipitation Index of 12.4 centimeters and a one day rainfall total of 10.85 centimeters
40
(4.27 inches). The November 17, 1981 event had an Antecedent Precipitation Index of
10.2 centimeters and a three day rainfall total of 18.08 centimeters (7.12 inches). The
Antecedent Precipitation Index values for the 1992 earthquake data set had the largest
difference between the control and study year at 11.6 centimeters and 14.5 centimeters,
respectively. For the control year (January 10, 1995), the three day rainfall total was
24.05 centimeters (9.47 inches) and for the study year (January 1, 1997), the three day
rainfall total was 22.61 centimeters (8.90 inches). The difference between the control and
study year Antecedent Precipitation Index values for the 1992 earthquake data set may be
the reason that the percent increase in landslide occurrence during this time was greater
than the other earthquake data sets.
For the magnitude-frequency analysis, the cumulative frequency plots (Figures 4
and 5) follow the power law trend observed for landslide frequencies in other studies
(Hovius et al. 1997, Hovius et al. 2000, Dai and Lee 2001, Guzzetti et al. 2002, and
Martin et al. 2002). The plots flatten out the lower end of the graph and steepen at the
upper bounds. This is likely due to a lack of data at the lower bounds because of the
difficulty in identifying small landslides and at the upper bounds because the period of
record may not be long enough to provide accurate data (Guzzetti et al. 2002 and Martin
et al. 2002). It has been determined that many small landslides are not accounted for
when doing an aerial photographic inventory and can under represent landslide
frequencies (Robison et al. 1999, Wills and McCrink 2002, and Brardinoni et al. 2003).
41
This case study attempts to identify a trend of increased sediment production in
terms of shallow landslides after the de-stabilization of hillslopes due to strong shaking
associated with earthquakes followed by large rain events. I interpret the results to
suggest that there is a trend of increasing landslides given the afore-mentioned conditions
in this region. Further research in northwestern California is recommended to look at
which combination of hillslope characteristics, such as geology, slope gradient, harvest
methods, etc, are the most sensitive to this combination of natural hazards. This study
only looked at the magnitude-frequency distributions of individual years and only
accounted for shallow landslides. Additional research may attempt to look at the areafrequency or volume-frequency distributions over time and for different types of
landslides, such as bedrock-dominated landslides.
REFERENCES
Anderson, S. A. and N. Sitar. 1995. Analysis of rainfall-induced debris flows. Journal of
Geotechnical Engineering 121:544-552.
Benda, L. E. and T. Dunne. 1997. Stochastic forcing of sediment supply to channel
networks from landsliding and debris flow. Water Resources Research
33(12):2849-2863.
Blake, M. C., A. S. Jayko, Jr., and R. J. McLaughlin. 1988. Metamorphic and tectonic
evolution of the Franciscan Complex, Northern California. Pages 1035-1060 in
W. G. Ernst, editor. Metamorphic and crustal evolution of the western United
States. Prentice Hall, New Jersey.
Brardinoni, F., O. Slaymaker, and M. A. Hassan. 2003. Landslide inventory in a rugged
forested watershed: a comparison between air-photo and field survey data.
Geomorphology 54:179-196.
Cafferata, P. and T. E. Spittler. 1998. Logging impacts of the 1970s vs. the 1990s in the
Caspar Creek watershed. In R. R. Ziemer, editor. Proceedings of the Conference
on Coastal Watersheds: The Caspar Creek Story; 6 May 1998, Ukiah, California.
United States Department of Agriculture Pacific Southwest Research Station,
General Technical Report PSW GTR-168, Albany, California. 149 pp.
California Department of Natural Resources, Division of Forestry. 1954. Black and white
photographs, flight CVL-11N, Flight Lines 11N, 12N, 13N, and 14N, Scotia,
California. August 1954, nominal scale 1:26,400.
California State Water Resources Control Board. 2002. Final 2002 Region 1 (North
Coast) Clean Water Act Section 303(d) List of Water Quality Limited Segments,
Santa Rosa, California. Available at
http://www/waterboards.ca.gov/tmdl/docs/2002reg1303dlist.pdf.
Casadel, M., W. E. Dietrich, and N. L. Miller. 2003. Testing a model for predicting the
timing and location of shallow landslide initiation in soil-mantled landscapes.
Earth Surface Processes and Landforms 28:925-950.
Cascade Aerial Maps and Surveying, Inc. 1981. Black and white photographs, Flight CHUM-81, Flight Lines 13A, 14A, 16A, 17A, 19A, 20B, 21B, and 22B, Scotia,
California. June 2-21, 1981, nominal scale 1:12,000.
42
43
Cascade Aerial Maps and Surveying, Inc. 1994. Color photographs, Flight HUM 94,
Flight Lines 17, 18, 19, 22, 25, and 26, Scotia, California. July - August 1994,
nominal scale 1:12,000. Coe, J. A., J. A. Michael, R. A. Crovelli, W. Z. Savage,
W. T. LaPrade, and W. D. Nashem. 2004. Probabilistic assessment of
precipitation-triggered landslides using historical records of landslide occurrence,
Seattle, Washington. Environmental & Engineering Geoscience X(2):103-122.
Crozier, M. J. 1999. Prediction of rainfall-triggered landslides: a test of the Antecedent
Water Status Model. Earth Surface Processes and Landforms 24:825-833.
Dadson, S. J., N. Hovius, H. Chen, W. B. Dade, J-C. Lin, M-L. Hsu, C-W. Lin, M-J.
Horng, T-C. Chen, J. Milliman, and C. P. Stark. 2004. Earthquake-triggered
increase in sediment delivery from an active mountain belt. Geology 32(8):733736.
Dai, F. C. and C. F. Lee. 2001. Frequency-volume relation and prediction of rainfallinduced landslides. Engineering Geology 59:253-266.
Dhakal, A. S. and R. C. Sidle. 2004. Distributed simulations of landslides for different
rainfall conditions. Hydrological Processes 18:757-776.
Dietrich, W. E., T. Dunne, N. F. Humphrey, and L. M. Reid. 1982. Construction of
sediment budgets for drainage basins. United States Department of Agriculture
Forest Service, Pacific Northwest Forest and Range Experiment Station, General
Technical Report PNW-141:5-23, Portland, Oregon.
Fedora, M. A. 1987. Simulation of storm runoff in the Oregon Coast Range. United
States Department of the Interior Bureau of Land Management, BLM Technical
Note 378:48-52, Corvallis, Oregon.
Guzzetti, F., B. D. Malamud, D. L. Turcotte, and P. Reichenbach. 2002. Power-law
correlations of landslide areas in central Italy. Earth and Planetary Science Letters
195:169-183.
Hovius, N., C. P. Stark, and P. A. Allen. 1997. Sediment flux from a mountain belt
derived by landslide mapping. Geology 25:231-234.
Hovius, N., C. P. Stark, H-T. Chu, and J-C. Lin. 2000. Supply and removal of sediment
in a landslide-dominated mountain belt: Central Range, Taiwan. The Journal of
Geology 108:73-89.
Humboldt County Assessor. 1962/1963. Black and white photographs, Flight H-S-2-3,
Flight Lines 21 and 27B, Scotia, California, nominal scale 1:28,500.
44
Jakob, M. and H. Weatherly. 2003. A hydroclimatic threshold for landslide initiation on
the North Shore Mountains of Vancouver, British Columbia. Geomorphology
54:137-156.
Kelsey, H.M. and A. O. Allwardt. 1987. Geology of the Iaqua Buttes 15-Minute
Quadrangle, Humboldt County, California, California Department of
Conservation Division of Mines and Geology, Sacramento, California.
Kilbourne, R. T. 1985a. Geology and geomorphic features related to landsliding,
McWhinney Creek 7.5-Minute Quadrangle, Humboldt County, California:
California Department of Conservation Division of Mines and Geology,
Sacramento, California.
Kilbourne, R. T. 1985b. Geology and geomorphic features related to landsliding,
Hydesville 7.5-Minute Quadrangle, Humboldt County, California: California
Department of Conservation Division of Mines and Geology, Sacramento,
California.
Lehre, A. K. 1982. Sediment budget of a small coast range drainage basin in NorthCentral California. United States Forest Service Pacific Northwest Forest and
Range Experiment Station, General Technical Report PNW-141:67-77, Portland,
Oregon.
Martin, Y., K. Rood, J. W. Schwab, and M. Church. 2002. Sediment transfer by shallow
landsliding in the Queen Charlotte Islands, British Columbia. Canadian Journal of
Earth Sciences 39:189-205.
McLaughlin, R. J., S. D. Ellen, M. C. Blake, A. S. Jayko, Jr., W. P. Irwin, K. R. Aalto, G.
A. Carver, and S. H. Clarke, Jr. 2000. Geology of the Cape Mendocino, Eureka,
Garberville, and southwestern part of the Hayfork 30 x 60 minute quadrangles
and adjacent offshore area, Northern California. United States Department of the
Interior United States Geological Survey, Menlo Park, California.
Montgomery, D. R., K. M. Schmidt, H. M. Greenberg, and W. E. Dietrich. 2000. Forest
clearing and regional landsliding. Geology 28(4):311-314.
National Climate Data Center. 2004. Climate-radar data inventories station list, Scotia,
California, Asheville, North Carolina. Available at
http://www4.ncdc.noaa.gov/cgi-win/wwcgi.dll?wwDI~SelectStation~USA~CA.
National Earthquake Information Center. 2005. Earthquake Database. United States
Department of the Interior United States Geological Survey, Denver, Colorado.
Available at http://neic.usgs.gov/neis/epic/epic_rect.html
45
Onda, Y., M. Tsujimura, and H. Tabuchi. 2004. The role of subsurface water flow paths
on hillslope hydrological processes, landslides and landform development in steep
mountains of Japan. Hydrological Processes 18:637-650.
Pearce, A. J. and A. J. Watson. 1986. Effects of earthquake-induced landslides on
sediment budget and transport over a 50-yr period. Geology 14:52-55.
Reid, L. M. 1998. Calculation of average landslide frequency using climatic records.
Water Resources Research 34(4):869-877.
Reid, L. M. and T. Dunne. 1996. Rapid evaluation of sediment budgets. Catena Verlag,
Reiskirchen, Germany, 164 pp.
Robison, E. G., K. A. Mills, J. Paul, L. Dent, and A. Skaugset. 1999. Oregon Department
of Forestry Storm Impacts and Landslides of 1996: Final Report. Forest Practices
Technical Report Number 4, Salem, Oregon.
Scotia Pacific Geology Archives. 1978. Black and white photographs, Flight C-STCS-17
B1171, Flight Lines 7, 8, 9, 16, 17, 19, 20, 21, and 22, Scotia, California. July 18,
1978, nominal scale 1:12,000.
Scotia Pacific Geology Archives. 1984. Black and white photographs, Flight: unknown,
Flight Lines: unknown, Scotia, California.
Spittler, T. E. 1983. Geology and geomorphic features related to landsliding, Redcrest
7.5-Minute Quadrangle, Humboldt County, California: California Department of
Conservation Division of Mines and Geology, Sacramento, California.
Swanson, F. J., L. E. Benda, S. H. Duncan, G. E. Grant, W. F. Megahan, L. M. Reid, and
R. R. Ziemer. 1987. Mass failures and other processes of sediment production in
Pacific Northwest forest landscapes. In E. O. Salo and T. W. Cundy, editors.
Streamside Management: Forestry and Fishery Interactions. Proceedings of
Symposium held at University of Washington, 12-14 February 1986, Seattle,
Washington.
WAC, Inc. 1997. Color photographs, Flight HUM-97, Flight Lines 17, 18. 19, 22, 24, 25,
and 26, Scotia, California. July 20 - August 2, 1997.
Western Regional Climate Center. 2006. Period of record monthly climate summary for
Scotia, California, Reno, Nevada. Available at http://www.wrcc.dri.edu/cgibin/cliRECtM.pl?ca8045.
Wills, C. J. and T. P. McCrink. 2002. Comparing landslide inventories: the map depends
on the method. Environmental & Engineering Geoscience VIII(4):279-293.
46
Wilson, R. C. and D. K. Keefer. 1985. Predicting aerial limits of earthquake-induced
landsliding. In J. I. Ziony, editor. Evaluating earthquake hazards in the Los
Angeles region - an earth-science perspective. United States Geological Survey
Professional Paper 1360 pp. 316-345, Menlo Park, California.
Ziemer, R. R. 1981. The role of vegetation in the stability of forested slopes. Pages 291308 in International Union of Forest Research Organization, XVII IUFRO World
Congress Proceeding, Division I.
Ziemer, R. R. 1984. Response of progressive hillslope deformation to precipitation. Pages
91-98 in C.L. O'
Laughlin and A. J. Pearce, editors. Proceedings of the
Symposium on the effects of forest land use on erosion and slope stability, 7-11
May 1984, Honolulu, Hawaii.
Ziemer, R. R. and J. S. Albright. 1987. Subsurface pipeflow dynamics of north-coastal
California swale systems. Pages 71-80 in R. L. Beschta, T. Blinn, G. E. Grant, F.
J. Swanson, and G. G. Ice, editors. Erosion and sedimentation on the Pacific Rim,
proceedings of the Corvallis Symposium. International Association of
Hydrological Sciences Publication No. 165, Wallingford, U. K.
Appendix A. Calculated Antecedent Precipitation Index values (in inches) during the
period of record from December 1940 through December 1999 in five year
intervals.
Date
Date
47
9/1/1949
5/1/1949
1/1/1948
9/1/1947
5/1/1947
1/1/1947
9/1/1946
5/1/1946
1/1/1946
9/1/1945
5/1/1945
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
1/1/1945
API
API Values 1945-1949
12/1/1944
3/1/1944
1/1/1949
9/1/1944
12/1/1943
9/1/1948
6/1/1944
9/1/1943
5/1/1948
6/1/1943
3/1/1943
12/1/1942
9/1/1942
6/1/1942
3/1/1942
12/1/1941
9/1/1941
6/1/1941
3/1/1941
7.00
6.00
5.00
4.00
3.00
2.00
1.00
0.00
12/1/1940
API
API Values December 1940 - December 1944
48
Appendix A. Calculated Antecedent Precipitation Index values (in inches) during the
period of record from December 1940 through December 1999 in five year
intervals (continued).
5/1/1953
9/1/1953
1/1/1954
5/1/1954
9/1/1954
5/1/1958
9/1/1958
1/1/1959
5/1/1959
9/1/1959
1/1/1953
9/1/1952
5/1/1952
1/1/1952
9/1/1951
5/1/1951
1/1/1951
9/1/1950
5/1/1950
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
1/1/1950
API
API Values 1950 - 1954
Date
Date
1/1/1958
9/1/1957
5/1/1957
1/1/1957
9/1/1956
5/1/1956
1/1/1956
9/1/1955
5/1/1955
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
1/1/1955
API
API Values 1955-1959
49
Appendix A. Calculated Antecedent Precipitation Index values (in inches) during the
period of record from December 1940 through December 1999 in five year
intervals (continued).
5/1/1963
9/1/1963
1/1/1964
5/1/1964
9/1/1964
5/1/1968
9/1/1968
1/1/1969
5/1/1969
9/1/1969
1/1/1963
9/1/1962
5/1/1962
1/1/1962
9/1/1961
5/1/1961
1/1/1961
9/1/1960
5/1/1960
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
1/1/1960
API
API Values 1960 - 1964
Date
Date
1/1/1968
9/1/1967
5/1/1967
1/1/1967
9/1/1966
5/1/1966
1/1/1966
9/1/1965
5/1/1965
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
1/1/1965
API
API Values 1965 - 1969
50
Appendix A. Calculated Antecedent Precipitation Index values (in inches) during the
period of record from December 1940 through December 1999 in five year
intervals (continued).
9/1/1973
1/1/1974
5/1/1974
9/1/1974
9/1/1978
1/1/1979
5/1/1979
9/1/1979
5/1/1973
1/1/1973
9/1/1972
5/1/1972
1/1/1972
9/1/1971
5/1/1971
1/1/1971
9/1/1970
5/1/1970
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
1/1/1970
API
API Values 1970 - 1974
Date
Date
5/1/1978
1/1/1978
9/1/1977
5/1/1977
1/1/1977
9/1/1976
5/1/1976
1/1/1976
9/1/1975
5/1/1975
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
1/1/1975
API
API Values 1975 - 1979
51
Appendix A. Calculated Antecedent Precipitation Index values (in inches) during the
period of record from December 1940 through December 1999 in five year
intervals (continued).
9/1/1983
1/1/1984
5/1/1984
9/1/1984
9/1/1988
1/1/1989
5/1/1989
9/1/1989
5/1/1983
1/1/1983
9/1/1982
5/1/1982
1/1/1982
9/1/1981
5/1/1981
1/1/1981
9/1/1980
5/1/1980
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
1/1/1980
API
API Values 1980 - 1984
Date
Date
5/1/1988
1/1/1988
9/1/1987
5/1/1987
1/1/1987
9/1/1986
5/1/1986
1/1/1986
9/1/1985
5/1/1985
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
1/1/1985
API
API Values 1985 - 1989
52
Appendix A. Calculated Antecedent Precipitation Index values (in inches) during the
period of record from December 1940 through December 1999 in five year
intervals (continued).
9/1/1993
1/1/1994
5/1/1994
9/1/1994
9/1/1998
1/1/1999
5/1/1999
9/1/1999
5/1/1993
1/1/1993
9/1/1992
5/1/1992
1/1/1992
9/1/1991
5/1/1991
1/1/1991
9/1/1990
5/1/1990
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
1/1/1990
API
API Values 1990 - 1994
Date
Date
5/1/1998
1/1/1998
9/1/1997
5/1/1997
1/1/1997
9/1/1996
5/1/1996
1/1/1996
9/1/1995
5/1/1995
7.000
6.000
5.000
4.000
3.000
2.000
1.000
0.000
1/1/1995
API
API Values 1995 - 1999