National Assessment Of Shoreline Change Part 3: Historical 
Shoreline Change and Associated Coastal Land Loss Along 
Sandy Shorelines of the California Coast

Cheryl J. Hapke(1), David Reid(2), Bruce M. Richmond(2), 
Peter Ruggiero(3), and Jeff List(4)

2006

U.S. Geological Survey 
Open-file Report 2006-1219.

U.S. Department of the Interior
U.S. Geological Survey

(1) U.S. Geological Survey, Coastal Field Station, 
Department of Geosciences, University of Rhode Island, 
Kingston, RI 02881

(2) U.S. Geological Survey, Pacific Science Center, Santa 
Cruz, CA 95060

(3) Dept. of Geosciences, Oregon State University, 
Corvallis, OR 97331

(4) U.S. Geological Survey, Woods Hole Science Center, 
Woods Hole, MA 02543

Any use of trade, firm, or product names is for descriptive 
purposes only and does not imply endorsement by the U.S. 
Government.

Contents

EXECUTIVE SUMMARY....1

INTRODUCTION....1

U.S. Geological Survey National Assessment of Shoreline 
Change....1

Disclaimer...2

Acknowledgments....2

THE ROLE OF STATE AND FEDERAL GOVERNMENTS....4

PRIOR NATIONAL AND CALIFORNIA COAST SHORELINE 
ASSESSMENTS....4

METHODS OF ANALYZING SHORELINE CHANGE....5

Compilation of Historical Shorelines....5

Delineation of a Modern (Lidar-derived) Shoreline....5

Geographic Information System (GIS) Procedures....6

Calculation and Presentation of Rates of Change....7

Beach Alterations and Shoreline Definitions that Influence 
Rates of Change....8

Human Activities....8

Shoreline Definitions....9

Estimating the proxy-datum bias and the bias 
uncertainty....10

Uncertainties and Errors....11

End-point (short-term) shoreline change error ....13

Linear regression (long-term) shoreline change error....14

GEOLOGIC HISTORY AND SETTING....15

General Geology of the California Coast....15

Climate	....19

Coastal Processes....20

Waves	....20

Tides	....21

Winds	....22

Currents....22

Littoral cells and transport directions....22

Sand Sources....23

GEOMORPHOLOGY OF THE CALIFORNIA COAST....24

Cliffs	....24

Beaches....24

Coastal Dune Complexes....26

Estuaries and Lagoons....26

General Characteristics of the California Coast 
Sections....27

Northern Section:  Oregon Border to Tomales Bay....27

Central Section: Tomales Bay to Point Conception....30

Southern Section: Point Conception to the Mexican 
Border....30

HISTORY OF INFRASTRUCTURE DEVELOPMENT....30

HISTORICAL SHORELINE CHANGE ANALYSIS....33

Northern California....33

Klamath Region....33

Eureka Region....34

Navarro Region....36

Russian River Region....40

Central California....42

San Francisco North Region....43

San Francisco South Region....43

Monterey Bay Region....47

Big Sur Region....50

Morro Bay Region....50

Santa Barbara North....54

Southern California....56

Santa Barbara South Region....57

Santa Monica Region  ....57

San Pedro Region....61

Oceanside Region....63

San Diego Region....65

DISCUSSION AND FURTHER CONSIDERATIONS....67

Summary of Shoreline Changes....67

Planned Updates and Related Research....68

Influence of Human Activities....68

REFERENCES....68

Figures

Figure 1. 	Index map of California showing the fifteen 
regions discussed in the text....3

Figure 2. 	Example of a lidar profile from April 10, 
1998 at Santa Cruz, California....7

Figure 3. 	Examples of common conditions where 
transects are eliminated in the absence of 
	four shoreline intersections....9

Figure 4.  	Major tectonic elements and geomorphic 
provinces of California ....16

Figure 5.  	Index map showing locations of place names 
discussed in Geologic History and Geomorphology 
section....17

Figure 6.  	Simplified geologic map of California....18

Figure 7.  	General wave directions for central 
California based on offshore wave buoy data....20

Figure 8.  	Monthly mean sea level for selected tide 
gauges along the California coast....21

Figure 9.  	Map showing major littoral cell boundaries, 
coastal watersheds, and conceptual net longshore 
drift directions for the California coast....23

Figure 10. 	Average annual sand and gravel discharge 
from major rivers in California....25

Figure 11. 	Sketch of common coastal landforms of 
California....26

Figure 12. 	Beach profiles from Cowells Beach in Santa 
Cruz illustrating beach erosion over an El Ni_o winter 
and the subsequent recovery the following summer....27

Figure 13. 	Map showing the major coastal dune complexes 
of California....28

Figure 14A. Index map showing the four analysis regions in 
Northern California and various locations....29

Figure 14B. Index map showing the six analysis regions in 
Central California and various locations ....31

Figure 14C. Index map showing the five analysis regions in 
Southern California and various locations....32

Figure 15. 	Shoreline change rates for the Klamath 
region....35

Figure 17. 	Shoreline change rates for the Eureka 
region....37

Figure 18. 	Spit and jetty on north side of Humboldt Bay 
Harbor in photograph taken in June 1987....38

Figure 19. 	Shoreline change rates for the Navarro 
region....39

Figure 20. 	Photographs from 1972 (top) and 2002 
(bottom) show the widening of the spit beach at the 
	Ten Mile River mouth....40

Figure 21. 	Shoreline change rates for the Russian River 
region....41

Figure 22. 	Many of the large rivers in Northern 
California have well-developed sandy spits such as this one 
	extending across the mouth of the Russian River....42

Figure 23. 	Shoreline change rates for the San Francisco 
North region....44

Figure 24. 	Houses on the spit at Stinson Beach are 
partially buried by sand during an El Ni_o winter storm in 
1983....45

Figure 25. 	Shoreline change rates for the San Francisco 
South region....46

Figure 26. 	A riprap revetment protects an apartment 
building that overlooks a narrow beach near 
	Pillar Point Harbor in a photograph taken in February, 
2002....47

Figure 27. 	Shoreline change rates for the Monterey Bay 
region....48

Figure 28. 	Aerial photographs of the Santa Cruz Yacht 
Harbor show the impoundment of sand against the 
	constructed jetties....49

Figure 29. 	Shoreline change rates for the Big Sur 
region....51

Figure 30. 	JP Burns waterfall shows the beach that 
formed as a result of the sediment added to the system 
	from the 1983 landslide....52

Figure 31.  Shoreline change rates for the Morro Bay 
region....53

Figure 32.  Development of a tombolo at Morro Rock after a 
causeway was built in the 1930s....54

Figure 33.  Shoreline change rates for the Santa Barbara 
North region....55

Figure 34.  Photographs from January 1989 shows the well-
developed dune field at Guadalupe Dunes....56

Figure 35.  Shoreline change rates for the Santa Barbara 
South region....58

Figure 36.  Dredging of spit at Santa Barbara Harbor....59

Figure 37.  Shoreline change rates for the Santa Monica 
region....60

Figure 38.  Oblique aerial photograph of a breakwater along 
the highly engineered Santa Monica coastline....61

Figure 39.  Shoreline change rates for the San Pedro 
region....62

Figure 40.  Oblique aerial photograph of the Los Angeles 
Harbor....63

Figure 41.  Shoreline change rates for the Oceanside 
region....64

Figure 42.  Narrow beach fronting tall coastal bluffs at 
Torrey Pines City Beach....65

Figure 43.  Shoreline change rates for the San Diego 
region....66

Figure 44.  Oblique aerial photograph of Zuniga Point and 
breakwater at the entrance to the San Diego Harbor....67

Tables

Table 1. 	Providers and original sources of historical 
shorelines for each California region....5

Table 2. 	Dates of compiled shorelines in different regions 
for selected periods....6

Table 3. 	List of tide gauge measurements used to calculate 
mean high water elevation....8

Table 4.  	Absolute horizontal and vertical differences 
between high water and mean high water shorelines....10

Table 5.  	Maximum estimated measurement errors for 
California shorelines....11

Table 6A. 	Average shoreline change rates for Northern 
California....12

Table 6B. 	Average shoreline change rates for Central 
California....12

Table 6C. 	Average shoreline change rates for Southern 
California....12

Table 7.  	Coastal cliff rock type along the California 
coast (from Runyan and Griggs, 2002)....19

Table 8.  	Estimated annual littoral drift rates and 
directions along the California Coast....24

Table 9A.  	Maximum and minimum shoreline change rates: 
Northern California....34

Table 9B.  	Maximum and minimum shoreline change rates: 
Central California....45

Table 9C.  	Maximum and minimum shoreline change rates: 
Southern California....59

EXECUTIVE SUMMARY

Beach erosion is a chronic problem along many open-ocean 
shores of the United States. As coastal populations 
con_tinue to grow and community infrastructures are 
threatened by erosion, there is increased demand for 
accurate informa_tion regarding past and present trends and 
rates of shore_line movement. There is also a need for a 
comprehensive analysis of shoreline movement that is 
consistent from one coastal region to another. To meet 
these national needs, the U.S. Geological Survey is 
conducting an analysis of histori_cal shoreline changes 
along open-ocean sandy shores of the conterminous United 
States and parts of Hawaii and Alaska. One purpose of this 
work is to develop standard repeatable methods for mapping 
and analyzing shoreline movement so that periodic updates 
regarding coastal erosion and land loss can be made 
nationally that are systematic and internally con_sistent. 
In the case of this study, the shoreline being measured is 
the boundary between the ocean water surface and the sandy 
beach.

This report on the California Coast represents the first of 
two reports on long-term sandy shoreline change for the 
western U.S., the second of which will include the coast of 
the Pacific NW, including Oregon and Washington. A report 
for the Gulf of Mexico shoreline was completed in 2004 and 
is available at: http://pubs.usgs.gov/of/2004/1043/.  This 
report summarizes the methods of analysis, interprets the 
results, provides explanations regarding long-term and 
short-term trends and rates of change, and describes how 
different coastal communities are responding to coastal 
erosion. Shore_line change evaluations are based on 
comparing three histori_cal shorelines digitized from maps, 
with a recent shoreline derived from lidar (Light Detection 
and Ranging) topographic surveys. The historical shorelines 
generally represent the following periods: 1800s, 1920s-
1930s, and 1950s-1970s, whereas the lidar shoreline is from 
1998-2002. Long-term rates of change are calculated using 
all four shorelines (1800s to lidar shoreline), whereas 
short-term rates of change are calculated for only the most 
recent period (1950s-1970s to lidar shoreline). The rates 
of change presented in this report represent past 
conditions and therefore are not intended for predicting 
future shoreline positions or rates of change.  Due to the 
geomorphology of the California Coast (rocky coastline 
instead of beach) as well as to data gaps in some areas, 
this report presents beach erosion rates for 45% of 
California's 1100 km of coast.

The average rate of long-term shoreline change for the 
State of California was 0.2_0.1 m/yr, an accretional trend.  
This is based on shoreline change rates averaged from 
14,562 individual transects, of which 40% were eroding.  Of 
the transects on which the shoreline was eroding, the long-
term erosion rates were generally lowest in Southern 
California where coastal engineering projects have greatly 
altered the natural shoreline movement.  On a regional 
scale, long-term accretion rates were either equal to 
(Central California) or greater than (Northern and Southern 
California) the long-term erosion rates, yielding the net 
accretional trend for the entire state.  This accretional 
trend is most likely due to changes in the large volumes of 
sediment that are added to the system from large rivers and 
to the impact from coastal engineering and beach 
nourishment projects.

The average rate of short-term shoreline change for the 
state was erosional.  The net short-term rate as averaged 
along 16,142 transects was -0.2_0.4 m/yr.  Of the transects 
used to measure short-term change, 66% had erosional 
trends.  In addition erosion rates were higher in the 
short-term period, possibly related to the localized 
artificial nourishment that occurred over much of the 20th 
century but that has recently slowed or stopped (Flick, 
1993; Wiegel, 1994).  Short-term accretion rates were 
highest in Northern California where the overall magnitudes 
of shoreline change are systematically higher than in 
Central and Southern California. The most stable (low 
erosion and accretion rates) California beaches were most 
commonly found in Central California. 

Seawalls and/or riprap revetments have been constructed in 
all three sections of California, although many of these 
structures were built to protect houses and infrastructures 
from the erosion of coastal cliffs and bluffs rather than 
to protect against long-term beach erosion.  California 
permits shoreline stabilization structures where homes, 
buildings or other community infrastructure are imminently 
threatened by erosion.  

A second California report that is following this 
publica_tion will include analyses and reports on long-term 
coastal cliff erosion, as this hazard is of equal or 
greater concern to coastal communities in many areas along 
the California Coast.

INTRODUCTION

U.S. Geological Survey National Assessment of Shoreline 
Change

Sandy ocean beaches represent some of the most popular 
tourist and recreational destinations in the United States, 
and also constitute some of the most valuable real estate 
in the country. These changing and ephemeral interfaces 
between water and land are the sites of intense residential 
and commercial development even though they are frequently 
subjected to a range of natural hazards that can include 
flood_ing, storm impacts, coastal erosion and tsunami 
inundation. Because population and economic trends have 
made the coasts so valuable, the U.S. Geological Survey 
(USGS) is conducting a National Assessment of Coastal 
Change Haz_ards. One component of this effort, the National 
Assessment of Shoreline Change, documents changes in 
shoreline posi_tion as a proxy for coastal change.  
Shoreline position is one of the most commonly monitored 
indicators of environmen_tal change (Morton, 1996), and it 
is easily understood by those who are interested in 
historical movement of beaches.

A principal purpose of the USGS shoreline change research 
is to develop a repeatable surveying methodology so that 
shorelines for the continental U.S., and portions of Hawaii 
and Alaska, can be periodically and systematically updated 
in an internally consistent manner.  In addition, new 
methods for developing datum-based shorelines and 
assess_ing coastal change can provide the opportunity to 
achieve more comprehensive assessments of error in the 
future. The primary objectives of this effort are: (1) to 
develop and implement improved methods of assessing and 
monitoring shoreline movement, (2) to obtain a better 
understanding of the processes controlling shoreline 
movement, and (3) to enter into partnerships to facilitate 
data dissemination. 

Achieving these ongoing objectives requires research that 
(1) examines the original sources of shoreline data (maps, 
air photos, global positioning system (GPS), lidar), (2) 
evaluates the utility of different shoreline proxies 
(geomorphic feature, water mark, tidal datum, elevation 
contour) including the errors associated with each method, 
(3) investigates the bias and potential errors associated 
with integrating different shoreline proxies from different 
sources, (4) develops standard uniform methods of shoreline 
change analysis, (5) determines the effects of human 
activi_ties on shoreline movement and rates of change, and 
(6) investigates alternative mathematical methods for 
calculat_ing historical rates of change and forecasting 
future rates of change.

This report summarizes historical changes in the California 
sandy shoreline, both accretion and erosion, but emphasizes 
the erosion hazard because of its impacts on natural 
resources and the economy. The descriptions of coastal land 
loss for each region (Figure 1) within the state provide a 
more comprehensive view of coastal processes and key 
references that can be used to learn more about coastal 
change in a regional context.

Disclaimer

Results of the National Assessment of Shoreline Change are 
organized by coastal regions. This report for California is 
part of a series of reports that will include text 
summarizing methods, results, and implications of the 
results in addition to maps, via Internet Map Server (IMS), 
illustrating rates of shoreline change. Rates of shoreline 
change are being published for the purpose of regional 
characterization. The shoreline change results and products 
prepared by the USGS are not intended for comprehensive 
detailed site specific analysis of shoreline movement, nor 
are they intended to replace any official sources of 
shoreline change information identified by local or state 
government agencies, or other federal entities that are 
used for regulatory purposes. Rates of shoreline change 
presented herein may differ from other published rates, and 
differences do not necessarily indicate that the other 
rates are inaccurate. Some discrepancies are expected, 
considering the many possible ways of determining shoreline 
positions and rates of change, and the inherent uncertainty 
in calculating these rates. Rates of shoreline change 
presented in this report represent shore_line movement 
under past conditions. The results are not intended for 
predicting future shoreline positions or future rates of 
shoreline change.

This publication was prepared by an agency of the United 
States Government. Neither the United States Gov_ernment 
nor any agency thereof, nor any of their employ_ees, makes 
any warranty, expressed or implied, or assumes any legal 
responsibility for the accuracy, completeness, or 
usefulness of any information apparatus, product, or 
process disclosed in the report, or represents that its use 
would not infringe privately owned rights. Reference to any 
specific commercial product, process, or service by trade 
name, trademark, manufacturer, or otherwise does not 
necessarily constitute or imply its endorsement, 
recommendation, or favoring by the United States Government 
or any agency thereof. Any views and opinions of authors 
expressed herein do not necessarily state or reflect those 
of the United States Government or any agency thereof.

Acknowledgments

This report was made possible by the hard work and generous 
cooperation of many individuals. We owe a debt of gratitude 
to Mike Rink (NOAA) and Paul Frascione (Information 
Manufacturing Corporation) for providing digital historical 
shorelines and scans of selected T-sheets, and David Doyle 
(NOAA) for providing datum corrections so that T-sheets 
could be rectified before they were digitized by the USGS. 
An enthusiastic and untiring USGS team was responsible for 
developing the methods and computer codes for calculating 
operational mean high water elevations and extracting the 
lidar shorelines. The lidar research and development team 
included Abby Sallenger, Jeff List, Karen Morgan, Eric 
Nelson, Hillary Stockdon, and Kathy Webber. Tara Miller and 
Kathy Webber provided invaluable help in data processing 
and analysis.  Rob Thieler worked closely with TPMC 
Environmental Services to develop and improve the Digital 
Shoreline Analysis System (DSAS) code for shoreline change 
measurement. Brian Spear (UCSC) and Evan Lindenbach (UCSC) 
provided assistance by digitizing shorelines and cliff 
edges, georectifiying maps and prepar_ing metadata. Bruce 
Rogers provided valuable assistance in the drafting of 
figures, and Ben Melosh (UCSC) helped with background data 
compilation. Ann Gibbs provided excellent advice and input 
regarding data presentation.  Comments from and discussions 
with Ed Thornton, Bob Guza, Dick Seymour, Bob Wiegel, Mark 
Crowell, Lesley Ewing, Bob Morton and Sam Johnson were also 
very helpful.  Finally, a detailed review by Gary Griggs 
was invaluable and greatly improved the report.

THE ROLE OF STATE AND FEDERAL GOVERNMENTS

One reason for conducting this National Assessment of 
Shoreline Change is that there is no widely accepted 
standardized method of analyzing shoreline changes. Each 
state or region has its own data needs and coastal zone 
man_agement responsibilities (e.g. construction set-back 
lines), and therefore different techniques and standards 
are used to compile shorelines and to calculate rates of 
shoreline move_ment. Consequently, existing calculated 
rates of shoreline change and projected shoreline positions 
are inconsistent from state to state and even within 
states, such as in Califor_nia, and cannot be compared 
directly.  These inconsisten_cies were clearly demonstrated 
by the Federal Emergency Management Agency (FEMA) sponsored 
erosion studies (Crowell and Leatherman, 1999) that were 
used as the basis for evaluating erosion hazards (The Heinz 
Center, 2000).   Within California, the FEMA sponsored 
erosion studies only addressed coastal cliff erosion, not 
sandy shoreline ero_sion. The USGS National Assessment of 
Shoreline Change represents the first time that shorelines 
from original data sources have been compiled and rates of 
shoreline change have been calculated on a national scale 
using internally consistent methods. The results of this 
analysis allow direct comparison of rates of change from 
one coastal segment to another and form the basis for 
future comparison of shore_line position.

Several federal agencies (USGS, FEMA, NOAA, U.S. Army Corps 
of Engineers (USACE) have regulatory or administrative 
responsibilities pertaining to shorelines. Yet these 
responsibilities are quite different, requiring differ_ent 
approaches and offering substantial opportunities for 
cooperation. For example, the USACE is authorized and 
funded by Congress to report on the economic and 
envi_ronmental implications of shoreline change and the 
costs of erosion mitigation. Their National Shoreline 
Management Study (Stauble and Brumbaugh, 2003) is being 
conducted using existing shoreline data. The USGS will 
share data and information, such as the lidar-derived 
shoreline and rates of change, in support of their effort. 
NOAA has the mandate to establish the official shoreline 
boundary for the nation using tidal datums. Their emphasis 
is on safe navigation and using the shoreline to generate 
nautical charts. NOAA also has a developing program (V 
datum), which will greatly assist other agencies in 
establishing alternative shorelines for a variety of 
purposes where the official shoreline is inappropriate. 
FEMA is authorized and partially funded by Congress to map 
coastal (and riverine) flood hazard areas.  These maps and 
associated information are used for flood risk assessment, 
floodplain management, and setting insur_ance rates through 
the National Flood Insurance Program (NFIP). Because of 
perceived deficiencies in the way the NFIP considers 
coastal erosion, Congress authorized FEMA to report on the 
economic impact of erosion hazards on coastal communities, 
and on the NFIP.  To accomplish this, FEMA contracted state 
agencies and academic researchers to conduct a pilot study 
of erosion hazards that included shoreline change data for 
limited geographic areas. The USGS is responsible for 
conducting research pertain_ing to coastal change hazards 
including shoreline change, understanding the processes 
that cause coastal change, and developing models to predict 
future change. The USGS is the only government agency that 
has a dedicated program to monitor coastal change into the 
future using consistent methods nationwide. Such a program 
is critically important to assess national issues, such as 
the coastal impacts of sea level rise.

PRIOR NATIONAL AND CALIFORNIA COAST SHORELINE ASSESSMENTS

There are very few studies of regional sandy shoreline 
erosion for California. The USACE (1971) conducted the 
first national assessment of coastal erosion that included 
California. That study identified areas of critical and 
non-critical erosion on the basis of economic development 
and potential for property loss, but rates of shoreline 
movement were not quantified. Numerous analyses have been 
con_ducted for specific sites by private consultants or 
contrac_tors, or cities and counties where erosion rates 
have been required for regulatory or management purposes.  
Some of these analyses were incorporated into Dolan and 
others (1985), and Griggs and Savoy (1985), where rates of 
change were presented on maps, and the long-term trends of 
erosion and accretion were summarized in an accompanying 
text.  The Griggs and Savoy (1985) compilation has recently 
been updated (Griggs and others, 2005a), although most of 
the erosion hazards addressed therein pertain to coastal 
cliff and bluff erosion, with the exception of Southern 
California.

Since these earlier works, methods of obtaining, analyzing, 
displaying, and storing shoreline data have improved 
substantially, and coastal change has continued. 
Furthermore, coastal scientists have not agreed on standard 
methods for analyzing and reporting shoreline changes, nor 
have they identified rigorous mathematical tests that are 
widely accepted for quantifying the change and associ_ated 
errors. Consequently, there are critical needs for (1) a 
nationwide compilation of reliable shoreline data including 
the most recent shoreline position, and (2) a 
standardization of methods for obtaining and comparing 
shoreline positions and mathematically analyzing the 
trends.

METHODS OF ANALYZING SHORELINE CHANGE

Compilation of Historical Shorelines

Coastal scientists in U.S. universities and government 
agencies have been quantifying rates of shoreline movement 
and studying coastal change for decades.  Before GPS and 
lidar technologies were developed, the most commonly used 
sources of historical shoreline position were NOAA 
Topo_graphic Sheets (T-sheets, see Shalowitz, 1964) and 
aerial photographs.  Ideally, extraction of shoreline 
position from these data sources involves geo-referencing 
and removing distortions from maps or aerial photographs, 
followed by digitizing shoreline position. Depending on 
coastal loca_tion, data source, and scientific preference, 
different proxies for shoreline position are used to 
document coastal change, including the high water line (for 
discussion of the high water line (HWL) see Shalowitz, 
1964), wet-dry line, veg_etation line, dune toe or crest, 
toe or berm of the beach, cliff base or top, and the line 
of mean high water (MHW). 

The USGS National Assessment of Shoreline Change analysis 
for California incorporates shoreline positions from 4 time 
periods and three unique data sources. To main_tain 
consistency at a national scale, these four periods are 
mid- to late1800s, 1920s-1930s, 1950s-1970s, and post-1997.  
Several organizations have provided the USGS with digital 
maps and/or shoreline data (Table 1). The historical 
shorelines from the 1850-1890s and 1920s-1930s were 
digi_tized from scanned and georeferenced historical T-
sheets. In addition, shorelines were digitized from USGS 
Digital Raster Graphic (DRG) maps where data gaps in the T-
sheets existed, as these were the only source of shoreline 
data that could be located for the data gap areas.  These 
occurred for the third period (1950s-1970s) for most of 
Central and Northern California. The modern (post-1997) 
shoreline represents a MHW elevation derived from lidar 
data.

Shorelines were compiled for the state following the 
guidelines established for selected periods (mid- to late 
1800s, 1920s-1930s, 1950s-1970s, and post-1997) as closely 
as possible. Table 2 lists the final range of years (and 
months where known) for shorelines compiled for each period 
by region.

Delineation of a Modern (Lidar-derived) Shoreline

The most recent shoreline used in this National Assess_ment 
(post-1997) was derived from lidar (Light Detec_tion and 
Ranging) data.  The USGS, in collaboration with NASA, has 
been using the NASA Airborne Topographic Mapper (ATM) to 
map coastal areas since 1997 (Krabill and others, 2000; 
Sallenger and others, 2003).  The ATM surveys ground 
elevation using an elliptically rotating blue-green laser. 
GPS (global positioning system) positions and inertial 
navigation systems are used to correct for aircraft pitch, 
roll, and heading, providing ground elevations with 
accuracies of about "15 cm (Sallenger and others, 2003). 
The lidar surveys used to extract shorelines for this 
report were conducted either in 1998 or 2002 (Table 2). 

To compare with historical shorelines, an operational MHW 
shoreline was extracted from the lidar surveys using a 
method developed by Stockdon and others (2002) (Fig_ure 2). 
Shorelines were extracted from cross-shore pro_files which 
consist of bands of lidar data 10 m wide in the alongshore 
direction and spaced every 20 m along the coast.  A least-
squares linear regression line is passed through the 2-D 
cluster of data that encompasses the operational MHW datum 
(Table 3) and is limited to the seaward-sloping foreshore. 
The regression equation is then used to derive the 
horizontal intersection of the operational MHW datum with 
the profile, giving the shoreline position for that 
profile. Repeating this procedure at successive profiles 20 
m apart generates points that can be connected to create a 
continu_ous shoreline. 

To determine the operational MHW elevation, Cali_fornia was 
divided into 3 sections (Northern, Central and Southern 
California). For each section, the operational MHW 
elevation represents an average of MHW elevations from 
individual open-ocean or near open-ocean tide gauges (Weber 
and others, 2005). A list of tide gauges and MHW elevations 
used in each section is presented in Table 3. The lidar-
extracted MHW shoreline is not necessarily the same as a 
MHW shoreline surveyed by a licensed land surveyor. This is 
because the operational MHW elevation used for the lidar 
shoreline is an average of the MHW elevations at sev_eral 
tide gauges. Furthermore, the lidar-extracted shoreline is 
intended only as a reference feature for measuring 
shore_line change. It is not intended to establish legal 
boundaries.

Because inland bays generally are not suitable sites for 
extraction of a lidar shoreline and because this report 
focuses on the open-ocean coasts, extensive bay areas such 
as San Francisco and Tomales Bay shorelines were not 
included in the shoreline change analysis. Also, lidar data 
were not available for all sandy beaches in California; 
gaps exist in Northern California along the sandy 
shorelines near Arcata and Eureka, as well as along a 
stretch of coast around San Simeon and Cambria in Central 
California. When lidar data are available for these gaps, 
the shoreline change analy_ses will be conducted and 
provided as on-line updates and in future reports.

Geographic Information System (GIS) Procedures

NOAA T-sheet indexes were used to determine T-sheet 
availability for shorelines that were not already available 
as ESRI ArcGIS shapefiles. T-sheets were then requested 
from NOAA and received as scanned TIF images. Existing 
digital shorelines for each period were compiled and a 
quality assessment was performed.

Scanned TIF image T-sheets were rectified using Erdas 
Imagine geographic imaging software by placing at least 6 
well-spaced ground control points (GCPs) on selected T-
sheet graticules in geographic coordinates. Some T-sheets 
produced before 1930 required additional coordinate 
transformation information from NOAA to convert from the 
United States Standard Datum (USSD) to the North American 
Datum of 1927 (NAD27). The datum transforma_tion was 
applied to T-sheet graticule coordinates prior to 
rectification. Total Root Mean Square (RMS) error for the 
rectification process was maintained below 1 pixel, which 
is approximately 4 m at a scale of 1:20,000 and 
approximately 1.5 m at a scale of 1:10,000. Typically the 
resulting RMS was much lower than one pixel. Newly geo-
referenced T-sheets were loaded in ArcGIS and shorelines 
were digitized.  All shoreline vectors were converted to 
the Universal Trans_verse Mercator (UTM) projection with 
the North American Datum of 1983 (NAD83).

Shorelines from all sources were merged to produce a single 
shoreline for each of the 4 time periods by sec_tion of 
California (Northern, Central and Southern). Final 
shorelines were coded with 6 attribute fields (ID, Type, 
Date, Description, Source, and Accuracy) to prepare for 
calculating shoreline change rates with the Digital 
Shoreline Analysis System (DSAS; Thieler and others, 2003). 

Calculation and Presentation of Rates of Change

Rates of long-term shoreline change were generated in a GIS 
with the Digital Shoreline Analysis System (DSAS), an 
ArcGIS tool developed by the USGS in cooperation with TPMC 
Environmental Services. The tool is designed to efficiently 
lead a user through the major steps of shoreline change 
analysis. This ArcGIS tool contains three main com_ponents 
that define a baseline, generate orthogonal transects at a 
user-defined separation along the coast, and calculate 
rates of change (linear regression, endpoint rate, average 
of rates, average of endpoints, jackknife). The extension 
utilizes Visual Basic scripts to develop transects and 
rates, and uses the Visual Basic programming environment to 
automate and customize the user interface.

Baselines were constructed seaward of, and parallel to, the 
general trend of the four shorelines. The coastline of 
California, and hence the baselines, are curvilinear. Using 
DSAS, transects were spaced 50 m apart. Transects were 
manually eliminated to prevent calculation of rates in 
areas where less than four shorelines were intersected. 
Fewer than four shorelines can result from one or more of 
the following conditions (Figure 3): 1) the position of a 
river mouth has changed or migrated, 2) shoreline segments 
were missing (data gaps), 3) a harbor or other coastal 
structure eliminated one or more of the shorelines, and 4) 
no lidar shoreline is available for rocky coasts.  

Long-term rates of shoreline change were calculated at each 
transect using a linear regression applied to all four 
shoreline positions from the earliest (1800s) to the most 
recent (derived from lidar). Linear regression was selected 
because it has been shown to be the most statistically 
robust quantitative method when a limited number of 
shorelines are available (Crowell and others, 1997).  It is 
also the most commonly applied statistical technique for 
expressing shore_line movement and estimating rates of 
change (Crowell and Leatherman, 1999). Short-term rates of 
shoreline change were calculated using the endpoint method 
comparing the 1970s and most recent (lidar-derived) 
shoreline positions. Long-term rates and short-term rates 
of shoreline change, as defined here, are used throughout 
the report. 

Beach Alterations and Shoreline Definitions that Influence 
Rates of Change

Human Activities

Attempts to stabilize the shore can greatly influence rates 
of shoreline change. Activities such as beach nour_ishment 
or emplacement of shoreline stabilization struc_tures tend 
to alter coastal processes, sediment transport, and 
shoreline position. For example, beach nourishment 
artificially causes rapid, temporary shoreline accretion. 
Depending on the frequency of beach nourishment, the 
placement of large volumes of sand on the beach will bias 
the rates of observed shoreline change toward accretion or 
stability, even though the natural beach, in the absence of 
nourishment, may have an erosional trend.  In addition, the 
emplacement of shoreline protection structures such as 
seawalls, bulkheads and revetments can result in both 
active and passive erosion of the beach.  In the case of 
passive erosion, the back beach area is fixed by the 
structure, and the beach in front gradually narrows. 
Eventually erosion will cease (until the structure fails), 
thus indicating a stable shoreline in the shoreline change 
record.  Active erosion associated with shoreline 
protection structures refers to the acceleration of 
shoreline erosion in front of a structure caused by the 
alteration of wave, tide and current patterns.

Clayton (1991), Flick (1993) and Wiegel (1994) pro_vide a 
summary of identifiable beach nourishment projects on the 
U.S. West Coast that had been conducted up to the late 
1980s. These records were used to identify shoreline 
segments that had been influenced by beach nourishment.  
Only projects that pre-date the lidar shoreline were 
included. There is no distinction made between large 
volume, continu_ous projects and small volume, finite 
projects. According to Flick (1993), Wiegel (1994), and 
many others, beaches along the coast of Southern California 
were extensively nourished from the early part of the 20th-
century through the mid-1970s. Nourishment programs became 
far less frequent in the post-1970s era. 

Differentiating between natural rates of erosion and the 
influences of beach nourishment is difficult because 
studies have not been conducted to specifically address 
this issue. In addition, available data may be inadequate 
to address this question because there are not enough 
shoreline positions immediately before, after, and between 
nourishment proj_ects. Human responses to shoreline 
erosion, including beach nourishment and emplacement of 
structures, are included in the discussion of the results 
of the shoreline change analysis.

Shoreline Definitions

Inclusion of a lidar-derived shoreline represents a new 
approach to the investigation of shoreline change. The 
three pre-lidar historical shorelines come from topographic 
maps that use the HWL as the shoreline proxy. For more than 
150 years, the HWL has served as the most commonly used 
shoreline because it could be visually identified in the 
field. With advanced technologies, such as GPS and lidar, 
it is now possible to objectively define the shoreline on 
the basis of an elevation or a tidal datum, such as MHW. 
Changing the shoreline definition from a proxy-based 
physical feature that is uncontrolled in terms of an 
elevation datum (HWL) to a datum-based shoreline defined by 
an elevation contour (MHW) has important implications with 
regard to inferred changes in shoreline position and 
calculated rates of change.  

Morton and others (2004) first compiled published and 
unpublished data to evaluate the horizontal and verti_cal 
differences in HWL determined from beach profiles, aerial 
photographs, or GPS surveys, and the MHW derived from beach 
profiles, GPS surveys, or lidar surveys. We have updated 
this to include the most recent available analyses (Table 
4). The HWL and MHW positions were established at the same 
time, or within a few weeks of one another at multiple 
sites around the U.S. where the beach and wave 
characteristics are diverse. Comparing these HWL and MHW 
positions assumes that the observed proxy-datum offsets are 
entirely artifacts of shoreline definition and are not 
related to actual changes in the beach profile due to 
sediment transport (erosion or accretion processes) between 
the survey dates. This is a relatively safe assump_tion 
considering the short intervals between surveys or the 
knowledge that a particular shoreline segment is relatively 
stable.  Moore and others (2006) avoided the need for this 
assumption by deriving HWL and MHW shorelines from aerial 
photography and lidar data collected during the same tidal 
cycle.  

Table 4 shows that average absolute horizontal and vertical 
offsets between the HWL and MHW range from a few meters to 
more than 50 m, and vertical offsets can be as much as 2 m. 
Most of the horizontal offsets are less than 20 m, and most 
of the vertical offsets are less than 1 m. Offsets are 
typically greatest on relatively flat beaches where high 
waves produce high wave runup (i.e. southwest Washing_ton). 
Conversely, offsets are least where beaches are rela_tively 
steep and wave runup is low.  For the data analyzed by 
Morton and others (2004), the MHW was seaward of the HWL on 
virtually all of the transects (Table 4). This nearly 
systematic horizontal offset between the HWL and the MHW 
causes shoreline positions and calculated rates of change 
to imply slower erosion, a change from erosion to 
accretion, or faster accretion than actual shoreline 
move_ment can account for. 

The recent study by Moore and others (2006) illus_trated 
that overall, the importance of incorporating a proxy-datum 
offset into shoreline change analysis depends on several 
factors including the magnitude of the offset, the length 
of time over which rates are being measured and the 
statistical significance of the shoreline change rates.  
This proxy-datum offset is particularly important when 
averaging shoreline change rates alongshore. Since the 
proxy-datum offset is a bias, virtually always acting in 
the same direction, the error associated with the apparent 
shoreline change rate shift does not cancel during 
averaging and it is important to quantify the bias in order 
to account for the rate shift. The shoreline change rates 
presented in this report have been calculated by accounting 
for the proxy-datum bias using the methodology described 
below.

Estimating the proxy-datum bias and the bias uncertainty

Comparison of HWL shorelines and a MHW datum-based 
shoreline for a single-day survey on Assateague Island 
(Moore and others, 2006) revealed an average hori_zontal 
offset between shoreline indicators of 18.8 m (Table 4).  
Vertical offsets were also substantial and were strongly 
correlated with foreshore beach slope.  A simple total 
water level model, that combines the effects of tidal 
variations and wave runup, (Ruggiero and others, 1996; 
Ruggiero and others, 2001; Ruggiero and others, 2003) 
successfully reproduced these vertical offsets suggesting 
that the proxy-datum offset is primarily governed by wave 
runup. In order to estimate the proxy-datum bias for the 
State of California we use the approach outlined in Moore 
and others (2006) with the improvement of including the 
wave runup formula_tion of Stockdon and others (2006).  The 
horizontal offset between HWL and MWH shorelines can be 
estimated by:

Equation (1)

where ZT is the tide level, tan b is the beach slope, Ho is 
the deepwater significant wave height, and Lo is the deep-
water wave length given by linear theory as gT2/2p, where g 
is the acceleration due to gravity and T is the peak wave 
period.  

In order to calculate the bias, as well as the bias 
uncer_tainty, for this regional shoreline change analysis, 
long-term best estimates and measures of uncertainty are 
derived for beach slope, wave height, wave length, and tide 
level.  The best estimate for beach slope was derived by 
averaging individual lidar transect slope estimates within 
1-km blocks along the coast.  We take the long-term mean 
wave height and length to be the best estimate to use in 
the bias calcu_lation.  The long-term mean wave height is 
derived from USACE Wave Information Studies (WIS) hindcasts 
while the long-term mean wave length is derived from long-
term buoy records (NDBC and CDIP) along the California 
Coast.  Finally, the best estimate of the tide level 
responsible for generating HWL shorelines is taken as the 
elevation of MHW (see Table 3) (Weber and List, 2005).  The 
mea_sures of uncertainty for the beach slope, wave height, 
and wave length are estimated as the difference between the 
95% exceedance statistic and the 50% exceedance statistic 
of the cumulative distributions.  This gives a 90% 
confi_dence interval on each of the cumulative 
distributions.  The uncertainty of assuming that the tide 
responsible for leaving HWL-type shorelines was at MHW is 
calculated simply by MHHW-MHW 

The proxy-datum bias, and the associated uncertainty, is 
calculated at each of the 1-km blocks in which the aver_age 
beach slope has been calculated.  The nearest WIS station, 
wave buoy, and tide gage to each individual 1-km block were 
used in the application of Equation 1.  Once the bias was 
calculated, it was incorporated into DSAS and applied on a 
transect-by-transect basis, so that the estimated bias is 
removed from the final long- and short-term shore_line 
change rates. The bias, averaged over 815 1-km sec_tions of 
the California coast, was approximately 18 m with an 
average uncertainty of approximately 8.7m.

Uncertainties and Errors

Documented trends and calculated rates of shoreline change 
are only as reliable as: (1) measurement errors that 
determine the accuracy of each shoreline position, (2) 
sampling errors that account for the variability of 
shoreline position, and (3) statistical errors associated 
with compil_ing and comparing shoreline positions.  Anders 
and Byrnes (1991), Crowell and others (1991), Thieler and 
Danforth (1994), and Moore (2000), provided general 
estimates of the typical measurement errors associated with 
mapping methods and materials for historical shorelines, 
registry of shoreline position relative to geographic 
coordinates, and shoreline digitizing. 

For this analysis we report estimates of individual 
shoreline position uncertainty (Table 5) and shoreline 
change uncertainty for the regional averages presented in 
Table 6A-C.  Uncertainties associated with shoreline change 
on individual transects can be calculated using similar 
meth_ods as are used for the regional averages as discussed 
below for both long- and short-term analyses. 

The largest shoreline position errors were errors of _10 m, 
which were attributed to scales and inaccuracies in the 
original surveys (T-sheets) and typical positioning errors 
associated with DRGs (_15 m).  Stockdon and others (2002) 
provided estimates of GPS positioning errors ("1 m) and 
regression errors ("1.5 m) associated with deriva_tion of 
the MHW elevation from the lidar data.  A previ_ously 
unreported error term in shoreline change analyses is the 
uncertainty in HWL shorelines due to variations in water 
levels.  Our estimates of the uncertainty associated with 
the proxy-datum bias in effect quantify this error term for 
the first time.  Following the methodology of Taylor 
(1997), Equation 1 was used to translate the estimates of 
the uncertainty of each parameter into an estimate of the 
uncertainty of the proxy-datum bias.  Equation 1 can also 
be used to demonstrate that the uncertainty of the proxy-
datum bias is equivalent to the uncertainty in any 
individual HWL shoreline.

Sampling errors relating to the local short-term 
vari_ability of true shoreline positions (Morton, 1991; 
Douglas and Crowell, 2000) are less well known.  Along the 
Califor_nia coast, as in many locales worldwide, there is 
pronounced cyclical erosion and accretion of the shoreline.  
This variability is driven by variations in wave conditions 
from summer to winter, years with severe versus average 
storms or swells, and episodic events like El Ni_os or 
hurricanes. In addition, the seasonal shoreline variability 
also has a high spatial variability, depending on the 
orientation of the coast with respect to the wave direction 
and effects of refraction or reflection from headlands, 
offshore islands and manmade structures. As a result, an 
uncertainty term quantifying sea_sonal shoreline 
variability  for  regionally averaged shore_line change 
rates is a rough estimate at best.  Site specific, 
temporally dense data are required to evaluate short-term 
shoreline variability.  The lack of reliable high frequency 
data regarding short-term variability (of true shoreline 
position) at most coastal sites limits the ability to 
quantify this uncertainty into the overall shoreline 
position uncer_tainty.  Studies that do exist for 
California (Shepard, 1950; Bascom, 1954; Johnson, 1971) 
focus on changes in beach width or profile. An estimate of 
the variability in the posi_tion of the MSL intersect on 
the beach from eleven profile envelopes from La Jolla 
(Shepard, 1950) is approximately 9 m.  In Monterey Bay, 
similar qualitative estimates from 9 profiles, surveyed 
over 15 years (Dingler and Reiss, 2002), suggests an 
average variability envelope of the MHW of approximately 40 
m.  However, these data include both the 1982-83 and 1997-
98 El Nios and thus incorporate extreme conditions.  One 
of the most extensive records to date is the 20-year record 
of beach profiles surveyed by the Army Corps of Engineers 
at Duck, N.C. Using 460 shoreline posi_tions from the Duck 
profile data, Barton and others (2003) showed that the 
envelope of shoreline positions around a relatively stable 
shoreline was about _20 m.   

Due to the lack of accurate, systematic data regarding the 
seasonal variation of the shoreline along the California 
coast, the error values reported here do not include an 
uncer_tainty term for the seasonal shoreline position 
variability in the quantification of errors associated with 
the regionally averaged shoreline change rates. For the 
long-term shoreline change analysis we assume that the 
seasonal variability in each shoreline is random and 
uncorrelated to the others and that the regression error 
will account for this uncertainty (see Linear regression 
(long-term) shoreline change error below).  For the short-
term analysis it is likely, at least in Northern and 
Central California, that due to the length of time over 
which our rates are calculated, the seasonal variability 
uncertainty term has a negligible impact on the total error 
value. In Northern and Central California, the shorelines 
from the most recent historical shoreline DRGs are based on 
aerial photographs from the 1940s and 1950s. Table 2 
includes not only the years of the data sources, but also 
the months of the photography on which the T-sheet maps 
were based for the most recent historical shoreline.  In 
Southern California nearly all of the source data are from 
the winter months, as is the lidar data.  Therefore, the 
sea_sonal variability term is again assumed not to have a 
mea_surable impact on the error term for the regionally 
averaged rates presented in this report.  Independent 
comparisons of our shoreline change results with published 
rates in South_ern Monterey Bay (Thornton and others, 2006) 
are in close agreement, even in the short-term. However, we 
recommend that anyone using the data associated with this 
report for a more site-specific analysis incorporate an 
error term to account for seasonal shoreline position 
variability.

Estimates of the maximum positional errors for this study 
are provided in Table 5 to show how each error con_tributes 
to inaccuracy in the shoreline position.  The annual_ized 
error for short-term shoreline change is calculated and 
subsequently incorporated into the shoreline change rate 
calculations as outlined below. The uncertainty on the 
short-term (end-point) rates, using a best estimate for 
California shorelines is "0.4 m/yr (Table 5 and Table 6A-
C).  

End-point (short-term) shoreline change error 

The total error for the end-point shoreline change rate, 
(Esp)(Equation 2), is calculated by taking the square root 
of the sum of the squares (or adding in quadrature) of: 
georef_erencing error (Eg), digitizing error (Ed), T-sheet 
survey or DRG error (Et), and shoreline position error 
(Ep), similar to the methods outlined by Crowell and others 
(1993). Values for each of the error terms are given in 
Table 5. The georeferencing error represents the elected 
maximum acceptable RMS error for T-sheets at a scale of 
1:20,000 in this study.  The georeferencing error is 
applied to the historical shorelines that are derived from 
T-sheets only. The digitizing error reflects the maximum 
error specified in past studies (Anders and Byrnes, 1991; 
Crowell and others, 1991; Moore, 2000), and is applied to 
the historical shore_lines only. The maximum T-sheet survey 
error, determined by Shalowitz (1964), incorporates all of 
the errors associ_ated with the mapping process including 
distance to rodded points, plane table position, and 
identification of the HWL. The maximum DRG error is the 
stated accuracy of USGS Topographic Quadrangle maps from 
which the DRGs are derived; National Map Accuracy Standards 
give _15 m as the maximum acceptable error.  The T-sheet 
survey error is applied to all historical shorelines; 
however, note that the error associated with the 1950s-
1970s era T-sheets is considerably lower than the older T-
sheets; this difference is based on findings by Ruggiero 
and others (2003), as well as the fact that more recent 
shorelines are derived from aerial photos or other sources.  
Shoreline position error is the maximum error associated 
with the derivation of the lidar shoreline (Stockdon and 
others, 2002) for lidar data and the average bias 
uncertainty (8.7 m) for the historical shore_lines.  Thus, 
the total shoreline position error as shown in Table 5 for 
each shoreline is expressed by:

Equation (2)

A separate Esp is calculated for each period. For the 
short-term shoreline change rates only these values can be 
com_bined and annualized to provide an error estimation for 
the shoreline change rate at any given transect. The 
annualized error (Ea) is expressed by:

Equation (3)

For determining short-term uncertainty error at a specific 
location (at an individual transect) we can add the 
uncertainty terms from Table 5 to get a total uncertainty 
of the shoreline change rate at a given location.  Dividing 
this total by the time between shoreline dates provides the 
error on the short-term change rate at that location.

Linear regression (long-term) shoreline change error

Linear regression is the most commonly applied statistical 
technique for expressing shoreline movement and estimating 
rates of change (Crowell and Leatherman, 1999) where there 
are a statistically valid number of samples.  Because 
linear regression fails to recognize the potential for 
temporal differences in trend (trend reversals) and 
accelera_tions or decelerations (Morton, 1991; 1996), 
average trends and rates of shoreline change in this study 
were calculated for both long-term (entire period) and 
short-term (most recent) time scales. Long-term rates of 
shoreline change were determined at each transect by taking 
the slope of the regression line applied to all four 
shoreline positions. The resulting rates are reported in 
units of m/yr (Table 6A-C). Uncertainties for the average 
shoreline change rates are reported as the " values in 
Table 6A-C.  

Two uncertainty terms arise in the calculation of the long-
term shoreline change rates.  The first term is the 90% 
confidence interval of the linear regression shoreline 
change rate for each transect.  The second term arises from 
the uncertainty in our best estimates of the proxy-datum 
offsets.  We calculate linear regression slopes using 
shoreline data that has been adjusted based on our best 
estimate of the proxy-datum bias as well as data that has 
been adjusted according to our best estimate of the " the 
bias uncertainty.  From this analysis we get a best 
estimate of the shoreline change rate and an uncertainty of 
the rate due to the bias uncertainty.  At each transect we 
can add the regression error and the proxy-datum bias 
uncertainty error to get a total uncertainty of the 
shoreline change rate at a given loca_tion.

However, in terms of calculating regionally-aver_aged 
shoreline change rate uncertainties the two terms discussed 
above need to be treated differently.  Because the 90% 
confidence interval on the linear regression of each 
transect is assumed to be random and independent, when 
averaged over many transects the resulting average 
uncertainty associated with this term can be quite small; 
the greater the number of transects over which the 
uncertainty is averaged, the smaller the uncertainty on the 
average rate.  However, for the second term we need to 
account for the fact that the proxy-datum offset is a bias 
and always acts in one direction.  Therefore, the 
regionally averaged shoreline change rate uncertainty 
associated with the proxy-datum bias is simply the average 
value of the error resulting from the uncertainty of the 
proxy-datum bias.  The regionally averaged total shoreline 
change uncertainty terms can be expressed by:

Equation (4)

where U is the alongshore averaged shoreline change rate 
uncertainty, C is the linear regression 90% confidence 
inter_val, B is the shoreline change rate uncertainty 
associated with the proxy-datum bias, and n is the number 
of transects included in average.    

Field observations and prior studies of shoreline move_ment 
within each analysis region in California suggest that the 
trends and relative rates of change presented in this study 
are as accurate as the methodology allows. Reliability of 
the mapped results increases as both the persistence of the 
trend and the magnitude of the rates increase. Stated 
another way, confidence in the analytical results is 
greatest where the rates of shoreline erosion or accretion 
are high and the trend has persisted for decades. On the 
other hand, confidence in the absolute results decreases 
where the shore_line is relatively stable and the rates of 
change are low. This is because minor differences in 
historical or lidar shoreline positions can substantially 
alter the regression line and the calculated results.  Data 
confidence also decreases in areas where frequent trends 
reversals occur.

Advanced technology such as GPS and lidar can better 
constrain shoreline positions, reduce the methodological 
errors, and improve the accuracy (reduce the error) of 
future shorelines. Establishing a datum-based shoreline 
(lidar derived MHW) as the standard for comparison 
provides, for the first time, the ability to perform an 
error analysis that is both quantitative and meaningful, in 
terms of its application. In the future, each electronic 
MHW shoreline could be pre_sented with an accompanying 
error bar that would define the alongshore envelope of 
confidence. Subsequent shorelines and associated confidence 
envelopes would provide a more precise basis for 
determining the statistical significance of observed 
shoreline change. Unfortunately, the use of lidar or any 
other shoreline mapping technology will still require 
distinguishing between short-term variability in shoreline 
position and the long-term trend of shoreline change.

GEOLOGIC HISTORY AND SETTING

California straddles the boundary between the Pacific and 
North American tectonic plates (Figure 4).  The diverse 
landscape and complex geology of the California coast is 
largely a result of the interactions between these plates.  
Lateral movement between the two plates occurs along the 
San Andreas Fault Zone (SAFZ), which extends nearly 1300 
kilometers from the Gulf of California to Shelter Cove near 
Point Delgada in Humboldt County (Figure 5).  Lateral 
movement on the fault zone averages 2.5-3 cm/yr (Harden, 
1998) with a total accumulated displacement from slip 
dur_ing earthquakes and aseismic creep of at least 560 
kilome_ters since lateral movement began about 15-25 
million years ago.

Inman and Nordstrom (1971) recognized the impor_tance of 
tectonic setting to the development of coasts worldwide.  
They developed a coastal classification scheme based upon 
the position of a given coast relative to plate movement.  
Within this classification scheme they recog_nized three 
first-order classes:  collision coasts, trailing-edge 
coasts, and marginal sea coasts.  Collision coasts (i.e. 
active margins) are characterized as being relatively 
straight and mountainous, having the presence of coastal 
cliffs and raised marine terraces, and bordered by narrow 
continental shelves.  Coastal watersheds are typically 
steep and undergo high rates of erosion.  Although the 
California coast south of Cape Mendocino presently borders 
a transform margin dominated by lateral movement, and is 
therefore not strictly collision controlled, it maintains 
many of the characteris_tics of a collision coast.  Between 
Cape Mendocino and the Oregon border, the coast is a 
collision coast.

Movement along the SAFZ has created three broad geomorphic 
provinces (Figure 4) along the coast: Coast Ranges, 
Transverse Ranges, and Peninsular Ranges (Cali_fornia 
Geological Survey, 2002a).  The northwest trending Coast 
Ranges run roughly parallel to the SAFZ and extend from the 
Oregon border in the north to the east-west trend_ing 
Transverse Ranges in the south.  The Coast Ranges are 
composed mostly of uplifted Mesozoic and Cenozoic marine 
sedimentary rocks that typically form a terraced and wave-
cut coastline.  The range is broken by the depression 
forming San Francisco Bay.  

The Transverse Ranges trend roughly east-west and lie 
oblique to the general northwest trend of the California 
coast. They extend from the San Bernardino Mountains to the 
offshore islands of San Miguel, Santa Rosa, and Santa Cruz.  
Intense north-south compression from SAFZ move_ment has 
resulted in very high uplift rates in this region 
(California Geological Survey, 2002a).  Tertiary 
sedimen_tary rocks are the dominant rock type of the 
Transverse Ranges along the coast.

The Peninsular Ranges extend from the Transverse Ranges to 
the Mexican border, and, like the Coast Ranges, trend in a 
northwest direction.  Along the coast they are composed 
mostly of Tertiary sedimentary rocks and further inland are 
characterized by Sierra Nevada-type rocks includ_ing 
granitics and older metamorphic rocks (Figure 6).  The Los 
Angeles basin and offshore islands of Santa Catalina, Santa 
Barbara, San Clemente, and San Nicolas are consid_ered part 
of the province.

	To summarize, the features of the California coast 
have formed over millions of years of interaction between 
two large tectonic plates that continues today.  Proxim_ity 
to an active tectonic margin results in features such as: 
diverse rock types in close juxtaposition, high relief, 
high erosion rates of the land surface, and high rates of 
sediment supply to the coast.  Block uplift and subsidence 
between high-angle reverse faults occur within the broader 
transform margin scenario.  Segmentation of the coast 
through these types of vertical crustal movements, as well 
as horizontal (strike-slip) displacement forms important 
structural founda_tions for coastal sedimentary 
environments.

General Geology of the California Coast

	The diverse morphology of the California coast is 
primarily a result of the local geology where lithology, 
geologic structure, and vertical tectonic movement play a 
prominent role in the configuration of the coast.  Figure 6 
is a generalized geologic map showing the major rock types 
of California (California Geologic Survey, 2002b).  
Tertiary and Mesozoic sedimentary rocks are clearly the 
dominant coastal rock type; they are mostly marine in 
origin and represent sediment deposition, lithification, 
and uplift along the Pacific-American plate subduction / 
transform bound_ary.  The Mesozoic rocks, which include the 
Franciscan Complex, are typically sandstone and shale from 
oceanic crust and deeper marine settings. The Tertiary 
rocks such as those of the Monterey Formation tend to be 
sandstone, shale, and conglomerate from more shallow marine 
environ_ments closer to the continental margin.  
Crystalline rocks are also present along the coast and are 
most common near San Francisco and Monterey.

The strength of the rocks exposed along the coast is a 
critical parameter in determining the erodability of the 
coast (Benumoff and others, 2000; Hapke, 2005).  Stronger 
rocks form prominent headlands that resist erosion and 
often form natural boundaries to littoral and aeolian 
transport.  Weaker rocks erode more quickly and form 
embayments where coastal sediment may accumulate.  Monterey 
Bay is an excellent example of an embayed coast where 
resistant rocks in Santa Cruz and Monterey (Figure 5) form 
head_lands and the interior of the bay is backed by easily 
eroded Quaternary shallow marine, aeolian, and fluvial 
deposits.  Coastal cliffs tend to be either high, steeply-
dipping coastal mountains that plunge directly into the 
sea, or, broad near- planar marine terraces.

Marine terraces are prominent features for much of the 
California coast and are best developed where uplifted 
marine clastic rocks form the bedrock.  Terrace 
preservation varies from moderate to poor in the other rock 
types that form coastal slopes including metamorphic, 
granitic, and ophiolitic terranes.  Marine terraces form 
when coastal cliff retreat generates wave-cut platforms, 
most notably during sea-level highstands, and are preserved 
as a slightly sea_ward-sloping planar surface during 
tectonic uplift (Anderson and others, 1999).  Local uplift 
rates, duration of marine pla_nation, and terrace 
composition determine the width and ele_vation of the 
terraces - they are typically 10s of meters high and 100s 
of meters wide.  The terrace surface often contains beach, 
dune, or alluvial deposits and when combined with terrace 
erosional material they can provide an important component 
of sediment contribution to the coast.  Weaker rock types 
with an abundant sand component may contrib_ute a 
significant amount of sediment to the beach system (up to 
~10-30%; Hearon and Willis, 2002; Inman and Mas_ters, 1991; 
Runyan and Griggs, 2002).  Table 7 shows the approximate 
amount of different rock types for the cliffed portion of 
the California coast (~72% of the 1760 km long coast).  
Cliff retreat rates vary dramatically from very low in 
granitic terranes to several meters per year in cliffs 
formed in poorly-consolidated sediment.  In addition to 
providing sediment to the coast, marine terraces are 
important features because of their low surface relief and 
proximity to the ocean they are the sites of numerous 
developments along the California coast (Griggs and others, 
2005c).   

Climate

The climate of California is strongly influenced by a 
persistent zone of high pressure in the north Pacific, a 
southerly flowing cold water ocean current, and the Sierra 
Nevada mountains, which block the continental air from 
affecting the coastal climate. During the summer months the 
northward migration of the semi-permanent North Pacific 
High diverts most storm tracks to the north.  California 
seldom receives rain from Pacific storms during the summer 
but coastal fog is widespread. Cold upwelling waters at the 
surface come into contact with the relatively warm moist 
air from the Pacific causing massive fog banks to form.  
Dur_ing the winter the North Pacific High migrates 
southward directing storms towards California.  
Occasionally storms will arrive from the southwest and are 
accompanied by relatively warm temperatures and heavy rains 
(often referred to as the pineapple express).  Average 
annual precipitation varies dramatically from north to 
south with 80 inches and above in the north and only about 
10 inches reaching the San Diego area.

The seasonal weather patterns are modified during El Ni_o 
and La Ni_a events.  During El Ni_os California's climate 
is typically characterized by above normal rain_fall, 
warmer sea-surface temperatures, and large waves from 
Pacific-generated storms often resulting in increased beach 
erosion.  The 1997-98 ENSO (El Nio - Southern Oscillation) 
was a significant climatic event responsible for widespread 
coastal flooding and beach loss (USGS/UCSC/NASA/NOAA 
Collaborative Research Group, 1998).  La Ni_as are 
generally accompanied by colder ocean temperatures, drier 
conditions, and less severe storms.  El Ni_o's and La 
Ni_a's generally last for 6 to 18 months and their 
occurrence and intensity are related to longer term 
atmospheric variations termed the Pacific Decadal 
Oscil_lation (PDO).  The PDO is an ENSO-like phenomenon 
that lasts for 20 to 30 years and consists of warm and cool 
phases (Zhang and others, 1997).  The cool phase, which is 
likened to an extended La Ni_a, is characterized by a cool 
wedge of lower than normal sea-surface heights and ocean 
temperatures in the eastern equatorial Pacific resulting in 
cooler temperatures and lower rainfall in California. 
Condi_tions during the warm phase are reversed and are 
similar to extended El Nio conditions.  Because phases 
tend to last between 20-30 years, with the last warm phase 
starting in 1977, some believe that we have entered a cool 
phase marked by the inception of the 1998/99 La Ni_a event 
as discussed in Hare and Mantua (2002). 

Coastal Processes

Waves

Waves and currents are the primary forces that move 
sediment in the littoral zone and annual wave height 
varia_tions are responsible for seasonal erosion and 
accretion patterns.  Wave characteristics along the 
California coast depend on weather patterns, geographical 
effects such as offshore islands, storm climatology, 
coastline orientation and local bathymetry.  The offshore 
wave climate of Cali_fornia is characterized by four 
regimes (Figure 7): Northern Pacific swell, Southern 
Hemisphere swell, northwest wind waves, and by locally 
driven seas (Storlazzi and Wingfield, 2005).  North Pacific 
swell is generated by extra tropical storms, mid-latitude 
low-pressure systems, and cold fronts that originate in the 
North Pacific.  Southern swell is domi_nant in the 
summertime and generated by winter storms in the Southern 
Hemisphere.  Northwest wind waves gener_ated by daily sea 
breeze conditions are more common in the northern part of 
the state and are strongest in the spring and early summer 
months.  Local seas are driven by wind and storms along the 
coast.  Given the variety of local and sea_sonal variations 
in wave climate, the predominant direction of nearshore 
sediment transport along the California coast is from 
north-to-south (Hearon and Willis, 2002).  Wave climate 
varies along the California coast and can region_ally 
summarized as follows (after Storlazzi and Wingfield, 
2005):

In northern California the average wave height is greatest 
from November to February and averages about 3 m, with 
approximately 20% of the time wave heights are greater than 
4 m.  Summer wave heights are smaller with mean values 
around 1.8 m with waves higher than 4 m being extremely 
rare.  Early winter is the most common time for waves to 
exceed 6 m.  During El Nio winter months mean annual wave 
heights are 0.3 m - 1.2 m greater than normal winter 
months.  El Nio driven storms typically approach from the 
west or southwest and may cause local littoral drift to the 
north - counter to the predominant southerly drift.  La 
Ni_a winter months have slightly higher than average wave 
height values of 0.1 m - 0.4 m whereas during the summers 
wave heights are smaller than average. 

Central California is a transition zone between harsh 
stormy waves of the northeast Pacific and milder conditions 
of Southern California.  North Pacific Swell is the largest 
swell to impact the region with heights between 2m - 10m 
and periods ranging between 10 - 25 seconds.  These waves, 
which are generated by storms in the North Pacific, occur 
most commonly between October and May.  Northwest wind 
waves are generated from sea breeze and are dominant from 
April to October.  The height of these waves typi_cally 
varies between 1 and 4 meters with a period of 3 to 10 
seconds.  Southern Swell occurs between April and October 
and typical wave heights range from 0.3 - 3 m with a period 
of 10 - 25 seconds.  Local wind-driven waves are generated 
by storms passing through central California.  They 
gener_ally occur between October and April with typical 
heights 1 and 4 meters and periods of 3 to 10 seconds.  

	In southern California peak wave heights are greatest 
from November to February and average about 2.4 m during 
this time.  In the summer wave heights are smaller with 
mean values around 1.8 m.  Waves greater than four meters 
occur about 11% of the time at Point Concep_tion (Figure 5) 
and are most common during the month of March.  Waves that 
damage the Southern California coast originate from extra-
tropical storms in the northeast Pacific or Southern 
Hemisphere, although the second case is rare (Newberger, 
1982).  During El Ni_o winter months, wave heights at Point 
Conception are 0.7 m above average.  In general, the 
southern region of the West Coast experiences more storms 
and higher wave energy during ENSO events (Seymour, 1998).  
Wave conditions along the southern Cali_fornia coast are 
extremely variable due to coastal configura_tion, 
bathymetry, orientation of coastline and the presence of 
several large offshore islands.  Wave height measure_ments 
can be substantially different over distances of a few 
miles (Newberger, 1982).  The Channel Islands block waves 
approaching from the south and Point Conception blocks 
waves from the north. Waves that propagate into the 
chan_nel are severely refracted by irregular shallow 
bathymetry, producing large spatial variations in swell 
wave height and direction (Guza and O'Reilly, 2001).

Tides

California has a mixed semidiurnal tidal regime of two 
unequal high and low tides a day with total open-coast 
elevation changes of about 2.1 m in Crescent City and 1.6 m 
in La Jolla (Figure 5).  The two daily high and low tides 
are unequal in amplitude with the lower-low tide of the day 
usu_ally following the higher-high. The monthly tidal 
variations are dominated by the spring-neap cycle with 
spring tides occurring during full and new moons and neap 
tides occur_ring during half moons.  The highest monthly 
tides during summer and winter months are higher than the 
highest tides in fall or spring.  Tide ranges increase from 
the south to north along the coast and higher tide ranges 
occur in San Diego and San Francisco Bays than in adjacent 
open coast areas (Flick, R.E., 1998).  

Tidal range influences beach processes along the California 
coast because it determines the extent of beach exposure 
and inundation throughout the tidal cycle.  Espe_cially 
crucial to beach erosion episodes are the timing and height 
of the highest tides in conjunction with the maximum wave 
height and surge developed during storms.  Com_parisons 
between impacts of the 1982-83 and 1997-98 El Ni_o storms 
on California's coast (Storlazzi and Griggs, 1998; 
Storlazzi and others, 2000) show that greater dam_age 
occurred in the 1982-83 event, in part, because the high 
tides were slightly higher and peak waves coincided with 
maximum high tides.  The differences in tidal height 
between these two El Nio winters is primarily due to the 
4.4yr lunar perigee cycle with a small contribution from 
the 18.6 year lunar node cycle (Flick, 1998).  This cycle 
enhanced peak high tides in 1982-83, 1986-87, 1990-91, 
1995-96, and 1999-2000.  

	Long-term trends in California tide records are 
consistent with the general rise in mean sea level over the 
last century recorded throughout the world.  Figure 8 shows 
long-term trends in mean sea level for selected California 
tide gauges as reported by the National Ocean Service 
(http://140.90.121.76/sltrends/sltrends_states.shtml?region
=ca), and analyzed by Flick and others (2003).  Both San 
Francisco and San Diego exhibit about 20 cm of sea-level 
rise over 93 years whereas Los Angeles exhibits a lower 
total rise of only 6 cm over 76 years. Crescent City, an 
exception to the sea-level rise trends, shows a relative 
sea-level fall of 3.2 cm over 66 years that is most likely 
the result of local tectonic uplift.

Winds

	Winds are important for generating waves that drive 
littoral sediment transport and for blowing sand off 
beaches resulting in potential sand loss from the littoral 
system.  The wind climate of California is strongly 
influ_enced by the North Pacific High that creates a 
predominant northwesterly air flow over most of the state.  
The intensity and position of the North Pacific High often 
determines the direction and strength of winds affecting 
coastal California.  The North Pacific High is stronger and 
located more north_erly during summer months and moves 
south and weakens during winter months, allowing storms to 
reach the state.  Coastal wind flow is predominantly 
parallel to the coast either from the northwest or the 
southeast.  When winds are from the northwest, flow is 
along the coast but Ekman trans_port induces an onshore 
component, which is strengthened by local sea breezes 
(Zhiqian and others, 1997).  Associated with northwest 
winds is the creation of a jet effect in the vicinity of 
some of the more prominent headlands.  Strong jets of air 
and large eddies are projected around headlands such as 
Point Reyes, Point Sur, and Point Arguello (Figure 5).  
Wind speeds in the immediate vicinity of these major 
headlands can be two or three times as great as the wind 
flow at nearby areas.  

In general, wind flow from the north is more aligned with 
the coast, the strongest flow is pushed offshore, and there 
is usually no associated daily sea breeze.  During strong 
northern flows high wind speeds extends over a large area 
from Northern California to Point Conception.  During 
northeast or east flow conditions the along-coast 
variability is significantly larger and winds are weaker 
(Zhiqian and others, 1997).

	These wind patterns are altered by the passage of 
Pacific storms most of which arrive in the winter.  As a 
storm approaches, the cold fronts are marked by strong 
easterly or southeasterly winds that can reach speeds of 50 
km/hr or more.  After the storm passes winds turn toward 
the southwest.  With the passage of the rare warm front, 
storm winds can reach 30 - 40 km/hr.  In Southern 
Califor_nia, after the passage of a cold front, Santa Ana 
winds will often blow down from the north to northeast.  
These winds are sometimes extremely intense and can blow 
between 90 to 145 km/hr and extend 160 kilometers seaward.  
Although it is rare, when Santa Ana winds blow during the 
summer they produce hot and dry conditions that increase 
the fire danger.

Currents

The California current system forms the eastern edge of the 
North Pacific gyre and is primarily driven by wind stress 
patterns over the North Pacific Ocean (California Coastal 
Commission, 1997).  Changes of the ocean circu_lation 
pattern are caused by the interactions between the sub-
tropical high pressure cell over the North Pacific and the 
atmospheric thermal low over California and Nevada. The 
interaction between these pressure regions results in a 
dominant southward-directed wind along the coast of 
Cali_fornia in spring and summer driving the California 
Current towards the equator (Hickey, 1979).  Maximum 
southward wind along the California coast occurs between 
Cape Men_docino and San Francisco in the spring (Nelson, 
1977).  The associated Ekman transport moves water 
perpendicularly away from the coast allowing cold, 
nutrient-rich waters to upwell from the deep (Newberger, 
1982).  

During the late fall and early winter southward winds 
weaken, reducing upwelling and allowing a near-shore, 
northward-flowing current north of Point Conception called 
the Davidson Current, to prevail (Hickey, 1979).  In the 
Southern California Bight (coastal Southern California and 
offshore waters) a counter-clockwise eddy occurs called the 
Southern California Countercurrent.  It is a northwestward-
flowing current south of Point Conception and inshore from 
the Channel Islands.  The current runs shore parallel until 
it reaches Point Conception where one branch flows 
southwest joining the California Current and the other 
branch con_tinues northward as a narrow countercurrent 
(Newberger, 1982).  The Southern California Counter current 
occurs in all seasons but is best developed in winter 
(Maloney and Chan, 1974).

Littoral cells and transport directions

The prevailing southerly transport direction for 
Cali_fornia littoral sediment is driven by North Pacific 
swell and northwest wind waves (see Figure 7).  There are 
local reversals in this prevailing direction due to 
orientation of the coast and/or southerly wave events.  
Littoral cells are seg_ments of the coast with distinct 
sediment sources, defined longshore transport pathways, and 
sinks where the sediment is removed from the littoral 
system.  Conceptually, the cell boundaries delineate an 
area where the sediment budget can be balanced for 
quantitative analysis.  Southern California littoral cells 
were first defined by Inman and Chamberlain (1960) and 
statewide littoral cells were identified by Habel and 
Armstrong (1978).  In California the cells are typi_cally 
bound by either prominent rocky headlands that block 
littoral transport around them, or, submarine canyons that 
cross the continental shelf to a shallow enough depth as to 
intercept alongshore moving sediment.  Submarine canyons 
are clearly the largest sink for beach sand loss in 
California with an estimated removal from some of the 
larger canyons at:  Scripps and La Jolla - 270,000 m3/yr, 
Mugu - 765,000 m3/yr and Monterey - 230,000 m3/yr (Griggs 
and others, 2005b).  Once sediment enters the submarine 
canyon system it is permanently lost from the littoral 
system.  Another large sediment sinks are coastal dune 
fields where wind-blown sand is removed from the active 
littoral system.  However, unlike submarine canyons, 
subsequent erosion of the dunes can re-supply adjacent 
beaches with sand.  Figure 9 shows the boundaries of 
littoral cells and coastal watersheds along the California 
coast.  The boundaries between many of these cells, 
however, and the amounts and rates of sediment transport 
are poorly understood.  Long-term harbor dredge records are 
one of the best long-term sources of longshore transport 
rates (Table 8) where harbor dredging is under_taken.  

Sand Sources

The primary sources of coastal sediment for California are 
the fluvial drainage systems that reach the coast.  These 
systems range from short, steep, ephemeral streams that 
deliver a wide mix of sediment grain sizes, to more mature 
rivers which often have well-developed estuaries.  
Califor_nia's coastal streams have exceptionally high 
sediment loads due to the steep landscapes, geologically 
young and tectoni_cally active terrain, and, in central and 
Southern California, relatively sparse vegetation cover 
(Willis, 2002a). Sediment yield per size of drainage basin 
for California rivers is typi_cally very high when compared 
to other regions of the U.S.  

Estimated sand and gravel discharge for the major 
California streams that enter the open coast is shown in 
Figure 10.  Average annual bedload discharges range from a 
few thousand m3/yr for the smaller creeks to nearly 3 
million m3/yr for the Eel River in northern California 
(Wil_lis, 2002a and b) (Figure 5).  These estimates should 
be considered maximum estimates of beach-quality material 
supplied from coastal streams because of numerous 
uncer_tainties and assumptions, and  the fact that they 
include sand finer than 0.125 mm which is unlikely to 
remain in an energetic beach environment. In addition to 
the rivers shown in Figure 10, the large Sacramento and San 
Joaquin Rivers empty into San Francisco Bay (Figure 5), the 
largest estuary on the west coast.  A large ebb-tidal delta 
has formed at the entrance to the bay.  Numerous smaller 
ungauged streams also reach the coast and can supply 
significant amounts of sediment because of their steep, 
easily erodible watersheds (Willis, 2002b).  On average 70 
to 95% of the beach sand in California is derived from 
coastal streams (Runyon and Griggs, 2002; Willis, 2002a).  
In general, sand and gravel discharges from coastal 
watersheds decrease from north to south (primarily rainfall 
controlled), although the Trans_verse Range has a 
relatively high sediment discharge (lithol_ogy and 
vegetation controlled).  Infrequent severe floods are 
thought to be responsible for delivering the majority of 
sedi_ment to the coast and a single large storm can deliver 
more sand to the beaches than years of low to moderate 
rainfall.  In addition, sediment discharge during extreme 
events can lead to open-coast ephemeral delta formation 
(Richmond, 1988) and delivery of abundant coarse-grained 
sediment.  El Nio years are typically times of significant 
sediment introduction to the coast because of increased 
likelihood of extreme rainfall events (Inman and Jenkins, 
1999).

Coastal cliffs are the next major source and sand sup_ply 
varies with cliff lithology and strength.  In some areas 
such as the Oceanside littoral cell, the coastal bluffs 
have been found to be a major source of beach sand (Young 
and Ashford, 2006). Softer cliffs composed of coastal sand 
deposits provide the most beach quality sediment when 
eroded. Subordinate sources of coastal sediment include 
marine planation of submerged rock, material of biologic 
origin such as shells, and possibly onshore transport of 
relict shelf sediment.  

GEOMORPHOLOGY OF THE CALIFORNIA COAST

The California coast encompasses a wide range of coastal 
landforms a product of complex geology and dynamic coastal 
processes.  Coastal landforms include steep cliffs, 
uplifted terraces, beaches, dunes, barrier spits, 
estuar_ies and lagoons (Figure 11). 

Cliffs

	Nearly three-fourths of the California coastline are 
backed by cliffs which fall into two broad general 
catego_ries: high steep cliffs and marine terraces.  High 
cliffs occur where mountains directly border the coast such 
as along the Big Sur coast and most of northern California.  
The high cliffs may be hundreds of meters or more in 
height, they occupy about 13% of the California coastline, 
and are typi_cally composed of more resistant rock types 
such as granite and rocks of the Franciscan Complex (Griggs 
and Patsch, 2004).  Marine terraces and coastal bluffs, 
which were dis_cussed earlier, form about 60% of the 
remaining coast and are common from Mendocino to San Diego.  
Where tectonic uplift has persisted, multiple terraces are 
often preserved.

Beaches

Beaches are ubiquitous features of the California coast and 
are important for a number of reasons:  a) they act as a 
natural buffer that protects coastal land during storms,  
b) they are a valuable recreational and economic resource, 
and c) they provide habitat such as nesting sites for the 
endan_gered snowy plover and haul-outs for protected marine 
mammals.  California beaches are not as long and 
continu_ous as those along passive margins (e.g. the U.S. 
South Atlantic and Gulf coasts) in part because the young 
and steep nature of the coast has not allowed enough 
geologic time for extensive sandy coastal plains to 
develop.  Beach types found in California include pocket 
beaches, long expanses of linear to gently curved beaches, 
barrier spit beaches at stream mouths, and cuspate 
headlands.  Pocket beaches are bound by headlands, and 
occur in both small stream valley and cliffed-coast 
settings.  Pocket beaches are probably the most common 
beach type in California, although their total length is 
smaller than the total length of California's linear 
beaches. Long expanses of beach typi_cally front the major 
dune complexes, larger stream valleys, and coastal plain or 
concaved areas (e.g. Monterey Bay and Santa Monica Bay).  
Cliffed coastlines can be fronted by both permanent and 
seasonal beaches.  Permanent beaches occur where there is 
abundant sediment supply, both along_shore and offshore.  
Seasonal beaches, which typically are present in the summer 
months and are lost during winter months, are common along 
exposed coasts with a limited offshore supply of sand.  

Because of the relatively high wave energy and a steeper 
and narrower continental shelf along the California coast, 
pronounced deltas do not form.  Instead, barrier spits and 
ebb and tidal bars develop where the streams reach the sea.  
Beaches that form at the mouths of stream valleys and 
embayments are typically a mixture of both fluvial- and 
littoral-derived sediment (mostly sand).  The barriers are 
typically barren to sparsely vegetated indicating an 
unstable substrate prone to occasional marine overwash and 
breach_ing.  Seasonal changes in wave climate and rainfall 
result in a concomitant change in barrier style.  In 
winter, periods of high waves and heavy rainfall cause 
overwash and chan_nelization of the barrier spits, reducing 
their overall size.  During the summer months, there are 
smaller waves and low precipitation and the barrier spits 
may completely block stream mouths due to reduced stream 
flow and beach accre_tion.

Seasonal beach change in California is caused by annual 
variations in wave climate that produce narrow beaches 
during winter months and wide beaches during the calmer 
summer months (Dingler and Reiss, 2002).  Dra_matic beach 
erosion, both in rate and amount, occurs during large 
storms.  Subsequent recovery is less rapid, often requiring 
several months for the beach to achieve its pre-storm 
configuration.  Beaches without an abundant offshore sand 
supply take much longer to recover (Brown and others, 
1998).  Figure 12 illustrates the seasonal change in beach 
profile shape during the intense 1997-98 El Ni_o winter 
season at Cowells Beach in Santa Cruz.

Coastal Dune Complexes

Cooper (1967) mapped the coastal dunes of Califor_nia and 
recognized that coastal dune complexes are best developed 
where there is: a) a nearby source of fluvial-sup_plied 
sediment, b) a structural high at the coast, such as a 
headland, to trap littoral drift or a low-relief stretch so 
dunes can migrate inland, and, c) strong consistent onshore 
winds.  Orme (1992) further noted that dune fields are best 
preserved in coastal areas that have undergone net tectonic 
subsidence or limited uplift in the Quaternary.  Aeolian 
deposits are often interbedded with fluvial and nearshore 
facies and the larger complexes represent multiple episodes 
of dune building.  In many areas the modern dunes represent 
surficial deposits overlying older, and larger, dune 
systems.  There is some indication (Orme, 1992) that 
significant coastal dune building occurs at lower sea-level 
positions when large quantities of sand are exposed on the 
emergent continental shelf.  

Modern dune building removes sediment from the lit_toral 
supply; in some places this can be a substantial portion of 
the littoral sediment budget.  For example, it has been 
estimated that about 150,000 m3 of sand are blown inland 
each year along the 55 km stretch of coastline from Pismo 
Beach to Point Arguello (Figure 5) (Griggs and others, 
2005c). Where the present coastline is undergoing retreat, 
such as in southern Monterey Bay, the dunes are reworked 
and supply sediment to the beach.  The major dune 
com_plexes of California are shown in Figure 13 along with 
their effective wind directions.  

Estuaries and Lagoons

U.S. West Coast estuaries and coastal lagoons typi_cally 
form in drowned-stream valleys cut below the level of the 
uplifted coastal plain (Peterson and Phipps, 1992) or in 
subsiding coastal blocks.  Four general types of 
estuarine/lagoon embayments occur in California: a) large 
embay_ments with high freshwater inflow, b) large 
embayments with relatively low freshwater inflow, c) large 
freshwater bodies with limited intertidal environments, 
and, d) ephem_eral streams with limited estuarine 
environments. 

The largest California estuary is the San Francisco Bay 
system that forms the outlet for the contiguous Sacramento-
San Joaquin Delta watershed.  This is a large embayment 
(~4,100 km2) with high freshwater inflow that drains more 
than 40% of the land area of the State of California (Chin 
and others, 2004).  Bay environments include marshes, 
intertidal mudflats, and subtidal channels.  The remainder 
of estuaries in California are much smaller in size but 
typically contain the same depositional environments.  

Embayments currently with low fluvial input, such as 
Bolinas Lagoon, Drakes Estero, Tomales Bay, Bodega Bay, 
Elkhorn Slough, and Morro Bay (Figure 5), appear to be 
structurally controlled depressions not presently connected 
to a major fluvial source.  In these examples, the 
embayment size is large compared to present stream 
discharge.  Embay_ment downcutting was probably enhanced 
during lower sea-level stands and the subsequent period of 
higher Holocene sea level resulted in bay infilling.  At 
present, many of the morphologic bay features appear to be 
tidally controlled.

The major rivers of California are typically character_ized 
by relatively high flow but narrow confined estuaries.  
These drainages are characterized by well-defined stream 
channels entering a restricted coastal depositional plain, 
and the location of the stream mouth is often controlled by 
a geologic feature such as a resistant headland.  
Inter_tidal environments are relatively limited in size 
because of extensive floodplain deposition (abundant sand).  
The rivers are the main suppliers of sand to the California 
coast (Figure 10).  Fine-grained sediment typically 
bypasses the coastal zone and is deposited in deeper water.  
Ephemeral streams are similar to the larger rivers but on a 
smaller scale.

General Characteristics of the California Coast Sections

Northern Section:  Oregon Border to Tomales Bay

The coast of Northern California (Figure 14A) can be 
characterized as a rugged landscape with high rainfall and 
low population.  Steep coastal cliffs dissected by 
numer_ous streams result in high sediment loads delivered 
to the coast.  Franciscan Complex rocks are common and the 
more resistant units often result in an irregular coast 
with steep cliffs, small offshore islands and sea stacks.  
Barrier spits and beaches are common features at stream 
valleys and embayments with the largest barrier in the 
region extending across Humboldt Bay.  Large dune complexes 
occur south of Smith River, between the Little and Eel 
Rivers, and south of Tenmile River (Figure 13).  Other 
large dune fields are present north of headlands at Point 
Arena and Bodega Head, and at the entrance to Tomales Bay 
(Figure 5).  Marine terraces and wave-cut bluffs are common 
between the areas dominated by the steep mountain cliffs.  
The terraces south of Cape Mendocino are Holocene features 
that are undergo_ing rapid uplift.  According to Savoy and 
others (2005), as much as 1 m of uplift occurred during a 
single earthquake in 1992 along the Cascadia subduction 
zone.  The heads of Mattole and Delgada submarine canyons 
reach into shallow water where they can intercept littoral 
transport.

Central Section: Tomales Bay to Point Conception

Central California (Figure 14B) is the most diverse coastal 
region of the state having characteristics of both the 
north and south regions plus a few unique features of its 
own.  This section represents the transition zone between 
the relatively wet and high wave energy north and the drier 
and lower wave energy southern section.  Unique embayments 
at Tomales, San Francisco, Monterey, and Morro-Estero Bays 
(Figure 5) form natural harbors along the rugged coastline.  
Marine terraces and coastal bluffs are well devel_oped 
south of Point Reyes, in the Monterey Bay region, parts of 
the southern Big Sur coast, and stretches along the San 
Luis Obispo County coast.  High relief coastal slopes occur 
at the Marin Headlands and Devils Slide north and south of 
San Francisco respectively, and along most of the Big Sur 
coast.  Between Morro Bay and Point Conception, coastal 
mountains of the San Luis Range, Point Sal Ridge, and the 
Santa Ynez Mountains of the western Transverse Ranges 
alternate with intervening basins forming the greater Santa 
Maria basin.  There are large dune complexes at Point 
Reyes, southern Monterey Bay, Morro Bay, and near the 
mouths of the Santa Maria and Santa Ynez Rivers (Figure 5).  
The Santa Maria and Santa Ynez Rivers are presently dammed 
resulting in a significant reduction of sediment reaching 
the coast from past conditions.  The heads of Mon_terey, 
Carmel, and Partington submarine canyons lie just offshore 
where they are thought to be major sinks for beach sand 
moving alongshore.

Southern Section: Point Conception to the Mexican Border

The coast of Southern California, extending from Point 
Conception to the Mexican border (Figure 14C), is markedly 
different from the rest of the state.  Point Concep_tion 
marks a dramatic change in coastal orientation due to 
tectonic movement along the Transverse Ranges that has 
resulted in an east-west trending coast.  Further south, 
the coast gradually returns to the northwest-southeast 
trend.  Coastal cliffs and marine terraces are widespread 
and are typically fronted by narrow beaches.  Unusual 
boulder deltas occur in the Santa Barbara area, notably at 
El Capitan and Rincon (Figure 5), and are thought to be 
remnant flood deltas at the mouths of steep mountain 
creeks.  The larg_est river in this section in this section 
is the Santa Clara River with an estimated average annual 
sand and gravel discharge of 912,000 m3 (Figure 10).  Other 
notable rivers are the Ventura, Los Angeles, and Santa Ana.  
There are a number of submarine canyons with heads near the 
lit_toral zone, including: Mugu, Hueneme, Redondo, Dume, 
Newport, Scripps, and La Jolla canyons (Figure 5).  The 
narrow coastal plains of the Santa Barbara area are 
replaced by broader plains in Ventura-Oxnard, Santa Monica 
- Los Angeles Basin, and Mission Bay to Imperial Beach.  
The dune complexes are not as well developed as those in 
the rest of the state but moderately large dune fields 
occur near Oxnard, north of Palos Verdes, and at Silver 
Strand - Impe_rial beaches (Figure 5).  This section is the 
most urbanized stretch of coast in California.

HISTORY OF INFRASTRUCTURE DEVELOPMENT

The first European to visit the coast of California is 
widely held to be Juan Rodriguez Cabrillo, a Portuguese 
explorer who is credited with the "discovery" of 
Califor_nia in 1542.  The first permanent European 
settlement was established in what is now San Diego in 
1769. Settlement of the coastal areas proceeded slowly in 
California, partly because of the dangerous nature of the 
Pacific coastal waters, and partly because access from 
inland was inhibited by the steep and rugged terrain.  
Northern California was settled primarily by Russian fur 
traders, and most coastal development in the State was 
restricted to large natural har_bors such as San Diego Bay, 
Monterey Bay, San Francisco Bay and Humboldt Bay.

By 1850, the total population of California was only 
93,000.  Population grew over the years, but there was an 
explosion following World War II; the State's population 
increased from 10 to 20 million between 1950 and 1970 
(Pincetl, 2004) and in 2005 is about 36 million.  Today, 
California is the most populous state in the union, and it 
is estimated that 80% of California residents live within 
50 km of the coast (Griggs, 1994).  

Much of the coast of Central and Northern California is 
very rugged, inaccessible and therefore undeveloped.  This 
results in the focusing of developmental pressures over a 
smaller percentage of the coast resulting in variations in 
coastal hazards.  Along much of the Northern California 
coast, the most important coastal hazards are large 
land_slides that can damage coastal roads, and the rapid 
retreat of coastal cliffs where community infrastructure 
exists at the top or base of the cliff.  Central California 
has a mixture of hazards; in addition to large coastal 
landslides and coastal cliff erosion, there are linear 
stretches of sandy shoreline that have been developed with 
homes and infrastructure.  Southern California, which has 
the greatest percent of sandy shorelines also has the 
greatest percent of coastal armor_ing, engineering 
structures and nourishment programs.  The wide, sandy 
beaches that exist today in Southern California were 
created and are maintained through a variety of coastal 
engineering projects and nourishment programs (Flick, 
1993).

Practices such as damming coastal rivers and building 
various coastal engineering structures (groins, jetties and 
breakwaters) may be adversely affecting beach resources.  
During the post-World War II building boom, many homes and 
communities were established on or near the coast, with 
houses often built on the sand, especially in Southern and 
parts of Central California.  Eventually these homes were 
threatened by shoreline erosion, and the response was 
fre_quently to construct some type of protection structure.  
The California Coastal Act was passed in 1976, and with it 
the California Coastal Commission was formed.  The Coastal 
Act requires statewide regulation and planning for coastal 
development, but also allows local governments to 
imple_ment policies for coastal erosion hazard mitigation.  
The Coastal Commission has slowed the widespread 
emplace_ment of shoreline protection structures, but the 
Coastal Act states that such structures shall be permitted 
to protect exist_ing development if it is threatened by 
erosion.

The post-World War II rapid increase in population and 
construction also coincided with a period of relative 
climatic quiescence on the West Coast.  The period from the 
1940s through the early 1970s had no major El Ni_o events 
and average or below average number of damaging coastal 
storms (Storlazzi and Griggs, 2000).  Rapid build_ing took 
place near the coast during this time because it was 
considered desirable and not a high-hazard zone.  This 
period also coincided with the development of several major 
coastal engineering projects in Southern California, which 
resulted in the addition of large volumes of sand to the 
beach systems.  In the mid-1970s, the West Coast entered 
into a climatic period when the intensity and number of 
severe storms substantially increased.  The destructive El 
Nio winters of 1982-83 and 1997-98 are evidence of this 
stormier period.  Widespread damage to both public and 
private property occurred during those winters.  According 
to Griggs and Fulton-Bennett (1988), total losses during 
the winter of 1982-83 reached $200 million (in 2006 
dollars), and numerous houses, businesses and existing 
coastal pro_tection structures were damaged.

HISTORICAL SHORELINE CHANGE ANALYSIS

This section presents the results of the California sandy 
shoreline (herein referred to as shoreline) change analysis 
and discusses, where applicable, the effects of engineering 
structures and beach nourishment programs on the rates of 
shoreline change. Each California section (Northern, 
Central and Southern) is subdivided into regions (Figure 
1), which are based broadly on littoral cells and breaks in 
data cover_age.  Tables 6A-C summarize both long-term and 
short-term average rates of shoreline change within each 
region. Addi_tionally, Tables 7A-C present the maximum and 
minimum erosion and accretion rates for each region in 
California.  

The description of shoreline change includes informa_tion 
and discussion on human-induced changes. Most of the 
substantial erosion/accretion trends and/or reversals in 
trend are related to human intervention within the natural 
coastal system; these are virtually inseparable topics of 
discussion. In California, shorelines are eroding primarily 
because of an increase in storm intensity, sea-level rise, 
climatic changes, and as a consequence of human activities 
that disrupt the natural sediment supply.  

In the discussions below, rates are referenced from Tables 
6A-C and 7A-C, where shoreline change rates are presented 
as the region-average net rate for the long-term (1800s-
1998/2001) and short-term (1950s/70s - 1998/2001) analysis, 
as well as by the magnitude of the erosion-only and 
accretion-only rates.  Errors and uncertainty values are 
not shown in the text for clarity; refer to Table 6A-C for 
these values.  To compare how net trends and rates may have 
changed from the long-term to the short-term, a statistical 
t-test was performed to determine whether the long-term and 
short-term rates were significantly different from one 
another at the 90% confidence interval.  The t-test results 
found that in all regions except the San Pedro region, the 
change from long-term to short-term was statistically 
significant.  Within the remaining 14 regions, the net 
shore_line change rate became more erosional from the long-
term to the short-term with the exception of the Russian 
River region.

The average net rate of long-term shoreline change for 
California was 0.2 m/yr, an accretional trend.  This is 
based on shoreline change rates averaged from 14,562 
individual transects, of which 40% were eroding.  Our 
analysis found that the only regions in California that 
experienced long-term negative net shoreline change were in 
Central Califor_nia (San Francisco South and Monterey Bay 
regions), both with region-averaged rates of -0.2 m/yr 
(Table 6B).  The highest region-averaged net rate was 
measured in the San Diego region (0.9 m/yr).  Overall, 
Central California had the lowest overall net long-term 
shoreline change, likely because of the lack of major 
coastal engineering projects, such as those that result in 
more accretional rates in South_ern California by adding 
sediment to the littoral system. In addition, the high 
volumes of sediment input from rivers likely contribute to 
the lower overall erosional trend in Northern California.  
When the erosion versus accretion rates were separated out, 
the average long-term erosion rate for the state was found 
to be -0.2 m/yr.  

The average net rate of short-term change for Califor_nia 
was -0.2 m/yr, based on 16,142 transects, along which 66% 
were eroding.  Negative (erosional) net short-term 
shoreline change was measured in 10 of the 15 regions.  For 
those transects along which erosion was recorded, the 
aver_age short-term erosion rate was -0.8 m/yr. The short-
term average erosion rates were highest in Central 
California (Table 6B).

It is important to keep in mind that the change rates 
discussed in this report represent change measured through 
the date that the lidar was collected and thus may not 
reflect the most recent trends in shoreline change.  In 
addition, although erosion rates in some areas are 
relatively low, many of California's beaches are narrow and 
even a small amount of local erosion may present serious 
hazards to the coastal resources and community 
infrastructure in a given area.  

Northern California

The Northern California analysis extends from the Ore_gon 
border to Tomales Bay, a distance of approximately 550 km 
(Figure 1).  For the presentation of the shoreline change 
analysis Northern California was divided into four regions: 
Klamath, Eureka, Navarro and Russian River (Figure 14A).  

Much of Northern California is highly crenulated, rocky 
coastline with small sections of pocket beaches, except for 
near major river mouths such as the Klamath, Smith, Eel and 
Russian Rivers, and a few areas where steep coastal cliffs 
are fronted by narrow beaches.  As a result of this 
geomorphology, there were many gaps in the data; the long-
term change was measured along only 148 km of the 
shoreline, and short-term change over 168 km.  Both long-
term (0.5 m/yr) and short-term (0.3 m/yr) net shoreline 
change rates were accretional when averaged over all of the 
Northern California transects.  Of the 2,966 transects 
along which long-term shoreline change was measured, 23% 
had erosional trends, with an average erosion rate of -0.3 
m/yr (Table 6A).  For the short-term analysis, the percent 
of beach eroding more than doubles, increasing to 47% and 
the average short-term erosion rate was -0.6 m/yr.

Klamath Region

The Klamath region covers approximately 112 km of coastline 
and extends from the Oregon border to Patrick's Point 
(Figure 1).  This region lies within the Smith and Klamath 
littoral cells (Figure 9), where rivers of the same names 
supply abundant sediment to the beach systems.  The 
coastline here is sparsely developed, except for the area 
around Crescent City, and includes long stretches of State 
and National Park lands. The only significant engineering 
structures are the breakwaters protecting the Crescent City 
Harbor. According to Clayton (1991) there is harbor sand 
by-passing every several years; however the frequency is 
not consistent.  In addition, the harbor was dredged in the 
1970s, and material was placed north of the harbor to 
attempt to slow chronic bluff erosion (Savoy and others, 
2005).

For the Klamath region, long-term change rates were 
measured along 71.5 km of shoreline.  The net long-term 
rate, averaged over 1,430 transects, was 0.7 m/yr.  Along 
those transects with a long-term erosional trend, the 
average erosion rate was -0.4 m/yr and was found along 25% 
of the coast.  The average long-term accretion rate, which 
occurred along 75% of the coast in this region, was 1.0 
m/yr (Table 6A).  The long-term accretion rate in the 
Klamath region was the highest in Northern California.  The 
maximum long-term erosion rate (-1.2 m/yr) occurred on the 
shoreline of a dynamic spit that extends across much of the 
Klamath River mouth (Table 9A).

The average short-term net shoreline change rate in the 
Klamath region is accretional (0.4 m/yr).   Forty-eight 
per_cent of the coast along which short-term shoreline 
change was measured was erosional, and the average erosion 
rate was -0.6 m/yr.  The remaining 52% of the measured 
coast in this region had a short-term accretion rate of 1.3 
m/yr.  The highest short-term erosion rate, -2.6 m/yr, was 
along Big Lagoon Beach, north of Patrick's Point (Table 9A; 
Figure 15).  This area was heavily impacted during the 
1982-83 El Ni_o winter storms (Figure 16), which may have 
influenced the short-term erosion rate.

The rate of net shoreline change in the Klamath region 
decreased from the long-term (0.7 m/yr) to the short-term 
(0.4 m/yr), and the percent of the coastline eroding 
increased from 25% in the long-term to 48% in the short-
term (Table 6A).  

North of the Crescent City Harbor, shoreline change becomes 
increasingly erosional in both the long- and short-term 
periods (Figure 15) near the harbor as opposed to areas 
further north.  The highest accretion rates north of 
Crescent City were located immediately south of the Smith 
River mouth where there are extensive dune systems.  There 
were local increases in the rates of accretion adjacent to 
the north and south breakwaters of the Crescent City Harbor 
(Figure 15).  This area is composed of broad tidal flats, 
and the high rates may have been a function of the tide 
level when the shoreline data were collected.

South of the Klamath River mouth, the magnitude of 
shoreline change increased substantially.  At the northern 
end of Redwood State Park where Ossagon Creek empties onto 
the beach at Gold Bluffs Beach, the highest accretion rates 
in the State were observed (4.8 m/yr long-term and 7.3 m/yr 
short-term).  While most of the high accretion rates in 
other parts of the State were associated with engineering 
structures or beach nourishment, the accretion rates here 
were apparently natural.

Eureka Region

The Eureka region, which begins 6 km south of Trini_dad 
Head and extends 74 km south to Cape Mendocino (Figures 14A 
and 17) falls within the Eureka littoral cell.  Most of the 
coastline consists of sandy beaches as compared with the 
other Northern California regions.  Long, linear beaches, 
dunes systems and spits have formed through deposition of 
sand by the Eel, Mad and Little Rivers.  While still 
sparsely developed by California standards, the Eureka 
region, which includes the towns of Arcata and Eureka, is 
the most developed and populous coastal area of the 
North_ern California regions.  Humboldt Bay Harbor lies 
between Eureka and a seaward barrier spit and is the 
largest harbor in Northern California; jetties were 
constructed there in the 1800s to keep a channel in the 
spit open for boat traffic.  North Spit and South Spit now 
converge at the Humboldt Bay jetties; unfortunately there 
is a gap in the lidar data for the spits, except 
immediately adjacent to the jetties.  There_fore, we were 
unable to calculate long- or short-term rates for 18 km of 
sandy shoreline along the spits. 

The long-term net shoreline change rate for the Eureka 
region was 0.7 m/yr, an accretional trend similar to that 
measured for the Klamath region.  Virtually all of the 
shore_line was accreting at a long-term average rate of 0.7 
m/yr, observed along 96% of the measured shoreline. The 
average long-term erosion rate for the Eureka region is -
0.2 m/yr (Table 6A).  Of the total 24.7 km of sandy 
shoreline that was measured, long-term erosion occurred 
along only 4% of the coast. The highest erosion rates were 
measured on either side of the Eel River mouth, where a 
maximum long-term rate of -0.4 m/yr, was observed (Table 
9A). 

Short-term net average shoreline change rates for the 
Eureka region, measured along 32.6 km of coastline, were 
0.4 m/yr, a less accretional trend from the long-term 
rates.  The average short-term erosion rate was -0.9 m/yr 
(Table 6A) and was measured along 51% of the analyzed 
coast.  The average short-term accretion rate, 1.8 m/yr, 
was the highest average accretion rate in the State, and 
was mea_sured along 49% of the analyzed coast.

Short-term change rates varied along coast, and were 
predominantly erosional near the Mad River, the North Spit 
of Humboldt Bay, and south of the Eel River.  The maxi_mum 
erosion rate (-2.7 m/yr) in this region was along North 
Spit Beach, immediately north of the Humboldt Bay jetty 
(Figure 18).

The highest accretion rates (both long- and short-term) 
occurred in the northern portion of the region, on the 
south side of the mouth of the Little River (Figure 17; 
Table 9A), along Little River State Beach.  The beach here 
is backed by a substantial dune system.  Similarly, in the 
southern part of the region, within the Eel River State 
Wildlife area, there was a strong accretional trend in both 
long- and short-term rates in an area that is backed by 
substantial dunes.  

Navarro Region

The Navarro region extends along 207 km of coast_line and 
contains both the Ten Mile and Navarro littoral cells 
(Figure 9).  This section begins approximately 11 km south 
of Point Delgada and ends at Point Arena (Figures 14A and 
19).  The towns of Fort Bragg and Mendocino are located 
within the Navarro region; otherwise, this stretch of 
coastline is very rugged, inaccessible, and there is little 
development.  The only major coastal engineering structure 
along this coast is the breakwater at the Noya Harbor, on 
the south side of Fort Bragg. With a few exceptions, the 
coast in the Navarro region is crenulated and rocky with 
steep cliffs; there are some scattered pocket beaches and 
occa_sional narrow beaches fronting the cliffs that 
generally are not passable at high tide.  Exceptions 
include the extensive beach and dune system south of the 
Ten Mile River mouth (Mac Kerricher State Park) (Figure 
20), and several beaches formed in the vicinity of larger 
creek mouths, such as West_port-Union Landing State Beach, 
and Manchester Beach State Park (Figure 14A).  

Of the 207 km of coastline in this region, only 31.5 km had 
measurable sandy shorelines for our long-term analysis, due 
primarily to the lack of continuous beaches. The net long-
term shoreline change was accretion that averaged 0.1 m/yr.  
This rate was much lower than the average rates for the 
Eureka and Klamath regions discussed above. Along those 
transects where erosion was measured, the average long-term 
erosion rate was -0.1 m/yr, averaged  along 28% of the 
coast (Table 6A).  Long-term accretion, measured along 72% 
of the coast, averaged 0.2 m/yr. The maximum long-term 
erosion rate (-0.6 m/yr) was located within DeHaven Creek 
Beach north of Fort Bragg (Table 9A). Long-term accretion 
rates reached a maximum of 0.7 m/yr along Ten Mile Beach 
south of the Ten Mile Rive mouth.

Net short-term shoreline change, as averaged along 32.8 km 
of coastline, was found to be undetectable at the 
significant figures appropriate for this analysis and 
therefore are reported as 0.0 m/yr  in Table 6A.  Of the 
measurable stretches of sandy shoreline, 50% eroded and 50% 
accreted.  The average short-term erosion rate was -0.5 
m/yr, and the accretion rate was 0.6 m/yr.  The maximum 
short-term erosion rate of -1.4 m/yr occurred at DeHaven 
Creek Beach (Table 9A), and the maximum short-term 
accretion rate of 3.3 m/y occurred just north of the Ten 
Mile River mouth (Figure 19).

The maximum long- and short-term erosion rates in the 
Navarro region are both found along isolated narrow beaches 
in the northern half of the region.    These beaches are 
difficult to access and no development is threatened as a 
result of the higher erosion rates.  Both long- and short-
term maximum accretion rates were near the Ten Mile River 
mouth north of Fort Bragg.  The high long- and short-term 
accretion rates were likely related to the large volumes of 
sand discharged by the Ten Mile River (Merritts and others, 
2005).

Russian River Region

The Russian River region begins 12 km south of Point Arena 
along a remote, rocky stretch of coastline that has little 
development, and extends 155 km south to Tomales Point 
(Figures 14A and 21).  Similar to the other regions in 
Northern California, there are few linear stretches of 
sandy shoreline, especially in the northern half of the 
region.  The most extensive beaches are formed near large 
rivers such as the Gualala and the Russian Rivers (Figure 
21). In addition, a wide sandy beach and dune system exist 
at Salmon Creek Beach just north of Bodega Head. The 
Russian River region contains both the Russian River and 
Bodega Bay littoral cells.

Of the 155 km of coast in this region, we were only able to 
measure long-term shoreline change along 21.8 km, primarily 
because of the lack of linear beaches; we did not measure 
shoreline change rates on pocket beaches smaller than 0.5 
km in length.  The average net long-term shore_line change 
rate for the Russian River region was 0.2 m/yr. Average 
long-term erosion was -0.2 m/yr and occurred over only 28% 
of the coast (Table 6A).  Similar to the other regions in 
Northern California, a much higher percentage of the coast 
is accreting in the long-term than eroding.  The average 
long-term accretion rate for the Russian River region was 
0.3 m/yr and was observed along 72% of the coast. The 
maximum long-term accretion rate, 1.8 m/yr, was at Dillon 
Beach, and the maximum long-term erosion rate of -0.7 m/yr 
was along Sonoma Coast State Beach (Figure 22; Table 9A).

Net short-term shoreline change averaged 0.4 m/yr, measured 
along 24.1 km of the coast. Short-term erosion occurred 
along 35% of the coast, and the average rate was -0.4 m/yr 
(Table 6A).  This is the lowest percentage of eroding 
coastline of the four Northern California regions. The 
average short-term accretion rate was 0.8 m/yr.

The maximum short-term accretion rate (3.5 m/yr) was at 
Dillon Beach (Figure 22; Table 9A) and the highest short-
term erosion rate (-1.6 m/yr) occurred along Sonoma Coast 
State Beach ~1.5 km south of the Russian River mouth..  

Sandy shorelines in the northern 100 km of this region are 
rare and occur only where small pocket beaches form at the 
mouths of rivers and creeks.  Overall the shoreline change 
was accretional; the highest erosion rates were near the 
Russian River.  This is the only region in the state in 
which the average rate of net shoreline change increased 
from the long-term to the short-term.

Central California

The Central California section begins approximately 5 km 
south of Tomales Point in Point Reyes National Sea_shore 
(PRNS) and extends south to El Capitan State Beach, just 
north of Santa Barbara, a total distance of approxi_mately 
740 km (Figure 14B).  Central California is divided into 
six regions including San Francisco North, San Fran_cisco 
South, Monterey Bay, Big Sur, Morro Bay and Santa Barbara 
North.  The average net long-term shoreline change rate for 
Central California was found to be undetectable at the 
significant figures appropriate for this analysis and is 
reported as 0.0 m/yr.  In the short-term, however, the 
aver_age net rate is strongly erosional (-0.5 m/yr).  

There are many gaps in our analysis along this coast, as 
much of the shoreline is rocky with isolated pocket 
beaches; there are a few continuous linear beaches such as 
in the Monterey Bay region.  Coastal engineering structures 
and nourishment projects are limited to small harbor 
construc_tion (e.g. Port San Luis, Santa Cruz) and some 
harbor by-passing.  Numerous seawalls and revetment exist 
along the coast but these are primarily related to issues 
of coastal cliff erosion mitigation, not to protect 
structures from erosion of the sandy shoreline.  

San Francisco North Region

The San Francisco North region is 93 km long and includes 
the Point Reyes, Drakes Bay and Bolinas Bay litto_ral cells 
(Figure 9).  This is primarily a rocky coastline, with 
narrow beaches backed by high coastal cliffs, small 
isolated pocket beaches between rocky headlands, and an 
expansive dune field at Point Reyes.   There are two very 
small, devel_oped sections of the coast in this region at 
Bolinas and Stin_son Beach.  Due to a data gap in the 
1800s-era t-sheets we have no long-term shoreline change 
rates for either of these areas.  Other than these two 
areas, the coast here is undevel_oped and remote, and falls 
entirely within either PRNS or the Golden Gate National 
Recreation Area (GGNRA).

Net long-term shoreline change rates in this region, 
averaged along 45.1 km of coast, were low and averaged 0.1 
m/yr (Table 6B).  Forty-six percent of the shoreline was 
eroding in the long-term at an average rate of -0.2 m/yr.  
Long-term accretion rates of 0.3 m/yr occurred along 54% of 
the coast.  The highest and lowest long-term rates occurred 
north of Point Reyes Headland  where the long-term trend 
was largely accretional (Figure 23).  However, the maximum 
long-term erosion rate for the San Francisco North region 
of -0.5 m/yr was at Limantour Beach, which is north of 
Point Reyes (Table 9B).

Net average short-term shoreline change rates were measured 
along 51.9 km of coastline, and the average change rate was 
-0.5 m/yr.  Eighty-one percent of the coast was eroding 
(short-term) with the rate of erosion averaging -0.7 m/yr.  
Short-term accretion rates, averaging 0.5 m/yr, occurred 
along only 19% of the coast.  

Short-term shoreline change trends north of Point Reyes 
Headland (Figure 23) were highly variable with accretion 
dominant in the north, changing to predominantly erosion in 
the south.  The maximum short-term erosion rate of -3.1 
m/yr was measured at Point Reyes Beach (Figure 23).  This 
trend is driven by the position of the most recent (lidar) 
shoreline and may indicate a rotation of the beach during 
the 1997-98 El Nino where the dominant littoral transport 
changed directions from southward to northward in many 
local areas.

In the San Francisco North region, the long- and short-term 
shoreline change rates were significantly differ_ent; there 
was an overall shift from a net shoreline change trend that 
was 0.1 m/yr in the long-term to a net shoreline change 
rate that was strongly erosional (-0.5 m/yr) in the short-
term.  In addition, the percent of coastline along which 
erosion was measured increased from 46% in the long-term to 
81% of the short-term. 

As demonstrated in Figure 23, from Point Reyes headland to 
Point Bonita, the sandy beaches were relatively stable in 
the long-term.  In the short-term, this section of beach as 
primarily erosional, with a few localized excep_tions (i.e 
south of Drakes Estero).  The short-term erosion rates at 
Stinson Beach were the highest of those measured in the 
southern portion of the San Francisco North region.  Winter 
storm waves frequently inundate Stinson Beach, moving large 
volumes of sand, and threatening homes built on the sand 
spit.  Figure 24 shows a house buried by sand that had been 
eroded from a location further north. Riprap has been 
emplaced in many areas to protect the houses from beach 
erosion (Savoy and others, 2005).

San Francisco South Region

The San Francisco South region is 115 km long and extends 
from the mouth of San Francisco Bay to Davenport (Figures 
14B and 25).  The northern coast in this region is urban 
and includes San Francisco, Pacifica and Half Moon Bay; the 
southern half is largely undeveloped and agricultural. The 
San Francisco littoral cell is within this region (Figure 
9).  The geomorphology of the coastline is variable, with 
linear beaches backed by dunes, steep cliffs with narrow 
fronting beaches, rocky coast with small pocket beaches, 
and steep, high-relief coast with no sandy shore_line.  
There are no known beach nourishment projects in this 
region, although a dredge spoil deposit offshore may be 
contributing material to the beach (Barnard and Hanes, 
2006).  Additionally, wind-blown sand is regularly removed 
from the inland side of the dunes and from the adjacent 
highway and added to the south end of the beach (Wiegel, 
2002). The most notable coastal engineering structures are 
the O'Shaughnessy and Great Highway seawalls along Ocean 
Beach in San Francisco and the Pillar Point Harbor at Half 
Moon Bay.  

For this analysis we calculated net average long-term 
shoreline change rates for 56.3 km of coastline, and the 
average rate was -0.2 m/yr.  Long-term erosion occurred 
along 76% of the coast at an average long-term rate of -0.4 
m/yr.  For the 24% of the coast along which accretion 
occurred, the long-term average accretion rate was 0.1 
m/yr.  The maximum long-term accretion rate (0.4 m/yr) in 
this region was located 0.25 km south of Mussel Rock, and 
the maximum long-term erosion rate of -1.8 m/yr occurred on 
the north side of Point Ao Nuevo (Figure 25; Table 9B).

Net short-term shoreline change, with an average rate of -
0.5 m/yr, was measured along 57.5 km of coast in the San 
Francisco South region.  Along the portions of coast where 
the short-term shoreline change was erosional, the rate was 
-0.7 m/yr, averaged over 81% of the coast.  The average 
short-term accretion rate was 0.5 m/yr. 

Short-term change trends in the central portion of this 
region are more variable than the long-term trends; erosion 
was relatively high north and south of Pillar Point Harbor 
(Figure 26) where the breakwater disrupts the natural 
trans_port of sand and focuses wave energy at the south end 
of the breakwater. The maximum short-term accretion rates 
were found along the central area, where they reach a 
maximum of 2.2 m/yr at Tunitas Beach (Figure 25).  The 
maximum short-term erosion rate, -2.6 m/yr, was along the 
north side of Point Ano Nuevo.

Both the long-term and short-term net trends were 
ero_sional, and the rates more than doubled from the long-
term to the short-term.  The percents of coast eroding and 
accret_ing were similar in both the long-term and the 
short-term (Table 6B). Along Ocean Beach, both were 
relatively stable at the very northern end of the beach 
adjacent to the mouth of San Francisco Bay.  However, both 
long-term and short-term rates became strongly erosional to 
the south except immediately north and south of Mussel 
Rock.  

The long- and short-term maximum erosion rates (-1.8 m/yr 
and -2.6 m/yr, respectively; Table 9B) were observed 
immediately north of Point A_o Nuevo.  This area of rapid 
erosion was adjacent to a former sand spit that connected 
A_o Nuevo Island to the mainland (Griggs and others, 2005).  
The spit was breached sometime in the late 1800s, providing 
a path for the transport of sand to the south.

Monterey Bay Region

The Monterey Bay region begins approximately 2 km north of 
Davenport in Santa Cruz County and extends 75 km to Del 
Monte State Beach in Monterey (Figures 14B and 27).  This 
region includes the Santa Cruz and Southern Monterey Bay 
littoral cells, and is characterized by a vari_able coast 
that includes rocky points and pocket beaches, cliffed 
coastline with narrow fronting beaches, and linear beach 
and dune systems.  Development varies from urban (city of 
Santa Cruz and environs) to rural/agricultural.  The Santa 
Cruz Small Craft Harbor, built in the early 1960s, 
cur_rently has an active entrance channel dredging programs 
and the sand is placed downcoast from the harbor mouth.  
One beach in this region, Capitola, is down-coast from the 
Yacht Harbor and has been nourished.

The total length of sandy shoreline along which long-term 
change was measured in the Monterey Bay region is 50.7 km.  
The average net long-term shoreline change rate was -0.2 
m/yr.  Along the 41% of the coast that had a long-term 
erosional trend, the average rate was -0.6 m/yr. Long-term 
accretion occurred along 59% of the sandy shoreline, and 
had an average rate of 0.4 m/yr (Table 6B).  

Long-term shoreline change throughout the central portion 
of the Monterey Bay was accretional. However, in the 
northern portion of the bay near the Santa Cruz Yacht 
Harbor, the shoreline change trend shifts from accretional 
west of the harbor to erosional east of the harbor (Figure 
27).  The effects of the harbor appear to diminish south of 
Capitola State Beach, where the change rates are strikingly 
uniform. In the southern part of Monterey Bay there was a 
noticeable shift in the long-term shoreline change trend 
from strongly accretional in the north to erosional in the 
south (Figure 27).  Both the maximum long-term accretion 
and erosion rates were measured in the southern area (Table 
9B).  The maximum long-term erosion rate of -1.3 m/yr 
occurred at Indian Head Beach, and the maximum accretion 
rate (1.2 m/yr) occurred further south at Salinas River 
State Beach (Figure 27).  

The net short-term shoreline change rate in the Mon_terey 
Bay region was -0.6 m/yr, measured over 51.5 km of coast.  
Along those portions of the coast that had an ero_sional 
trend, the average rate was -0.8 m/yr, and occurred along 
77% of the coast. The average short-term accretion rate, 
0.3 m/yr, is the lowest in the Central California region.

The maximum short-term accretion rate (1.8 m/yr) was 
measured just south of the harbor on Twin Lakes State Beach 
(Figure 27; Table 9B). This maximum is likely due to 
material that was dredged from the harbor channel every 
winter and spring and placed on or just offshore of this 
beach (Griggs and Johnson, 1976; Wiegel, 1994). In the 
northern part of the Bay, the large pulse of short-term 
accre_tion near Capitola Beach was the result of beach 
nourish_ment projects.  This project was implemented 
shortly after the harbor jetties were built to compensate 
for the disrupted downcoast transport of sand (Griggs and 
Johnson, 1976; Clayton, 1991).  

The northernmost portion of the Monterey Bay region is 
primarily a rocky coastline with scattered small pocket 
beaches; therefore, there is little sandy shoreline along 
which to measure change.  The first continuous stretches of 
beach in this region are associated with the San Lorenzo 
River mouth at Main Beach in Santa Cruz (Figure 27).  The 
net average rates of change in the Monterey region were 
significantly different, and there were distinct trends in 
the rates of change from the long-term to the short-term. 
The net average change rate more than doubles from the 
long-term (-0.2 m/yr) to short-term net change of -0.6 
m/yr. In addition, the percent of coast experiencing 
erosion increased by 36%.  This trend suggests that the 
Monterey Bay region is undergoing a shift to overall 
increased erosion in the more recent time period.

In general, in the northern postion of the bay, the long-
term and short-term trends of accretion gradually increased 
to the southeast where sand is impounded against the 
north_western Yacht Harbor jetty (Figure 28).  In the 
Southern Monterey Bay, accretional trends to the north 
gradually shifted to erosional trends to the south. The 
general area where erosion becomes more predominant 
corresponds to the portion of coast where sand mining 
practices throughout the 20th century removed large volumes 
of sand from the beach and dunes (Griggs and Patsch, 2005; 
Thornton and others, 2006). 

Big Sur Region

The Big Sur region extends along 165 km of largely remote 
and rugged coastline from Point Pi_os in the north to near 
Cape San Martin in the south (Figures 14B and 29).  The 
littoral cells within this region are the Carmel River cell 
and the Point Sur cell (Figure 9). This region includes the 
development associated with Monterey and Carmel in the 
north; the remainder of the coast is essentially 
undeveloped.  The primary hazards along this coast are 
large landslides that threaten roads and small development.  
The only sandy shorelines are along small pocket beaches 
and the exten_sive beach and dune system at the mouth of 
the Little Sur River extending to Point Sur.  There are no 
known coastal engineering structures or beach nourishment 
projects.  Due to the lack of linear stretches of sandy 
shoreline, we were able to measure shoreline change along 
only 27 km of the Big Sur region.  

The net long-term average shoreline change rate was found 
to be undetectable at the significant figures appropri_ate 
for this analysis and is reported as 0.0 m/yr in Table 6B.  
The average long-term erosion and accretion rates were both 
low (-0.1 and 0.2 m/yr, respectively), but accretion 
occurred over a much higher percent of the shoreline, 61% 
versus 39% for the eroded areas.  The maximum long-term 
erosion rate (-0.8 m/yr) was measured in the northern 
portion of the region at the southern end of Carmel River 
State Beach (Figure 29).  

In the short-term, the net average shoreline change rate is 
was -0.2 m/yr.   Short-term erosion occurred along 65% of 
the coast, with rates averaging -0.5 m/yr.  Short-term 
accretion rates averaged 0.4 m/yr.  Similar to the maximum 
long-term erosion rate, the maximum short-term erosion rate 
was in the northern portion of the region at Carmel River 
State Beach and Carmel City Beach (Figure 29) where the 
maximum short-term erosion rate was -1.7 m/yr (Table 9B).  
Pfeiffer Beach, which is approximately 13 km south of Point 
Sur, had the maximum short-term accretion rate (2.4 m/yr) 
in this region.

Beaches along the Big Sur region are widely scattered and 
typically occur only at or near the mouths of rivers and 
creeks.  The longest continuous stretches of beach are near 
the Little Sur River mouth and the dune system at Point Sur 
(Figure 29) where there is adequate sand supply.  The 
highest long-term accretion rate was at the site of the 
Julia Pfeiffer-Burns landslide, which occurred in 1983.  As 
a result of the landslide, a small beach was created where 
none had existed before (Hapke, 2005; Figure 30).  Overall, 
the net shoreline change rate for the Big Sur region became 
more erosional from the long-term to the short-term.

Morro Bay Region

The Morro Bay region is 105 km long, includes the section 
of coast from San Carporforo Creek in the north to Point 
Bachon in the south (Figures 14B and 31) and falls within 
the Morro Bay littoral cell.  This is a lower relief coast 
than the Big Sur region to the north, with stretches of 
rocky coastline with no beaches, low cliffs backing narrow 
beaches, as well as several linear beach and dune systems.  
The largest dunes are in the southern part of the region at 
Morro Strand State Beach and Montana De Oro State Park 
(Figure 14B). Shoreline change (both long-term and short-
term) was measured along only 22.3 and 22.9 km of coast 
respectively, partly due to the rocky nature of the 
coastline, and partly due to gaps in the lidar data.  The 
Morro Bay region is moderately developed with the developed 
sections of coast concentrated in the southern areas.  The 
towns of San Simeon, Cambria, Cayucas and Morro Bay are 
within this region.

In the Morro Bay region, the net average long-term 
shoreline change rate of 0.1 m/yr was the one of the 
highest (most accretional) in Central California (the San 
Francisco North region also had a net long-term rate of 0.1 
m/yr) (Table 6B).  Accretion was measured along 65% of the 
coast, and the average rate of the accreting sections was 
0.3 m/yr.  Where the beach was eroding, the rates averaged 
-0.1 m/yr.  The maximum long-term erosion rate (-0.6 m/yr; 
Table 9B) was measured in the northern part of the region 
along a small, unnamed pocket beach.

The average short-term shoreline change rate, -0.7 m/yr, 
was the most erosional net change rate in Central 
Cali_fornia.  Where the beach was eroding (80% of the 
coast), the short-term erosion rates averaged -1.0 m/yr, 
the highest in Central California.  The short-term 
accretion rates averaged 0.4 m/yr. 

Shoreline change rates in the Morro Bay region were highly 
variable in both the long-term and short-term (Figure 31).   
Beaches in the southern portion of the region were largely 
stable in the long-term, but becoming highly ero_sional in 
the short-term, suggesting a more recent disruption of the 
sand supply in this area.  Figure 32 shows an area of long-
term beach accretion at Morro Rock, which is the site of 
the highest accretion rate (1.5 m/yr) in the Morro Bay 
region.  This high accretion was related to the trapping of 
sand up coast from the Morro Bay harbor breakwater and the 
Morro Rock causeway, which was built during the 1930s - 
1940s.  The maximum short-term accretion rate was located 
just downcoast of the breakwater (1.2 m/yr) (Figure 31; 
Table 9B).  For the long-term period, beaches along the 
Montana De Oro shoreline were stable; however in the short-
term, this area eroded rapidly, and included the maximum 
short-term erosion rate of -3.4 m/yr.

Santa Barbara North

The Santa Barbara North region extends for 186 km from 
Point San Luis in the north to El Capitan State Beach in 
the south (Figures 14B and 33).  The division between the 
Santa Barbara North and South regions is the transition 
from UTM Zone 10 (northwest) to UTM Zone 11 (southeast), 
and was necessitated by our analysis techniques.  The Santa 
Barbara North region contains the Santa Maria River and 
Santa Ynez River littoral cells along with the northern 
half of the Santa Barbara cell (Figure 14B).  Much of the 
coast is rugged and remote, and not highly developed.  An 
excep_tion is the area extending from Avila Beach to Pismo 
State Beach where some seawalls and riprap have been 
emplaced to protect coastal roads and buildings from cliff 
erosion.  In addition there is a small harbor and 
breakwater at Port San Luis. The coast is predominantly 
cliffed with small pockets beaches or narrow linear 
beaches.  However, linear stretches of wide beaches are 
present from Pismo State Beach south through the expansive 
beach and dune systems at Oceano and Guadalupe Dunes 
(Figure 34) and within Vandenberg Air Force Base, which 
occupies more than 60 km of coast_line in the region.  
There are no known beach nourishment projects in this 
region (Clayton, 1991; Wiegel, 1994).

Ninety-nine point two kilometers of shoreline were measured 
in this region and the long-term net shoreline change rate 
was found to be undetectable at the significant figures 
appropriate for this analysis and is reported as 0.0 m/yr 
in Table 6B.  Long-term erosion was measured along 56% of 
the coast and the average long-term rate was -0.2 m/yr 
(Table 6B).  Long-term accretion rates averaged 0.2 m/yr.

The short-term net average shoreline change rate was -0.6 
m/yr, , as averaged over 113.3 km of coastline.  The short-
term average accretion rate of 0.9 m/yr was the highest in 
Central California and occurred along 20% of the coast.  
The short-term average erosion rate of -1.0 m/yr, was the 
same as the rate observed in the Morro Bay region.  

The long-term and short-term shoreline change rates were 
significantly different.  The net average shoreline change 
shifted to a more erosional trend from the long-term (0.0 
m/yr) to the short-term (-0.6 m/yr).  There were distinct 
changes in the patterns and magnitudes of shoreline change 
from north of Point Arguello to the southern limit of this 
region.  To the north, the magnitudes of change, especially 
in the short-term, were highly variable and oscillated from 
erosion to accretion (Figure 33).  North of Point Sal, 
long-term accretion shifted to high rates of short-term 
erosion, with rates increasing dramatically from north to 
south.  The highly (spatially) variable change rates also 
occurred in the central portion of this region between 
Point Sal and Point Arguello. South of Point Arguello, the 
coastline was stable during the long-term period, however, 
the short-term trend is strongly erosional along this 
undeveloped coast.  In the northern part of this region, 
short-term erosion rates were high along the central part 
of Pismo State Beach and exceeded  -2.0 m/yr in some areas.  
In general, along the Pismo State Beach coast the long-term 
trend was stable with the exception of the southern segment 
where long-term change went from dominantly accretion to 
the most rapid erosion in this section, which was at 
Guadalupe Dunes (Figure 33; Table 9B).  This dominant trend 
of erosion, just south of the Santa Maria River, is likely 
related to flood control projects on the Santa Maria River. 
The highest short-term erosion rates (-6.7 m/yr) were the 
highest in the state for a non-nourished system.  The 
highest accretion rates both in the long- and short-term 
were within Vanden_berg Air Force Base, approximately 10 km 
north of Puri_sima Point.

Southern California

The Southern California section extends from El Capitan 
State Beach north of Santa Barbara to the Mexico border 
(Figure 1), approximately 420 km of coastline. The 
shoreline change data for this section of the California 
coast is divided into five regions: Santa Barbara South, 
Santa Monica, San Pedro, Oceanside and San Diego (Figure 
14C).  

This section of coastline has the longest stretches of 
continuous, linear beaches in the state, although there are 
many areas where the beaches are narrow and are backed by 
coastal cliffs or bluffs.  This is also the most engineered 
coastline in the state, consisting of numerous harbors, 
ports, breakwaters, jetties and groins.   There are only a 
few small data gaps for Southern California: in the Point 
Fermin area, and in the San Clemente - Laguna Beach region. 
Both of these gaps are due to lack of 1800s-era t-sheets. 

A total of 280.7 km of coastline was included in our long-
term Southern California analysis, whereas the short-term 
analysis covered 315.0 km of coast.  The net long-term 
shoreline change rate for the section was accretional, with 
an average rate of 0.3 m/yr and the net average short-term 
rate was -0.1 m/yr.

Santa Barbara South Region

The Santa Barbara South region begins within the Santa 
Barbara littoral cell, at El Capitan Beach State Park, 
approximately 15 km north of Goleta Point and the 
Uni_versity of California Santa Barbara campus (Figures 14C 
and 35).  This region includes the beach communities of 
Santa Barbara, Ventura and Oxnard among others.  With the 
exception of the coast north of Santa Barbara, this is a 
highly developed to urbanized coastline and numer_ous 
engineering structures and nourishment projects have 
greatly altered the natural patterns of shoreline change. 
The beaches along this stretch of coast are narrow, and 
undergo large seasonal fluctuations in beach volume 
(Norris, 1964; Thompson, 1987; Flick, 1993).

Long-term shoreline change trends were measured along 84.6 
km of the Santa Barbara South region.  The net average 
long-term shoreline change rate was 0.1 m/yr (Table 6C), 
and of the measured coast, 44% accreted and 56% eroded.  
The average long-term accretion rate was higher than the 
erosion rate, 0.5 m/yr versus -0.2 m/yr. The maximum long-
term accretion rate (2.0 m/yr) was located at West Beach, 
Santa Barbara, immediately adjacent to the harbor 
breakwater.

Between the 1970s and 1990s the net average shore_line 
change rate was -0.5 m/yr, measured along 88.0 km of the 
coast.  The short-term erosion rate, which averaged -1.2 
m/yr, occurred along 72% of the coast.  The short-term 
average accretion rate, 1.1 m/yr, was the highest in 
South_ern California, and was observed along 28% percent of 
the region.

North of Santa Barbara, most of the coastline had little 
measurable change in the long-term (Figure 35).  In the 
short-term, however, the area at and just north of Isla 
Vista experienced high short-term erosion rates, exceeding 
-2.0 m/yr. In Santa Barbara, shoreline change was strongly 
influ_enced by the breakwater construction and subsequent 
exten_sive sand-bypassing (Figure 36) at Santa Barbara 
Harbor (Clayton, 1991; Wiegel, 1994). Relatively high long-
term erosion south of Santa Barbara at Sandyland and 
Carpinte_ria beaches (-0.2 to -0.4 m/yr) changed to a 
strong trend of accretion in the short-term (Figure 35).  
Recent anecdotal evidence suggests this area is currently 
undergoing rapid erosion; the short-term accretion likely 
was an artifact of disrupted or reversed transport 
directions during the 1997-98 El Nio. This analysis only 
utilizes data through 1998, and shoreline change trends may 
have become more erosional since then.  

South of Rincon Point, there is an increase in the spatial 
density of harbors, marinas and ports, such as at Ventura, 
Channel Islands and Port Hueneme.  These structures 
substantially affect the shoreline change rates.  
Emplacement of groin fields along Buenaventura Beach in the 
1960s produced a long-term accretion rate of 2.0 m/yr; 
however, the wide beaches that developed on the north side 
of the groins eroded rapidly from the 1970s to the 1990s, 
when erosion rates exceeded -2.0 m/yr.  The highest erosion 
rates in both the long-term (-0.7 m/yr) and short-term (-
5.5 m/yr) were located at Ormond Beach, approximately 6 km 
south of Port Hueneme Harbor.  The maximum short-term 
accretion rate of 6.0 m/yr was measured at South Beach in 
Ventura (Table 9C). Overall, the net shoreline change rate 
changed from slightly accretional to strongly erosional 
from the long-term to the short-term.

Santa Monica Region  

The Santa Monica region is approximately 85 km long and 
extends from Point Dume to Point Vincente (Palos Verdes) 
(Figures 14C and 37).  This region is within the Santa 
Monica littoral cell and the Point Dume subcell (Inman and 
Frautschy, 1966). The coastline, which is exten_sively 
developed, includes the well-known beach communi_ties of 
Los Angeles County (including Malibu, Manhattan Beach, 
Redondo Beach and Santa Monica).  The coast has been highly 
engineered, including beach nourishment projects, shoreline 
armoring, construction of jetties, groin fields and 
offshore breakwaters (California Dept. of Naviga_tion and 
Ocean Development, 1977; Clayton, 1991; Flick, 1993; 
Wiegel, 1994). Prior to the 1920s, the beaches within Santa 
Monica Bay were relatively narrow.  The first beach 
nourishment began in 1938 and continued into the 1990s, 
although the volumes decreased substantially in the more 
recent time period (Clayton, 1991; Flick, 1993; Leidersdorf 
and others, 1994).

The net average long-term shoreline change rate, measured 
along 66.0 km of coast, was 0.4 m/yr. The aver_age long-
term erosion rate was -0.1 m/yr (Table 6C) and occurred 
along 31% of the coast.  The average long-term accretion 
rate was 0.7 m/yr.  

During the more recent time period, the net short-term 
shoreline change rate, averaged over 75.2 km of coast, was 
-0.1 m/yr.  Where the short-term rate was erosional, the 
average rate was -0.5 m/yr; this occurred along 60% of the 
beaches. The average accretion rate, 0.9 m/yr, occurred 
along 40% of the beach.

The highest short-term erosion rates (-2.2m/yr) in the 
Santa Monica region were observed at Trancas Beach north of 
Point Dume, within the Dume subcell.  Additionally the 
highest short-term accretion rates (4.0 m/yr) were also 
mea_sured in the northern portion of the region, at 
Amarillo State Beach north of Malibu Point (Figure 37; 
Table 9C).

The average erosion rate in this region increased five-fold 
from the long-term to the short-term (Table 6C).  Accretion 
rates remained nearly consistent from one time period to 
the next.  Widespread accretion was related to the 
construction of coastal facilities. According to Flick 
(1993) an average of 800,000 m3/yr of sand was placed on 
Santa Monica beaches between the 1940s and the 1960s.  This 
material was primarily from two projects, construction of 
the Hyperion sewage facility and dredging of Marina del 
Rey.

In the long-term, much of the northern Santa Monica 
littoral cell was stable with little or no measurable 
change (Figure 37).  The short-term trends along the 
northern portion of the littoral cell are more variable.  
Beginning at the interior of Santa Monica Bay, where groin 
fields exist along Santa Monica State Beach, the long-term 
change trend became predominantly accretional to Hermosa 
Beach (Figure 37).  According to Coastal Frontiers (1992), 
as of the early 1990s, this approximately 32-km section of 
coast had 5 breakwaters, 3 jetties, 19 groins, 5 revetments 
and 6 piers (Figure 38).

The short-term trend showed primarily erosion throughout 
the northern half of the region except north and south of 
Malibu.  From the interior beaches of Santa Monica Bay to 
the southern end of the region, the short-term change 
trend, while highly variable, shifts to erosional (Figure 
38).From the 1970s to the 1990s, the 2.5 km stretch of 
beach at Dockweiler State Beach eroded at a maximum rates 
of over 1.9 m/yr (Figure 37), despite the extensive groin 
fields and nourishment projects.  The long-term change at 
Dockwei_ler State Beach was accretional, due primarily to 
massive nourishment projects.  The distinct shift to 
erosion began sometime after 1970, when artificial material 
was no longer placed on these beaches (Flick, 1993; Wiegel, 
1994).  

San Pedro Region

This region includes both the San Pedro littoral cell and 
the Laguna subcells to the south (Figure 9). The small 
(~14 km long) Palos Verdes subcell to the north of Point 
Fermin was not covered by this report because the coastline 
here is rocky with occasional narrow pocket beaches, and 
thus has little sandy shoreline. The San Pedro region 
extends approximately 67 km from Point Fermin to Dana Point 
(Figures 14C and 39). The massive Los Angeles Harbor 
complex and breakwater west of Long Beach (Figure 40) 
occupy the northern 14 km of the region.  The communities 
of Long Beach, Huntington Beach and Newport Beach (Fig_ure 
14C) are all located within the San Pedro region. The 
Laguna littoral subcells begin at Newport Bay and extend 
south approximately 22 km to Dana Point.  Due to a data gap 
in the 1800s-era t-sheets we were not able to calculate 
long-term shoreline change rates along a large potion of 
the southern half of this region, although we do have more 
data for the short-term analysis.

Net long-term shoreline change rates in the San Pedro 
region averaged 0.5 m/yr.  The average long-term erosion 
rate, which was -0.3 m/yr, was the highest in Southern 
California.  However, long-term erosion was observed along 
only 12% of the 30.3 km of shoreline analyzed.  The 
aver_age rate of long-term accretion was 0.6 m/yr (Table 
6C). 

The net short-term change rate, averaged along 46.3 km of 
coastline, is 0.5 m/yr, the highest rate in of all 
Cali_fornia regions, and the only net accretional short-
term trend in Southern California.  For the short-term 
period, erosion in the San Pedro region was observed along 
35% of the coast and averaged -0.5 m/yr.  The average 
accretion rate was 
1.0 m/yr.  

Beach nourishment and coastal construction projects greatly 
influenced the shoreline change patterns within the San 
Pedro region (Herron, 1987; Clayton, 1991; Flick, 1993; 
Wiegel, 1994).  There was a dominantly accretional trend 
throughout the northern half of the San Pedro region 
(Figure 39) . The accretion is a result of ongoing 
nourish_ment programs that were designed to counteract a 
loss in natural sediment input from the Los Angeles, San 
Gabriel and Santa Ana Rivers where major flood control 
structures trap natural sediment (Clayton, 1991; Flick, 
1993; Wiegel, 1994). Accretion rates from Seal Beach to 
Huntington State Beach (Figure 39) were substantially 
higher in the short-term than the long-term.  Low rates of 
long-term erosion at Bolsa Chica State Beach make this the 
only section of coast in the San Pedro littoral cell to 
have measurable long-term erosion, with a maximum of -0.4 
m/yr.  The area of maxi_mum short-term erosion was on 
Newport Beach where the short-term rates reached -2.2 m/yr 
(Table 9C).  There were very few areas of measurable long-
term erosion through_out the southern portion of the San 
Pedro region, with the exception of a small stretch of 
beach south of Newport Bay Harbor where the long-term 
erosion rate was -2.4 m/yr. The pattern of short-term rates 
in the southern half of the San Pedro region indicated that 
this section of coast was stable (Figure 39).  

Oceanside Region	

The Oceanside region is within the Oceanside littoral cell, 
which is the second largest of the Southern California 
cells (Figure 9).  This region extends approximately 90 km 
from Dana Point to Point La Jolla in the south (Figures 14C 
and 41). The many beach communities in this region include 
Carlsbad, Solana Beach, Encinitas, San Clemente, Oceanside 
and Del Mar. Nearly 15 km of shoreline north of the 
Oceanside Harbor is within the Camp Pendelton Marine Corps 
Base.  Much of the shoreline consists of narrow beaches 
backed by cliffs and many of the beaches have been 
nourished (Flick, 1993).  According to the U.S. Army Corps 
of Engineers (1991), nearly 26 million m3 of sand were 
placed on beaches in the Oceanside littoral cell from 1954 
to 1988, and the earliest nourishment began in the late 
1920s on Doheny State Beach (Clayton, 1991).

The net long-term shoreline change rate for the Oceanside 
region, averaged over 78.0 km, was 0.2 m/yr.  Average long-
term erosion was -0.1 m/yr, and occurred along 31% of the 
coast.  Average long-term accretion was 0.3 m/yr, the 
lowest average long-term accretion rate of the Southern 
California regions (Table 6C). 

The net short-term average shoreline change rate for the 
Oceanside region was -0.1 m/yr and was assessed over 79.3 
km of coastline. The average short-term erosion rate, -0.6 
m/yr, occurred along 67% of the coast.  The aver_age short-
term accretion rate was 0.9 m/yr, and the highest short-
term accretion rate, 6.8 m/yr, was measured at Doheny State 
Beach (Table 9C), where sand-fill was placed north of the 
San Juan Creek jetty in 1964 (Price, 1966; Wiegel, 1994).  

There is a clear differentiation in shoreline change trends 
between the northern and southern parts of the Oceanside 
region.  Most of the beach north of Oceanside Harbor 
(Figure 41) was stable or accreting, except immedi_ately 
adjacent to the Harbor where the maximum long-term 
accretion rate of 1.9 m/yr was recorded. This accretion was 
related to the construction of the harbor jetties which, 
when completed in 1968, began to trap vast amounts of sand 
moving downcoast (Flick 1993).   The short-term change 
north of the harbor was predominantly accretion, except for 
the areas around San Onofre State Beach and the Santa 
Margarita River mouth.  South of the Oceanside Harbor, the 
shoreline was relatively stable in the long-term; however, 
the short-term trend was dominantly erosion, and erosion 
rates increased to the south.  The maximum short-term 
erosion rates, which were measured at Del Mar City Beach (-
3.5 m/yr), also were high at Torrey Pines Beach (-2.2 m/yr) 
(Figure 42) as well. According to Flick (1993), the north 
jetty at Oceanside Harbor either has trapped sand or 
deflected it offshore (or both), leading to an increasingly 
starved system in the southern part of the region.

San Diego Region

The San Diego region includes both the Mission Bay and 
Silver Strand littoral cells that together extend for 
approximately 45 km from Point La Jolla to the Mexico 
border (Figures 14C and 43).  The coastline in this region 
consists of rocky coast with small pocket beaches, low-
relief linear beaches, and narrow beaches backed by cliffs. 
The shoreline is highly engineered, with large coastal 
facili_ties such as the flood control jetties at Mission 
Bay and the 2300-m-long Zuniga Jetty at the entrance to San 
Diego Bay (Figure 44).  In addition, many beaches have been 
nour_ished, principally the result of coastal construction 
projects, beginning as early as the 1930s (Clayton, 1991). 
As a result of data gaps in the 1800s-era t-sheets in this 
area, our long-term analysis within the San Diego region is 
limited to the linear beaches of Pacific Beach and Mission 
Beach Parks in the northern half of the region.

Long-term shoreline change rates for the San Diego region 
were measured along 21.9 km of sandy shoreline. The net 
average long-term rate was 0.9 m/yr, the highest net change 
rate in the state. Average long-term erosion is 
-0.1 m/yr, and occurred along 21% (Table 6C) of the 
shore_line. The average long-term accretion rate was 1.2 
m/yr, the highest average long-term accretion rate in the 
state.

The net average short-term shoreline change rate, measured 
along 26.2 km of coastline, was -0.8 m/yr and occurred 
along 90% of the measured shoreline.  Both the net 
shoreline change and the percent of eroding beaches changed 
substantially from the long- to the short-term (Table 6C).  
This suggests that the region became increas_ingly unstable 
in the latter part of the 20th century.

Although the long-term shoreline change trend was 
accretional in the San Diego region, both the rate of 
erosion and the percentage of eroding coast increased 
significantly in the short-term period (Figure 43; Table 
6C).  Short-term erosion was measured over large stretches 
of coastline, such as along Mission Beach Park just north 
of the northern Mission Bay jetty, as well as along the 
southern portion of Silver Strand State Beach.  The highest 
short-term erosion rate (-3.6 m/yr) was observed at Mission 
Beach Park 
(Table 9C). Other than just north of the Mission Bay jetty, 
the Mission Bay littoral cell showed little long-term 
change. In the southern half of the San Diego region, there 
was rapid long-term accretion (3.3 m/yr) adjacent to Zuniga 
Point and breakwater (Figure 44) on Coronado Island.  The 
effect of this structure diminished to the south. The 
highest long-term accretion rates were directly related to 
the entrapment of sand against an along-shore barrier 
(USACE, 1986; Wiegel, 1994).  Short-term shoreline change 
in the southern half of the region shifted from accretion 
in the north (with the exception of immediately adjacent to 
the breakwater) to erosion in the south.  The highest 
erosion rates along this section of coast were over -2.0 
m/yr.

DISCUSSION AND FURTHER CONSIDERATIONS

Summary of Shoreline Changes

According to a recent study by the California Depart_ment 
of Boating and Waterways and the California State Coastal 
Conservancy (2002) the state of California has 1,860 km of 
open ocean coastline. Of this, 1,188 km has some type of 
fronting beach.  In many cases, especially in Northern and 
Central California, the beaches are narrow strips of sand 
fronting coastal cliffs or bluffs and may only be exposed 
during lower tides.  Shoreline change analyses were not 
conducted for the approximately 36% of the total length of 
the California coastline that is characterized as rocky.  
In this report, long-term rates of shoreline change are 
provided for 728.1 km of the total length of sandy shore, 
and short-term rates are provided for 807.1 km. Of the 
sandy shorelines, gaps in either the lidar data or T-sheets 
resulted in a lack of four shorelines along 27% of the 
coast characterized as beach.  Therefore, in this report we 
present long-term shoreline change rates for 40% of the 
total Cali_fornia coast and short-term rates for 44% of the 
total length of coastline.

Of the California shoreline where long-term rates of change 
were quantified 40% were eroding; the high_est regionally-
averaged long-term erosion rate, -0.2 m/yr, occurred in the 
Monterey Bay and San Francisco South regions.  This rate is 
high due to the artificially high ero_sion in the southern 
portion of the Monterey Bay caused by long-term sand mining 
operations (Griggs and others 2005; Thornton and others, 
2006).  Average long-term erosion rates for California were 
highest in the San Pedro region in Southern California (-
0.3 m/yr), the Monterey Bay region in Central California (-
0.6 m/yr) and the Klamath region in Northern California (-
0.4 m/yr). The San Francisco South region experienced 
erosion along the most coastline (76%).  One of the highest 
specific areas of long-term erosion in the state (-1.8 
m/yr) was on the north side of Point A_o Nuevo in the San 
Francisco South region (Table 9B) where a spit was breached 
in the late 1800s and large volumes of sand where mobilized 
and transported down coast.  In Southern California, the 
highest measured long-term erosion rate, -2.4 m/yr, was 
south of Newport Bay Harbor.  In Northern California, the 
maximum long-term erosion rate (-1.2 m/yr) was adjacent to 
the Klamath River mouth where a dynamic spit shifts 
spatially through time.

Overall the highest long-term accretion rates were 
associated with coastal engineering structures and beach 
nourishment sites (Southern and Central California) and 
where there is high sediment supply from large rivers 
(Northern California).  The highest rate of long-term 
accre_tion (4.8 m/yr) occurred 10 km south of the Klamath 
River mouth, and appeared to be a natural rate, likely 
associated with sediment influx from the soft bluff and 
gullies that are incised in the bluffs.

In general, there was a statewide increase in the percent 
of sandy shoreline that eroded from the long-term (40%) to 
the short-term (66%).  This trend implies that erosion 
hazards have increased in California, especially from the 
1950s-70s to the late 1990s.  This may be related to the 
climatic shift that began in the mid-1970s when 
California's climate entered a period of more frequent and 
stronger storms, including two of the most intense, and 
damaging El Ni_o winters of the last century. It must also 
be remembered that our analysis only extends up to 1998 (or 
2002 in some areas) and does not include trends that may 
have developed since.

Planned Updates and Related Research

The USGS plans to revise and report on rates of shoreline 
change for California every 5 to 10 years, and thus this 
report and associated data should be considered a work in 
progress. The revision interval will depend on new 
information and technological advances that will allow 
relatively rapid shoreline position acquisition, 
processing, and dissemination. Future revisions will also 
incorporate the results of ongoing shoreline research. For 
example, we plan to continue to refine the methodology that 
we applied to quantify the effects of using different 
shoreline proxies on the shoreline change rates.  We will 
also explore other approaches to reduce shoreline 
positioning uncertainty (spatial errors) and shoreline 
sampling uncertainty (temporal variability). GPS technology 
has greatly reduced positioning errors so that they are no 
longer a significant component of the uncertainty analysis. 
GPS and lidar also eliminate the need for digitization and 
introduction of associated position_ing errors. The 
dynamics of sandy beaches ensure that short-term shoreline 
fluctuations will not be eliminated entirely from future 
shoreline positions, but data being collected in various 
coastal regions as part of the USGS regional studies will 
provide quantitative assessments of seasonal and 
inter_annual changes in shoreline position. These 
assessments will provide a means to determine if the 
detected shoreline change is within the expected range of 
movement and allow us to further constrain the 
uncertainties.

Influence of Human Activities

As coastal communities continue to grow along the 
California Coast, potential conflicts may arise between 
preservation of property (typically privately owned) and 
conservation of the beach (typically publicly owned). Past 
social responses indicate that these conflicts most likely 
will be resolved through a combination of beach nourishment 
projects and shoreline protection structures. Both of these 
engineering responses to erosion alter the natural beach 
pro_cesses and eventually lead to artificial shoreline 
positions. 

Adding sand to eroding beaches is a common method to 
mitigate storm damage and to maintain a recreational beach. 
Beach nourishment alters the rates of retreat by causing 
rapid artificial accretion of the shoreline. In those areas 
where nourishment is frequent, the trends of shore_line 
change will be biased toward accretion or stability. 
Additionally, the proposed removal of dams in some of the 
watersheds in California may alter the shoreline change 
trends, as previously impounded sediment begins to make its 
way into the littoral system. Passive erosion of the beach 
by emplacement of seawalls or revetments may initially lead 
to an increase in the rate of erosion, but the rate will 
slow to zero if the beach erodes away in front of the 
structure.  Because many beaches are already altered by 
shoreline protection projects and more will be altered in 
the future, the methods of analyzing shoreline movement 
have to take shoreline stabilization activities into 
account so that the documented trends and derived rates of 
change can be expressed in their proper context.  

Distinguishing between natural rates of shoreline movement 
and those influenced directly by human activi_ties is 
crucial when historical rates of change are used for 
planning and to project future shoreline positions. 
Improved methods of analyzing shoreline movement will be 
needed to document the natural rates of shoreline change.

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Com_parative impacts of the 1982-83 and 1997-98 El Ni_o 
winters on the central California coast:  Journal of 
Coastal Research, v. 16, n. 4, p. 1022-1036.

Storlazzi,C.D. and Wingfield,D.K, 2005,  Spatial and 
tem_poral variations in oceanographic and meteorologic 
forc_ing along Central California:1980-2002:  U.S. 
Geological Survey Scientific Investigations Report 2005-
5085, 30 pp.

Taylor, J.R., 1997, An Introduction to Error Analysis: The 
Study of Uncertainties in Physical Measurement, Univer_sity 
Science Books, Sausalito, CA, 327 pp.

Thieler, E.R., and Danforth, W.W., 1994, Historical 
shore_line mapping (1). Improving techniques and reducing 
positioning errors: Journal of Coastal Research, v. 10, p. 
549-563.

Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and 
Miller, T.L., 2005, Digital Shoreline Analysis System 
(DSAS) version 3.0; An ArcGIS(c) extension for calculating 
shore_line change: U.S. Geological Survey Open-File Report 
2005-1304.

Thompson, Warren C., 1987, Seasonal orientation of 
Cali_fornia beaches: Shore and Beach, v. 55, n. 3/4, p. 67-
70.

Thornton, E.B., Sallenger, A.H., Conforto Sesto, J., Egley, 
L. A. , McGee, T., and. Parsons, A.R., 2006, Sand Mining 
Impacts on Long-Term Dune Erosion in Southern Mon_terey 
Bay, Marine Geology, v. 229, n. 1-2, p. 45-58.

U.S. Army Corps of Engineers, 1971, National Shoreline 
Study, California Regional Inventory, 106 pp.

U.S. Army Corps of Engineers, 1986, Southern California 
coastal processes data summary: Coast of California Storm 
and Tidal Wave Study, CCSTWS 86-1, 572 pp.

U.S. Army Corps of Engineers, 1991, State of the Coast 
Report, San Diego Region: Coast of California Storm and 
Tidal Wave Study, Los Angeles District.

U.S. Army Corps of Engineers, 2003, California costal 
sediment master plan, 905(b) reconnaissance report, Los 
Angeles District, 34 pp.

USGS/UCSC/NASA/NOAA Collaborative Research Group, 1998, A 
collaborative program to investigate the impacts of the 
1997-98 El Ni_o winter along the California coast:  Shore 
and Beach, v. 66, n. 3, p. 24-32.

Weber, K.M., List J.H., and Morgan, K.M., 2005, An 
opera_tional mean high water datum for determination of 
shore_line position from topographic lidar data: U.S. 
Geological Survey Open-File Report 2005-1027.

Wiegel, R.L., 1994, Ocean beach nourishment on the USA 
Pacific Coast: Shore and Beach, v. 62, n. 1, p. 11-36.

Wiegel, R.L., 2002, Large quantity of sand blown inland 
over top of seawall: Shore and Beach Observation, v. 70, n. 
2, p. 11-12.

Willis, C.M., 2002a, Impediments to fluvial delivery of 
sediment to the shoreline,  In M. Coyne and K. Sterrett 
(eds.), California Beach Restoration Study: California 
Department of Boating and Waterways and State Coastal 
Conservancy, Sacramento, California,  p. 130-177.  
Available on-line at: 
http://www.dbw.ca.gov/beachreport.asp

Willis, C.M., 2002b, Assessing natural and human 
altera_tions to coastal sediment supply in California and 
the impacts on regional beach sustainability, Ph.D. 
Disserta_tion, University of California Santa Cruz, Santa 
Cruz, CA, 142 pp.

Open-File Report 2006-1219   

Open-File Report 2006-1219   

Figure 1. Index map of California showing the fifteen 
regions discussed in the text.

Open-File Report 2006-1219   

Open-File Report 2006-1219   

Table 1. Providers and original sources of historical 
shorelines for each California region.

Section

Organization

Original Data Source

Spatial Coverage

Northern California

NOAA Coastal Services Center

NOAA T-sheets

Oregon Border to Tomales Point

U.S. Geological Survey

DRGs

NOAA Vectorization Project

NOAA T-sheets

Central California

NOAA Coastal Services Center

Scanned NOAA T-sheets

Tomales Point to El Capitan Beach

NOAA Vectorization Project

NOAA T-sheets

U.S. Geological Survey

DRGs

Tomales Point to Point Estero

Southern California

NOAA Coastal Services Center

Scanned NOAA T-sheets

El Capitan Beach to Mexico Border

NOAA Vectorization Project

NOAA T-sheets

Open-File Report 2006-1219   

Table 2. Dates of compiled shorelines in different regions 
for selected periods.

Region

Selected Periods 

1800s

1920s - 1930s

1950s - 1970s

month

post-1998

month

Klamath

1859-1870

1926-1929

1955-1964

June, July

2002

Sept.

Eureka

1854-1870

1929

1956-1968

June, July, Aug.

2002

Sept.

Navarro

1870-1874

1929-1935

1957-1968

n/a

2002

Oct.

Russian River

1862-188

1929-1930

1952-1971 

July, Nov.

2002

Oct.

San Francisco N

1853-1862

1929-1931

1952

July

1998

Apr.

San Francisco S

1853-1900

1929-1932

1946-1953

June, July, Aug. Oct.

1998

Apr.

Monterey Bay

1853-1910

1932-1933

1945-1952 

July, Aug.

1998

Apr.

Big Sur

1876-1891

1933-1934

1947-1976 

Mar., May, June

1998/2002 

Apr./Oct.

Morro Bay

1871-1887

1934

1947-1976 

Mar.

1998/2002 

Apr./Oct.

Santa Barbara. N

1869-1888

1933-1934

1976

Mar.

1998

Apr.

Santa Barbara S

1855-1871

1932-1934

1974-1976 

Feb., Mar., Oct.

1998

Apr.

Santa Monica

1857-1877

1933

1972-1974

Mar.

1998

Apr.

San Pedro

1859-1885

1920-1934

1971-1974 

Mar.

1998

Apr.

Oceanside

1886-1889

1933-1934

1972

Mar.

1998

Apr.

San Diego

1852-1889

1933

1972

Mar.

1998

Apr.

Open-File Report 2006-1219   

Figure 2. Example of a lidar profile from April 10, 1998 at 
Santa Cruz, California for (a) the entire cross-shore 
region and (b) an expanded view of the foreshore region. 
(a) Laser returns off of the water's surface are seen as 
green symbols seaward of x = 230 m. Blue symbols indicate 
data points within _ 0.5 m of the operational MHW datum. 
Red symbols indicate data points along the cliff face and 
top. (b) The asterisk marks the cross-shore position of the 
operational MHW shoreline on the foreshore. The horizontal 
error bar represents the 95% confidence interval about the 
estimate. After Stockdon and others (2002).

Open-File Report 2006-1219   

Table 3. List of tide gauge measurements used to calculate 
mean high water elevation.

Site Name

MHW above NAVD88 (m)

Average of MHW

Northern California

Crescent City, CA

1.80

1.81

Trinidad Bay, CA

1.76

Arena Cove, CA

1.52

Central California

Arena Cove, CA

1.52

1.46 

Point Reyes, CA

1.49

Monterey Harbor, CA

1.40

San Simeon, CA

1.43

Southern California

Port San Luis, CA

1.37

1.33

Santa Barbara, CA

1.35

Rincon Island, CA

1.34

Santa Monica, CA

1.35

Huntington Beach, CA

1.32

La Jolla, CA

1.28

Imperial Beach, CA

1.33

Figure 3. Examples of common conditions where transects are 
eliminated in the absence of four shoreline intersections.

Open-File Report 2006-1219  10

Table 4.  Absolute horizontal and vertical differences 
between high water and mean high water shorelines (modified 
from Morton and others, 2004).

Location

Survey Date                  HWL

Survey Date MHWL

Length of Shore    (km)

No. of Observations

Average Horizontal Offset      (m)

Average Vertical Offset      (m)

% MHWL with Seaward Offset

Data Source or Reference

Galveston Is., TX1

01-27-95

01-27-95

Point

1

18

0.6

100

Morton and Speed, 1998

North Padre Is., TX1

08-16-95

08-16-95

1.6

6

8

0.4

100

09-14-95

09-14-95

1.6

6

8

0.2

100

09-28-95

09-28-95

1.6

6

12

0.2

100

10-06-95

10-06-95

1.6

6

6

0.3

100

Duck, NC2

1994-19962

Point

111

40

2.0

100

Pajak and Leatherman, 2002

Klipsan, WA3

05-26-99

05-28-99

3.0

171

22

0.5

100

Ruggiero and others, 2003

09-21-99

09-24-99

3.0

171

52

0.8

100

Ocean Shores, WA3

05-26-99

05-28-99

4.0

200

23

1.0

100

07-27-99

07-22-99

4.0

200

8

0.2

100

05-06-01

05-07-01

4.0

200

30

1.0

100

Oysterville, WA3

09-21-99

09-10-99

3.5

201

49

0.9

100

Assateague Is., 

MD/ VA4

03-16-98, 03-17-98

04-03-98

58.6

1172

11

0.7

99

National Park Service (M. Duffy)

09-29-99,  10-28-99

10-01-99

60.0

1200

20

1.6

100

06-13-01,  06-14-01

06-05-01

52.4

1049

8

0.6

92

10-01-02

09-12-02

47.7 

953

22

1.4

98

Coastal Research and Engineering, Inc. (M. Byrnes)

05-06-02

05-06-02

47

470

18.8

1.2 - 1.3

100

Moore and others, 2006

1 Simultaneous measurement of HWL and MHWL at beach 
profiles coordinated with tide gauge measurements

2 Video camera projections of HWL for 111 days during a 
three-year period and MHWL from generalized beach profiles

3 Nearly simultaneous aerial photographs (HWL) and GPS 
surveys (MHWL) 

4 Nearly simultaneous GPS (HWL) and lidar surveys (MHWL)

Open-File Report 2006-1219  11

Table 5.  Maximum estimated measurement errors for 
California shorelines.

Measurement Errors (m)

Time Period*

1

2

3a

3b

4

Georeferencing (Eg)

4

4

4

4

--

Digitizing (Ed)

1

1

1

1

--

T-sheet survey/T-sheet, DRG position (Et)

10

10

3

15

--

Shoreline position uncertainty (Eo)

8.7

8.7

8.7

8.7

1.5

Total shoreline position error (Esp) (m)

13.9

13.9

10.1

17.8

1.5

Annualized short-term rate error (m/yr)

0.4

*Time periods: 1=1800s; 2=1920s-1930s; 3a=1970s; 3b=1950s; 
4=post-1997

Table 6A. Average shoreline change rates for Northern 
California

	No. of Transects	Average of Rates (m/yr)	Erosion Rate (m/yr)	% Erosion
	Accretion Rate (m/yr)	% Accretion
Analysis Region	LT	ST	LT	ST	LT	ST	LT	ST	LT	ST	LT	ST
Klamath	1430	1573	0.7+0.1	0.4+0.4	-0.4+0.1	-0.6+0.4	25	48	1.0+0.1
	1.3+0.4	75	52
Eureka	493	652	0.7+0.2	0.4+0.4	-0.2+0.3	-0.9+0.4	4	51	0.7+0.2
	1.8+0.4	96	49
Navarro	608	656	0.1+0.1	0.0+0.4	-0.1+0.1	-0.5+0.4	28	50	0.2+0.1
	0.6+0.4	72	50
Russian River	435	483	0.2+0.1	0.4+0.4	-0.2+0.1	-0.4+0.4	28	35
	0.3+0.1	0.8+0.4	72	65
No. California	2966	3364	0.5+0.1	0.3+0.4	-0.3+0.1	-0.6+0.4	23	47
	0.7+0.1	1.2+0.4	77	53

Note:  LT = long-term; ST = short-term

Table 6B. Average shoreline change rates for Central 
California

	No. of Transects	Average of Rates (m/yr)	Erosion Rate (m/yr)	% Erosion
	Accretion Rate (m/yr)	% Accretion
Analysis Region	LT	ST	LT	ST	LT	ST	LT	ST	LT	ST	LT	ST
San Francisco N	902	1039	0.1+0.1	-0.5+0.4	  -0.2+0.1	-0.7+0.4	46
	81	0.3+0.1	0.5+0.4	54	19
San Francisco S	1125	1150	-0.2+0.1	-0.5+0.4	-0.4+0.1	-0.7+0.4	76	81
	0.1+0.1	0.5+0.4	24	19
Monterey Bay	1013	1031	-0.2+0.1	-0.6+0.4	-0.6+0.1	-0.8+0.4	41	77
	0.4+0.1	0.3+0.4	59	23
Big Sur	512	533	0.0+0.1	-0.2+0.4	-0.1+0.1	-0.5+0.4	39	65	0.2+0.1
	0.4+0.4	61	35
Morro Bay	447	458	0.1+0.1	-0.7+0.4	-0.1+0.1	-1.0+0.4	35	80	0.3+0.1
	0.4+0.4	65	20
Santa Barbara N	1983	2267	0.0+0.1	-0.6+0.4	-0.2+0.1	-1.0+0.4	56	80
	0.2+0.1	0.9+0.4	44	20
Central California	5982	6478	0.0+0.1	-0.5+0.4	-0.3+0.1	-0.8+0.4	53	79
	0.2+0.1	0.6+0.4	47	21

Note:  LT = long-term; ST = short-term

Table 6C. Average shoreline change rates for Southern 
California

	No. of Transects	Average of Rates (m/yr)	Erosion Rate (m/yr)	% Erosion
	Accretion Rate (m/yr)	% Accretion
Analysis Region	LT	ST	LT	ST	LT	ST	LT	ST	LT	   ST	LT
	ST
Santa Barbara S	1692	1760	0.1+0.1	-0.5+0.4	-0.2+0.1	-1.2+0.4	56	72
	0.5+0.1	1.1+0.4	44	28
Santa Monica	1319	1504	0.4+0.1	-0.1+0.4	-0.1+0.1	-0.5+0.4	31	60
	0.7+0.1	0.9+0.4	69	40
San Pedro	605	925	0.5+0.1	0.5+0.4	-0.3+0.2	-0.5+0.4	12	35	0.6+0.1
	1.0+0.4	88	65
Oceanside	1561	1587	0.2+0.1	-0.1+0.4	-0.1+0.1	-0.6+0.4	31	67	0.3+0.1
	0.9+0.4	69	33
San Diego	437	524	0.9+0.1	-0.8+0.4	-0.1+0.1	-1.0+0.4	21	90	1.2+0.2
	0.5+0.4	79	10
So. California	5614	6300	0.3+0.1	-0.1+0.4	-0.2+0.1	-0.8+0.4	36	64
	0.6+0.1	0.9+0.4	64	35

Note:  LT = long-term; ST = short-term

Figure 4.  Major tectonic elements and geomorphic provinces 
of California (modified from California Geological Survey, 
2002a and CGS website: 
(http://www.consrv.ca.gov/cgs/information/publications
/teacher_features/faults.htm).

Figure 5.  Index map showing locations of place names 
discussed in Geologic History and Geomorphology section.

Figure 6.  Simplified geologic map of California (modified 
from California Geological Survey generalized geologic map 
available on-line at: 
http://www.consrv.ca.gov/cgs/rghm/rgm/index.htm).

Table 7.  Coastal cliff rock type along the California 
coast (from Runyan and Griggs, 2002).

Rock Type
Km of Coast
% of Cliffed Coast

Pliocene Marine

688

39%

Unconsolidated Quaternary

480

28%

Miocene, Oligocene, Tertiary and Cretaceous Marine

335

19%

Older Metamorphic & Sedimentary (Franciscan)

177

10%

Granitic

53

3%

Tertiary and Miocene Volcanic

18

1%

Figure 7.  General wave directions for central California 
based on offshore wave buoy data (modified from Storlazzi 
and Wing_field, 2005).

Figure 8.  Monthly mean sea level for selected tide gauges 
along the California coast.  Mean sea-level trends, based 
on the total sea level rise (SLR) for each site are: 
Crescent City - 0.48 mm/yr, San Francisco +2.13 mm/yr, Los 
Angeles +0.84 mm/yr, and San Diego +2.15 mm/yr.  Data are 
from the National Ocean Service.

Figure 9.  Map showing major littoral cell boundaries, 
coastal watersheds, and conceptual net longshore drift 
directions for the Cali_fornia coast, modified from Habel 
and Armstrong (1977), Griggs and others (2005b), and U.S. 
Army Corps of Engineers (2003).  

Table 8.  Estimated annual littoral drift rates and 
directions along the California Coast (after Griggs and 
others, 2005b).

Location

Annual Rate (m3)

Direction

Santa Cruz

230,000

East

Santa Barbara

230,000

East

Ventura

460,000-765,000

Southeast

Santa Monica

210,000

Southeast

Oceanside

270,000

South

Figure 10.  Average annual sand and gravel discharge from 
major rivers in California.

Figure 11.  Sketch of common coastal landforms of 
California.

Figure 12.  Beach profiles from Cowells Beach in Santa Cruz 
illustrating beach erosion over an El Ni_o winter and the 
subsequent recovery the following summer.  The dashed gray 
line is the MHW elevation.  From unpublished USGS data.

Figure 13.  Map showing the major coastal dune complexes of 
California (modified from Cooper, 1967).

Figure 14A. Index map showing the four analysis regions in 
Northern California and various locations as discussed in 
the text.

Figure 14B. Index map showing the six analysis regions in 
Central California and various locations as discussed in 
the text.

Figure 14C. Index map showing the five analysis regions in 
Southern California and various locations as discussed in 
the text.

Table 9A.  Maximum and minimum shoreline change rates: 
Northern California

Region

Long-term

(m/yr)

Location

Short-term

(m/yr)

Location

Klamath

Max. erosion

-1.2

Klamath River mouth, south side

-2.6

Big Lagoon Beach, 3.0 km north of Patrick's Point

Max. accretion

4.8

Gold Bluffs Beach, Prairie Creek 

Redwoods State Park

7.3

Gold Bluffs Beach, Prairie Creek 

Redwoods State Park

Eureka

Max. erosion

-0.4

Eel River mouth, south side

-2.7

North Spit Beach, 0.8 km north of Humboldt Bay jetty

Max. accretion

2.5

Little River mouth, south side

4.7

Little River mouth, south side


Navarro

Max. erosion

-0.6

DeHaven Creek Beach

-1.4

DeHaven Creek Beach

Max. accretion

0.7

Ten Mile Beach, 0.6 km south of the

Ten Mile River mouth

3.3

Ten Mile Beach, north side of 

Ten Mile River mouth

Russian River

Max. erosion

-0.7

Sonoma Coast State Beach, 1.3 km 

south of Russian River mouth

-1.6

Sonoma Coast State Beach, 1.5 km 

south of the Russian River mouth

Max. accretion

1.8

Dillon Beach

3.5

Dillon Beach

Figure 15.  Shoreline change rates for the Klamath region.  
The maximum long-term erosion rate was -1.2 m/yr on the 
south side of the Klamath River mouth, and the maximum 
short-term erosion rate of -2.6 m/yr was measured at Big 
Lagoon County Park Beach.

Figure 16.  Bluff erosion at Big Lagoon Beach after an El 
Ni_o storm in the winter of 1983 (photo: Gary Griggs, 
UCSC).

Figure 17.  Shoreline change rates for the Eureka region.  
The maximum long-term erosion rate was -0.4 m/yr on the 
south side of the Eel River mouth, and the maximum short-
term erosion rate of -2.7 m/yr was measured along North 
Spit Beach.

Figure 18.  Spit and jetty on north side of Humboldt Bay 
Harbor in photograph taken in June 1987. North is to the 
left in the photograph. (photo: Copyright (c) 2002-2005 
Kenneth & Gabrielle Adelman, California Coastal Records 
Project, www.californiacoastline.org)

Figure 19.  Shoreline change rates for the Navarro region.  
The maximum long-term erosion rate was -0.6 m/yr at DeHaven 
Creek Beach, and the maximum short-term erosion rate of 1.4 
m/yr was also measured at DeHaven Creek Beach.

Figure 20.  Photographs from 1972 (top) and 2002 (bottom) 
show the widening of the spit beach at the Ten Mile River 
mouth.  Also note the increased vegetation on the dunes. 
(photo: Copyright (c) 2002-2005 Kenneth &Gabrielle Adelman, 
California Coastal Records Project, 
www.californiacoastline.org).

Figure 21.  Shoreline change rates for the Russian River 
region.  The maximum long-term erosion rate was -0.7 m/yr 
on Sonoma Coast State Beach, and the maximum short-term 
erosion rate of -1.6 m/yr was also measured along a remote 
beach along Sonoma Coast State Beach.

Figure 22.  Many of the large rivers in Northern California 
have well-developed sandy spits such as this one extending 
across the mouth of the Russian River (photo: Copyright (c) 
2002-2005 Kenneth & Gabrielle Adelman, California Coastal 
Records Project, www.californiacoastline.org).

Figure 23.  Shoreline change rates for the San Francisco 
North region.  The maximum long-term erosion rate was -0.5 
m/yr on Limantour Beach east of Drakes Estero; the maximum 
short-term erosion rate of -3.1 m/yr was measured at Point 
Reyes Beach just north of Point Reyes.

Table 9B.  Maximum and minimum shoreline change rates: 
Central California

Region

Long-term

(m/yr)

Location

Short-term

(m/yr)

Location

San Francisco N

Max. erosion

-0.5

Limantour Beach, 2.5 km east of Drakes Estero

-3.1

Pt Reyes Beach, immed. north of Pt Reyes

Max. accretion

1.0

Pt Reyes Beach, 9 km north of Pt Reyes

0.9

Pt Reyes Beach, 12 km south of Tomales Pt.

San Francisco S

Max. erosion

-1.8

North side of Pt. A_o Nuevo

-2.6

North side of Pt. A_o Nuevo

Max. accretion

0.4

0.25 km south of Mussel Rock

2.2

Tunitas Beach

Monterey Bay

Max. erosion

-1.3

Indian Head Beach, Marina

-2.4

Seaside, 3 km north of  Laguna Del Ray

Max. accretion

1.2

Salinas River State Beach

1.8

Twin Lakes Beach, 0.3 km east of harbor

Big Sur

Max. erosion

-0.8

North end of Carmel River State Beach

-1.7

Carmel City Beach

Max. accretion

0.7

JP Burns Landslide, Big Sur Coast

2.4

Pfeiffer Beach

Morro Bay

Max. erosion

-0.6

South of Ragged Pt. - narrow pocket beach

-3.4

Montana De Oro State Park

Max. accretion

1.5

Immed. north of Morro Rock

1.2

Morro Bay, 800 m south of breakwater

Santa Barbara N

Max. erosion

-1.1

Guadalupe Dunes, SLO Co.

-6.7

Guadalupe Dunes, SLO Co.

Max. accretion

1.1

Vandenberg Air Force Base

4.7

Vandenberg Air Force Base

Figure 24.  Houses on the spit at Stinson Beach are 
partially buried by sand during an El Ni_o winter storm in 
1983 (photo: Gary Griggs, UCSC).

Figure 25.  Shoreline change rates for the San Francisco 
South region.  The maximum long-term erosion rate was -1.8 
m/yr on the north side of Point A_o Nuevo; the maximum 
short-term erosion rate of -2.6 m/yr was also measured on 
the north side of Point A_o Nuevo.

Figure 26.  A riprap revetment protects an apartment 
building that overlooks a narrow beach near Pillar Point 
Harbor in a photograph taken in February, 2002.  Note that 
the beach (back_ground) with no revetment is much wider 
(photo: Gary Griggs, UCSC).

Figure 27.  Shoreline change rates for the Monterey Bay 
region.  The maximum long-term ero_sion rate was -1.3 m/yr 
on Indian Head Beach near Marina.  The maximum short-term 
erosion rate of -2.4 m/yr was measured near Seaside.

Figure 28.  Aerial photographs of the Santa Cruz Yacht 
Harbor show the impoundment of sand against the constructed 
jetties.  The top photo is from 1963, one year after the 
jetties were constructed.  The bottom photo is from 1987, 
and shows a now wide, sandy beach (Seabright Beach) on the 
upcoast side of the jetty (photos: Santa Cruz Harbor 
Master's Office).

Figure 29.  Shoreline change rates for the Big Sur region.  
The maximum long-term erosion rate was -0.8 m/yr on the 
north end of Carmel River State Beach.  The maximum short-
term erosion rate of -1.7 m/yr was measured at Carmel City 
Beach.

Figure 30.  JP Burns waterfall shows the beach that formed 
as a result of the sediment added to the system from the 
1983 landslide.  a) photo taken July 10, 1963 shows 
waterfall pouring directly into the ocean (from photo 
archives, Caltrans),  b) photo taken June 10, 2003 shows 
water now pouring on to a beach (photo: Cheryl Hapke, 
USGS).

Figure 31.  Shoreline change rates for the Morro Bay 
region.  The maximum long-term erosion rate was -0.6 m/yr 
along a narrow pocket beach south of Ragged Point.  The 
maximum short-term ero_sion rate of -3.4 m/yr was measured 
at Montana De Oro State Park.

Figure 32.  Development of a tombolo at Morro Rock after a 
causeway was built in the 1930s.  Top photo was taken in 
1936 just after the completion of the causeway.  The 
postcard (lower image) is from the 1950s and shows a sandy 
tombolo leading out to Morro Rock (photos: http://morro-
bay.com/morro-rock/).

Figure 33.  Shoreline change rates for the Santa Barbara 
North region.  The maximum long-term ero_sion rate was -1.1 
m/yr at Guadalupe Dunes; the maximum short-term erosion 
rate of    -6.7 m/yr was also measured at Guadalupe Dunes, 
and was the highest short-term rate measured in the state.

Figure 34.  Photographs from January 1989 shows the well-
developed dune field at Guadalupe Dunes; the beach in this 
area has the highest short-term erosion rates in the State 
(photo: Copyright (c) 2002-2005 Kenneth & Gabrielle 
Adelman, California Coastal Records Project, 
www.californiacoastline.org).

Figure 35.  Shoreline change rates for the Santa Barbara 
South region.  The analysis begins at El Capitan Beach 
State Park in the north, and extends 110 km southeast to 
Point Magu.  The maximum long-term ero_sion rate was -0.7 
m/yr at Ormond Beach and the maximum short-term erosion 
rates was -5.5 m/yr, also at Ormond Beach.

Figure 36.  Dredging of spit at Santa Barbara Harbor. 
Dredged material is placed down-drift of the harbor where 
it replenishes East Beach, which accreted more than 6.0 
m/yr from the 1970s to 1990s.  (photo: Copyright (c) 2002-
2005 Kenneth & Gabrielle Adelman, California Coastal 
Records Project, www.californiacoastline.org)

Table 9C.  Maximum and minimum shoreline change rates: 
Southern California

Region

Long-term

(m/yr)

Location

Short-term

(m/yr)

Location

Santa Barbara S

Max. erosion

-0.7

Ormond Beach, 6 km south of Port 

Hueneme Harbor

-5.5

Ormond Beach, 1.7 km south of Port 

Hueneme Harbor

Max. accretion

2.0

West Beach, Santa Barbara, 

north of harbor 

6.0

Ventura South Beach, at Santa Clara 

River flood control channel

Santa Monica

Max. erosion

-0.3

Leo Carillo State Beach

-2.2

Trancas Beach, 6 km north of Pt Dume

Max. accretion

0.3

Trancas Beach, 4.5 km north of Pt Dume

4.0

Amarillo State Beach, 2 km north of Malibu Pt

San Pedro

Max. erosion

-2.4

1.5 km south of Newport Bay Harbor

-2.2

Newport Beach

Max. accretion

2.0

Huntington State Beach, north of jetty

2.8

Huntington State Beach, 0.6 km north of jetty 

Oceanside

Max. erosion

-0.3

Cardiff State Beach

-3.5

Del Mar Beach

Max. accretion

1.9

Oceanside Harbor (north side)

6.8

Doheny State Beach, south of Dana 

Point Harbor

San Diego

Max. erosion

0.0

---

-3.6

Mission Beach Park, north of jetty

Max. accretion

3.3

Silver Strand State Beach

1.6

Silver Strand State Beach

Figure 37.  Shoreline change rates for the Santa Monica 
region.  The analysis begins within the Dume subcell to the 
north near Solromar and extends to Vincente Point.  The 
maximum long-term erosion rate was -0.3 m/yr at Leo Carillo 
State Beach and the maximum short-term erosion was -2.2 
m/yr at Trancas Beach.

Figure 38.  Oblique aerial photograph of a breakwater along 
the highly engineered Santa Monica coastline (Copyright (c) 
2002-2005 Kenneth & Gabrielle Adelman, California Coastal 
Records Project, www.californiacoastline.org).

Figure 39.  Shoreline change rates for the San Pedro 
region. The analysis extends from Los Angeles Harbor to 
Dana Point. The maximum long-term erosion rate was -2.4 
m/yr south of Newport Bay Harbor and the maximum short-term 
erosion was -2.2 m/yr at Newport Beach.

Figure 40.  Oblique aerial photograph of the Los Angeles 
Harbor (photo: Cheryl Hapke, USGS).

Figure 41.  Shoreline change rates for the Oceanside 
region.  The analysis extends from Dana Point to Point La 
Jolla. The maximum long-term erosion rate was -0.3 m/yr at 
Cardiff State Beach and the maximum short-term erosion rate 
was -3.5 m/yr at Del Mar Beach.

Figure 42.  Narrow beach fronting tall coastal bluffs at 
Torrey Pines City Beach.  The short-term beach erosion 
rates are high in this area (photo: Gary Griggs, UCSC).

Figure 43.  Shoreline change rates for the San Diego 
region.  The analysis extends from Dana Point to the Mexico 
border. There is no measurable long-term erosion rate in 
this region; the maximum short-term rate was -3.6 m/y at 
Mission Beach Park.

Figure 44.   Oblique aerial photograph of Zuniga Point and 
breakwater at the entrance to the San Diego Harbor (photo: 
Cheryl Hapke, USGS).

(Alternative text)

Logo:  USGS, science for a changing world

Cover photo taken from an aircraft flying low just offshore 
looking back at the coastline.  Surf in the foreground with 
a stream flowing under a small highway bridge in the 
background 

Cover background photo looking up a long stream valley from 
offshore

Figure 1. Outline of the state of California with small 
lines dividing the state coast into fifteen sections 
numbered 1 through 15 going from Oregon to Mexico

Figure 2. Two XY plots of a profile of lidar data showing 
elevation in meters versus cross-shore distance in meters.  
In the upper plot dots in profile are colored green where 
the laser returns are off of the water's surface, blue 
where laser returns are off the beach near the elevation of 
MHW, and red along the cliff face and top. In the lower 
plot, a small green star and a red line at 0.5 m elevation 
indicate where the shoreline is. 

Figure 3.  Yellow dots mark where vertical yellow lines 
intersect colored shorelines. 

Equation 1:  The horizontal offset between the HWL and MHW 
shorelines is equal to the tide level plus 1.1 times 0.35 
times the tangent of the beach slope times the square root 
of the deepwater significant wave height times the 
deepwater wave length plus the square root of the deepwater 
significant wave height times the deepwater wave length 
times 0.563 times the tangent of the square of the beach 
slope, all minus the elevation of mean high water, and the 
whole value divided by the tangent of the beach slope.

Equation 2: The shoreline position error is equal to the 
square root of the sum of the squares of the georeferencing 
error, the digitizing error, the t-sheets survey error and 
the absolute position error.

Equation 3: The annualized error is equal to the square 
root of the sum of the squares of the shoreline position 
error from time one plus the shoreline position error from 
time two, all divided by time.

Equation 4: The Uncertainty is the square root of the sum 
of the squares of the linear regression 90% confidence 
interval, all divided by the number of transects, all plus 
the sum of the proxy-datum bias uncertainty divided by the 
number of transects.

Figure 4.  A colored picture of the state of California 
with squiggly white, purple and red lines.

Figure 5. An outline of California with small lines and 
text.

Figure 6.  A colorful picture of California with areas of 
yellow, green, orange and blue representing the geology.  

Figure 7.  Colored semi-circles with tangential arrows 
point toward an outline of the Monterey Bay.

Figure 8.  Four XY plots of squiggly lines showing sea-
level rise in centimeters versus year. 

Figure 9.  An outline of the state of California with tan 
areas near coast showing coastal watersheds and purple 
boxes offshore showing littoral cells.

Figure 10.  A bar graph of rivers in California where the 
length of the bars show the amount of sand and gravel 
discharge in cubic meters per year.

Figure 11.  A  drawing of a section of coast with green 
hills dissected by rivers that flow into a blue ocean to 
represent different landforms.

Figure 12.  An XY plot of elevation in meters versus 
distance in meters. Colored lines in the plot show the 
profile of the beach as it eroded during an El Nino winter.

Figure 13.  An outline of California surrounded by boxes 
containing outlines of smaller sections of the California 
coast. Small areas along the coast colored yellow show 
where coastal dunes are located.

Figure 14A. Outline of Northern California with lists of 
numbered text of locations and numbers along the coast 
showing the locations of specific areas.

Figure 14B. Outline of Central California with lists of 
numbered text of locations and numbers along the coast 
showing the locations of specific areas.

Figure 14C. Outline of Southern California with lists of 
numbered text of locations and numbers along the coast 
showing the locations of specific areas.

Figure 15.  Squiggle plot: An XY plot showing shoreline 
change rate in meters per year versus distance along the 
shore in kilometers. Changes from zero to eight indicate 
accretion. Changes from zero to negative eight indicate 
erosion.  This plot is from the Oregon Border to Patrick's 
Point. 

Figure 16.  Photograph taken from the beach looking at a 
house on a cliff with piles of eroded material at the base 
of the cliff. 

Figure 17.  Squiggle plot from Little River State Beach to 
Cape Mendocino.

Figure 18.  Photograph taken from the air of a beach next 
to a man-made rock jetty.

Figure 19.  Squiggle plot from Cape Mendocino to Point 
Arena.

Figure 20A.  First of 2 photographs taken from the air of a 
beach next to a river. The beach is much wider in the lower 
photograph.

Figure 20B.  Second of 2 photographs taken from the air of 
a beach next to a river. The beach is much wider in the 
lower photograph.

Figure 21.  Squiggle plot from Point Arena to Tomales 
Point.

Figure 22.  Photograph taken from the air of a beach that 
almost blocks the mouth of a river flowing into the ocean.

Figure 23.  Squiggle plot from Tomales Point to Point 
Bonita.

Figure 24.  Photograph taken from the beach showing house 
buried in sand.

Figure 25.  Squiggle plot from the entrance to San 
Francisco Bay to Davenport.

Figure 26.  Photograph looking down the beach of a house on 
the beach surrounded by a rock wall.

Figure 27.  Squiggle plot from Wilder Ranch State Park to 
Laguna Del Rey.

Figure 28A.  One of two aerial photographs of a harbor 
taken 24 years apart showing changes to the beaches on 
either side of the harbor.

Figure 28B.  One of two aerial photographs of a harbor 
taken 24 years apart showing changes to the beaches on 
either side of the harbor.

Figure 29.  Squiggle plot from Point Pinos to Cape San 
Martin.

Figure 30.  Two photographs of a rocky clif with a 
waterfall. The waterfall in the top photo pours into the 
ocean and the same waterfall pours onto the beach in the 
lower photo.

Figure 31.  Squiggle plot from San Carporforo Creek Beach 
to Point Bachon.

Figure 32.  Two photographs of a large rock island near a 
wide sandy beach. A sliver of sand connects the island to 
the beach in the lower photograph.

Figure 33.  Squiggle plot from Point San Luis to El Capitan 
Beach State Park.

Figure 34.  Photograph taken from air of a large field of 
sand dunes next to the beach. 

Figure 35.  Squiggle plot from El Capitan Beach State Park 
to Point Magu.

Figure 36.  Photograph taken from air of the mouth of a 
harbor with a large sand body near the entrance.

Figure 37.  Squiggle plot from Solromar to Vincente Point.

Figure 38.  Photograph taken from air of a beach with a 
shore perpendicular manmade rock wall just offshore.

Figure 39.  Squiggle plot from Los Angeles harbor to Dana 
Point.

Figure 40.  Photograph taken from the air of a large 
harbor.

Figure 41.  Squiggle plot from Dana Point to Point La 
Jolla.

Figure 42.  Photograph taken from the air of a narrow beach 
in front of tall cliffs with buildings on top.

Figure 43.  Squiggle plot from Point La Jolla to the Mexico 
Border.

Figure 44.   Photograph taken from the air of a wide harbor 
mouth.