levee failures and social vulnerability in the sacramento_burton y cutter_2008

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Levee Failures and Social Vulnerability in theSacramento-San Joaquin Delta Area, California

Article in Natural Hazards Review · August 2008

Impact Factor: 1.14 · DOI: 10.1061/(ASCE)1527-6988(2008)9:3(136)

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Christopher G. Burton

Global Earthquake Model

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Susan Cutter

University of South Carolina

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Available from: Christopher G. Burton

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Levee Failures and Social Vulnerability in theSacramento-San Joaquin Delta Area, California

Christopher Burton1 and Susan L. Cutter2

Abstract: This paper examines the spatial variability in the social vulnerability of residents to potential levee failures in the Sacramento

Delta region. To determine the likely flood exposure, levees of concern to the U.S. Army Corps of Engineers and California’s Department

of Water Resources were mapped. The HAZUS-MH loss estimation software and 100-year protection standard were used to hypothetically

breach levees to determine a coarse approximation of the level and spatial extent of inundation. To assess the differential social conse-

quences of such an event, a social vulnerability index was computed at the census tract level for San Joaquin, Sacramento, and Yolo

counties following the vulnerability metrics developed by Cutter et al. in 2003. When integrated with the flood exposure data, there is a

clustering of high social vulnerability zones within high risk flood areas. While the spatial pattern is not uniform throughout the tricounty

area, these pockets of high vulnerability largely driven by social factors warrant management concern about the disproportionate impact

of catastrophic levee failures on these populations and the level of local, state, and federal preparedness to cope with such an event.

DOI: 10.1061/ ASCE1527-698820089:3136

CE Database subject headings: Levees; Failures; Social factors; California; Deltas.

Introduction

The 15 U.S. government national planning scenarios include only

two natural hazard events—an earthquake and a hurricane. No-

ticeably absent is a large-scale flood event—one either caused by

excessive runoff or some breach of a levee system such as oc-

curred in New Orleans during Hurricane Katrina. This is a curious

omission given that flooding accounted for 27% of the nation’s

property losses and 17% of the fatalities from natural hazards

from 1960–2005 Hazards and Vulnerability Research Institute

2007.

Planning for catastrophes is relatively new within emergencymanagement. A catastrophe is a very large event that surpasses

local and regional capabilities to adequately respond, and is often

described as a worst-case event Rubin 2007. The National Re-

sponse Plan NRP includes a catastrophic incident annex, but as

Hurricane Katrina in 2005 illustrated, most basic local and state

plans do not address catastrophic events Harrald 2007. In fact, a

June 2006 review on current emergency operations found that the

majority of the Nation’s emergency operations urban areas and

states were inadequate to manage catastrophic events Depart-

ment of Homeland Security DHS and Department of Transpor-

tation DOT 2006. This same report also noted that

“comprehensive national guidance on the potential consequences

associated with catastrophic risks and hazards should be devel-oped to drive risk management and operational planning DHS/ DOT 2006, xi.” According to the same report, such guidanceneeds to address special needs populations, or those segments of the population that are most vulnerable. Catastrophic planning forflood events requires thinking about worst cases, such as damfailures or levee failures in major metropolitan areas, not just500-year rainfall-induced events.

The recent report on flooding in the Central Valley found thatthe current flood control system in the region was incapable of handling the threat of severe flood, thus, exposing urban areas to

considerable risk Independent Review Panel 2007. In fact, Sac-ramento may be the nation’s most vulnerable urban area to cata-strophic flooding. This paper illustrates the disproportionateexposure and impacts on communities from a levee failure or aprogression of failures, using California’s Sacramento-SanJoaquin Delta area as the case study. Given that there are rela-tively few county or subcounty studies assessing spatial trends inhazards vulnerability within the delta region, this paper is timely.It utilizes the existing methodological approach on social vulner-ability metrics Cutter et al. 2003 to assess the relative vulner-ability of residents in order to: 1 better understand the spatialrelationships between vulnerable populations and areas of highestrisk due to a levee breach scenario; and 2 examine the socialcharacteristics contributing to vulnerability and the resulting pat-

tern of uneven capacity for preparedness, response, recovery, andmitigation within the region.

Floodplain Development in the Delta

Since the dawn of sedentary agriculture, humans have been at-tracted to the rich soils of alluvial floodplains. Densely populatedurban centers evolved from smaller settlements along rivers andcoasts, which provided ready access to transportation and tradingopportunities. As the cities grew and the density of people andinfrastructure increased, the use of structural measures such as

1Ph.D. Candidate, Dept. of Geography, Univ. of South Carolina,

Columbia, SC 29208. E-mail: [email protected], Hazards and Vulnerability Research Institute and Carolina

Distinguished Professor, Dept. of Geography, Univ. of South Carolina,

Columbia, SC 29208. E-mail: [email protected]

Note. Discussion open until January 1, 2009. Separate discussions

must be submitted for individual papers. To extend the closing date by

one month, a written request must be filed with the ASCE Managing

Editor. The manuscript for this paper was submitted for review and pos-

sible publication on August 16, 2007; approved on February 21, 2008.

This paper is part of the Natural Hazards Review, Vol. 9, No. 3, August

1, 2008. ©ASCE, ISSN 1527-6988/2008/3-136–149/$25.00.

136 / NATURAL HAZARDS REVIEW © ASCE / AUGUST 2008

Downloaded 11 Jul 2009 to 76.126.183.32. Redistribution subject to ASCE license or copyright; see http://pubs.asce.org/copyright


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levees became an effective tool in controlling floods and reducingflood losses Kelly 1989. In the United States, there are approxi-mately 25,000 miles of levees, each constructed and maintainedby a myriad of agencies, organizations, local authorities, andlandowners FIFMTF 1992; Pielke 1999; Tobin 1995. The ArmyCorps of Engineers is responsible for the design, construction,and maintenance of more than 10,500 miles of the nation’s leveesystem. Certified Army Corps levees offer protection up to the100-year flood standard in over 1,000 floodplain communities.State, local, and privately owned levees make up the remaining

14,500 miles of the nation’s levee system. Many fail to meetofficial standards and provide inconsistent levels of protectionTobin 1995.

As the 2005 events in the Gulf Coast demonstrated, structuralefforts to contain and channel floodwaters can fail due to themagnitude of the flood event, lack of levee maintenance, poorinitial construction, or some combination of the above. Leveeeffectiveness can be compromised in many ways, all of whichincrease the hazard potential in communities. Among these are:1 hydrological factors such as flooding induced by the poorplacement of levees; 2 changing environmental conditions suchas deforestation or increased urbanization that can significantlyalter a river’s hydrological regime; 3 technological weaknessessuch as the use of materials found susceptible to seepage; and 4

social constraints that serve to increase the potential for lossTobin 1995. Communities with levees may be at greater risk than normal due to the “levee effect,” caused by a false sense of security where floodplain inhabitants perceive that all flood risk has been eliminated once a levee is constructed Tobin 1995. Thelevee effect increases vulnerability to flooding in two differentways Pielke 1999; State of California 2005. First, it creates asense of complacency, which in turn, reduces flood preparednessand mitigation actions. Second, the levee effect provides incen-tives to continue to build structures in harm’s way. The latter issignificant in California’s Central Valley, where tens of thousandsof homes are in low lying basins surrounded by an aging, ofteninsufficiently maintained, levee infrastructure Independent Re-view Panel 2007; State of California 2005.

Nearly 43% of Americans live in counties with levees Inter-agency Levee Policy Review Committee 2006, not only produc-ing a high potential for flood risk across the nation, but anincreasing public interest in levees and levee systems. The NewOrleans levee failures generated considerable mass media andpublic interest prompting many to ask where the next catastrophemay occur Perrow 2007. California’s Sacramento-San JoaquinDelta region is seen as a likely worst-case disaster scenario givenits concentration of levees and people, and multiple potentialmechanisms for failure e.g., earthquakes, excessive snowmeltcombined with heavy rainfall, poor maintenance Flynn 2007.

Delta Threat Revealed

The Sacramento-San Joaquin Delta once was a largely rural areaconsisting of approximately 738,000 acres of land within sixcounties. The region is protected by a network of 1,100 miles of levees USACE 2006a, and is critical to the national economy asit provides irrigation water to more than 7 million acres of thenation’s prime agricultural land and drinking water to 22 millionCalifornia residents. The delta region has a population base of more than 500,000 residing within cities and towns such as Isle-ton, Tracy, and Pittsburg and in adjoining areas such as Stockton,Sacramento, and West Sacramento Fig. 1.

Within the delta region there are 385 miles of project levees

incorporated into Sacramento and San Joaquin Federal FloodControl Projects USACE 2006a. The project levees are gener-ally located on the main stems of the Sacramento and San Joaquinrivers. The remaining 750 miles of levees within the delta gener-ally do not conform to federal project levee standards and, thus,are not certified nor maintained by the U.S. Army Corps of En-gineers. Instead, these levees are maintained by local reclamationdistricts, where it has become increasingly difficult to carry outadequate maintenance programs due to fiscal cuts, an aging infra-structure, and increased instability mainly caused by seepage and

erosion State of California 2005. In addition, subsidence adja-cent to levees and earthquake liquefaction are constant threats.

During the last century, there have been more than 140 docu-mented levee failures and island inundations in the delta. Themost recent failure occurred on the upper Jones Tract on June 3,2004 on a privately owned and maintained levee. The Jones Tractbreach occurred without warning and resulted in 12,000 acres of land inundated with 160,000 acre feet of water. While the causeof the failure remains unknown, the taxpayer’s burden exceeded$100 million State of California 2005.

Growth in the Delta: Increasing Vulnerability to Damage and Loss of Life

The growth machine in California is powerful, and the pressure tourbanize rapidly presents a major challenge to the delta area’sflood management system. In 1990, there were around 812,500people living behind levees in Sacramento, San Joaquin, and Yolocounties, and by 2005 this had increased by 28% to more than onemillion Independent Review Panel 2007. It is projected that in2020, nearly 1.3 million people in the tricounty area will livebehind levees. Using census data and information from the Inde-pendent Review Panel 2007, we estimate that in 2005, the popu-lation living behind levees represented 41% of the totalpopulation in Sacramento County, 59% of San Joaquin County’stotal population, and 47% of Yolo County’s population.

Cities within the delta have collectively grown by 18% since

2000, driven by a gap in median home prices between the SanFrancisco Bay Area and the Central Valley, which is now tens of thousands of dollars Eisenstein et al. 2006. From 2000 to 2005,nearly all Delta cities and towns grew by at least 10% Table 1,and during this 5-year period, population growth in some com-munities such as Brentwood and Elk Grove exceeded 50%.

Vulnerability as a Concept

Defining Vulnerability

Vulnerability science and research builds upon the multidisci-plinary tradition of hazards and disasters research Mileti 1999;

Wisner et al. 2004. Although a multitude of definitions exist,vulnerability is defined here as the potential for loss and involvesa combination of factors that determine the degree to which aperson’s life or livelihood is put at risk by a particular eventAdger 2006; Eakin and Luers 2006; National Research Council2006. Differences according to wealth, gender, race and class,history, and sociopolitical organization influence the patterns of disaster damages, mortality, and the ability of communities toreconstruct following a disaster. These factors also produce varia-tions in vulnerability among groups of people and between placesBankoff et al. 2004; Dow 1992; Downing 1991; Enarson 2007;Ngo 2001; Tierney 2006.

NATURAL HAZARDS REVIEW © ASCE / AUGUST 2008 / 137



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Theoretical and analytical approaches have been developedto address vulnerability to disaster impacts where the conceptsof exposure, resistance, and resilience are often starting pointsBruneau et al. 2003; Burton et al. 1993; Chakraborty et al. 2005;Chang and Shinozuka 2004; Cutter et al. 2006; Pelling 2003;

Turner et al. 2003. Exposure is a measure of risk that is directlyrelated to hazard proximity and the environmental characteristicsat a particular place. Resistance measures the ability of a popula-tion to protect itself from an environmental threat, for examplethe use of structural mitigation for floodplain development Burby1998. Finally, resilience addresses a population’s coping capacityand ability to recover following a disaster Folke 2006.

Vulnerability Paradox Revisited

Considerable research attention has focused on the components of biophysical vulnerability and the vulnerability of the built envi-

ronment, yet researchers know the least about the social aspects

contributing to vulnerability Birkmann 2006; Borden et al. 2007;

Heinz Center 2002. Components contributing to socially con-

structed vulnerabilities are largely ignored, mainly due to the fact

that social vulnerability is not a directly observable phenomenon

Enarson 2007 and because of difficulties that arise during quan-

tification Cutter et al. 2003. Therefore, social vulnerability is

most often described using a set of composite proxy indicators

that include age, race, health, income, and the quality of the built

environment. A number of studies have successfully quantified

vulnerability utilizing metrics specific to one particular place and

one unit of analysis Boruff et al. 2005; Chakraborty et al. 2005;

Cutter et al. 2000; Odeh 2002; Rashed and Weeks 2003; Wu et al.

2002. A broader comparative framework by Cutter et al. 2003

took this place-based approach a step further and they developed

a robust vulnerability metric to compare all U.S. counties. Their

Fig. 1. Sacramento-San Joaquin Delta region




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social vulnerability index SoVI integrates social inequalitiesfactors that influence the susceptibility to harm of variousgroups with place inequalities characteristics of communitiesand the built environment, such as economic vitality and levels of urbanization to provide a relative measure of social vulnerabilityfor the nation.

Contextual Models of Social Vulnerability

Considering the multitude of approaches to vulnerability research,it should not be surprising that conceptual models diverge in ex-plaining the root causes of vulnerability. Some causal models takeexposure as given in an effort to help researchers understand

differential access to resources or loss. Perhaps the most wellknown is the pressure and release model Wisner et al. 2004,which suggests that a progression of vulnerability connects haz-ard impacts to specific root causes political and economic sys-tems, and limited access to power, structures, and resources.Another example is the circle of vulnerability model Alexander2000. A second modeling framework explains causality using arisk/hazard approach, which assumes that vulnerability is a func-tion of proximity to the source of risk or hazard Davidson 1997;Davidson and Lambert 2001; Dilley et al. 2005; Federal Emer-gency Management Agency 1997.

A third approach is the systematic spatial integration of bio-physical and social components into a place-specific assessmentof vulnerability. While the antecedents to such an approach are

found much earlier Hewitt and Burton 1971, more recent work provides baseline spatial modeling by integrating both biophysi-cal and social perspectives into the vulnerability of place modelVPM Cutter et al. 2000. Other researchers have utilized asimilar approach either implicitly or explicitly where both naturalhazards risk and the social conditions within a hazardous area areidentified Clark et al. 1998; Odeh 2002; Polsky 2004; Rashedand Weeks 2003; Rygel et al. 2006; Wood and Good 2004; Wu etal. 2002. The merger between these distinct systems allows re-searchers to better understand how separate vulnerabilities usingeither single or multiple threats and social vulnerability indica-tors interact as they affect specific places.

Methods

This paper applies the VPM to assess the differential impacts inthe delta region. The Sacramento-San Joaquin Delta encompassesportions of six counties: Alameda, Contra Costa, Sacramento,San Joaquin, Solano, and Yolo. For this paper, we focused onSacramento, San Joaquin, and Yolo counties—the countiescontaining the Sacramento and San Joaquin rivers and their tribu-taries. Susceptibility to flooding in the tricounty area, shown inFig. 2, is based on FEMA’s Q3 flood zone delineations. Out of

the 2.1 million acres within the tricounty area, approximately43% are in designated flood zones. This includes nearly 672,325acres of land within the 100-year flood zone designation with anadditional 264,062 acres of land area within the 500-year zoneFig. 2.

Within the tricounty area, the physical and social analysis wasconducted at the census tract level of geography. An alternativeapproach would have been to utilize data at finer resolutions,specifically the block group, block, or parcel levels. However,important socioeconomic variables are often not available beyondthe census tract-level resolution, and the data are less reliable dueto techniques employed by the census bureau to maintain theconfidentiality of information. Variables utilized within the socialvulnerability index below were collected from the U.S. census,

and it is assumed that all population parameters are distributedequally throughout each tract.

Social Vulnerability Index

One of the most common approaches for performing vulnerabilityassessments is the use of a set of composite proxy indicators. Themethod we employed for modeling vulnerability was the socialvulnerability index, a robust comparative metric that uses 42 in-dependent socioeconomic, demographic, and built environmentvariables Cutter et al. 2003. Utilized as a tool for exploringbroad patterns among places, the SoVI is based on the empiricalresearch consensus about the major influences on social

vulnerability—age, gender, race, education, socioeconomic status,and the quality of the built environment. Significant also are spe-cial needs populations such as the infirmed, non-English speakingimmigrants, and the institutionalized. Due to a limited availabilityof socioeconomic variables, subcounty resolutions only included36 of the original 42 SoVI variables included in this analysisTable 2. The SoVI construction is a three-tiered process: 1input data standardization; 2 a factor analytic approach plusrotation; and 3 an additive modeling methodology. The endresult is a univariate score that broadly represents the relativelevels of social vulnerability within the delta region. All socioeco-nomic data were converted to percentages, per capita, or densityfunctions and following this initial preprocessing were standard-ized through conversion to “ z scores” with zero means and unit

variances. The z scores for each of the 36 variables were thenplaced into a factor analysis more specifically a principal com-ponents analysis to reduce the variables into a smaller set of components. The resulting factors or components are linear com-binations of correlated variables that represent a broader measureof how certain factors contribute to vulnerability. Manly 2005explains that the objective of a factor analysis is to take variablesand find combinations of these variables to produce componentsthat are uncorrelated in order of their importance, but merelydescribe the variation in the data. The lack of correlation betweencomponents indicates that the factor analysis is measuring differ-ent “dimensions” of the data. The principal components analysis

Table 1. Population Changes in Delta Communities

City 2000 2005 % change

Antioch 90,532 101,049 12

Brentwood 23,302 40,912 76

Dixon 16,103 17,179 7

Elk Grove 70,000 121,609 74

Fairfield 96,178 105,026 9

Galt 19,472 22,955 18

Isleton 828 820 −1

Lathrop 10,445 12,565 20Lodi 57,011 62,467 10

Manteca 49,255 61,927 26

Pittsburg 56,769 62,605 10

Rio Vista 4,571 6,837 50

Sacramento 407,018 452,959 11

Stockton 243,771 279,513 15

Suisun City 26,118 27,716 6

Tracy 56,929 78,307 38

Vacaville 88,642 96,735 9

West Sacramento 31,615 40,206 27

Note: Adapted from Eisenstein et al. 2006.




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allows us to explore these multivariate dimensions to see theiroverall contribution to the social vulnerability within the deltaregion. Our extraction methods used the Kaiser criterion eigen-values greater than 1 and a varimax rotation. The varimax rota-tion minimizes the number of variables that load high on a singlefactor, which increases the percentage of variation between eachfactor. The exact procedures for replicating the SoVI can be found

at http://www.cas.sc.edu/geog/hrl/sovi.html.Once the components were derived, slight adjustments to their

directionality were made with respect to their known influence onvulnerability. On a per component basis, this was accomplishedby selecting all factor scores +0.500 and −0.500. Utilizingthe selected scores and their corresponding variables only,each factor was then subjectively binned in accordance to theirvariable’s known influence on vulnerability. For example, a factorwith high positive loadings on percent populations aged 65and older and percent social security recipients would be catego-rized as an age indicator. A positive directionality was assigned toall factors known to increase vulnerability such as race and eth-

nicity, whereas a negative directionality was assigned to all fac-tors known to decrease vulnerability wealth. In the latter case,we multiplied the loading values by −1 to define the final dimen-sion since replacing a component with its inverse allows the finaldimension to subtract from the overall vulnerability index. Allfactors were then summed to yield a composite score. In the ab-sence of any theoretical justification for weighting each compo-

nent differently, they are equally weighted in the additive model.Overall index scores were mapped as standard deviations fromthe mean to allow for a visual representation of the spatial vari-ability in social vulnerability. Mapping vulnerability in this man-ner delineates the degree to which some places are morevulnerable than others, and highlights those geographic units thatare at the ends of the distribution e.g., high and low social vul-nerability. Note that the SoVI is not an absolute measure of vulnerability, but a comparative one, permitting us to visually ornumerically see how similar or how different places are relative toeach other.

There are a number of important caveats to the use of factor

Fig. 2. Study area with FEMA Q3 flood designations Note: 500-year flood designation also encompasses 100-year flood designation




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analysis. The output scores do not always capture the most im-portant or ideal factors, but rather those that best explain the

variation in input data Rogerson 2001. In this regard, the outputof the factor analysis is highly dependent on the input variables.We have addressed this through the selection of input variables,which were derived from the empirical research on posteventstudies of disaster impacts on people and their communities. Sec-ond, the determination of the directionality of the component is asubjective process, but one based on expert judgment. Again, wehave addressed this element as well using the empirical literatureon what constructs increase or decrease vulnerability, literaturethat is reviewed elsewhere Cutter et al. 2003; Heinz Center2002. Despite these caveats, the ability to replicate SoVI at dif-ferent scales of analysis and for different regions of the countries

with similar results in terms of components and explained vari-ance suggests it is a fairly robust algorithm Borden et al. 2007;Boruff et al. 2005; Cutter et al. 2006.

Defining Inundation Risk

To determine a likely flood exposure due to levee failure withinthe Sacramento-San Joaquin area, we mapped the hydrologicalsystem within the region using designations based on U.S. ArmyCorps of Engineers levees of maintenance concern USACE

2006b and critical erosion sites identified by the California De-partment of Water Resources State of California 2007 Fig. 3.Critical reaches within the area’s hydrological system were iden-tified by the designated levee’s name or river mile. To emulate alikely worst-case scenario, hypothetical levee breaches weresimulated along the reaches containing all levees of concern. Todo this, we utilized the “what-if” levee scenario provided withinFEMA’s HAZUS MH 2 flood model.

The HAZUS flood model is an integrated system developedfor use by floodplain managers and other decision makers as amethod to identify and quantify flood risks within flood-proneareas Scawthorn et al. 2006. Two analytical processes comprisethe HAZUS flood methodology: 1 a flood hazard analysis,which was employed as a means to delineate discharge extentfollowing a hypothetical levee breach scenario; and 2 a floodloss estimation analysis, which we did not use in this study. TheHAZUS methodology includes DEM-based stream network de-lineation, hydraulic analysis, and flood hazard analysis in whichthe user has the capability of adding a levee alignment reflectiveof the level of desired protection e.g., protection for a 10-, 50-,100-, 200-, or 500-year event. We selected a 100-year level of protection for modeling purposes. Reaches identified as critical,but not adequately represented within the HAZUS model wereomitted from further analysis. Paralleling a designated reach, thelevee option allows the user to draw a levee alignment two gridcells wide and high enough to restrict flow within the DEM.Levees were simulated on both sides of reaches identified as criti-

cal within our study area. In areas identified as protected by alevee, flow within the model was restricted and flood depths weremodeled as zero for frequencies less than or equal to the recur-rence interval of the level of protection selected for that leveeFEMA 2003a, b. On the southern or western side of thesereaches, levee segments were drawn with a 500 to 1,000 foot gap.A flood analysis for the levee reaches was employed allowing usto emulate where floodwaters would be restricted while floodingtracts below the hypothetical breaches.

The writers are aware that the debate over the impacts of leveebreaching within the delta region is based on highly sophisticatedhydrologic and engineering performance models. The purpose of this paper is not to propose a high resolution methodology aimedat flood zone delineation and flood analysis, nor to critique such

efforts. Instead, we are interested in a coarse approximation of thespatial extent of a levee-breach inundation based on a worst-casescenario, so that we could examine the characteristics of thosepopulations living within the inundation zone more closely. Theuse of Q3 data, social data at the census tract level, andHAZUS-MH allow us to develop these broad spatial patterns.Due to uncertainties in results produced by the HAZUS-MHmodel that are often attributed to the use of national datasets torepresent local conditions, the coupling of components, simplifi-cations within the model, and errors introduced as part of themathematical processing FEMA 2003a, great care must be takenin interpreting the results for very localized applications. Rather,

Table 2. SoVI Variables

Variable Description

QBLACK Percent African American population

QINDIAN Percent Native American population

QASIAN Percent Asian or Pacific Islander population

QSPANISH Percent Hispanic population

MIGRA Percent international migration

QKIDS Percent population under 5 years old

QPOP65O Percent population 65 years or older

QSSBEN Percent social security recipientsMEDAGE Median age

QFEMALE Percent female

QFHH Percent female headed households

QFEMBLR Percent female labor force participation

PERCAP Per capita income

QRICH Percent families earning more than $100,000 in 2000

QPOVTY Percent persons living in poverty

MDHSEVAL Median house value

MEDRENT Median rent

QRENTER Percent renter occupied housing units

PPUNIT Average number of people per household

QCVLUN Percent civilian unemployment

QED12LESS Percent population over 25 years old with less than12 years of education

QCVLBR Percent civilian labor force participation

QRFRM Percent rural farm population

QURBAN Percent of population living in urban areas

QMOHO Percent of housing units that are mobile homes

HODENT Number of housing units per square mile

QAGRI Percent employed in primary industry farming,

fishing,

mining, forestry

QTRANS Percent employed in transportation, communications,

and public utilities

QSERV Percent employed in service occupation

PHYSICN Number of physicians per 100,000 populationNRRESPC Nursing home residents per capita

HOSPTPC Number of community hospitals per capita

QLANDFRM Land in farms as a percent of total land area

MAESDEN Number of manufacturing establishments per

square mile

EARNDEN Earnings in all industry per square mile

COMDEVDN Number of commercial establishments per square

mile

Note: Adapted from Cutter et al. 2003.




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the analysis provides a subcounty profile of vulnerability to leveebreaches incorporating both exposure inundation and impactsocial vulnerability. The results should be used to guide plan-ning and growth management at the community level and floodmitigation planning at the county and regional scale.

Results

Factors Contributing to Social Vulnerability

The principal components analysis produced nine composite fac-tors, explaining 76.7% of the variance among tracts Table 3.

Socioeconomic status low was the largest contributor to socialvulnerability as explained by high positive loadings for poverty,service industry employment, and high negative loadings on percapita income, wealth, median home value, and median rent. Thepoverty indicator accounts for 24.4% of variation within thedataset. Essentially, households with insufficient financial re-serves are likely to be disproportionately affected by a disaster.The poor often suffer higher mortality rates, and their homes maysustain greater damage following a significant event due to thenature of the housing stock and its location Laska and Morrow2006; Peacock et al. 1997; Phillips and Morrow 2007; Tobin et al.2006. Structural maintenance to the home, costly upgrades for

conformity to building standards, and the adoption of mitigationstrategies are often out of reach for low income residents. Typi-cally, poor households will also recover more slowly, possiblynever regaining preimpact status.

The second component identified ethnicity as the next signifi-cant factor contributing to vulnerability with 14.6% of the vari-ance explained. Within this context, race and ethnicity contributeto vulnerability through a lack of access to resources based on

Fig. 3. Study area levees of concern for a Sacramento County; b Yolo County; and c San Joaquin County

Table 3. SoVI Factors

SoVI factors

Percent variance

explained

1 Socioeconomic status poverty 24.4

2 Race/ethnicity Hispanics 14.6

3 Age elderly 11.4

4 Development density 6.7

5 Renters 4.8

6 Females 4.6

7 Race African American/Asian 3.6

8 Race Native Americans 3.4

9 Health care institutions 3.2

Note: Cumulative % explained variance76.65.




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language, culture, educational levels and the economic margin-alization that is often associated with racial and ethnic disparitiesCutter et al. 2003. Factor 2 is characterized by high positiveloadings for Hispanic populations, low-wage agricultural employ-ment, and rural populations.

Age, specifically the elderly, was identified as the third con-tributing factor characterized by high positive loadings for popu-lations aged 65 and over, persons receiving social security

benefits, and median age. The age factor explains 11.4% percentof the variation. Age is a significant factor because the elderlymay have mobility concerns or constraints increasing the burdenof care and reducing resilience Ngo 2001; O’Brien and Mileti1992.

Spatial Distribution of Socially Vulnerable Populations

Understanding the distribution of social vulnerability and thevariability of individual components contributing to vulnerabilityis an integral part of disaster management, planning, and mitiga-tion. Fig. 4 depicts the spatial variation in social vulnerability for

Sacramento, Yolo, and San Joaquin counties. The classification isbased on standard deviations from the mean, but the labeling of the categories e.g., high top 20%, represents +1 standard de-viation was simplified for presentation purposes.

While the spatial pattern is not uniform throughout, there aresignificant pockets of high levels of vulnerability that warrantmanagement concern. Of special interest is a clustering of mod-erate to high and high vulnerability in southern Sacramento and

San Joaquin counties Fig. 4. In addition to this urban cluster of tracts, there is another large section of the tricounty area with highlevels of social vulnerability west of the main north-south inter-state I-5. This largely rural area is home to significant clusters of Hispanics and agricultural workers. The characterization of thehigh social vulnerability clusters was verified by field observa-tions based on the writers’ local knowledge of the area.

Exposure to Levee-Induced Flooding

For the delta region, a 500-year flood event is a worst-case hazardscenario. The flood control system is designed to protect against

Fig. 4. Spatial variability in social vulnerability




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loss of life and property for the 100-year event, yet aging infra-structure, lack of maintenance, and increased development haveforeshadowed a likely disaster in the region, prompting the Inde-pendent Review Panel to state that “one hundred year protectionis not an acceptable level of protection for urban areas” Indepen-dent Review Panel 2007.

Fig. 5 presents a spatial representation of a modeled levee

breach scenario derived from the HAZUS-MH flood model. Weused the HAZUS-MH levee scenario as a simple means to delin-eate likely worst-case flood areas for planning and decision mak-ing purposes. Further, we modeled levee breaches on bothUSACE and California Department of Water Resources levees of concern Fig. 3.

Our results Fig. 5 show that within the tricounty area, themost significant inundation occurs directly within the delta corri-dor of Sacramento County in a swath spanning north/south fromthe outskirts of the southern Sacramento metropolitan area west-ward to Isleton. Here, the delineated flood extent is the mostsignificant with estimated flood levels of 13 feet on average. Most

of the inundated areas from the levee breaches occur within theSacramento River basin and are within the 500-year floodplain.Historically, the area has been subject to floods that result fromwinter and spring rainfall, and major floods occurring within thelast 20 years 1983, 1986, 1995, and 1997 have caused signifi-cant damage USACE 2002. In the cities of Sacramento andWest Sacramento, there are more than 115,194 residential parcels

that could be damaged in a 500-year flood, more than one-third of them currently without flood insurance Independent ReviewPanel 2007, 1–6. Populations occupying this zone have high andmoderate-to-high social vulnerability. Located in the areas span-ning south from the Sacramento metropolitan area to Isleton, thehigh social vulnerability may impede movement out of harm’sway due to a lack of resources and the ability to sequester reliabletransportation. Recovery for the most vulnerable communitiesmay be difficult and long lasting, with the possibility of somecommunities never reaching preimpact status. Along the SanJoaquin river basin, considerably fewer residential parcels10,284 are at risk of a 500-year event USACE 2002.

Fig. 5. Modeled levee-induced flooding Note: triangles indicate locations of hypothetical levee breach areas




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Composite Vulnerability Assessment

Although mapping the spatial variability of socially vulnerablepopulations is useful, it does not adequately represent the truenature of all components contributing to the vulnerability at aparticular place. The aggregation of a community’s biophysicalrisk with its social context is critical because people are oftennot considered vulnerable in the absence of a certain degree

of exposure to physical threats. For this paper, we employed aplace-based vulnerability metric in which the delta region’sflood risk was merged with its relative social vulnerability to pro-duce a composite vulnerability score using a simple GIS overlayprocedure.

Fig. 6 represents the spatial distribution of the combinedphysical levee breach and social vulnerability. Not surprisingly,areas of highest vulnerability are found along a large north/southcorridor directly within the Sacramento-San Joaquin Delta. Itis within this corridor that communities are significantly vulner-able to levee-failure flooding and also have the highest levels of social vulnerability. Within this area, a considerable amount

of land area falls within the FEMA 500-year flood designa-

tion, further compounding flood risk to populations and overall

vulnerability.

Further Thoughts on Vulnerability Drivers

Up to this point, we have provided a rather spatially descriptive

analysis of the components of vulnerability—social andphysical—and how they map on the landscape of the tricounty

Delta region. To further assess the spatial variation in social vul-

nerability to levee failures, and to examine those factors contrib-

uting to the vulnerability of Delta populations, all census tracts

fully contained by and intersecting FEMA 500-year flood desig-

nations were separately selected. Each tract intersecting and con-

tained within HAZUS inundation polygons created by the levee

breach scenarios and all tracts not within a flood inundation zone

were also selected. Each tract was nominally coded to differenti-

ate between flood zones where: a value of 1 represents all tractswithin the FEMA designated 100-year flood inundation zone, 2

Fig. 6. Modeled levee inundation and social vulnerability Note: triangles indicate locations of hypothetical levee breach areas




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represents all tracts within the 500-year zone, 3 represents alltracts within the levee breach zone, and a value of 4 represents alltracts not within a breach area and/or 100- or 500-year zone.Using this form of scaling, we employed an analysis of varianceas a comparative metric. We chose an ANOVA because it repre-sents a conceptual extension of the two-sample t -test for differ-ences of means that allows for comparisons across an excess of two samples. Our aim was to examine if the extent of socialvulnerability within the area exhibited heterogeneity between thefour identified flood inundation zones.

Results from the analysis of variance Table 4 show a signifi-cant divergence in vulnerability scores among flood inundationgroups p0.017. The highest average vulnerability scores fallwithin tracts exposed to our hypothetical levee breach scenarios.Here, the average social vulnerability scores are more than doublethose calculated within the 100-year and 500-year flood inunda-tion zones. The lowest average vulnerability scores are found innoninundation zones where residents are relatively free of floodrisk.

A second sensitivity test examined the relative importance of components of the place vulnerability land area in 100-year floodzone + land area in 500-year flood zone + social vulnerabilityscore Table 5. Using the place vulnerability score as the depen-dent variable, a linear regression was performed to examine the

standardized beta coefficients of each of the independent vari-ables to assess their relative strength in contributing to place vul-nerability. We acknowledge that the index values utilized withinour multiple regression analysis are deterministic rather than sto-chastic. Our use of systematically derived values as a dependentvariable violates the assumption of statistical independence ran-domness of variables. It was not our intention to predict or makestatistical inferences pertaining to the prediction of vulnerability.Rather, the regression analysis was employed as a means to assessthe relative importance of variables contributing to place-basedvulnerability. Within a regression, if the randomness assumptionis not valid, it is still possible to estimate regression coefficientswhere the relative importance of variables is assessed. While thephysical exposure variables are significant with the exception of

the levee inundation, it is the social characteristics of the popu-lation that are producing the overall vulnerability in the deltaregion. The lack of statistical significance of the levee inundationbeta coefficient is primarily a function of the relatively smallnumber of tracts land area not already included in the 100- and500-year flood zones.

To simplify the visual representation of all flood hazards, not just those caused by levee breaches, we constructed a place vul-nerability index for the tricounty area. Construction of the indexis summarized as follows:1. Within a geographic information system, all census tracts

falling within FEMA’s 100-year flood designation were se-

lected and coded using Boolean logic. A value of 1 was as-signed to each tract falling within the 100-year designatedfloodzone. A value of zero was applied to all tracts outside of the 100-year zone.

2. Census tracts falling within FEMA’s 500-year designationand those tracts inundated by the hypothetical breachscenarios were coded in an identical manner to that of the100-year zone. Because all census tracts falling within the500-year flood designation are, by default, included withinthe 100-year flood zone, an overlap exists.

3. The Delta area’s social vulnerability scores were standard-ized in a manner in which all census tracts were assigned avalue between 0 and 1, increasing linearly by 0.20 basedupon the relative contribution of each score to social vulner-ability e.g., those tracts falling within the bottom 20% of scores −1 standard deviation were assigned a value of 0.20, whereas those tracts falling within the top 20% + 1standard deviation of scores were assigned a value of 1.Middle values were assigned scores of 0.40, 0.60, and 0.80,respectively.

The values that we derived using the 100-, 500-year, and stan-dardized social vulnerability scores were then summed andmapped. Standardizing all values with a range from 0 and 1 as-sured that the contributions of physical risk and social vulnerabil-

ity were not skewed based upon exceptionally high or low valuesof vulnerability at a particular location. Rather, the compositescores are simply dictated by location and by the social vulner-ability at a particular place.

By simplifying the visual representation to focus on censusunits Fig. 7, not the hydrography, we see pockets of high vul-nerability to flooding exist in the Stockton and Sacramento met-ropolitan areas where high social vulnerability is also coupledwith some moderate to low levels of flood inundation. While thepotential inundation or biophysical vulnerability may be lessthan those areas west of Interstate 5, the ability of communities torespond to and recover from such flooding is low because of theirpreexisting social vulnerability. Such a place-based vulnerabilityassessment provides an overview of areas most likely to be ex-

posed to, adversely affected, and differentially impacted follow-ing a levee induced flood event. The use of a composite metric inthis manner may be more useful to emergency managers andplanners than simply mapping the spatial variability of sociallyvulnerable communities, or the distribution of flooding.

Conclusion

The impacts from a natural event will be expressed differentiallyacross and within communities. To be effective, disaster planners,managers, and coordinators must not only understand the physical

Table 5. Linear Regression Model Used to Determine Relative

Significance of Independent Variables on Place Vulnerability

Variable Beta t Significance VIF

Dependent variable: place vulnerability

Land area in 100-year floodzone

as % total area

0.095 2.055 0.041 1.357

Land area in 500-year floodzone

as % total area

0.208 4.904 0.000 1.138

Land in levee inundation zone

as % total area

0.061 1.391 0.165 1.201

Social vulnerability SoVI score 0.463 1 1.154 0.000 1.087

Table 4. ANOVA Results for Social Vulnerability

Social vulnerability

Zone Mean

Standard

deviation

Standard

error

100-year flood zone 1.054 2.930 0.159

500-year flood zone 0.862 2.728 0.160

Levee inundation zones 1.842 3.110 0.372

No flood threat 0.705 2.917 0.147

All zones 0.928 2.894 0.088

Note: Sum of squares: 84.65, df: 3, mean square 28.22, F: 3.39, p0.017.




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agents, but also the social characteristics that give rise to thevulnerabilities within the communities they protect. A first step isto identify and map those areas hosting populations that may bemore susceptible to loss and those that will lack the ability toquickly recover following an event. This paper presented a meth-odology and example for vulnerability assessments using a two-tiered approach: a spatial delineation of vulnerability based on thecombination of physical parameters and social indicators; and

then a statistical determination of the drivers of vulnerabilitywithin the region. Our findings reveal there are spatial differencesin vulnerability and that these are based on the underlying socialcharacteristics of communities as well as the risk for flood inun-dation due to levee failures. Disaster mitigation and planningunder such circumstances may require special attention wherecultural differences and language barriers affect the way in whichthese communities prepare for and respond to risk. A one-size fitsall mitigation strategy does not address the drivers behind thevulnerability in the tricounty region. For example, preparedness,response, and recovery from catastrophic flooding may take acompletely different trajectory and form in the delta islands west

of Interstate 5 where the social vulnerability is characterized byHispanic residents engaged in agricultural contrasted to those inthe downtown areas of Stockton east of Interstate 5 where thevulnerability drivers are mainly age and lower socioeconomic sta-tus. However, the physical vulnerability is still important even asthe social landscape changes. As Kelly noted nearly two decadesago, “The inland sea has disappeared, but it is now clear as itnever was before how powerful a river system has been put under

control, and how vulnerable that structure of control will alwaysbe” Kelly 1989, p. 315.

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