A thematic mapping method to assess and analyze potential urban hazards and risks caused by flooding
Introduction
Flooding has been a major concern in the U.S. and many other counties across the world because of the extreme amount of social and economic loss, including deaths. Since the 1960s, the frequency of high tide flooding has increased by a factor of 5 to 10 in several U.S. coastal communities (Hayhoe et al., 2018). The minor infrastructure damage is also increased by 5–10 times caused by daily tidal flooding events (Ezer & Atkinson, 2014; Sweet & Park, 2014; Sweet, Park, Marra, Zervas, & Gill, 2014). Recent U.S. climate assessment report indicates that the Southeast part of the USA has faced four major inland flood events in the three years (2014–2016) that caused billions of dollars in property damages and 120 deaths (Carter et al., 2018; NOAA NCEI, 2018). In 2006, United States Geological Survey (USGS) reported that the U.S. faced $6 billion in property damages and 140 deaths on average annually because of floods (USGS, 2006), while in the water year 2016 (October 1, 2015–September 30, 2016), the direct flood damages are $11.54 billion with 168 flood-related deaths (NWS-NOAA, 2017). Hurricane Harvey and Maria were the most severe tropical cyclone rainfall events that affected the United States in recent years. The NOAA estimated that Hurricane Harvey caused $125 billion in property damages and 64 deaths in Texas in 2017 (Blake & Zelinsky, 2018). Southern Texas was mostly affected by Harvey's flooding, where 300,000 structures and 500,000 cars were flooded (Blake & Zelinsky, 2018). Puerto Rico and the U.S. Virginia Islands were mostly affected by floods of Hurricane Maria, which caused $90 billion in property damages (Pasch, Penny, & Berg, 2019).
According to the U.S. Federal Emergency Management Agency (Wright, 2007), the main causes of flood damages are debris impact, hydrodynamic forces, soaking, hydrostatic forces, contaminants, and sediment. People generally want to live near the water bodies; likewise, the United States people who live in near the water bodies have the better access to transportation, water supply, water power, seafood supply, and nice landscapes (Wright, 2007). At the same time, the communities near water bodies that are flood-prone, often experience the most flood damages. In the United States, floodplains contain approximately 10 million households and $800 to $900 billion in property subject to flood risk (Wright, 2007). Flood-related property losses have recently risen to above $10 billion a year, from approximate $3.3 billion in the mid-1980s (Frangos, 2003; NWS-NOAA, 2017). According to the international Emergency Events Database (EM-DAT, 2016), China had the worst floods in 1931 and 1959 regarding most deaths that had caused 3.7 million and 2 million deaths, respectively. Regarding property damages, Thailand and China both experienced the worst floods in 2011 and 1988, respectively; and the estimated property damage for Thailand was $40 million, and for China it was $30 million (EM-DAT, 2016). In the U.S. history of the flood from 1900 to 2016, 2945 deaths and $63.7 billion in property damages were caused (EM-DAT, 2016).
Most flooding studies typically use the social vulnerability index (SVI), which is designed to highlight the areas where are the high concentrations of vulnerable populations, typically the minorities. The commonly used SVI methods are deductive, hierarchical, and inductive. Among these three approaches, the deductive method is the most common one. In the deductive approach, it often contains less than ten indicators, typically including age, ethnicity, gender, etc., to construct a social vulnerability index (Collins, Grineski, & De Lourdes Romo Aguilar, 2009; Cutter, Mitchell, & Scott, 2000; Lein & Abel, 2010). The social vulnerability for each block of census data can also be calculated by using the deductive approach, which normalizes and aggregates the value to index (Cutter, Burton, & Emrich, 2010). This interpretation could be misleading, because the level of social vulnerability can be varied with the type of vulnerability indicators. In the hierarchical approach, it considers up to twenty indicators, often including socioeconomic status, demographic structure, special needs, etc., which are then separated into groups known as sub-indices (Chakraborty, Tobin, & Montz, 2005; Flanagan, Gregory, Hallisey, Heitgerd, & Lewis, 2011; Mustafa, Ahmed, Saroch, & Bell, 2011). Usually, the indicators possess similar dimensions of vulnerability grouped together. The inductive approach is most recently used for the social vulnerability indices (Burton, 2010; Burton & Cutter, 2008; Finch, Emrich, & Cutter, 2010; Schmidtlein, Shafer, Berry, & Cutter, 2011; Tate, Cutter, & Berry, 2010) and is usually applied to a large dataset, which has more than twenty factors. Then the factors were reduced to a smaller number by using the principal component analysis that aggregates to compute the final index. Among these three approaches, the hierarchical modeling approach is most accurate (Tate, 2012).
The SVI typically describes a general and overall assessment of potential risk for minorities. Recently, Fahy, Brenneman, Chang, and Shandas (2019) used GIS technology to develop a combined index of Topographic Wetness Index (TWI) and Urban Heat Index (UHI), which could identify the spatial patterns for environmental hazards in urban areas. However, there is minimum research exploring the spatial demographic characteristics of urban communities in flood hazard areas, which are the primary key to not only understand potential flooding risk to urban residents but also to spatially and efficiently establish and operate urban hazard management. To fill the knowledge gap of the spatial vulnerability of urban residents to flooding, we propose a thematic mapping method, i.e., location quotient (LQ), to spatially and demographically quantify and map urban residents' flood risk assessment. Our research of urban flood risk assessment will also help understand the multi-dimensional aspects of urban flood vulnerability in an inclusive way, which is critical in urban flood risk assessment and monitoring (Cho & Chang, 2017).
This study uses GIS and quantitative cartographic methods to conduct flood risk assessments, which will contribute to flooding disaster management policy and strategy formulation. This integrated GIS and geovisualtization approach is of particular importance to help solve current flood risk assessment problems, and the fine demographic vulnerability analysis provides novel insight to potential urban flood risk assessment, which is important to inform decision and policy makers (Torrieri & Michael, 2006).
Section snippets
Study area
Birmingham is the most populous city in the State of Alabama, USA. It has a total area of 393.42 km2 with the total land area of 388.24 km2 and the water area of 5.18 km2. According to the 2014 U.S. Census, the city's population was 212,237. Geographically, the city of Birmingham located in a valley on the western slopes of the Appalachian Mountains. In Birmingham, there are total eight watersheds, and they are Village Creek, Shades Creek, Black Warrior River, Valley Creek, Turkey Creek, Five
Methodology and data
Using Birmingham, AL, USA, a historical flood hazard city, as the study area, this study proceeds as below. Firstly, SVI is calculated as a type of the flood risk assessment, which identifies the location of vulnerable populations in Birmingham. Secondly, location quotient (LQ) as a thematic mapping method is proposed for urban residents' social vulnerability assessment and mapping. Social and demographic factors were calculated accordingly to quantify flood risk assessment. Location quotient
Social vulnerability index
The two subcomponents of social vulnerability were normalized and displayed using GIS to show the spatial variation of the overall social vulnerability in the flood hazard zones of Birmingham (Fig. 3). The social vulnerability scores for each block provide a comparative assessment, and the blocks mapped in red color show the higher level of social vulnerability. However, the majority of the blocks possesses low to moderate social vulnerability, with value ranges from 0 to 0.75. Finally, the
Discussions
This research shows how urban hazards' vulnerability, such as flood, can be more extensively and comprehensively assessed by designing a location quotient analysis of demographic and other socio-economic factors. Economic, cultural, and other potential discriminations put some populations at higher risk. Notably, the poorer groups live-in high-risk areas such as near levees, and inner cities, which are considered as the source of risk and put people in the threat in any disastrous event.
Conclusions
We designed a location quotient method to spatially study and assess social vulnerability factors across the flood hazard areas in Birmingham. The location quotient thematic mapping provides a deep understanding about why a particular area has a low, moderate, and high social vulnerability. Furthermore, LQ for social vulnerability factors is quantified and mapped at the block group level within the 100 year's flood zone in Birmingham for different minorities and the White people. The LQ map of
References (56)
- et al.
Vulnerability to environmental hazards in the Ciudad Juárez (Mexico)-El Paso (USA) metropolis: A model for spatial risk assessment in transnational context
Applied Geography
(2009) - et al.
Characteristics of online and offline health information seekers and factors that discriminate between them
Social Science and Medicine
(2004) - et al.
Race, class, and hurricane Katrina: Social differences in human responses to disaster
Social Science Research
(2006) - et al.
Spatial analysis of urban flooding and extreme heat hazard potential in Portland, OR
International Journal of Disaster Risk Reduction
(2019) - et al.
Schooling, basic skills and economic outcomes
Economics of Education Review
(2002) Returns to education: A global update
World Development
(1994)- et al.
Modeled earthquake losses and social vulnerability in Charleston, South Carolina
Applied Geography
(2011) - et al.
Literacy as a pathway between schooling and health-related communication skills: A study of venezuelan mothers
International Journal of Educational Development
(2005) - et al.
Women, work, and family in America
Population Reference Bureau
(1996) - et al.
National hurricane center tropical cycle report: Hurricane harvey
(2018)
Shelter, housing and recovery: A comparison of U.S. disasters
Disasters
The Northridge earthquake: Vulnerability and disaster
Household and community recovery after earthquakes
Levee failures and social vulnerability in the Sacramento-San Joaquin Delta area, California
Natural Hazards Review
Social vulnerability and hurricane impact modeling
Natural Hazards Review
Southeast. Impacts, risks, and adaptation in the United States: Fourth national climate assessment
Population evacuation: Assessing spatial variability in geophysical risk and social vulnerability to natural hazards
Natural Hazards Review
Recent research approaches to urban flood vulnerability, 2006–2016
Natural Hazards
Village Creek watershed improvement plan: Stream and channel improvements
Vulnerability to environmental hazards
Progress in Human Geography
Cutter. Socail vulnerability.Pdf
Social Science Quarterly
Disaster resilience indicators for benchmarking baseline conditions
Journal of Homeland Security and Emergency Management
Revealing the vulnerability of people and places: A case study of Georgetown County, South Carolina Susan
Annals of the Association of American Geographers
Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model
Hydrology and Earth System Sciences
Spaef: Spatial efficiency
The human impact of floods: A historical review of events and systematic literature review
PLOS Currents Disasters
The international disaster database
Accelerated flooding along the U.S. East Coast: On the impact of sea-level rise, tides, storms, the Gulf Stream, and the North Atlantic Oscillations
Earth’s Future
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