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. Author manuscript; available in PMC: 2024 Feb 2.
Published in final edited form as: Clim Risk Manag. 2023 Jun 10;41:100529. doi: 10.1016/j.crm.2023.100529

Multi-Hazard property buyouts: Making a case for the acquisition of flood and contaminant-prone residential properties in Galena Park, TX

Kayode Atoba a, Galen Newman b, Garrett Sansom c
PMCID: PMC10836021  NIHMSID: NIHMS1957310  PMID: 38312112

Abstract

The aftermath of extreme flood events can be particularly devastating for residential communities in proximity to flood-prone petrochemical facilities, as they are likely to experience multiple impacts from a single flood event. Hazard impacts could be from flood inundation to their properties, and floodwaters carrying contaminants from nearby facilities into their homes. While property acquisition or buyouts have been effectively used as a flood mitigation strategy, current buyout selection processes only factor in flood exposure, thereby ignoring other hazards such as exposure of properties to potential chemical substance transfer. In this paper, we identify properties that are eligible for flood buyouts but are also at a high risk of contaminant transferal during extreme flood events. We apply a benefit–cost analysis methodology to assess the economic viability of buyouts and proximity metrics to prioritize buyouts of contaminant-prone properties in Galena Park, Texas. Results indicate that, in selected flood-only property acquisition scenarios, cumulative avoided flood losses exceed the cost of property acquisition. However, although with lower cost-benefit values, a selection criterion that factors a combination of flood and contaminant-prone properties as buyouts results in multiple properties being removed from harm’s way. Our findings emphasize the potential economic benefits of applying a multi-hazard selection criterion in dealing with flood property buyouts, especially in socially vulnerable communities with high exposure to both flooding and contaminant transfer.

Keywords: Property acquisition, Buyouts, Benefit-cost assessment, Contaminant transfer, Flood risk, Hazardous material

1. Introduction

Extreme flood events are on the rise in coastal communities. For example, in 2017, three major tropical cyclones made landfall in the United States, leading to over $265 billion in direct losses and even more in induced losses (NOAA, 2017). Although these storms cause significant loss of lives and property, they also often reveal several other vulnerabilities within which the human and built environment systems are also exposed. One of such adverse impact is the potential for toxic contamination from nearby industrial facilities (Stafford et al., 2019). In 2017, Hurricane Harvey demonstrated how natural hazards and changing environmental conditions can substantially increase pollutant releases from industrial facilities. The aftermath of Hurricane Harvey led to several industrial toxic releases and the failure of at least 40 waste treatment plants in the Houston area; this increased the exposure of nearby residents to fecal contamination as well as the potential for heavy metals such as lead, arsenic, and so on both inside and outside of their homes (Kaplan and Healy, 2017). The location of many of these facilities in already vulnerable communities further exacerbates existing negative public health consequences. This situation creates a multi-hazard risk of both flooding and contaminant transferal.

Several flood mitigation strategies have been documented both in literature and in practice. One such strategy that also has the potential to benefit properties at-risk of flood-induced contamination is property acquisition. Property acquisition, or buyouts, refers to the acquisition of at-risk properties by local government or flood control agencies, to perpetually eliminate the risk for repetitive flood damages for properties that are deep within the floodplain. Since 1989, over 40,000 flood-prone properties have been acquired across the US., primarily through Federal Emergency Management Agency (FEMA) program funds (Mach et al., 2019). This flood risk reduction strategy is gaining in popularity and is even expected to play an increasing role in local floodplain management (Winsemius et al., 2016, Wing et al., 2018). A major driving factor for buyouts is the potential economic benefits measured through avoided flood losses. For example, properties that have experienced repetitive flood damages within the 100-year floodplain can be considered cost effective for buyout purposes since such losses are no longer expected once the property is acquired. (Conrad et al., 1998, Tate et al., 2016, Zavar, 2015).

Although buyouts, as a flood risk reduction strategy, are increasing in popularity, policy makers show little consideration to pollution from contaminants when making decisions about buyout of flood-prone properties. This is not surprising because of the problematic nature of selecting properties as candidate for flood buyouts. Such problems are further heightened if other hazards and risks are to be considered as a selection criterion for acquisition purposes. This is evident in the lack of transparency in the selection process of many U.S. buyout programs (Greer and Binder, 2017, Siders, 2019), thereby limiting vulnerable populations from reaping the benefits of such programs. However, despite the problems associated with buyout programs, local communities still have the ability to provide a set of eligibility criteria that cater to their local interests (Atoba et al., 2020). This flexibility can be leveraged to account for contaminant-prone properties to be prioritized for flood-related buyouts. Keeping these in mind, this study considers the possibility of assessing economic benefits of buyouts while also prioritizing properties that are at risk of receiving heavy metal concentrations after or during flood events.

Despite the noted shortcomings of some buyout programs, the strategy itself is proven to be effective in mitigating the impacts of future floods (Tate et al., 2016, Atoba et al., 2021). Similarly, since flooded properties are at risk of contaminant transferal after major events (Zota et al., 2011), buying-out these flood and contaminant prone properties is a viable option of reducing the potential for contaminant transfer. It further serves the purpose of multi-hazard flood mitigation while using programmatic flood mitigation funds. However, conducting a buyout solely on the risk of contaminant transferal is problematic due to several reasons. Firstly, “proving” that residents are at risk of contaminants transfer is extremely difficult, hence limiting the possibility of a potential property acquisition. Unlike flood buyouts where flood risk is delineated by the regulatory floodplain, there is no regulated delineation of properties that are exposed to contaminant transfer based on a probability or storm return period. Second, there is currently no existing federal funding for the acquisition of contaminant-prone properties which is similar to flood buyouts.

While cost-benefit analysis plays a crucial role in assessing the economic feasibility of flood mitigation projects like buyouts, measuring the associated costs and benefits presents several challenges. One of the main difficulties lies in quantifying intangible factors such as socioeconomic and psychological distress, sense of place, and other social costs related to buyouts (Binder et al., 2015, Binder et al., 2020, Maldonado et al., 2013, Marino, 2018, Hausmann et al., 2016). These factors are inherently difficult to convert into monetary value and are not traditionally incorporated into the cost-benefit analysis of buyouts. Similarly, the monetization of non-flood-related benefits (referred to as co-benefits) resulting from these projects, such as the ecosystem services provided by buyouts through the conversion to natural open spaces, poses a challenge (Conrad et al., 1998, FEMA, 1998, Harter, 2007). Acknowledging the limitations of conventional BCA, FEMA, for instance, has recently adopted a more flexible approach by accepting a cost-benefit ratio of 0.75 or higher, provided that other conditions are satisfied. These conditions include the utilization of lower discount rates and the demonstration of additional benefits that cannot be easily monetized, such as ecosystem service benefits (FEMA, 2023).

Given the aforementioned challenges, the task of monetizing co-benefits, specifically the reduction in exposure to contaminant transfer in a flood buyout BCA, becomes even more arduous. To bridge this gap, this paper aims to investigate and illustrate how a non-monetary aspect of buyout BCA, namely contaminant risk exposure, can be recognized and incorporated using alternative quantitative measures alongside the conventional BCA for property buyouts.

To address this, we raise the research question: Could flood-related property buyouts be an economically viable means to acquire contaminant-prone properties in vulnerable locations? In this research, we explore the multi hazard exposure of residential properties in Galena Park, TX to both contaminants from petrochemical complexes and toxic release inventory sites. We combine exposure to contaminants with exposure to inland and storm surge-induced flooding, thereby making a case for acquiring properties that are exposed to multiple hazards in the study area. To answer the research question, we propose the following objectives: 1) identify the potential exposure of residential properties in Galena Park to contaminant-producing sites, 2) perform a multi hazard analysis of flood risk exposure and contaminants exposure, 3) measure the potential economic benefits of acquiring residential properties, and 4) propose best built environment management strategies for habitable areas in the context of multiple hazards.

2. Background

2.1. Proximity to environmental hazards and its public health impacts

Living near industrial developments has long been a public concern as it can contribute to negative health outcomes. For instance, one systematic review found a significant relationship between residential proximity to environmental hazards and adverse health outcomes, including pregnancy difficulties, childhood cancers (including leukemia, brain cancer, germ-cell tumors, non-Hodgkin’s lymphoma, and Burkitt lymphoma), asthma hospitalizations and chronic respiratory symptoms, stroke mortality, end-stage renal disease, and diabetes (Brender et al., 2011). Environmental exposures have likewise been well documented. Zota et al. (2011) found levels of heavy metals, including lead (Pb) and Arsenic (As), three times higher when living near a mining-impacted Superfund site compared to homes further away. Similar results have been witnessed in the greater Houston area, with elevated levels of exposure and risks to heavy metals (Sansom et al., 2016), runoff from Superfund sites (Iyer et al., 2016), and poor air quality associated with hazard events (Han et al., 2020). The importance of better understanding and improving environmental conditions is underscored in vulnerable communities.

Much work over the past few decades has provided evidence of a disparate experience of exposure risks within lower income or minority-majority communities. These susceptible groups living in environmental justice neighborhoods often experience the brunt of environmental exposures (Bullard, 2013, Anderton et al., 1994). Individuals and families within these areas experience higher levels of air (Miranda et al., 2011), water (Mascarenhas, 2007, Sansom et al., 2019), and soil (McClintock, 2012) contamination when compared to affluent neighborhoods. To further exacerbate the public health effects many of these communities face the threat of environmental emergency contamination events, both anthropogenic (e.g., chemical spills, dredging) and natural (e.g., hurricanes, floods), that increase the risk of exposure to hazardous substances linked to adverse effects on human health.

2.2. Empirical research on flooding and contaminant transfer

The convergence of natural disasters and environmental contamination as a result of anthropogenic sources heightens the potential for chemical mobility and transfer, especially in socially vulnerable areas (Newman et al., 2020). These effects have been clearly evidenced by temporal changes within soil contaminant concentrations associated with Hurricanes Harvey in Texas, Hurricane Katrina in Louisiana, and Hurricane Sandy along the east coast (Noor et al., 2021).

There is limited research on the connection between health outcomes of contaminant transfer during flood events. In fact, only a handful of studies focus on the transferal of chemical pollutants from industrial locations or superfund sites during flood events. A previous report by the EPA focused on the risk of dioxins transfer from the San Jacinto Waste pit located within the Houston Ship Channel (Brody et al., 2013). Other studies show that socially vulnerable communities in the Houston Ship Channel are at the risk of contaminant transfer due to the damage of above ground storage tanks during a flood event (Bernier et al., 2017), as well as increased levels of toxicity in flood waters because of Hurricanes and Tropical Cyclones in other locations (Erickson et al., 2019). Spillage from petrochemical tanks constitutes the bulk of studies on contaminant transfer during flood events (see Antonioni et al., 2015, Burleson et al., 2015, Krausmann and Mushtaq, 2008).

An estimated 53 million US residents (16 percent of the total US population) live within three miles of a Superfund site (US EPA, 2020). Those that live in close proximity to such facilities typically have disproportionately larger proportions of residents who have not completed high school, minority residents, lower rates of English-speaking residents, and households with incomes below the poverty level (Hendricks et al., 2018). Minority or lower-income populations have also been shown to be inequitably exposed to other hazardous sites which may not be listed as Superfund. For example, many are also located adjacent or proximate to sites listed on the Environmental Protection Agency’s the Toxic Release Inventory; among such sites, a high correlation exists between emission intensity and the population density of nonwhite populations (Rhubart and Galli Robertson, 2020). Severe storms and storm-related flooding are among the destructive natural hazards affecting the US and accounting for more than 80 fatalities and nearly $8 billion in damages annually, on average (NWS, 2019). For example, communities in close proximity to petrochemical storage tanks are especially at risk of contaminant transfer as a result of a potential tank failure due to a flood event. (Bernier et al., 2017). Flood waters do not respect political or property boundaries when present in large volumes and when moving at a high velocity.

During flood events, mobile water facilitates contaminant transport, relocating and spreading traces of toxic chemicals concentrated areas such as industrial facilities into other areas like residential neighborhoods; such relocation can then have deleterious effects on residents’ health and environmental conditions. Flood events dispersing contaminants into residential areas can have long-term negative public health consequence such as increases in risks related to waterborne diseases and outbreaks and incidences of chronic conditions such as asthma or cancer (Plumlee et al., 2014). Further, social vulnerability factors can further amplify these effects (Page and Berger, 2006).

The consequences of chemical transferal during flood events are heavily dependent on both the geographic location of the transferred areas and its proximity to areas with high concentrations of chemicals. For example, in agricultural areas, flooding is heavily associated with nutrient or pesticide runoff; urban areas are more associated with chemical or bacterial contamination; and industrial areas are more associated with spills, emissions, or secondary accidents related to what is being produced in their complexes (Diaz, 2004). Such concentrations tend to accrue more heavily in highly socially vulnerable neighborhoods (Hendricks et al., 2018).

Hurricane Sandy in 2012 is an example of a flood that was accompanied by the spread of contamination within both water and soil, albeit outside of Texas. Arsenic, lead, polychlorinated biphenyls (PCB), and polycyclic aromatic hydrocarbons (PAH) were detected in similar elevated concentrations in multiple locations following Hurricane Sandy (Mandigo et al., 2016). Aside from flooding along the Atlantic, many neighborhoods located along the Houston Ship Channel proximate to the Gulf of Mexico have been documented as having excess risks of exposure to emergency chemical spills and high-impact natural disasters. These exposures have been linked to poor health outcomes including cancer clusters in both children (linked cancers in children include brain, leukemia, glioma, and melanoma) and adults (linked cancers in adults include liver, brain, and cervical) (Linder et al., 2008). In fact, a 56% increased risk of acute lymphocytic leukemia among children living within two miles of the Houston Ship Channel has been shown, when compared to children living at least 10 miles away; residents of neighborhoods nearer to the Houston Ship Channel also have more than twice the rate of respiratory disease than other Texans (Newman et al., 2020).

3. Study area

In addition to the flood vulnerabilities associated with its coastal location, Texas also houses the US’s largest petrochemical complexes; these industries are primarily located along the Houston Ship Channel (Noor et al., 2021). A major petroleum refinery located near a given community in TX can produce up to 160,000 barrels of gasoline and other fuels per day (Malecha et al., 2020). Hazard vulnerabilities and industrial density interact synergistically with the highly socially vulnerable population living in coastal Texas. This study focuses on Galena Park, an incorporated municipality located adjacent to the eastern edge of the city of Houston in Texas. Galena Park was originally a railroad center, which later evolved into a petrochemical refinery center after Texaco acquired its first oil company in the city (Jordan, 2012).

Galena Park is both physically and socially vulnerable to both flood hazards and environmental impacts from toxic industrial activities. According to the 2010 census, there are 10,901 residents in the city, with about 86% minority population (80% Hispanic, 6% African American). The city typifies an environmental justice community, suffering from frequent repetitive flood events and is in close proximity to many industrial facilities and petrochemical complexes along the Houston Ship Channel (see Fig. 1). Galena Park has one of the highest petrochemical hazard density index in the Texas Gulf Coast and was disproportionately affected by petrochemical releases following hurricane Harvey (Flores et al., 2021). For example, after Hurricane Harvey in 2017, Galena Park was the location of widespread flooding as well as the location of the largest reported chemical spill with an overflow of hundreds of thousands of gallons of gasoline from storage tanks at Magellan’s Midstream Galena Park Terminal (TCEQ, 2017).

Fig. 1.

Fig. 1.

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Study area showing petrochemical refineries and residential communities in Galena Park, Texas in 2021.

The study area has several cases of documented contaminant transferal issues dating back to the 1980s with issues such as leakages from dredged dump sites, and investigation into dead fish (Jordan, 2012). Galena Park’s proximity to the Houston Ship Channel also exposes it to both inland riverine flooding as well as storm surge induced flooding coming from the Galveston Bay, with over 60% of the residential area exposed to a category 5 hurricane storm surge. Sections of Galena Park were also inundated by Hurricane Ike’s Storm Surge and a large portion of the residential area was inundated by Hurricane Harvey, with upwards of almost 23ft of flood inundation along a creek draining into the Houston Ship Channel. Hurricane Harvey also resulted in over 80 properties with significant damage to their structure and contents, as well as over $2.4 million in insured flood claim payouts.

4. Methods

4.1. Measuring flood and contaminant risk

To evaluate the distribution of flooding and contaminant transferal risk in Galena Park, we conducted an analysis to identify residential properties that have been exposed to historical flooding and their proximity to contaminant sites. A composite risk score was calculated for each parcel by combining four primary factors, which were then converted into ordinal scores. These factors include flood probability, storm surge exposure, proximity to toxic facilities, and proximity to industrial facilities. To determine the flood probability score, we adapted an existing flood probability random forest model developed by Mobley et al. (2021) that utilizes ratio scales of flood return periods ranging from 0 to 0.02% flood return period. These ratios were converted into a 5-point ordinal scale for each residential parcel. Additionally, we assessed storm surge exposure for each parcel to account for hurricane risk. This was achieved by utilizing data from the National Oceanic and Atmospheric Administration’s (NOAA) Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model. The category 1–5 storm surge exposure areas were converted into a 5-point ordinal score based on the highest storm surge exposure in the respective parcel’s location.

Furthermore, we assess exposure of residential properties to contaminant sites, through spatial proximity analysis. We evaluated toxic facility proximity using the Toxic Release Inventory (TRI) program dataset provided by the EPA. A distance band ranging from 100 to 500 m was established around each residential facility in Galena Park, and an ordinal score ranging from 1 to 5 was assigned to each property based on its proximity to the nearest TRI facility. Similarly, industrial facility proximity was assessed using data from the Texas Commission on Environmental Quality (TCEQ), employing a comparable approach. A distance of 100 to 500 m was measured from each residential property to the closest industrial facility in the TCEQ registry, and a corresponding score ranging from 1 to 5 was assigned to each property based on its proximity. Finally, the combined risk score for each parcel was computed by summing the scores from all four risk components, resulting in a composite contaminant and flood risk score that reflects the overall risk level for all residential properties in Galena Park. Similar public health studies have also used 100–500 m distance bands to measure risk and exposure to both built or natural environment features (Sansom et al., 2023, Zhou and Levy, 2007, Spycher et al., 2015, Staedke et al., 2003).

As shown in Fig. 2, all residential properties located within the 100-yr FEMA floodplain in the study area are categorized as high flood risk properties. As expected, several properties surrounding the FEMA floodplains are also exposed to high risk of flooding. Other portions of the city such as properties adjacent to the northwestern part of the community is considered medium to high risk for flooding. However, the northeastern portion of Galena Park has a relatively lower amount of flood risk compared to the main city. The flood risk score categories are consistent with the extent of flood damage that occurred during Hurricane Harvey in 2017.

Fig. 2.

Fig. 2.

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Flood Risk in Galena Park, TX.

The contaminant risk score for each residential property in Galena Park follows the locational pattern of TCEQ and TRI facility location in the study area. Most of the facilities are clustered in the southern portion of the city, with the majority of these facilities being petrochemical facilities and chemical storage tanks (see Fig. 3). Several other contaminant-source facilities are located around the eastern portion of the city. Properties within 100 m of these facilities are considered to have the highest risk and exposure to harmful contaminants.

Fig. 3.

Fig. 3.

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Composite Flood and Contaminant Risk in Galena Park, TX.

Fig. 3 also shows the composite flood and contaminant risk of the study area. The residential properties with the highest risk levels are those at the southernmost portion of the main city. These properties are not only in close proximity to petrochemical complexes but have also been historically damaged from frequent flood events. Additionally, several properties in the FEMA floodplains are not only exposed to flooding but are in proximity to TCEQ facilities with a high contaminant risk score.

4.2. Benefit-cost analysis of contaminant-prone buyouts

Using all residential properties in Galena Park, we calculated Benefit-Cost Ratios (BCR) to better assess the costs and benefit of acquiring properties for flood and contaminant risk reduction purposes. The BCR analysis was based primarily on the avoided losses from flooding, while exposure to contaminants informed the priority placed on whether the property should be acquired based on the flood BCR. Economic costs are incurred when a property is acquired using funds from various federal and/or local grants. Direct benefits are accrued from the acquisition based on the avoided annualized flood losses throughout the remaining economic life of the property. Generally, a ratio higher than 1 indicates that the scenario would have a net financial benefit to the community.

To determine damages from probabilistic floods, we calculate projected flood losses using the Average Annualized Loss (AAL) value of all residential properties in the study area. The AAL represents the discounted loss that a property will experience over its remaining economic life course as a result of probabilistic coastal in riverine flooding. The AALs used in this study were calculated by AIR Worldwide Corporation, a pioneer in the catastrophe modelling industry (AIR, 2019). We used the recommended US office of Management and Budget (OMB, 2016) discount rate of 2.8%, and a remaining economic life of 30 years for the property. Previous research in the study area also applied similar values for discounted property buyouts (Atoba et al., 2020). Generally, buyout benefits are calculated for each parcel with the formula:

Benefitsi=∑ilAALi(1+r)l

where l is the remaining economic life of the property in years, r is the discount rate, and i is the buyout property.

4.3. Creating a selection framework for flood and contaminant-prone property acquisition

The buyouts’ BCR for flood and contaminant-prone properties informed the selection framework in Fig. 4. All properties with BCR greater than or equal to 0.75 are prioritized. This is in line with the federal eligibility requirements which qualifies properties as cost effective for FEMA buyouts if they have a BCR of at least 0.75 (FEMA, 2013). This also allows for the acquisition of clusters of properties without necessarily excluding them for buyouts if they do not have a BCR of 1 or higher.

Fig. 4.

Fig. 4.

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Selection framework for flood and Contaminant buyouts BCR.

The flood and contaminant buyout selection framework (see Fig. 4) ensures that properties with higher return on investments are prioritized as buyouts. The selection criterion is divided into 3 categories based on the extent of economic return and risk from flood and contaminants. Tier 1, the buyout category with the highest priority, comprises all properties with high flood BCRs, thereby automatically making them cost effective for buyouts. These include all properties primarily selected from the cost benefit calculus rather than any factor related to flood and contaminant risk. Tier 1 also covers properties which have both high BCRs as well as high flood and contaminant risk score. This ensures that although these properties are cost effective for flood buyouts, they also have high exposure to contaminant transferal, thereby making a better case for their acquisition using flood buyouts programmatic funds. However, because of the strict selection criteria, only a limited number of properties meet this requirement.

Tier 2 buyouts relax the selection to include either properties with high flood BCR or high flood and contaminant risk score. This appears to be the most optimal selection of buyouts as properties with higher BCRs have the potential of offsetting properties which have lower BCRs but higher flood and contaminant risk. Although this tier excludes BCRs for selected properties, the risk framework already factors in the property’s exposure to flooding in determining its eligibility for being acquired using flooding program funds. The composite risk score in this tier ensures that the properties are either highly exposed to contaminant transfer or have experienced enough flooding and to be considered candidates for flood buyouts. Tier 3 buyouts, on the other hand, represent properties with high flood BCRs but medium risk scores. Properties would not be buyout eligible if they do not meet a minimum BCR of 0.75 irrespective of their flood risk or contaminant risk score.

5. Results

5.1. Benefits and cost of flood and contaminant prone buyouts

The selection framework resulted in five buyout scenarios in Galena Park. Table 1 shows the summary description of the buyout selection, which corresponds with the selection framework in Fig. 4. The flood only buyouts are categorized as Tier 1, implying that they should be prioritized since the use of flooding dollars is priority. The Tier 1 buyouts that prioritize both flood and contaminant risk require that the property has both a BCR greater than 0.75 and flood risk higher than 10. Tier 3 buyouts represent the least of the selection criteria in terms of strictness and allow for properties to be selected either if BCR is greater than 0.75 or composite risk score is between 5 and 10.

Table 1.

Scenario summary and relationship with selection framework.

Scenario Tier Risk Type Description
F1 Tier 1 Flood only All properties with BCRs ≥ 1
F2 Tier 1 Flood only All properties with BCRs ≥ 0.75
C1a Tier 1 Flood and contaminants BCR ≥ 0.75 and Risk Score ≥ 10
C1b Tier 2 Flood and contaminants BCR ≥ 0.75 or Risk Score ≥ 10
C2 Tier 3 Flood and contaminants BCR ≥ 0.75 or Risk Score 5 ≥ x < 10
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The selection process identified between 2 and 281 residential properties as candidate flood and contaminant buyouts in Galen Park depending on the selection scenario, with overall BCRs from these buyouts ranging between 0.149 and 1.122 (See Table 2). This result indicates the overall potential of identifying cost effective strategies of combining flood and contaminant risk and exposure as buyout criteria. Scenario F2, which represents a flood only selection criteria, displays the scenario with the highest return on investment, with a savings of $1.12 for every $1 spent on property acquisition and an average BCR of 1.22 for selected buyout candidates. This scenario results in the acquisition of about 17 properties costing about $1.8 million for acquisition but benefits or avoided damages of over $2 million throughout the remaining economic life of the property. The scenario with the second highest on investment is scenario F1, which is also a flood only scenario, resulting in 50 properties as suitable candidates for buyouts. This scenario generates almost a 1 to 1 ratio of cost-benefits. The third Tier 1 scenario generates just 2 properties as candidate buyouts with a 0.718 return on investment for every dollar spent on property acquisition. It is not surprising that the highest return on investments comes from flood only scenarios as there was no economic consideration for the cost of contaminant transferal in the Benefit-Cost calculus.

Table 2.

Summary of cost and benefits of Flood and contaminant buyout scenarios.

Scenario Tier No of properties Total Cost ($ million) Total Benefit ($ million) Total BCR Minimum Property BCR Maximum Property BCR Mean Property BCR
F1 Tier 1 17 1.879 2.109 1.122 1.006 2.642 1.228
F2 Tier 1 50 4.968 4.676 0.941 0.75 2.642 0.964
C1a Tier 1 2 0.152 0.135 0.756 0.757 0.809 0.78
C1b Tier 2 121 14.934 6.2 0.415 0.053 2.642 0.546
C2 Tier 3 281 365.76 54.564 0.149 0.044 2.642 0.175
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Tier 2 candidates represent the next level of priority and consist of properties with either high flood or contaminant flood risk. This is represented by scenario C1b which results in 121 properties as candidate buyouts. Unsurprisingly, the cost benefit ratio is relatively lower than those of the flood only scenario. The scenario shows that over $6 million will be accrued as avoided flood losses if these properties are acquired and returned to vacant open spaces. The BCR is just above half and is the fourth highest of all the scenario modeled in the study area. Tier 3 candidates represent the least in terms of economic benefits if selected as candidate buyouts, with a BCR of just 0.175. The selection criteria also led to the highest number of residential properties being selected as potential buyout candidates with about 281 properties selected for buyouts. This scenario represents the least cost-effective approach of combining flood and contaminant buyouts for the study area.

5.2. Spatial distribution of flood and contaminant-prone buyout candidates

The spatial distribution of buyout candidates reflects similar patterns as seen in the flood risk score of the residential properties in the study area. As shown in Fig. 5, Tier 1 candidates are widely distributed across the study area, with a few properties within the FEMA floodplains and several others beyond the regulatory floodplain. This also reflects the historical pattern of flood damage in the study area, as well as properties that were damaged after Hurricane Harvey. Tier 2 candidates, on the other hand, are more clustered, especially because of the criteria of proximity to contaminant sites. Several Tier 2 properties would also qualify for traditional FEMA buyouts as they fall within the regulatory floodplain. Other Tier 2 properties can be found in the southern portion of the study area and are selected as candidates primarily due to proximity to contaminant sites. Fig. 5 shows that several Tier 2 buyout candidates are also in proximity to other Tier 1 candidates, indicating the potential benefit of shared flood risk reduction.

Fig. 5.

Fig. 5.

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Different Tier of Flood and Contaminant Buyouts Candidates in Galena Park.

6. Discussion

This study identified properties in a residential community with high exposure to industrial contaminants and flooding by using a combination of spatial analysis and benefit cost analysis. Our findings provide an opportunity for decision makers to include factors beyond traditional flood risk requirements in buyout decision-making. This proactive multi-hazard approach can prevent household exposure to potential contaminant transfer in addition to benefits accrued from avoided flood losses throughout the remaining economic life of a property. Additionally, our multi-hazard approach provides planners the opportunity of using acquired properties as open space which may provide flood and contaminant buffer to existing developments that are not cost-effective for buyouts.

This case study highlights two important results. First, it shows what is previously known that properties with the highest flood risk have the highest return on investment for buyouts. This is primarily because the avoided losses used in the benefit cost calculations are based on average annualized loss estimates and historic damages that only occur from exposure to flood hazards. The flood only results also supports previous findings that high flood risk properties such as those within the 100-yr floodplain, and those with repetitive or significant one-time losses are automatically cost-effective as property buyouts (Conrad et al., 1998, Zavar, 2015).

Second, the results indicate that flood buyout funds can be leveraged for acquiring additional properties based on their proximity to toxic release sites in addition to their risk of flooding. The number of properties that can be acquired are significantly increased under this more inclusive scenario (scenario C1b) that accounts for contaminant risk factors in addition to flood risk, thereby removing more people from potential exposure to harmful contaminants. The results indicate that combining proximity to contaminant sites as a requirement for flood buyouts represents a return of investment of $0.54 for every dollar spent on property acquisition. This reduced amount of economic benefit compared to that of flood only buyouts is expected because property acquisition cost-benefit calculus does not account for proximity to contaminant sites. While this may appear to be the appropriate thing to do by removing people from contaminant-prone buildings, a moral expectation, contaminant exposure does not count towards avoided flood loss in a benefit-cost analysis.

Although adding contaminant risk to flood buyout selection criteria results in a reduced BCR, it provides a promising signal for decision makers in that including proximity to contaminant sites as a potential reason for flood-related buyouts can produce positive BCRs. For example, scenario C1a, which prioritizes both flood and contaminant risk, generated 2 properties with an average BCR of almost 1. Although the number of properties eligible for both flood and contaminant buyout are quite small, it can be offset by relaxing the selection criteria to include properties with high contaminant exposure, even if their flood buyout BCR is low, as seen in scenario C1b. This is important because even for flood buyouts, only a handful of properties have high BCRs; the majority of buyout candidates leverage other property’s high BCRs to enable a higher number of properties to be acquired so as to ensure maintenance costs of the resulting vacant land are spent efficiently post buyout. Previous studies have also found that not all properties in a selected area are completely cost-effective for buyouts (see Kousky and Walls, 2014, Tate et al., 2016). Hence, high BCR properties can be used to offset low BCR properties. The extent and level of how these can be combined is left to local decision makers.

While the results in this study suggest that BCR reduces when contaminant flood risk is considered as a criterion for flood buyouts, the spatial configuration of the buyout candidates is worthy of further examination. As seen in Fig. 5, Tier 1 candidates seem to have a scattershot distribution primarily because of a focus on cost-benefit calculus. The Tier 1 flood only buyout candidates in the study area typify existing buyout programs, which rarely result in creating open space clusters and can leave local communities with the burden of maintaining small, isolated vacant parcels (Freudenberg et al., 2016, Maly and Ishikawa, 2013, Zavar and Hagelman, 2016). The lack of spatial clusters from this flood only buyout programs which focus solely on BCRs provides little ecological benefits even after the property is returned to a vacant open space after buyouts (Freudenberg et al., 2016).

The results in our study show that clustering of property buyouts can occur if exposure to contaminant facilities is factored into the selection criteria. The Tier 2 candidates in this analysis have better spatial clusters because their selection is based on both flood risk and proximity to potential contaminant sites. Although their individual property related BCRs are lower than those of the flood only buyouts, they also have a high composite flood and contaminant risk score. This implies that, even though they might not be the most cost-effective candidate for buyouts, they will still incur significant avoided flood losses in addition to the benefits of removing those properties and their residents from exposure to potential contaminants. These potential buyout properties would be converted to effective open spaces which cluster around industrial sites and provide better opportunities to serve as buffer to existing residential developments within the community.

Although the costs of Buyouts are borne mostly by the federal government, and partly by local governments, the benefits are more general in the form of open space restoration, reduction in the use of local resources for disaster response, and the potential of repurposing these open spaces for other ecological benefits. Additionally, returning the properties exposed to contaminant transfer back to vacant open spaces provides other opportunities such as restoring native vegetation, improved property value due to recreational open spaces, and biodiversity conservation (Harter, 2007, Geoghegan, 2002, Crompton, 2005, Hausmann et al., 2016).

7. Conclusion

This paper addressed the important question of whether flood-related property buyouts can be an economically viable means to acquire contaminant-prone properties in vulnerable locations. Through spatial proximity analysis and a cost-benefit calculus, this paper highlights the importance of identifying high risk properties for flood buyouts and emphasizes the benefits of clustering buyouts based on their proximity to contaminant sites, thereby fostering larger and more flood effective open spaces. Results show that flood only buyouts remain the most cost effective, however proximity to contaminant sites provide opportunities for other buyouts that are not just based on cost effectiveness. While the addition of these criteria does undermine the overall cost effectiveness of flood-related property acquisition, it provides opportunities for decision makers to identify properties that are likely to benefit from both reduced flood and contaminant risk in the future. Overall, our analysis identified about 50 flood-only buyouts and over 200 flood and contaminant candidate buyouts in Galena Park Texas.

Although our scenario analysis provides feasible buyout scenarios, decisions regarding selection metrics and the weight associated with each selection scenario is up to local decision makers who are in the best position to address local contextual factors as well as community desires. Granted, the decision to acquire either flood prone or contaminant prone properties may be difficult to make, especially for local communities who need to balance the loss of tax base with hazard resiliency. While our research did not focus on how local communities deal with the optimal allocation of mitigation funding, nevertheless, our study presents a systematic, geospatial data driven method that can be useful to many communities who consider the effective use of federal funds in purchasing flood-prone properties. This approach builds on an existing funding program for buyouts and call on local communities to seek other intuitive selection methods to cluster buyouts while also maximizing public health outcomes through reduced exposure of residents to potential contaminants. This approach can help local communities to stretch federal funds thereby ensuring the efficient use of these resources.

This case study is just a first step in identifying the potential for a multi-hazard mitigation strategy. Additional research and modeling are necessary to address some of the limitations and gaps in our study. Future work should focus on the uncertainties associated with combining multi-hazard BCRs as a criterion for decision making for local communities. A robust decision-making approach which considers uncertainties provides decision makers a better avenue for making informed decisions based on data uncertainty and resource distribution (see example in Mobley et al., 2020). Further, improved hydrology and hydrographic analysis is needed to better estimate the distribution of flood waters, thereby identifying the potential of contaminant transfer to each building in the selected study area. Estimating the monetary costs and benefits of contaminant transfer continues to be a gap in public health research and could contribute immensely to harnessing available federal funds for the purpose of multi-hazard mitigation.

Funding

This research has been funded by the Environmental Protection Agency, STARR Grant, Award# 84004601, and the National Institute of Environmental Health Sciences Superfund Grant #P42ES027704–01.

Footnotes

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

The authors do not have permission to share data.

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