Narrative
Destructive Wildfires in California and Important Government Policies
Introduction
In the summer of 2023, the York Fire scorched over 93,000 acres of California’s Mojave Desert, displacing hundreds of residents and obliterating entire neighborhoods. Yet, while the flames burned indiscriminately, their aftermath did not: low-income households, renters, and communities of color faced prolonged displacement, inadequate insurance payouts, and systemic barriers to recovery (Hahn et al. 2022; Hennighausen & James 2024). This project interrogates the intersection of wildfires and social vulnerability in California, arguing that systemic inequities—embedded in both environmental policy and data collection practices—amplify disaster risks for marginalized groups while obscuring their lived experiences (Thomas et al. 2022; CDC 2022). By synthesizing three datasets—the CDC’s Social Vulnerability Index (SVI) (CDC 2022), CAL FIRE’s California Wildfire Perimeters (CAL FIRE, 2023), and the U.S. Drought Monitor (NDMC et al. 2023)—with scholarly literature on environmental justice, this narrative seeks to answer two critical questions:
- Do counties with varying SVI Variables experience higher risk and recovery from wildfires?
- How does drought severity impact the spread and intensity of wildfires across the state?
These questions guide our analysis of how structural inequalities, from credit access disparities (Holmes 2019, as noted in preliminary research) to underfunded infrastructure, shape disaster outcomes. For instance, the SVI’s “housing and transportation” theme—which excludes unhoused populations (CDC 2022)—fails to account for the 45% of manufactured housing residents living in high-risk Wildland-Urban Interface zones (Pierce et al. 2022). Such gaps in data collection mirror gaps in policy, leaving marginalized communities disproportionately exposed to both fires and their aftermath (Gabbe 2020). Furthermore, drought severity, measured by the U.S. Drought Monitor (NDMC et al. 2023), has intensified fire risks in regions like the Central Valley, where aging water infrastructure and agricultural reliance exacerbate vulnerabilities (Goss et al. 2020).
While some studies claim affluent communities face higher wildfire risks due to “natural amenity migration” (Thomas et al. 2022), others demonstrate that poverty, race, and housing precarity—not geography—dictate survival (Masri et al. 2021; Davies et al. 2018). This project bridges these divides, showing how overlapping vulnerabilities (e.g., uninsured renters in fire-prone mobile homes) create compounding crises (Pierce et al. 2022). By centering voices excluded from datasets—such as undocumented immigrants omitted from census counts (CDC 2022) or Indigenous communities fighting cultural erasure in fire management policies (Steelman 2016)—this narrative challenges the myth of “natural” disasters. Instead, it frames wildfires as political phenomena, demanding not only better data but reparative justice (Versey 2021).
In the following sections, we explore how silences in the SVI, wildfire, and drought datasets perpetuate cycles of harm, how historical policies like redlining concentrate risk in marginalized neighborhoods (Tierney et al. 2022), and why inclusive storytelling is vital for equitable disaster response.
The CAL FIRE dataset reveals that 55.5% of large wildfires in California between 2019–2023 were ignited by lightning, while 14.48% stemmed from power line failures—a human-made cause disproportionately linked to aging infrastructure in rural and low-income counties (Pierce et al. 2022; Gabbe 2020). Notably, 26.56% of fires remain classified as “unknown” in origin, underscoring gaps in data transparency that obscure systemic risks, such as corporate negligence or inadequate maintenance of utility networks in marginalized communities (Steelman 2016).
Figure 1. Pie Chart of the Different Causes of Wildfire in California
Figure 2. Heat Map of California Wildfires from 2013 – 2024
The spatial distribution of fire damage, visualized in the map, further exposes inequities: regions like Butte County, where 32% of residents lack credit access (Holmes 2019), experienced “destroyed” (>50% damage) outcomes at higher rates, while affluent coastal counties like Santa Barbara saw more “minor” (10–25%) impacts despite similar fire exposure. This aligns with studies showing that rural, low-income communities—often dependent on manufactured housing and lacking evacuation resources—face compounded risks from both fire and recovery barriers (Masri et al. 2021; Hahn et al. 2022).
The power line causation trend intersects starkly with the Social Vulnerability Index (SVI): counties with high “housing/transportation” vulnerability scores, such as Sonoma and Shasta, correlate with clusters of power line-ignited fires. These regions often lack updated electrical grids and suffer from delayed emergency response due to underfunded infrastructure (Gabbe 2020). Meanwhile, the map’s “inaccessible” damage designation—frequent in remote, high-poverty areas like the Sierra foothills—reflects how marginalized communities are left off-grid in post-disaster assessments, exacerbating their invisibility in policy responses (Tierney et al. 2022). Scholarly work by Thomas et al. (2022) complicates this narrative, noting that wildfire risk is not solely dictated by poverty: affluent communities migrating to “natural amenity” zones (e.g., Malibu) also face high fire exposure. However, their adaptive capacity—evidenced by robust insurance coverage and political influence—contrasts sharply with the systemic neglect of rural, Indigenous, and low-income populations (Davies et al. 2018; Versey 2021).
Social Vulnerability
Insurance and Household Income
In the wake of natural disasters, many of those affected end up displaced and unable to replace their belongings. Insurance and household income are major vulnerability factors in determining an individual’s ability to adapt and recover. Households with low income are more likely to rent and spend a majority of their monthly income on rent; thus, these individuals have little money saved to cover unexpected damage, such as those threatened by wildfires (Tierney et al. 2022). Additionally, without insurance and credit, those who suffer lack the resources and funds to recover their belongings and return to their housing situation. These are just a few reasons why many socially vulnerable residents become displaced.
Trinity County and Mono County Stand Out as Having the Highest Population Percentage of Uninsured Individuals in California
Figure 3. Comparison of Population Percentages of Uninsured Individuals Across Different California Counties
In Figure 3 shown above, the box plot compares the percentage of uninsured individuals by plotting the different quartiles and potential outliers. We’ll be looking into Mono County and Trinity County, the right-most observations. 14.08% of Mono County is uninsured while similarly 13.85% of Trinity County’s population is uninsured. Referring back to the Map of California Fires, we see that Mono County is not in the line of fire; but, Trinity County has had many fires between 2013 and 2024.
Why do these counties have similar percentages of uninsured individuals when Trinity County seems to have more wildfire risk? To reduce the amount of possible displacement and loss of belongings, it is important to push for agendas that support those who are uninsured, especially when they historically have more wildfire risk. We can also look further into other comparisons between these 2 counties to see where improvements can be made.
Trinity County Has Higher Population Percentages for Measures Regarding Household Cost-Burden, Mobile Homes, Poverty, and No Vehicle
Figure 4. Comparison of Population Percentage of Different Vulnerability Measures Between Mono and Trinity County
Figure 4 compares population percentages for individuals who are uninsured, house cost-burdened, below the 150% poverty estimate, and have no vehicle. There is also a bar to show the percentage of mobile homes in both counties. As we can see from the side-by-side bar chart, Trinity County has a higher percentage across all measures other than uninsured individuals. This further addresses the need for an agenda that addresses these disparities across California counties by ensuring that residents have the proper resources and support to recover after wildfires. Developing frameworks that assess individuals’ vulnerabilities are more likely to encourage change that prioritizes the reduction of climate risks for everyone (Versey 2021).
Trinity County’s population percentage of housing cost-burdened residents is almost 5% higher than Mono County’s. By spending most of their income on housing, these residents may struggle to afford to replace necessities and belongings lost to wildfires. Trinity County’s population percentage for individuals below the 150% poverty estimate is over 17% above Mono County’s. Those who receive significantly less income than the poverty line may have low adaptive capacity, meaning that they cannot afford certain fire mitigation services and renters will not be eligible for as much federal housing assistance as homeowners (Davies 2018).
Low Income and Housing Prices: A Case Study of Camp Fire and Its Effects
Furthermore, low-income communities experience a higher frequency of wildfires which could be due to “differences in land management and/or the availability of resources for combatting wildfires before they grow large” (Masri 2021). Additionally, there is a contrast between rural and urban area census tracts, with rural areas having a greater land area affected by wildfires. Rural areas also had a “higher proportion of households without computers, internet, use of public transportation, and median incomes < $30,000 / year” compared to urban areas (Masri 2021). Due to these factors, rural areas may be more vulnerable to wildfires and their long-term consequences.
Interestingly, while lower-income communities may experience a higher wildfire frequency, higher-income neighborhoods tend to have a larger wildfire burn area. This may be due to wealthier communities living in “more vegetated fire-prone WUI areas on the outskirts of town within urban Census tracts” (Masri 2021). The WUI refers to wildland-urban interface areas which are areas of human development that combine with unoccupied wildlife areas and are at higher risk of wildfires.
A notable case is Butte County, which experienced the Camp Fire, one of the most destructive fires in California, it burned 11,000 homes, with low-income housing being disproportionately affected, and displaced around 50,000 people.
Butte County with relatively high average low-income population makes them vulnerable to impacts of wildfire
Figure 5. Low Income and Minority Population Estimates Across California Counties from 2018-2022
In Figure 5, above, which was created from the SVI dataset, Butte County has a relatively high proportion of low-income individuals. Furthermore, the fire started in a primarily rural, forested area coupled with the fact that there was “unusually dry vegetation and Red Flag conditions including strong winds and low humidity” which exacerbated the spread of the fire (Hennighausen 2024). These factors make residents of Butte County especially vulnerable to wildfires as they may face challenges recovering and relocating from the fire.
The displacement patterns of Butte County residents aftermath of the Camp Fire can be observed. Hennighausen’s results show that many of the evacuees stayed within 150 miles of the fire footprint and moved to low-fire risk areas. In addition, people moved toward areas that had lower unemployment rates and places with higher median incomes had lower evacuees moving into their areas. With all of these factors in mind, neighboring cities that were in low-fire-risk zones experienced an increase in housing prices as many evacuees moved into their cities. For example, Chico experienced an increase in rental prices, “contributing to homelessness and labor shortages” (Hennighausen 2024). This increase in rental prices in neighboring cities makes it difficult for low-income individuals who were affected by the fire to relocate and find housing, but also low-income residents of Chico may be priced out of their homes.
Minority Communities & Transportation
Transportation is a factor of vulnerability because it demonstrates if someone is able to sustain the cost of having a vehicle and if they don’t their access to public transportation (or lack thereof) constricts their job mobility and access to the workforce. Moreover, lack of access to transportation means that a person/people can be stranded and unable to evacuate in time/at all once a wildfire does break out. Lack of access to transportation can increase the impact of other vulnerability factors such as those with disabilities, the elderly, low income, and remote populations.
Minority information counts as a factor of vulnerability because it is a variable that is important to gain a nuanced understanding of communities and the context in which people are coming from. This trait intersects with variables such as socioeconomic status. Moreover, some communities might have language barriers delaying their wildfire response because of lack of resources/announcements published in languages other than English. Moreover, minority and immigrant groups tend to be less trustful of government agencies and are less likely to seek help.
California Droughts and Implications
Although there are a variety of causes that can ignite wildfires such as the sparks created by powerlines, we attempt to investigate whether drought has played a role in the increase in the occurrence of wildfires in California.
Drought Is One Factor That Initiates Wildfires in California
Figure 6. Line Graph Depicting Drought Conditions in California from 2013 – 2025
Figure 6 is a line graph created from the historical drought dataset from the National Integrated Drought Information System (NDIS). The x-axis shows the change in time from the period of 2001 to 2025 and the y-axis represents the percentage of states affected by the drought. Moreover, I chose the variables “Exceptional Drought (D4)” and “Extreme Drought (D3)” when making the line graph as it shows what years were most affected by the drought in California. When taking a glance at the chart, there is no obvious pattern. However, you can see that there are a couple of spikes. Specifically, from 2014 ~2017 and from mid-2020 to 2023, there were massive spikes in the areas affected by the drought in California.
Figure 7. Line Graph Depicting The Number of Wildfires in California from 2013 – 2024
When comparing Figure 6 to Figure 7, there are some overlapping periods when there is a concurrent spike in extreme drought conditions and the prevalence of wildfires in California. Specifically, from 2020 to 2022, drought conditions began to worsen as seen in Figure 1 and the number of California wildfires began to increase and reached its peak in 2020. Moreover, is it evident that drought conditions were exacerbated from 2014 till 2017. Therefore, “California has been under drought conditions since 2012, and the drought worsened considerably in the winter of 2013/14, which fueled an extreme fire season in 2014” and can be seen through the spike of fires starting from 2016 (Yoon 2015). When drought conditions rise, this leads to a lack of moisture in the environment and causes vegetation to dry out. As a result, dry vegetation becomes brittle and highly flammable which helps fuel wildfires. However, there are some periods where the spike of drought conditions does not necessarily match with the influx of wildfires. This can be explained by the fact that although drought severity causes wildfires by drying out vegetation, other factors can cause wildfires such as climate change and human activities.
How Does Human Influence Affect California Droughts?
To further explore the relationship between drought and human activity, we look to a study by Williams and co-authors that examines the anthropogenic influence on the severe California drought during the years 2012 to 2014. California reached the “lowest 3 year running average on record” (Williams 2015). The study utilizes the Penman-Monteith (PM) formula which calculates evapotranspiration affect (PET) and the Palmer Drought Severity Index (PDSI). PET relates to droughts because it measures the potential amount of water that can be evaporated from the soil and PDSI measures soil moisture. This study was able to isolate natural temperature variability and anthropogenic influence using 4 warming scenarios: “(1) linear trend, (2) 50 year low-pass filter (using a 10-point butterworth filter), (3) unadjusted mean trend from an ensemble of climate models, and (4) an adjusted version #3 (Williams 2015). Detailed methods on isolating these two measures can be further explored in the article.
For the drought between 2012-2014, the study claims that anthropogenic warming contribution to the drought was between 8-27%. Through this data, we can discuss the impacts of human contribution to drought and global warming. While the main cause of drought in 2012-2014 was “high atmospheric pressure over the Northeast Pacific that blocked cold-season storms from reaching CA,” humans contributed to making the drought more severe (Williams 2015). While not mentioned in the study, some examples of anthropogenic warming include burning of fossil fuels, deforestation, and irrigation. According to the California Department of Water Resources, 80 percent of all developed water is used by the agricultural sector in California and the department suggests they find a more efficient method to utilize water (water.ca.gov).
How Is Drought Connected To The Social Vulnerability Index?
Not only can droughts increase the risk of wildfires, but they can also affect populations differently. In the case of a wildfire emergency, drinking water access can become a critical issue. Populations in smaller and rural communities may face greater diffculties in finding drinking water if their main source is damanged (water.ca.gov). However, drinking water issues can also occur in urban areas. For example, during the 2017 Tubbs Fire in Northern California in 2017, affected communities had tap water contaminated with benzene due to heat damage to water pipes following the fire (Meadows 2022). In these cases, people with more financial flexibility are less likely to feel burdened when purchasing water for themselves and/or family.
Conclusion
How can social vulnerability predict the affected areas of wildfires in California?
Social vulnerability plays a significant role in predicting which communities are most affected by wildfires. The Social Vulnerability Index highlights that communities with more socioeconomic disadvantages, such as lower income, limited access to transportation, and unstable housing, are disproportionately impacted by wildfires. For example, renters and low-income households, particularly those in manufactured housing, face greater exposure to fire hazards and have lower adaptive capacity to prepare for or recover from disasters (Pierce et al. 2022; Masri et al. 2021). Additionally, rural communities with higher poverty rates and limited access to resources are more vulnerable to wildfires, as they often lack the infrastructure and financial means to mitigate risks or recover quickly (Masri et al. 2021). The SVI data, combined with wildfire perimeter data, can help identify which counties or census tracts are at higher wildfire risks, allowing for targeted interventions.
It is evident that there must be more policies made and programs offered to mitigate wildfire risk for everyone. However, it is important to address these vulnerability factors when creating these agendas in order to mitigate risks for those who are disproportionately affected. These policies can target financial, insurance, and credit assistance for low income and uneducated individuals. We can see some ongoing programs, such as the California FAIR Plan, that aid in obtaining insurance. This Plan also offers policyholders a discount on wildfire portions. While this is a great resource, as of 2020, the FAIR Plan covered less than 3% of residents. Additionally, although some residents do have insurance, we saw during the Eaton Fire that many companies attempted to cancel and prevent renewals on homeowners insurance.
How does drought severity impact the spread and intensity of wildfires across the state?
Drought severity, as measured by the U.S. Drought Monitor (USDM), has a direct and significant impact on the spread and intensity of wildfires in California. Prolonged drought conditions lead to drier vegetation, which serves as fuel for wildfires, increasing both the likelihood and intensity of fires (Westerling et al. 2006). The historical drought data shows that periods of severe drought (D3-D4 levels) correlate with larger and more destructive wildfires. Additionally, climate change has exacerbated drought conditions, leading to earlier snowmelt and longer fire seasons, which further increase wildfire risks (Goss et al. 2020). The combination of drought and high temperatures creates a fire-prone environment, particularly in regions with dense vegetation, making drought severity a critical factor in predicting wildfire behavior and intensity. However, it is crucial to remember that drought and temperature are not the only factors that contribute to wildfires. Other factors like high wind speeds impact wildfire spread greatly.