Search for: All records

This study investigates the complexities faced by emergency managers in wildfire-prone areas to uncover pressing issues and potential solutions. Four themes are discerned through three focus group discussions with emergency managers from nine counties across California. First, there is unequal access to resources for both risk assessment and response, with counties that have fewer resources facing significant challenges in effectively managing wildfire risks. Second, effective risk communication depends on the available resources and the unique characteristics of each community. Participants stress the need for improved communication tools to reach vulnerable groups (e.g., seniors, individuals with disabilities, non-English-speaking residents). Third, the complexity and confusion surrounding multi-level collaboration in wildfire management is a recurring theme. Participants note that unclear roles and responsibilities between state and federal agencies hinder response efforts, underscoring the need for better coordination and transparent communication at all levels. Fourth, innovative responses (e.g., creative evacuation strategies, collaborative efforts) are recognized as imperative for managing wildfires and their cascading impacts in resource-constrained areas. The findings highlight that achieving equitable and effective preparation, response, and resilience for vulnerable communities requires a comprehensive understanding of wildfire severity and community susceptibility, coupled with active collaboration among emergency managers, policymakers, and both governmental and non-governmental organizations. 

Post-wildfire mass wasting is a major problem throughout many regions worldwide. Recent dramatic increases in global wildfire activities coupled with a shift in wildfire-prone elevation to higher altitudes raise the need to better predict post-fire rainfall-triggered landslides. Despite its importance, only a limited number of studies have investigated landslide susceptibility in areas hit by wildfires using hydromechanical models. However, most of these studies follow either qualitative or semi-quantitative approaches without explicitly considering the fire’s effects on the impacted area’s physical behavior. This study aims to develop and employ a physics-based framework to generate susceptibility maps of rainfall-triggered shallow landslides in areas disturbed by wildfire. A coupled hydromechanical model considering unsaturated flow and root reinforcement is integrated into an infinite slope stability model to simulate the triggering of shallow landslides from rainfall. The impact of fire is considered through its effects on soil and land cover properties, near-surface processes, and canopy interception. The developed model is then integrated into a geographic information system (GIS) to characterize the regional distribution of landslide potential and its variability considering topography, geology, land cover, and burn severity. The proposed framework was tested for a study site in Southern California. The site was burned in the San Gabriel Complex Fire in June 2016 and experienced widespread landsliding almost three years later following an extreme rainstorm in January 2019. The proposed framework could successfully model the location of observed shallow landslides. The model also revealed a significantly higher likelihood for slope failure in areas burned at moderate to high severities as opposed to unburned and low-burn severity areas. The findings of this study can be employed to predict the timing and general locations of rainfall-triggered shallow landslides following wildfires. 

Globally, land subsidence (LS) often adversely impacts infrastructure, humans, and the environment. As climate change intensifies the terrestrial hydrologic cycle and severity of climate extremes, the interplay among extremes (e.g., floods, droughts, wildfires, etc.), LS, and their effects must be better understood since LS can alter the impacts of extreme events, and extreme events can drive LS. Furthermore, several processes causing subsidence (e.g., ice‐rich permafrost degradation, oxidation of organic matter) have been shown to also release greenhouse gases, accelerating climate change. Our review aims to synthesize these complex relationships, including human activities contributing to LS, and to identify the causes and rates of subsidence across diverse landscapes. We primarily focus on the era of synthetic aperture radar (SAR), which has significantly contributed to advancements in our understanding of ground deformations around the world. Ultimately, we identify gaps and opportunities to aid LS monitoring, mitigation, and adaptation strategies and guide interdisciplinary efforts to further our process‐based understanding of subsidence and associated climate feedbacks. We highlight the need to incorporate the interplay of extreme events, LS, and human activities into models, risk and vulnerability assessments, and management practices to develop improved mitigation and adaptation strategies as the global climate warms. Without consideration of such interplay and/or feedback loops, we may underestimate the enhancement of climate change and acceleration of LS across many regions, leaving communities unprepared for their ramifications. Proactive and interdisciplinary efforts should be leveraged to develop strategies and policies that mitigate or reverse anthropogenic LS and climate change impacts. 

Abstract Recent major investments in infrastructure in the United States and globally present a crucial opportunity to embed equity within the heart of resilient infrastructure decision-making. Yet there is a notable absence of frameworks within the engineering and scientific fields for integrating equity into planning, design, and maintenance of infrastructure. Additionally, whole-of-government approaches to infrastructure, including the Justice40 Initiative, mimic elements of process management that support exploitative rather than exploratory innovation. These and other policies risk creating innovation traps that limit analytical and engineering advances necessary to prioritize equity in decision-making, identification and disruption of mechanisms that cause or contribute to inequities, and remediation of historic harms. Here, we propose a three-tiered framework toward equitable and resilient infrastructure through restorative justice, incremental policy innovation, and exploratory research innovation. This framework aims to ensure equitable access and benefits of infrastructure, minimize risk disparities, and embrace restorative justice to repair historical and systemic inequities. We outline incremental policy innovation and exploratory research action items to address and mitigate risk disparities, emphasizing the need for community-engaged research and the development of equity metrics. Among other action items, we recommend a certification system—referred to as Social, Environmental, and Economic Development (SEED)—to train infrastructure engineers and planners and ensure attentiveness to gaps that exist within and dynamically interact across each tier of the proposed framework. Through the framework and proposed actions, we advocate for a transformative vision for equitable infrastructure that emphasizes the interconnectedness of social, environmental, and technical dimensions in infrastructure planning, design, and maintenance. 

Seasonal variations and climatic events cause fluctuations of water content and temperature in shallow unsaturated soils. Such fluctuations can alter the resilient modulus (MR) of subgrade, which is an important parameter in the design and evaluation of pavements. This paper presents a new model to determine MR of unsaturated subgrade soils under concurrent changes in water content and temperature. The proposed analytical model offers the following two new features distinguishing it from alternative models: (1) the model separately accounts for two different soil water retention mechanisms, namely capillary and adsorption, which enables it to predict MR over a wide range of suctions, and (2) it explicitly incorporates the effect of temperature in the calculation of MR through employing temperature-dependent expressions for matric suction and the soil water retention curve (SWRC). The proposed model showed high accuracy when validated against experimentally measured MR values for several different soils reported in the literature. The presented model is simple and can readily be employed in practice to determine MR of subgrade soils under concurrent variations of water content and temperature.