Search for: All records

Abstract Wildfire records demonstrate worsening patterns coupled with the spread to higher altitudes in several regions, raising the risk of post‐wildfire ground failures. This study investigates the post‐wildfire stability of unsaturated hillslopes against rainfall‐triggered shallow landslides. We developed a new physics‐based analytical framework incorporating wildfire‐induced changes in soil properties and near‐surface processes affecting the hillslope stability. A coupled hydromechanical infiltration model is integrated into an infinite slope stability analysis to simulate temporal changes in the depth profiles of soil water content, pressure head, and the resulting factor of safety (F.S.) of a vegetated slope. We consider the antecedent conditions of soil and vegetation cover, including the recovery phase after the fire, wildfire‐induced alterations in transpiration, and time‐varying infiltration rates. The model is verified against numerical simulations and employed in parametric studies evaluating the effects of wildfire severity and rainfall intensity‐duration. For the cases examined, it was shown that wildfire could reduce the F.S. of slopes by 25%. As a case study, the model successfully captured shallow rainfall‐triggered landslides that occurred in the Las Lomas watershed in California, USA, in 2019, 3 years after the Fish Fire burned the area. The proposed model uses measurable hillslope and wildfire characteristics and can be employed to evaluate the risk of shallow landslides in wildfire‐prone areas. 

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. 

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.