Due to the mixed distribution of buildings and vegetation, wildland-urban interface (WUI) areas are characterized by complex fuel distributions and geographical environments. The behavior of wildfires occurring in the WUI often leads to severe hazards and significant damage to man-made structures. Therefore, WUI areas warrant more attention during the wildfire season. Due to the ever-changing dynamic nature of California’s population and housing, the update frequency and resolution of WUI maps that are currently used can no longer meet the needs and challenges of wildfire management and resource allocation for suppression and mitigation efforts. Recent developments in remote sensing technology and data analysis algorithms pose new opportunities for improving WUI mapping methods. WUI areas in California were directly mapped using building footprints extracted from remote sensing data by Microsoft along with the fuel vegetation cover from the LANDFIRE dataset in this study. To accommodate the new type of datasets, we developed a threshold criteria for mapping WUI based on statistical analysis, as opposed to using more ad-hoc criteria as used in previous mapping approaches. This method removes the reliance on census data in WUI mapping, and does not require the calculation of housing density. Moreover, this approach designates the adjacent areas of each building with large and dense parcels of vegetation as WUI, which can not only refine the scope and resolution of the WUI areas to individual buildings, but also avoids zoning issues and uncertainties in housing density calculation. Besides, the new method has the capability of updating the WUI map in real-time according to the operational needs. Therefore, this method is suitable for local governments to map local WUI areas, as well as formulating detailed wildfire emergency plans, evacuation routes, and management measures.

The severity and frequency of wildfires have risen dramatically in recent years, drawing attention to the term ‘wildland-urban interface’ (WUI), the region where man-made constructions meet flammable vegetation. Herein, we mapped a finer-scale, novel linear WUI for California (CA) based on the intersection of boundaries of wildland vegetation and building footprint. The direct intersection is referred to as a direct WUI, whereas the intersection at 100-m is known as an indirect WUI. More fires were ignited closer to direct WUI than indirect WUI due to their proximity to communities. However, the overlap of past fire perimeters with indirect WUI is greater than that with direct WUI which shows that more areas were burned in the indirect WUI due to embers transported by strong wind gusts during large wildfires. The study’s findings will help land managers and policymakers in controlling fire dangers, land-use planning, and reducing threats to fire-prone communities.

Wildland fires are becoming more destructive and costly in the United States, posing increased environmental, social, and economic threats to fire-prone regions. Quantifying current wildfire risk by considering a wide range of multi-scale, and multi-disciplinary variables such as socio-economic and biophysical indicators for resiliency and mitigation measures, deems inherently challenging. To systematically examine wildfire threats amongst humans and their physical and social environment on multiple scales, a livelihood vulnerability index (LVI) analysis can be employed. Therefore, we produce a framework needed to compute the LVI for the top 14 American States that are most exposed to wildfires, based on the 2019 Wildfire Risk report of the acreage size burnt in 2018 and 2019: Arizona, California, Florida, Idaho, Montana, Nevada, New Mexico, Oklahoma, Oregon, Utah, Washington, and Wyoming. The LVI is computed for each State by first considering the State’s exposure, sensitivity, and adaptive capacity to wildfire events (known as the three contributing factors). These contributing factors are determined by a set of indicator variables (vulnerability metrics) that are categorized into corresponding major component groups. The framework structure is then justified by performing a principal component analysis (PCA) to ensure that each selected indicator variable corresponds to the correct contributing factor. The LVI for each State is then calculated based on a set of algorithms relating to our framework. LVI values rank between 0 (low LVI) to 1 (high LVI). Our results indicate that Arizona and New Mexico experience the greatest livelihood vulnerability, with an LVI of 0.57 and 0.55, respectively. In contrast, California, Florida, and Texas experience the least livelihood vulnerability to wildfires (0.44, 0.35, 0.33 respectively). LVI is strongly weighted on its contributing factors and is exemplified by the fact that even though California has one of the highest exposures and sensitivity to wildfires, it has very high adaptive capacity measures in place to withstand its livelihood vulnerability. Thus, States with relatively high wildfire exposure can exhibit relatively lower livelihood vulnerability because of adaptive capacity measures in place. On the other hand, States can exhibit a high LVI (such as Arizona) despite having a low exposure, due to lower adaptive capacities in place. The results from this study are critical to wildfire managers, government, policymakers, and research scientists for identifying and providing better resiliency and adaptation measures to support the American States that are most vulnerable to wildfires.

The environmental pollution, property losses and casualties caused by wildfires in California are getting worse by the year. To minimize the interference of wildfires on economic and social development, and formulate targeted mitigation strategies, it is imperative to understand the scale and extent of previous wildfire occurrences. In this study, we first investigated the temporal distributions of past wildfires in California divided by size and causes and analyzed the changes observed in the past two decades against the last century. The trend of wildfires in different time scales (yearly and monthly), as well as the distribution of wildfires across different spatial scales (administrative units, climate divisions in California from 2000 to 2019) were also studied. Furthermore, to extract the significant variables on the risk of wildfire occurrence, multivariate analyses of environmental and human-related variables with wildfire densities were carried out. The results show that the wildfire density distribution of the burned area in California conforms to the characteristics of the Pareto distribution. Over the past two decades, the frequency of small (<500 acres), human-caused wildfires has increased most rapidly, and they are widely distributed in central and western California. The wildfire season has lengthened and the peak months have been advanced from August to July. In terms of the variables related to the risk of wildfire occurrence, the temperature, vapor pressure deficit, grass cover, and the distance to roads are crucial. This study reveals the relationship between environmental and social background conditions and the spatial-temporal distribution of wildfires, which can provide a reference for wildfire management, the formulation of future targeted wildfire emergency plans, and the planning of future land use in California.

Past studies reported a drastic growth in the wildland-urban interfaces (WUI), the locations where man-made structures meet or overlap wildland vegetation. There is a perception that damages due to wildfires are mainly located at the WUI. However, there is no clear evidence that wildfire intensity and frequency are highest in these regions. In this work, we have reported the actual occurrences of wildfires with respect to WUI and how much of the WUI are on complex topography in California (CA), the state with the highest burned area and risk of wildfires. We calculated the overlap of the burned area from previous wildfire events in California in the last ten years with the WUI perimeters. Two currently existing WUI definitions are used for this purpose. Furthermore, we also calculated the number of fire ignition points that lie within the WUI perimeters. We found that a very small percentage of wildfire ignitions actually occurred in the WUI areas. Moreover, the overlap between the wildfire burned area and WUI areas was also found to be small. To find out if the wildfires burned in the vicinity of WUI areas, we created buffers around both the WUI areas and the wildfire perimeters separately and computed the impact of buffer distance on the overlap. This behavior has been connected to the importance of firebrand ignition from spot fires in the WUI. Moreover, a majority of WUI areas in CA was found to be situated on complex topography. Therefore, we conclude that in CA, wildfires are not limited to WUI regions only, but their main fire fronts burn farther away from the WUI and are mostly located on complex topography, where controlling large wildfires is more difficult and fire behavior is more complex. Results from this study will give direction for remapping the existing WUI definitions, will be helpful for wildfire management and will benefit policymakers and land managers at the state and local level to focus on the factors that determine the high-risk prone areas for future wildfires.

Wildfire indices are used globally to quantify and communicate a wide range of fire characteristics, including fire danger and fire behaviour. Wildfire terminologies, definitions and variables used to compute fire indices vary broadly. This makes it difficult to compare them under a common framework for regional assessment and for future improvements under changing climate and land-use/land-cover conditions. This paper reviews 24 fire indices used worldwide and proposes a simple framework within which they can be classified based on constitutive inputs used for their computation. We differentiate between constitutive inputs that are raw or directly measurable variables such as fuel, weather and topography (referred to as Level 1 inputs) and calculated constitutive inputs such as fuel moisture (as a function of ecology and hydrometeorology); fire behaviour (as a function of spread, energy, and ignition); and dynamic meteorology. These six calculated constitutive inputs are referred to as Level 2 inputs. Based on this classification, our findings indicate that the Burning Index from the United States National Fire Danger Rating System (NFDRS) and the Fire Weather Index from the Canadian Forest Fire Danger Rating System (CFFDRS), used by many countries worldwide, utilize the most comprehensive set of Level 2 inputs. In addition, the Level 2 input that is most frequently used by all fire indices is fuel moisture as a function of hydrometeorology and the least integrated input is that of fire ignition. We further group the fire indices in three types: fire weather, fire behaviour, and fire danger indices, according to the open literature definition of their predictant outputs and examine the specific constitutive inputs used in their computation. Most fire indices are based on Level 2 inputs (which use Level 1 inputs) and are predominantly fire danger and fire behaviour indices. This is followed by fire indices that use a combination of both Level 1 and Level 2 inputs, separately and are mostly fire danger indices. Only a few fire indices are computed solely with raw Level 1 inputs and are mainly fire behaviour indices. Providing a comprehensive view of the existing wildfire indices’ utilization and computational structure is expected to be a helpful resource for wildfire researchers and operational experts worldwide. 2

Partitioning evapotranspiration (ET) into its primary components, i.e., evaporation (E) and plant transpiration (T), is needed in a range of hydrometeorological applications. Using vegetation index (VI) to obtain spatially resolved T:ET ratio over large areas has emerged as a promising approach in this regard. Here, we assess the effectiveness of this approach in differently managed wheat systems. Results show a weak relation between T:ET and VI in disturbed (i.e., grazed) systems. Flux partitions based on a canonical T:ET vs. VI relation or one derived in a neighboring undisturbed wheat system introduce large errors in disturbed systems, thus underscoring the limits on the transferability of the VI-based ET partitioning approach. The effectiveness of the VI-based approach is found to be related to the strength of correlation between VI and vapor pressure deficit and/or radiation. This correlation metric can help identify settings where the approach is likely to be effective.

High frequency (30 Hz) two-dimensional particle image velocimetry (PIV) data recorded during a field experiment exploring fire spread from point ignition in hand-spread pine needles under calm ambient wind conditions are analysed in this study. As the flame spreads approximately radially away from the ignition point in the absence of ambient wind forcing, it entrains cooler ambient air into the warmer fire core, thereby experiencing a dynamic pressure resistance. The fire-front, comprising a flame that is tilted inward, is surrounded by a region of downdraft. Coherent structures describe the initial shape of the fire-front and its response to local wind shifts while also revealing possible fire-spread mechanisms. Vortex tubes originating outside the fire spiral inward and get stretched thinner at the fire-front leading to higher vorticity there. These tubes comprise circulation structures that induce a radially outward velocity close to the fuel bed, which pushes hot gases outward, thereby causing the fire to spread. Moreover, these circulation structures confirm the presence of counter-rotating vortex pairs that are known to be a key mechanism for fire spread. The axis of the vortex tubes changes its orientation alternately towards and away from the surface of the fuel bed, causing the vortex tubes to be kinked. The strong updraft observed at the location of the fire-front could potentially advect and tilt the kinked vortex tube vertically upward leading to fire-whirl formation. As the fire evolves, its perimeter disintegrates in response to flow instabilities to form smaller fire “pockets”. These pockets are confined to certain points in the flow field that remain relatively fixed for a while and resemble the behavior of a chaotic system in the vicinity of an attractor. Increased magnitudes of the turbulent fluxes of horizontal momentum, computed at certain such fixed points along the fire-front, are symptomatic of irregular fire bursts and help contextualize the fire spread. Most importantly, the time-varying transport terms of the turbulent kinetic energy (TKE) budget equation computed at adjacent fixed points indicate that local fires along the fire-front primarily interact via the horizontal turbulent transport term.