Predictive Understanding of Links Between Vegetation and Soil Burn Severities Using Physics‐Informed Machine Learning

Earth s Future, Journal Year: 2024, Volume and Issue: 12(8)

Published: Aug. 1, 2024

Abstract Burn severity is fundamental to post‐fire impact assessment and emergency response. Vegetation Severity (VBS) can be derived from satellite observations. However, Soil (SBS) assessment—critical for mitigating hydrologic geologic hazards—requires costly laborious field recalibration of VBS maps. Here, we develop a physics‐informed Machine Learning model capable accurately estimating SBS while revealing the intricate relationships between soil vegetation burn severities. Our classification uses VBS, as well climatological, meteorological, ecological, geological, topographical wildfire covariates. This demonstrated an overall accuracy 89% out‐of‐sample test data. The exhibited scalability with additional data, was able extract universal functional severities across western US. had largest control on SBS, followed by weather (e.g., wind, fire danger, temperature), climate annual precipitation), topography elevation), characteristics organic carbon content). relative processes changes regions. revealed nuanced SBS; example, similar lower wind speeds—that is, higher residence time—translates SBS. transferrable develops reliable timely maps using publicly accessible providing science‐based insights managers diverse stakeholders.

Language: Английский

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A Geospatial Analysis Approach to Investigate Effects of Wildfires on Vegetation, Hydrological Response, and Recovery Trajectories in a Mediterranean Watershed

Hydrology, Journal Year: 2025, Volume and Issue: 12(3), P. 47 - 47

Published: March 4, 2025

Wildfires are frequently observed in watersheds with a Mediterranean climate and seriously affect vegetation, soil, hydrology, ecosystems as they cause abrupt changes land cover. Assessing wildfire effects, well the recovery process, is critical for mitigating their impacts. This paper presents geospatial analysis approach that enables investigation of effects on hydrology. The prediction regeneration potential period needed restoration hydrological behavior to pre-fire conditions also presented. To this end, catastrophic occurred August 2021 wider area Varybobi, north Athens, Greece, used an example. First, extent severity fire its effect vegetation conducted using satellite imagery. history fires specific then analyzed remote sensing data regrowth model developed. affected was systematically analyzed. spatially distributed form order delineate areas which immediate interventions required rapid basin. response estimated based developed models. Curve Numbers post-fire runoff estimations were found be quite similar those derived from measured data. alignment shows SCS-CN method effectively reflects watershed, supports use assessing wildfire-affected areas. results proposed can provide important protection

Language: Английский

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Groundwater Vulnerability in the Aftermath of Wildfires at the El Sutó Spring Area: Model-Based Insights and the Proposal of a Post-Fire Vulnerability Index for Dry Tropical Forests

Fire, Journal Year: 2025, Volume and Issue: 8(3), P. 86 - 86

Published: Feb. 21, 2025

In response to the escalating frequency and severity of wildfires, this study carried out a preliminary assessment their impact on groundwater systems by simulating post-fire effects recharge. The focuses El Sutó spring area in Santa Cruz, Bolivia, region that is susceptible water scarcity frequent wildfires. United States Geological Survey (USGS) Soil-Water-Balance model version 2.0 was utilized, adjusting soil texture infiltration capacity parameters reflect changes induced wildfire events. findings indicated significant decrease recharge following hypothetical high-severity wildfire, with an average reduction approximately 39.5% first year post-fire. A partial recovery modeled thereafter, resulting estimated long-term 10%. Based these results, provisionally classified as having high vulnerability shortly after moderate extended period. Building model-based impacts, Fire-Related Forest Recharge Impact Score (FRIS) proposed. This index grounded properties dynamics designed assess hydrological wildfires dry tropical forests. Although remain exploratory, they offer predictive framework intended guide future studies inform strategies for managing impacts resources.

Language: Английский

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Digital soil mapping of soil burn severity

Soil Science Society of America Journal, Journal Year: 2024, Volume and Issue: 88(4), P. 1045 - 1067

Published: June 14, 2024

Abstract Fire alters soil hydrologic properties leading to increased risk of catastrophic debris flows and post‐fire flooding. As a result, US federal agencies map burn severity (SBS) via direct observation adjustment rasters burned area reflectance. We developed unique application digital mapping (DSM) SBS in the Creek which 154,000 ha Sierra Nevada. utilized 169 ground‐based observations combination with raster proxies forming factors, pre‐fire fuel conditions, fire effects vegetation build model (DSMSBS) using random forest algorithm compared DSMSBS established map. The had cross‐validation accuracy 48%. technique 46% agreement between field pixels. However, since is manual, it could not be cross‐validation. produced class uncertainty maps, showed high prediction probabilities around observations, low away from observations. aid assessment teams sample prioritization. report 107 km 2 more classified as moderate technique. conclude that blending factors based can improve mapping. This represents shift validating remotely sensed reflectance imagery toward quantitative landscape model, incorporates both soils information directly predict SBS.

Language: Английский

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Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severity

Ecological Informatics, Journal Year: 2024, Volume and Issue: 83, P. 102793 - 102793

Published: Aug. 23, 2024

Language: Английский

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