13 Jun 2025

User Guidelines on Catchment Post-Wildfire Hydrological Modeling

Abstract: Wildfires significantly alter watershed hydrology by increasing runoff due to reduced infiltration from soil-water repellency. To predict long-term wildfire impacts, a coupled framework was developed to simulate postfire changes in soil hydraulic properties, infiltration, and hydrological response. This framework integrates Wildfire-Induced Soil Hydraulic (WISH) Factors with a Soil-Moisture Threshold (SMT) formulation in the Green and Ampt infiltration model, representing reduced infiltration due to water repellency. Postfire inputs, including burn severity, soil type, and land use, are formatted for the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model to ensure realistic hydrological simulations. The approach was applied to the 41.7 km² Upper Arroyo Seco watershed in northeast Los Angeles County, where 95% of the area was burned during the August 2009 Station Fire. Hydrological simulations effectively captured increased water repellency and excess runoff following postfire rainfall, demonstrating the model’s ability to represent wildfire-induced watershed changes and improve postfire hydrological assessments.

20 Jun 2024

Spatial Variations in Vegetation Fires and Emissions in South and Southeast Asia during COVID-19 and Pre-pandemic

Abstract: Vegetation fires are common in South/Southeast Asian (SA/SEA) countries. However, few studies focused on vegetation fires and the changes during COVID compared to pre pandemic. This study fills an information gap and reports total fire incidences, total burnt area, type of vegetation burnt, and total particulate matter emission variations. Results from the short term 2020 COVID versus 2019 non COVID year showed a decline in fire counts varying from -2.88 to 79.43%. The exceptions in South Asia include Afghanistan and Sri Lanka, and Cambodia and Myanmar in Southeast Asia. The burnt area decline for 2020 compared to 2019 varied from -0.8% to 92% for South/Southeast Asian countries, with most burning in agricultural landscapes than forests. Several patches in S/SEA showed a decrease in fires for the 2020 pandemic year compared to long term 2012–2020 pre pandemic record, with Z scores greater or less than two denoting statistical significance. However, on a country scale, the results were not statistically significant in both S/SEA, with Z scores ranging from -0.24 to -1, although most countries experienced a decrease in fire counts. The study highlights variations in fires and emissions useful for fire management and mitigation.

10 Jun 2024

Post-wildfire Curve Number Estimates for the Southern Rocky Mountains in Colorado, USA

Abstract: The curve number method first developed by the USDA Soil Conservation Service (now the Natural Resources Conservation Service) is often used for post-wildfire runoff assessments. These assessments are critical for land and emergency managers making decisions on life and property risks following a wildfire event. Three approaches (i.e., historical event observations, linear regression model, and regression tree model) were used to help estimate a post-wildfire curve number from watershed and wildfire parameters. For the first method, we used runoff events from 102 burned watersheds in Colorado, southern Wyoming, northern New Mexico, and eastern Utah to quantify changes in curve number values from pre- to post-wildfire conditions. The curve number changes from the measured runoff events vary substantially between positive and negative values. The measured curve number changes were then associated with watershed characteristics (e.g., slope, elevation, northness, and eastness) and land cover type to develop prediction models that provide estimates of post-wildfire curve number changes. Finally, we used a regression tree method to demonstrate that accurate predications can be developed using the measured curve number changes from our study domain. These models can be used for future post-wildfire assessments within the region.