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Water supply impairment from increased contaminant mobilization and transport after wildfire is a major concern for communities that rely on surface water from fire‐prone watersheds. In this article we present a Monte Carlo simulation method to quantify the likelihood of wildfire impairing water supplies by combining stochastic representations of annual wildfire and rainfall activity. Water quality impairment was evaluated in terms of turbidity limits for treatment by modeling wildfire burn severity, postfire erosion, sediment transport, and suspended sediment dilution in receiving waterbodies. Water supply disruption was analyzed at the system level based on the impairment status of water supply components and their contributions to system performance. We used this approach to assess wildfire‐water supply impairment and disruption risks for a system of water supply reservoirs and diversions in the Front Range Mountains of Colorado, USA. Our results indicate that wildfire may impair water quality in a concerning 15.7–19.4% of years for diversions from large watersheds. Reservoir impairment should be rare for off‐network reservoirs—ranging from at most 0.01% of years for large reservoirs to nearly 2% of years for small reservoirs. System redundancy meaningfully reduced disruption risk for alternative conveyance routes (4.3–25.0% reduction) and almost eliminated disruption risk for a pair of substitutable terminal sources (99.9% reduction). In contrast, dependency among reservoirs on a conveyance route nearly doubled risk of disruption. Our results highlight the importance of considering water system characteristics when evaluating wildfire‐water supply risks. [ABSTRACT FROM AUTHOR]

Concerns over wildfire impacts to water supplies have motivated efforts to mitigate risk by reducing forest fuels. Methods to assess fuel treatment effects and prioritise their placement are needed to guide risk mitigation efforts. We present a fuel treatment optimisation model to minimise risk to multiple water supplies based on constraints for treatment feasibility and cost. Risk is quantified as the expected sediment impact costs to water supplies by combining measures of fire likelihood and behaviour, erosion, sediment transport and water supply vulnerability. We demonstrate the model's utility for prioritising fuel treatments in two large watersheds in Colorado, USA, that are critical for municipal water supply. Our results indicate that wildfire risk to water supplies can be substantially reduced by treating a small portion of the watersheds that have dense, fire-prone forests on steep slopes that drain to water supply infrastructure. Our results also show that the cost of fuel treatments outweighs the expected cost savings from reduced sediment inputs owing to the low probability of fuel treatments encountering wildfire and the high cost of thinning forests. This highlights the need to expand use of more cost-effective treatments, like prescribed fire, and to identify fuel treatment projects that benefit multiple resources. We combined measures of fuel treatment effectiveness, feasibility and cost in a linear optimisation model to prioritise fuels reduction type and location to protect water supplies from fire-related sediment. [ABSTRACT FROM AUTHOR]

In response to large, severe wildfires in historically fire-adapted forests in the western US, policy initiatives, such as the USDA Forest Service’s Collaborative Forest Landscape Restoration Program (CFLRP), seek to increase the pace and scale of ecological restoration. One required component of this program is collaborative adaptive management, in which monitoring data are used to iteratively evaluate and improve future management actions. Here, we assess the success of seven CFLRP treatments, implemented on 2,300 ha during the first three years of the Colorado Front Range Landscape Restoration Initiative (LRI) at achieving desired forest structure by comparing pre- and post-treatment conditions. We also compare post-treatment conditions with reconstructions of historical (ca. 1860) forest conditions to contextualize the magnitude of treatment effects. Restoration projects moved stands toward desired conditions by reducing basal area, tree density, and canopy cover and increasing average tree diameter, large gap cover, and abundance of small- to medium-sized tree groups. Post-treatment stands were similar to historical stands with respect to basal area of ponderosa pine; however, they had higher total tree density and fewer gaps than historical reference conditions, suggesting that restoration prescriptions may be improved with increased flexibility for density reduction of Douglas-fir and increased gap creation. This examination of early CFLRP treatment outcomes as they relate to desired conditions informs potential areas of adjustments to future treatments and provides baseline data to evaluate the evolution of treatments over the program’s lifespan. We also identify and discuss several scientific, social, and logistical constraints to large-scale restoration success and make several recommendations to improve restoration outcomes. [ABSTRACT FROM AUTHOR]

Supporting wildfire management activities is frequently identified as a benefit of forest roads. As such, there is a growing body of research into forest road planning, construction, and maintenance to improve fire surveillance, prevention, access, and control operations. Of interest here is how road networks directly support fire control operations, and how managers incorporate that information into pre-season assessment and planning. In this communication we briefly review and illustrate how forest roads relate to recent advances in operationally focused wildfire decision support. We focus on two interrelated products used on the National Forest System and adjacent lands throughout the western USA: potential wildland fire operational delineations (PODs) and potential control locations (PCLs). We use real-world examples from the Arapaho-Roosevelt National Forest in Colorado, USA to contextualize these concepts and illustrate how fire analytics and local fire managers both identified roads as primary control features. Specifically, distance to road was identified as the most important predictor variable in the PCL boosted regression model, and 82% of manager-identified POD boundaries aligned with roads. Lastly, we discuss recommendations for future research, emphasizing roles for enhanced decision support and empirical analysis. [ABSTRACT FROM AUTHOR]

Water supply impairment from increased contaminant mobilization and transport after wildfire is a major concern for communities that rely on surface water from fire-prone watersheds. In this article we present a Monte Carlo simulation method to quantify the likelihood of wildfire impairing water supplies by combining stochastic representations of annual wildfire and rainfall activity. Water quality impairment was evaluated in terms of turbidity limits for treatment by modeling wildfire burn severity, postfire erosion, sediment transport, and suspended sediment dilution in receiving waterbodies. Water supply disruption was analyzed at the system level based on the impairment status of water supply components and their contributions to system performance. We used this approach to assess wildfire-water supply impairment and disruption risks for a system of water supply reservoirs and diversions in the Front Range Mountains of Colorado, USA. Our results indicate that wildfire may impair water quality in a concerning 15.7-19.4% of years for diversions from large watersheds. Reservoir impairment should be rare for off-network reservoirs-ranging from at most 0.01% of years for large reservoirs to nearly 2% of years for small reservoirs. System redundancy meaningfully reduced disruption risk for alternative conveyance routes (4.3-25.0% reduction) and almost eliminated disruption risk for a pair of substitutable terminal sources (99.9% reduction). In contrast, dependency among reservoirs on a conveyance route nearly doubled risk of disruption. Our results highlight the importance of considering water system characteristics when evaluating wildfire-water supply risks., (© 2021 Society for Risk Analysis. This article has been contributed to by US Government employees and their work is in the public domain in the USA.)

Land managers often need to predict watershed-scale erosion rates after disturbance or other land cover changes. This study compared commonly used hillslope erosion models to simulate post-fire sediment yields (SY) at both hillslope and watershed scales within the High Park Fire, Colorado, U.S.A. At hillslope scale, simulated SY from four models- RUSLE, AGWA/KINEROS2, WEPP, and a site-specific regression model-were compared to observed SY at 29 hillslopes. At the watershed scale, RUSLE, AGWA/KINEROS2, and WEPP were applied to simulate spatial patterns of SY for two 14-16 km 2 watersheds using different scales (0.5-25 ha) of hillslope discretization. Simulated spatial patterns were compared between models and to densities of channel heads across the watersheds. Three additional erosion algorithms were implemented within a land surface model to evaluate effects of parameter uncertainty. At the hillslope scale, SY was only significantly correlated to observed SY for the empirical model, but at the watershed scale, sediment loads were significantly correlated to observed channel head densities for all models. Watershed sediment load increased with the size of the hillslope sub-units due to the nonlinear effects of hillslope length on simulated erosion. SY's were closest in magnitude to expected watershed-scale SY when models were divided into the smallest hillslopes. These findings demonstrate that current erosion models are fairly consistent at identifying areas with low and high erosion potential, but the wide range of predicted SY and poor fit to observed SY highlight the need for better field observations and model calibration to obtain more accurate simulations., (Copyright © 2020 Elsevier Ltd. All rights reserved.)