Scientists' warning on extreme wildfire risks to water supply

2020 is the year of wildfire records. California experienced its three largest fires early in its fire season. The Pantanal, the largest wetland on the planet, burned over 20% of its surface. More than 18 million hectares of forest and bushland burned during the 2019–2020 fire season in Australia, killing 33 people, destroying nearly 2500 homes, and endangering many endemic species. The direct cost of damages is being counted in dozens of billion dollars, but the indirect costs on water‐related ecosystem services and benefits could be equally expensive, with impacts lasting for decades. In Australia, the extreme precipitation (“200 mm day −1 in several location”) that interrupted the catastrophic wildfire season triggered a series of watershed effects from headwaters to areas downstream. The increased runoff and erosion from burned areas disrupted water supplies in several locations. These post‐fire watershed hazards via source water contamination, flash floods, and mudslides can represent substantial, systemic long‐term risks to drinking water production, aquatic life, and socio‐economic activity. Scenarios similar to the recent event in Australia are now predicted to unfold in the Western USA. This is a new reality that societies will have to live with as uncharted fire activity, water crises, and widespread human footprint collide all‐around of the world. Therefore, we advocate for a more proactive approach to wildfire‐watershed risk governance in an effort to advance and protect water security. We also argue that there is no easy solution to reducing this risk and that investments in both green (i.e., natural) and grey (i.e., built) infrastructure will be necessary. Further, we propose strategies to combine modern data analytics with existing tools for use by water and land managers worldwide to leverage several decades worth of data and knowledge on post‐fire hydrology

Estimating Evapotranspiration in a Post-Fire Environment Using Remote Sensing and Machine Learning

In the hydrological cycle, evapotranspiration (ET) transfers moisture from the land surface to the atmosphere and is sensitive to disturbances such as wildfires. Ground-based pre- and post-fire measurements of ET are often unavailable, limiting the potential to understand the extent of wildfire impacts on the hydrological cycle. This research estimated both pre- and post-fire ET using remotely sensed variables and support vector machine (SVM) methods. Input variables (land surface temperature, modified soil-adjusted vegetation index, normalized difference moisture index, normalized burn ratio, precipitation, potential evapotranspiration, albedo and vegetation types) were used to train and develop 56 combinations that yielded 33 unique SVM models to predict actual ET. The models were trained to predict a spatial ET, the Operational Simplified Surface Energy Balance (SSEBop), for the 2003 Coyote Fire in San Diego, California (USA). The optimal SVM model, SVM-ET6, required six input variables and predicted ET for fifteen years with a root-mean-square error (RMSE) of 8.43 mm/month and a R2 of 0.89. The developed model was transferred and applied to the 2003 Old Fire in San Bernardino, California (USA), where a watershed balance approach was used to validate SVM-ET6 predictions. The annual water balance for ten out of fifteen years was within ±20% of the predicted values. This work demonstrated machine learning as a viable method to create a remotely-sensed estimate with wide applicability for regions with sparse data observations and information. This innovative work demonstrated the potential benefit for land and forest managers to understand and analyze the hydrological cycle of watersheds that experience acute disturbances based on this developed predictive ET model

Increased dry season water yield in burned watersheds in Southern California

The current work evaluates the effects of the 2003 Old Fire on semi-arid systems in the San Bernardino Mountains, California. Pre- and post-fire daily streamflow are used to analyze flow regimes in two burned watersheds. The average pre-fire runoff ratios in Devil Canyon and City Creek are 0.14 and 0.26, respectively, and both increase to 0.34 post-fire. Annual flow duration curves are developed for each watershed and the low flow is characterized by a 90% exceedance probability threshold. Post-fire low flow is statistically different from the pre-fire values ( α  = 0.05). In Devil Canyon the annual volume of pre-fire low flow increases on average from 2.6E + 02 to 3.1E + 03 m ^3 (1090% increase) and in City Creek the annual low flow volume increases from 2.3E + 03 to 5.0E + 03 m ^3 (118% increase). Predicting burn system resilience to disturbance (anthropogenic and natural) has significant implications for water sustainability and ultimately may provide an opportunity to utilize extended and increased water yield

Vegetation and Fluvial Geomorphology Dynamics after an Urban Fire

The goal of this research was to characterize the impact of invasive riparian vegetation on burn severity patterns and fluvial topographic change in an urban Mediterranean riverine system (Med-sys) after fire in San Diego, California. We assessed standard post-fire metrics under urban conditions with non-native vegetation and utilized field observations to quantify vegetation and fluvial geomorphic processes. Field observations noted both high vegetation loss in the riparian area and rapidly resprouting invasive grass species such as Arundo donax (Giant Reed) after fire. Satellite-based metrics that represent vegetation biomass underestimated the initial green canopy loss, as did volumetric data derived from three-dimensional terrestrial laser scanning data. Field measurements were limited to a small sample size but demonstrated that the absolute maximum topographic changes were highest in stands of Arundo donax (0.18 to 0.67 m). This work is the first quantification of geomorphic alterations promoted by non-native vegetation after fire and highlights potential grass–fire feedbacks that can contribute to geomorphic disruption. Our results support the need for ground-truthing or higher resolution when using standard satellite-based indices to assess post-fire conditions in urban open spaces, especially when productive invasive vegetation are present, and they also emphasize restoring urban waterways to native vegetation conditions

Urban Fire Severity and Vegetation Dynamics in Southern California

A combination of satellite image indices and in-field observations was used to investigate the impact of fuel conditions, fire behavior, and vegetation regrowth patterns, altered by invasive riparian vegetation. Satellite image metrics, differenced normalized burn severity (dNBR) and differenced normalized difference vegetation index (dNDVI), were approximated for non-native, riparian, or upland vegetation for traditional timeframes (0-, 1-, and 3-years) after eleven urban fires across a spectrum of invasive vegetation cover. Larger burn severity and loss of green canopy (NDVI) was detected for riparian areas compared to the uplands. The presence of invasive vegetation affected the distribution of burn severity and canopy loss detected within each fire. Fires with native vegetation cover had a higher severity and resulted in larger immediate loss of canopy than fires with substantial amounts of non-native vegetation. The lower burn severity observed 1–3 years after the fires with non-native vegetation suggests a rapid regrowth of non-native grasses, resulting in a smaller measured canopy loss relative to native vegetation immediately after fire. This observed fire pattern favors the life cycle and perpetuation of many opportunistic grasses within urban riparian areas. This research builds upon our current knowledge of wildfire recovery processes and highlights the unique challenges of remotely assessing vegetation biophysical status within urban Mediterranean riverine systems

Impacts of Vegetation Removal on Urban Mediterranean Stream Hydrology and Hydraulics

Given the widespread presence of non-native vegetation in urban and Mediterranean watersheds, it is important to evaluate how these sensitive ecosystems will respond to activities to manage and restore native vegetation conditions. This research focuses on Del Cerro, a tributary of the San Diego River in California, where non-native vegetation dominates the riparian zone, creating flooding and fire hazards. Field data were collected in 2018 to 2021 and consisted of water depth, streamflow, and stream temperature. Our data set also captured baseline conditions in the floodplain before and after the removal of burned non-native vegetation in November 2020. Observed changes in hydrologic and geomorphic conditions were used to parameterize and calibrate a two-dimensional hydraulic model to simulate urban floodplain hydraulics after vegetation removal. We utilized the U.S. Army Corps of Engineers’ Hydrologic Engineering Center River Assessment System (HEC-RAS) model to simulate the influence of canopy loss and vegetation disturbance and to assess the impacts of vegetation removal on stream restoration. We simulated streamflow, water depth, and flood extent for two scenarios: (1) 2019; pre-restoration where non-native vegetation dominated the riparian area, and (2) 2021; post-restoration following the removal of non-native vegetation and canopy. Flooding after restoration in 2021 was more frequent compared to 2019. We also observed similar flood extents and peak streamflow for storm events that accumulated half the amount of precipitation as pre-restoration conditions. Our results provide insight into the responses of small urban stream reaches to the removal of invasive vegetation and canopy cover

Upland and Riparian Surface Soil Processes in an Urban Creek with Native and Non-Native Vegetation after Fire

Wildfires can pose environmental challenges in urban watersheds by altering the physical and chemical properties of soil. Further, invasive plant species in urban riparian systems may exacerbate changes in geomorphological and soil processes after fires. This research focuses on the 2018 Del Cerro fire, which burned upland and riparian areas surrounding Alvarado Creek, a tributary to the San Diego River in California. The study site has dense and highly flammable non-native vegetation cover (primarily Arundo donax) localized in the stream banks and has primarily native vegetation on the hillslopes. We estimated the post-fire organic matter and particle distributions for six time points during water years 2019 and 2020 at two soil depths, 0–15 cm and 15–30 cm, in upland and riparian areas. We observed some of the largest decreases in organic matter and particle-size distribution after the first post-fire rainfall event and a general return to initial conditions over time. Seasonal soil patterns were related to rainfall and variability in vegetation distribution. The riparian soils had higher variability in organic matter content and particle-size distributions, which was attributed to the presence of Arundo donax. The particle-size distributions were different between upland and riparian soils, where the riparian soils were more poorly graded. Overall, the greatest change occurred in the medium sands, while the fine sands appeared to be impacted the longest, which is a result of decreased vegetation that stabilized the soils. This research provides a better understanding of upland and riparian soil processes in an urban and Mediterranean system that was disturbed by non-native vegetation and fire

Effect of storms during drought on post-wildfire recovery of channel sediment dynamics and habitat in the southern California chaparral, USA

Current global warming projections suggest a possible increase in wildfire and drought, augmenting the need to understand how drought following wildfire affects the recovery of stream channels in relation to sediment dynamics. We investigated post-wildfire geomorphic responses caused by storms during a prolonged drought following the 2013 Springs Fire in southern California (USA), using multi-temporal Terrestrial Laser Scanning and detailed field measurements. After the fire, a dry-season dry-ravel sediment pulse contributed sand and small gravel to hillslope-channel margins in Big Sycamore Creek and its tributaries. A small storm in WY 2014 generated sufficient flow to mobilize a portion of the sediment derived from the dry-ravel pulse and deposited the fine sediment in the channel, totaling ~0.60 m3/m of volume per unit length of channel. The sediment deposit buried step-pool habitat structure and reduced roughness by over 90%. These changes altered sediment transport characteristics of the bed material present before and after the storm; the ratio of available to critical shear stress (t o / t c ) increased by five times. Storms during WY 2015 contributed additional fine sediment from tributaries and lower hillslopes and hyperconcentrated flow transported and deposited additional sediment in the channel. Together these sources delivered sediment on the order of six times that in 2014, further increasing t o / t c . These storms during multi-year drought following wildfire transformed channel dynamics. The increased sediment transport capacity persisted during the drought period characterized by the longer residence time of relatively fine-grained post-fire channel sedimentation. This contrasts with wetter years, when post-fire sediment is transported from the fluvial system during the same season as the post-fire sediment pulse. Results of this short-term study highlight the complex and substantial effects of multi-year drought on geomorphic responses following wildfire. These responses influence pool habitat that is critical to longer-term post-wildfire riparian ecosystem recovery

A Workflow to Estimate Topographic and Volumetric Changes and Errors in Channel Sedimentation after Disturbance

Light Detection and Ranging (LiDAR) methods, such as ground-based Terrestrial Laser Scanning (TLS), have enabled collection of high-resolution point clouds of elevation data to calculate changes in fluvial systems after disturbance, but are often accompanied by uncertainty and errors. This paper reviews and compares TLS analysis methods and develops a workflow to estimate topographic and volumetric changes in channel sedimentation after disturbance. Four analytic methods to estimate topographic and volumetric changes were compared by quantifying the uncertainty in TLS-derived products: Digital Elevation Model (DEM) of difference (DOD), Cloud to Cloud (C2C), Cloud to Mesh (C2M), and Multiple Model to Model Cloud Comparison (M3C2). Mean errors across surfaces within each dataset contributed to a propagation error of 0.015–0.016 m and 0.017–0.018 m for the point clouds and derived DEMs, respectively. The estimated error of the total volumetric change implied increased errors in the conversion of point clouds into a surface by C2M and DOD; whereas C2C and M3C2 were generally simpler, efficient, and accurate techniques for evaluating topographic changes. The comparison of methods to analyze TLS data will contribute to applications of remote sensing of hydro-geomorphic processes in stream channels after disturbance. The workflow presented also aids in estimating uncertainties inherent in data collection and analytic methods for topographic and volumetric change analysis

Effect of storms during drought on post-wildfire recovery of channel sediment dynamics and habitat in the southern California chaparral, USA

Current global warming projections suggest a possible increase in wildfire and drought, augmenting the need to understand how drought following wildfire affects the recovery of stream channels in relation to sediment dynamics. We investigated post-wildfire geomorphic responses caused by storms during a prolonged drought following the 2013 Springs Fire in southern California (USA), using multi-temporal Terrestrial Laser Scanning and detailed field measurements. After the fire, a dry-season dry-ravel sediment pulse contributed sand and small gravel to hillslope-channel margins in Big Sycamore Creek and its tributaries. A small storm in WY 2014 generated sufficient flow to mobilize a portion of the sediment derived from the dry-ravel pulse and deposited the fine sediment in the channel, totaling ~0.60 m3/m of volume per unit length of channel. The sediment deposit buried step-pool habitat structure and reduced roughness by over 90%. These changes altered sediment transport characteristics of the bed material present before and after the storm; the ratio of available to critical shear stress (t o / t c ) increased by five times. Storms during WY 2015 contributed additional fine sediment from tributaries and lower hillslopes and hyperconcentrated flow transported and deposited additional sediment in the channel. Together these sources delivered sediment on the order of six times that in 2014, further increasing t o / t c . These storms during multi-year drought following wildfire transformed channel dynamics. The increased sediment transport capacity persisted during the drought period characterized by the longer residence time of relatively fine-grained post-fire channel sedimentation. This contrasts with wetter years, when post-fire sediment is transported from the fluvial system during the same season as the post-fire sediment pulse. Results of this short-term study highlight the complex and substantial effects of multi-year drought on geomorphic responses following wildfire. These responses influence pool habitat that is critical to longer-term post-wildfire riparian ecosystem recovery