Evaluating Pre‐ and Post‐Fire Peak Discharge Predictions across Western U.S. Watersheds

Kinoshita, A. M.; Hogue, T. S.; Napper, Carolyn

doi:10.1111/jawr.12226

Cited by 16 publications

(27 citation statements)

References 24 publications

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“…Significant advances in post‐fire hydrology since the development of Rowe et al (1949) should be incorporated to improve the accuracy of predictions (Kinoshita et al, 2014). For example, sediment bulking is implicit in RCS, yet independent variables that are strongly linked to sediment production or sediment yield are not used.…”

Section: Discussionmentioning

confidence: 99%

“…The 2‐ and 10‐year recurrence interval predictions to assess watersheds are typically used by WERT and BAER teams because there is more confidence in flood flow prediction methods at smaller recurrence intervals compared to larger intervals such as 25‐, 50‐ 100‐year (Kinoshita et al, 2014). Additionally, the recovery period for local vegetation in southern California is typically 2–7 years, which influences the hydrologic response (Bell et al, 2009; Keeley & Keeley, 1981; Kinoshita & Hogue, 2011).…”

Section: Methodsmentioning

confidence: 99%

“…Federal Burned Area Emergency Response (BAER) teams and California State Watershed Emergency Response Teams (WERTs) are reliant on modelling to make informed decisions (Foltz et al, 2009) following field verification of soil burn severity categories (Parsons et al, 2010). The models used to predict these processes have varying degrees of sophistication (Cannon et al, 2004;Kinoshita et al, 2014;Robichaud et al, 2007). Debris flows, debris yields, and surface erosion estimates are based on either numerical modelling (Water Erosion Prediction Project derivatives) or relatively robust empirical models, where the independent variables are consistent with our physical understanding of geomorphic processes (Gartner et al, 2014;Robichaud et al, 2011;Staley et al, 2017).…”

Section: Introduction To Post-fire Hazards In Southern Californiamentioning

confidence: 99%

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An analytical solution for rapidly predicting post‐fire peak streamflow for small watersheds in southern California

Wilder

Lancaster²,

Cafferata³

et al. 2020

Hydrological Processes

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Following wildfires, the probability of flooding and debris flows increase, posing risks to human lives, downstream communities, infrastructure, and ecosystems. In southern California (USA), the Rowe, Countryman, and Storey (RCS) 1949 methodology is an empirical method that is used to rapidly estimate post‐fire peak streamflow. We re‐evaluated the accuracy of RCS for 33 watersheds under current conditions. Pre‐fire peak streamflow prediction performance was low, where the average R2 was 0.29 and average RMSE was 1.10 cms/km2 for the 2‐ and 10‐year recurrence interval events, respectively. Post‐fire, RCS performance was also low, with an average R2 of 0.26 and RMSE of 15.77 cms/km2 for the 2‐ and 10‐year events. We demonstrated that RCS overgeneralizes watershed processes and does not adequately represent the spatial and temporal variability in systems affected by wildfire and extreme weather events and often underpredicted peak streamflow without sediment bulking factors. A novel application of machine learning was used to identify critical watershed characteristics including local physiography, land cover, geology, slope, aspect, rainfall intensity, and soil burn severity, resulting in two random forest models with 45 and five parameters (RF‐45 and RF‐5, respectively) to predict post‐fire peak streamflow. RF‐45 and RF‐5 performed better than the RCS method; however, they demonstrated the importance and reliance on data availability. The important parameters identified by the machine learning techniques were used to create a three‐dimensional polynomial function to calculate post‐fire peak streamflow in small catchments in southern California during the first year after fire (R2 = 0.82; RMSE = 6.59 cms/km2) which can be used as an interim tool by post‐fire risk assessment teams. We conclude that a significant increase in data collection of high temporal and spatial resolution rainfall intensity, streamflow, and sediment loading in channels will help to guide future model development to quantify post‐fire flood risk.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introduction To Post-fire Hazards In Southern Californiamentioning

confidence: 99%

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An analytical solution for rapidly predicting post‐fire peak streamflow for small watersheds in southern California

Wilder

Lancaster²,

Cafferata³

et al. 2020

Hydrological Processes

Self Cite

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“…These models were applied to eight diverse basins in the western United States affected by wildfires. According to Kinoshita et al (2014), no one model performed sufficiently well for application to all study sites. The review results showed inconsistency between model predictions for events across the sites and poor results with larger return periods (25-and 50year events) and when applied to post-fire watershed simulations.…”

Section: Simulation Of Subsurface Flowmentioning

confidence: 97%

“…The soil burn severity map was an input for WEPP and GeoWEPP simulations to help to quantify burn effects on soils runoff and erosion. Kinoshita et al (2014) reviewed five models for post-fire peak discharge predictions: the Rowe Countryman and Storey (RCS) (Rowe et al, 1949), United States Geological Survey (USGS) Linear Regression Equations (Foltz et al, 2009), USDA Windows Technical Release 55 (TR_55) (USDA, 2009), Wildcat5 (Hawkins and Munoz, 2011), and U.S. Army Corps of Engineers (USACE) Hydrologic Modeling System et al, 2000;Letey, 2001). Post-wildfire infiltration into the unsaturated zone is controlled by fire-induced changes in soil-water storage and soil hydraulic properties.…”

Section: Introductionmentioning

confidence: 99%

PFHydro: A New Watershed-Scale Model for Post-Fire Runoff Simulation

Wang

Stern

King

et al. 2020

Environmental Modelling & Software

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Runoff increases after wildfires that burn vegetation and create a condition of soil-water repellence (SWR). A new postfire watershed hydrological model, PFHydro, was created to explicitly simulate vegetation interception and SWR effects for four burn severity categories: high, medium, low severity and unburned. The model was applied to simulate post-fire runoff from the Upper Cache Creek Watershed in California, USA. Nash-Sutcliffe modeling efficiency (NSE) was used to assess model performance. The NSE was 0.80 and 0.88 for pre-fire water years (WY) 2000 and 2015, respectively. NSE was 0.88 and 0.93 for WYs 2016 (first year post-fire) and 2017 respectively. The simulated percentage of surface runoff in total runoff of WY 2016 was about six times that of pre-fire WY 2000 and three times that of WY 2015. The modeling results suggest that SWR is an important factor for post-fire runoff generation. The model was successful at simulating SWR behavior.

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Long‐term hydrologic recovery after wildfire and post‐fire forest management in the interior Pacific Northwest

Niemeyer

Bladon

Woodsmith

2020

Hydrological Processes

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Elevated wildfire activity in many regions in recent decades has increased concerns about the short-and long-term effects on water quantity, quality, and aquatic ecosystem health. Often, loss of canopy interception and transpiration, along with changes in soil structural properties, leads to elevated total annual water yields, peak flows, and low flows. Post-fire land management treatments are often used to promote forest regeneration and mitigate effects to terrestrial and aquatic ecosystems.However, few studies have investigated the longer-term effects of either wildfire or post-fire land management on catchment hydrology. Our objectives were to quantify and compare the short-and longer-term effects of both wildfire and post-fire forest management treatments on annual discharge, peak flows, low flows, and evapotranspiration (AET). We analyzed ten years of pre-fire data, along with post-fire data from 1 to 7 and 35 to 41 years after wildfire burned three experimental catchments in the Entiat Experimental Forest (EEF) in the Pacific Northwest, USA. After the fire, two of the catchments were salvage logged, aerially seeded, and fertilized, while the third catchment remained as a burned reference. We observed increases in annual discharge (150-202%), peak flows (234-283%), and low flows (42-81%), along with decreases in AET (34-45%), across all three study catchments in the first seven year period after the EEF wildfire. Comparatively, annual discharge, peak flows, lows flows, and AET had returned to pre-fire levels 35-41 years after the EEF fire in the two salvage logged and seeded catchments. Surprisingly, in the catchment that was burned but not actively managed, the annual discharge and runoff ratios remained elevated, while AET remained lower, during the period 35-41 years after the EEF fire. We posit that differences in long-term hydrologic recovery across catchments were driven by delayed vegetation recovery in the unmanaged catchment. Our study demonstrates that post-fire land management decisions have the potential to produce meaningful differences in the long-term recovery of catchment-scale ecohydrologic processes and streamflow.

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Evaluating Pre‐ and Post‐Fire Peak Discharge Predictions across Western U.S. Watersheds

Cited by 16 publications

References 24 publications

An analytical solution for rapidly predicting post‐fire peak streamflow for small watersheds in southern California

An analytical solution for rapidly predicting post‐fire peak streamflow for small watersheds in southern California

PFHydro: A New Watershed-Scale Model for Post-Fire Runoff Simulation

Long‐term hydrologic recovery after wildfire and post‐fire forest management in the interior Pacific Northwest

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