Incorporating Impacts of Wildfire and Vegetation Recovery into a Watershed Model of the Feather River Basin
Changes in vegetation in a large watershed due to wildfire can have a substantial influence on actual evapotranspiration rates and water availability. After a large, intense wildfire, evapotranspiration rates are expected to decrease. As vegetation reestablishes, the evapotranspiration rates increase over a period of years, back to pre-fire conditions. Watershed models typically use input layers that are fixed or static and might not accurately reflect changes due to wildfires. The objective of this work is to incorporate changes in vegetation due to recent wildfires into the input layers of the Basin Characterization Model (BCM) which is being used in the Feather River Watershed.
The Feather River Watershed drains into Lake Oroville, which is the second-largest reservoir in the State of California. Lake Oroville is owned and operated by the California Department of Water Resources (DWR). DWR manages Oroville Dam to prevent flooding while also storing water for long-term domestic and agricultural use. Much of the water that drains into Lake Oroville comes from snowmelt in the Sierra Nevada mountains. Snowpack and snow-water equivalent (SWE) measurements have been traditionally used as a metric to forecast runoff into California reservoirs and anticipate water supply for the dry summer months. Changes in climate and the landscape due to multi-year drought and wildfire have a substantial impact on runoff and water supply forecasts. Water supply forecasts can be improved by addressing these data gaps in soil moisture and landscape-scale vegetation changes.
The Post-Fire Hazards Impacts to Resources and Ecosystems (PHIRE): Support for Response, Recovery, and Mitigation project effort to incorporate wildfire-induced vegetation loss and recovery into a watershed model is part of a larger effort to improve watershed modeling and water supply forecasts in the Feather River Watershed. The USGS in cooperation with DWR is using a USGS water balance model known as the Basin Characterization Model (BCM; Flint et al. 2021). The BCM is a monthly, fine-scale (270-meter), spatially distributed water balance model that has been rigorously calibrated to streamflow, actual evapotranspiration, snowpack, and potential evapotranspiration data across California. The statewide BCM was extracted to the Feather River Watershed, and locally refined and calibrated to improve the fine-scale characterization of local water balance processes.
Figure 1. Diagram showing the processes of the Basin Characterization Model which is a watershed model that will be used for the Feather River Watershed study (Flint and others, 2021).
Wildfire changes:
One limitation of current BCM applications is the inability to dynamically change vegetation and land use through time. Relationships between climate and vegetation are assumed to be constant for future simulations, and the current spatial pattern of vegetation types is limited to a static representation based on currently available published vegetation data. Updates to vegetation datasets can take many years and therefore are not suitable for modeling post-fire response in real-time. Modifying the vegetation layer in an area following a major wildfire will allow the BCM model to better represent reduced evapotranspiration in an area that was burned. Vegetation is also expected to recover over a period of several years depending on the climate and vegetation type. Changes in ETa can also be observed on a large spatial scale. Figure 3 is a map of pre-fire and post-fire ETa (downloaded from OpenET) over a large area in the Feather River Watershed.
Estimated actual evapotranspiration (ETa) from OpenET (figure 2) shows an area burned by the North Complex Fire in late 2021 and a monthly time series of ETa for the location indicated on the left panel of Figure 2.
Figure 2. Maps of Feather River Watershed near Lake Oroville 2019-2023, showing average annual actual evapotranspiration (ETa) before the North Complex Fire (Aug-Dec 2020) and recovery in subsequent years. Blue and green colors indicate high ETa, orange and yellow indicate low ETa. Source: OpenET.
Figure 3. The left panel shows the estimated actual evapotranspiration (ETa) near Lake Oroville in 2022. Green and blue represent high rates of ETa, and orange and yellow represent low rates of ETa. The area represented by low ETa in this area coincides with the same area that was burned in a large wildfire called the North Complex Fire, in late 2020. The right panel shows a time series of average ETa from the area enclosed in a box on the left plot. This shows a baseline of high ETa in the summer, and low ETa in the winter until late 2020. From 2021-2023, ETa has a distinctly different pattern due to the loss of vegetation. Source: OpenET.
Soil moisture data gap:
In addition to incorporating changes in vegetation due to wildfire into the watershed model, another major objective is to incorporate soil moisture observations. Soil moisture has a large influence on infiltration rates, infiltration capacity, and actual evapotranspiration rates. However, soil moisture is often not measured or monitored, therefore most watershed models have to estimate soil moisture through indirect means. Research has also shown that antecedent soil moisture can greatly impact snowmelt runoff estimates, particularly after multiyear droughts (Lapides and others, 2022). By measuring soil moisture on a continuous basis throughout a watershed, a model can more accurately predict soil infiltration and runoff.
In the Feather River Watershed, over 30 soil moisture monitoring stations are planned to be installed across the watershed. Their locations were determined by analyzing the hydrology, geology, elevation, and other factors to group areas together based on similar soil moisture response called “soil moisture response units” (SRMUs; following methods of Curtis and others, 2019). The Feather River Watershed was divided into 15 SRMUs with 2 soil moisture monitoring stations planned for each SMRU. Figure 4 shows a map of the Feather River Watershed with the SMRUs and planned locations for soil moisture monitoring stations. Soil moisture may also be used as an indicator of wildfire risk and forest health, though that is outside of the scope of this study. Figure 5 shows an example of soil moisture sensors used in this study. The soil moisture data will be telemetered in real-time using LoRa telemetry, which uses low-power, long-range radios to transmit data to local uplink sites, called gateways. The gateways relay data packets through cellular, to the USGS servers.
Figure 4. A map of the Feather River Watershed with the soil moisture response units (SMRUs) and planned locations for soil moisture monitoring stations.
Funding
Funding for this project is provided by the Robert T. Stafford Disaster Relief and Emergency Assistance Act (42 U.S.C. 5121 et seq.) and supplemental funding acts for Federal disaster relief activities. Through this funding USGS supports recovery efforts in declared natural disaster areas, to aid recovery efforts from widespread wildfires, devastating hurricanes, prolonged volcanic eruptions, and damaging earthquakes. This enables USGS to repair and replace equipment and facilities, collect high-resolution elevation data, and conduct scientific studies and assessments to support recovery and rebuilding decisions.
Figure 5. Soil moisture sensors installed in a soil moisture monitoring pit as part of a USGS monitoring station for real-time soil moisture monitoring. Photo credit: Michelle Stern, USGS
Monitoring and modeling soil moisture to improve runoff forecasting and drought characterization in the Feather River Basin
Changes in vegetation in a large watershed due to wildfire can have a substantial influence on actual evapotranspiration rates and water availability. After a large, intense wildfire, evapotranspiration rates are expected to decrease. As vegetation reestablishes, the evapotranspiration rates increase over a period of years, back to pre-fire conditions. Watershed models typically use input layers that are fixed or static and might not accurately reflect changes due to wildfires. The objective of this work is to incorporate changes in vegetation due to recent wildfires into the input layers of the Basin Characterization Model (BCM) which is being used in the Feather River Watershed.
The Feather River Watershed drains into Lake Oroville, which is the second-largest reservoir in the State of California. Lake Oroville is owned and operated by the California Department of Water Resources (DWR). DWR manages Oroville Dam to prevent flooding while also storing water for long-term domestic and agricultural use. Much of the water that drains into Lake Oroville comes from snowmelt in the Sierra Nevada mountains. Snowpack and snow-water equivalent (SWE) measurements have been traditionally used as a metric to forecast runoff into California reservoirs and anticipate water supply for the dry summer months. Changes in climate and the landscape due to multi-year drought and wildfire have a substantial impact on runoff and water supply forecasts. Water supply forecasts can be improved by addressing these data gaps in soil moisture and landscape-scale vegetation changes.
The Post-Fire Hazards Impacts to Resources and Ecosystems (PHIRE): Support for Response, Recovery, and Mitigation project effort to incorporate wildfire-induced vegetation loss and recovery into a watershed model is part of a larger effort to improve watershed modeling and water supply forecasts in the Feather River Watershed. The USGS in cooperation with DWR is using a USGS water balance model known as the Basin Characterization Model (BCM; Flint et al. 2021). The BCM is a monthly, fine-scale (270-meter), spatially distributed water balance model that has been rigorously calibrated to streamflow, actual evapotranspiration, snowpack, and potential evapotranspiration data across California. The statewide BCM was extracted to the Feather River Watershed, and locally refined and calibrated to improve the fine-scale characterization of local water balance processes.
Figure 1. Diagram showing the processes of the Basin Characterization Model which is a watershed model that will be used for the Feather River Watershed study (Flint and others, 2021).
Wildfire changes:
One limitation of current BCM applications is the inability to dynamically change vegetation and land use through time. Relationships between climate and vegetation are assumed to be constant for future simulations, and the current spatial pattern of vegetation types is limited to a static representation based on currently available published vegetation data. Updates to vegetation datasets can take many years and therefore are not suitable for modeling post-fire response in real-time. Modifying the vegetation layer in an area following a major wildfire will allow the BCM model to better represent reduced evapotranspiration in an area that was burned. Vegetation is also expected to recover over a period of several years depending on the climate and vegetation type. Changes in ETa can also be observed on a large spatial scale. Figure 3 is a map of pre-fire and post-fire ETa (downloaded from OpenET) over a large area in the Feather River Watershed.
Estimated actual evapotranspiration (ETa) from OpenET (figure 2) shows an area burned by the North Complex Fire in late 2021 and a monthly time series of ETa for the location indicated on the left panel of Figure 2.
Figure 2. Maps of Feather River Watershed near Lake Oroville 2019-2023, showing average annual actual evapotranspiration (ETa) before the North Complex Fire (Aug-Dec 2020) and recovery in subsequent years. Blue and green colors indicate high ETa, orange and yellow indicate low ETa. Source: OpenET.
Figure 3. The left panel shows the estimated actual evapotranspiration (ETa) near Lake Oroville in 2022. Green and blue represent high rates of ETa, and orange and yellow represent low rates of ETa. The area represented by low ETa in this area coincides with the same area that was burned in a large wildfire called the North Complex Fire, in late 2020. The right panel shows a time series of average ETa from the area enclosed in a box on the left plot. This shows a baseline of high ETa in the summer, and low ETa in the winter until late 2020. From 2021-2023, ETa has a distinctly different pattern due to the loss of vegetation. Source: OpenET.
Soil moisture data gap:
In addition to incorporating changes in vegetation due to wildfire into the watershed model, another major objective is to incorporate soil moisture observations. Soil moisture has a large influence on infiltration rates, infiltration capacity, and actual evapotranspiration rates. However, soil moisture is often not measured or monitored, therefore most watershed models have to estimate soil moisture through indirect means. Research has also shown that antecedent soil moisture can greatly impact snowmelt runoff estimates, particularly after multiyear droughts (Lapides and others, 2022). By measuring soil moisture on a continuous basis throughout a watershed, a model can more accurately predict soil infiltration and runoff.
In the Feather River Watershed, over 30 soil moisture monitoring stations are planned to be installed across the watershed. Their locations were determined by analyzing the hydrology, geology, elevation, and other factors to group areas together based on similar soil moisture response called “soil moisture response units” (SRMUs; following methods of Curtis and others, 2019). The Feather River Watershed was divided into 15 SRMUs with 2 soil moisture monitoring stations planned for each SMRU. Figure 4 shows a map of the Feather River Watershed with the SMRUs and planned locations for soil moisture monitoring stations. Soil moisture may also be used as an indicator of wildfire risk and forest health, though that is outside of the scope of this study. Figure 5 shows an example of soil moisture sensors used in this study. The soil moisture data will be telemetered in real-time using LoRa telemetry, which uses low-power, long-range radios to transmit data to local uplink sites, called gateways. The gateways relay data packets through cellular, to the USGS servers.
Figure 4. A map of the Feather River Watershed with the soil moisture response units (SMRUs) and planned locations for soil moisture monitoring stations.
Funding
Funding for this project is provided by the Robert T. Stafford Disaster Relief and Emergency Assistance Act (42 U.S.C. 5121 et seq.) and supplemental funding acts for Federal disaster relief activities. Through this funding USGS supports recovery efforts in declared natural disaster areas, to aid recovery efforts from widespread wildfires, devastating hurricanes, prolonged volcanic eruptions, and damaging earthquakes. This enables USGS to repair and replace equipment and facilities, collect high-resolution elevation data, and conduct scientific studies and assessments to support recovery and rebuilding decisions.
Figure 5. Soil moisture sensors installed in a soil moisture monitoring pit as part of a USGS monitoring station for real-time soil moisture monitoring. Photo credit: Michelle Stern, USGS