{ "culture": "en-US", "name": "", "guid": "", "catalogPath": "", "snippet": "These data were developed to meet requirements stipulated in Oregon Senate Bill 762 (2021) and Oregon Senate Bill 80 (2023) that Oregon State University develop a map of statewide wildfire hazard and summarize results for all properties in Oregon. \nThese data represent pixel-level wildfire hazard values based on burn probability and fire intensity, and which were used to inform property-level hazard values. Data are current as of January 7, 2025.", "description": "

Wildfire hazard (hazard) in these data represent the potential for damage to structures and other human development as a result of four criteria: climate, weather, topography and vegetation. We used simulation models to quantify and map burn probability and fire intensity for all locations, and then combined burn probability and fire intensity to calculate hazard. <\/SPAN><\/SPAN><\/P>

Burn probability is an estimate of the average annual likelihood that a fire will impact a given location. Pyrologix LLC. used the large fire simulator, FSim, to estimate burn probability based on 2022 landscape conditions. The modeling landscape used LANDFIRE 2.0.0 fuel data which had been updated to reflect disturbances through the end of 2021, and which was adjusted based on input from regional fire and fuels professionals. FSim uses spatial fire ignition probabilities based on historical fire records (1992 \u2013 2021) and daily weather inputs sampled from observed weather (2007 \u2013 2021) to simulate 10,000 plausible fire seasons across 14 modeling landscapes in Oregon. In each modeling landscape, Pyrologix calibrated the model using observed patterns in historical climate-fire occurrence linkages. All modeling was performed at 120-meter resolution and resampled to 30-meters. <\/SPAN><\/SPAN><\/P>

Fire intensity was modeled by Pyrologix LLC using the WildEST simulation tool and the same modeling landscape described above. Pyrologix developed 216 weather scenarios based on unique combinations of wind speed, wind direction and fuel moisture sampled from observed weather records. Wildfire behavior was simulated under each weather scenario, producing fire intensity level probabilities (represented as flame lengths) based on the average flame length from simulations and the relative likelihood of each weather scenario. All modeling was performed at a 30-meter resolution. The fire intensity levels include:<\/SPAN><\/SPAN><\/P>

  1. FIL1: 0-2 ft. flame length<\/SPAN><\/P><\/LI>

  2. FIL2: 2-4 ft. flame lengths<\/SPAN><\/P><\/LI>

  3. FIL3: 4-6 ft. flame lengths<\/SPAN><\/SPAN><\/P><\/LI>

  4. FIL4: 6-8 ft. flame lengths<\/SPAN><\/SPAN><\/P><\/LI>

  5. FIL5: 8-12 ft. flame lengths<\/SPAN><\/SPAN><\/P><\/LI>

  6. FIL6: > 12 ft. flame lengths<\/SPAN><\/P><\/LI><\/OL>

    OAR 629-44-1026 requires that hazard be adjusted in all agricultural areas identified as irrigated in at least one of five representative years. We used IrrMapper <\/SPAN>(Ketchum et al., 2020)<\/SPAN><\/SPAN> binary data layers from 2017 \u2013 2021 and identified all pixels in Oregon that were mapped as irrigated in at least one of those layers. We clipped the IrrMapper data to the extent of mapped agricultural fields using mapped field boundaries produced by the Oregon Water Resources Department (OWRD; Bromley et al., 2024). <\/SPAN><\/SPAN><\/P>

    During review of draft data in spring and summer 2024, county planners from Hood River and Baker County identified data gaps in IrrMapper. OSU worked with county planners to verify the data gaps and develop corrections that were applied statewide. <\/SPAN><\/SPAN><\/P>

    In Hood River County, planners observed that while the majority of orchards were mapped as irrigated in IrrMapper, there were persistent holes in the data which indicated the portion of a field had not been irrigated when in fact it had. The data gaps did not appear to align with any features on the ground (e.g., recently cleared crops, change in farming practices, etc.). To address this data gap, we selected all fields shown to be growing irrigated orchard crops from the OWRD field boundaries data and added the extent of those fields to the irrigated extent identified using IrrMapper. By adding field boundary extents, we filled in data holes among orchards in IrrMapper. <\/SPAN><\/SPAN><\/P>

    In Baker County, planners observed that IrrMapper data frequently did not characterize wetlands as irrigated, even when the wetlands are identified as irrigated hay fields in the OWRD data. We selected freshwater forested/shrub wetlands and freshwater emergent wetlands from the National Wetland Inventory (NWI; U.S. Fish and Wildlife Service, 2023), intersected the selected wetlands with the OWRD department, and added extent to the irrigated agriculture mask. The result was a raster mask representing:<\/SPAN><\/SPAN><\/P>