412. McGuire et al. (2021) Expected warning times from the ShakeAlert® earthquake early warning system for earthquakes in the Pacific Northwest
     The ShakeAlert® earthquake early warning system has been live since October 2019 for the testing of public alerting to mobile devices in California and will soon begin testing this modality in Oregon and Washington. The Pacific Northwest presents new challenges and opportunities for ShakeAlert owing to the different types of earthquakes that occur in the Cascadia subduction zone. Many locations in the Pacific Northwest are expected to experience shaking from shallow crustal earthquakes (similar to those in California), earthquakes that occur deep within the subducted slab, and large megathrust earthquakes that occur primarily offshore. The different geometries and maximum magnitudes associated with these types of earthquakes lead to a range of warning times that are possible between when the initial ShakeAlert Message is issued and when a user experiences strong shaking. After an earthquake begins, the strategy of the ShakeAlert system for public alerting is to warn people who are located close enough to the fault that the system estimates they will experience at least weak to moderate shaking. By alerting the public at these low levels of expected shaking, it is possible to provide sufficient warning times for some users to take protective actions before strong shaking begins. In this study, we present an analysis of past ShakeAlert Messages as well as simulations of historical earthquakes and potential future Cascadia earthquakes to quantify the range of warning times that users who experience strong or worse shaking are likely to receive. Additional applications for ShakeAlert involve initiation of automatic protective actions prior to the onset of shaking, such as slowing trains, shutting water supplies, and opening firehouse doors, which are beyond the scope of this paper. Users in the Pacific Northwest should expect that the majority of alerts they receive will be from shallow crustal and intraslab earthquakes. In these cases, users will only have a few seconds of warning before strong shaking begins. This remains true even during infrequent, offshore great (magnitude ≥8) megathrust earthquakes, where warning times will generally range from seconds to tens of seconds, depending on the user’s location and the intensity of predicted shaking that a user chooses to be alerted for, with the longest warning times of 50–80 seconds possible only for users located at considerable distance from the epicenter. ShakeAlert thus requires short, readily understood alerts stating that earthquake shaking is imminent and suggesting protective actions users should take. Extensive education and outreach efforts that emphasize the need to take actions quickly will be required for ShakeAlert to successfully reduce injuries and losses.
467. Jaeger et al. (2023) Predicting probabilities of late summer surface flow presence in a glaciated mountainous headwater region
     Accurate mapping of streams that maintain surface flow during annual baseflow periods in mountain headwater streams is important for informing water availability for human consumption and is a fundamental determinant of in-channel conditions for stream-dwelling organisms. Yet accurate mapping that captures local spatial variability and associated local controls on surface flow presence is limited. An empirical random-forest model was developed to predict streamflow permanence (late summer surface-flow presence) for Mount Rainier National Park and the surrounding mountainous area in western Washington, USA. This model was developed to improve upon the existing multi-state, regional-scale probability of stream permanence developed for the greater Pacific Northwest Region (PROSPER_PNW). The model was trained on 544 wet/dry observations collected during the late summer, baseflow period from 2018 to 2020 using the crowd-source mobile application, FLOwPER. Final model accuracy was 0.74 with drainage area and covariates describing geology, topography, and land cover as top predictors of streamflow permanence compared to coarser resolution climatic covariates. The prevalence of static covariates over climatic covariates as top ranked important covariates highlights the importance of scale when evaluating controls on streamflow permanence. Cross validation of the model indicates that streamflow permanence probabilities from this model is an improvement over the regional-scale PROSPER_PNW model demonstrating the utility of relatively simple, crowd-sourced data to address water resource needs, and that determination of important predictors of streamflow permanence is influenced by the spatial and temporal resolution of analysis.
466. Curran (2023) Deciphering the impacts of glacial melt, lahars, debris flows, flood regulation, levees, and downstream channel avulsion on sediment transport in the White River, Mt. Rainier, Washington State
     A critical first step in managing a gravel and sand river through a populated area is measuring sediment transport rates to identify areas of persistent erosion or aggradation and trends in bed grain size distribution; to understand the relative influence of large and small flows over sediment mobility and bed exchange and long-term channel adjustment to external perturbations. In rivers transporting sediment sizes from silt to boulders, data collection necessarily includes multiple approaches, both direct and indirect. Sediment measurement efforts, and how collected data are used to understand and manage the river, are described for a river in the Cascade Mountains in Washington State. The White River originates at Emmons Glacier on Mount Rainier and flows approximately 105 km downstream to a confluence with the Puyallup River and then another 16 km to Puget Sound. It is a wandering channel in that it has an irregularly sinuous planform with both meandering and braided reaches. Sediment eroded from Mt Rainier transports by debris flows, lahars, and atmospheric river driven floods. Flow and sediment transport rates are altered by operations at Mud Mountain Dam at RKm 42 and a fish trap and barrier at RKm 34. Bed surface and subsurface sediment samples have repeated throughout the river but transport data are less frequent. Suspended sediment was measured in the 1970s. Direct bedload sampling was undertaken in 1974 with a Helley Smith at RKm 34 and again in 2010 with an Elwha Sampler at RKm 14. Recent analyses have focused on indirect estimates of transport though bed volume change. Repeat LiDAR, aerial imagery, and Structure-from-Motion have been applied to develop hypotheses of ongoing channel bed adjustment to a 1906 avulsion that lowered the channel between RKm 118. A recent levee setback at RKm 8 is being monitored for its impact on bed elevations and side channel deposition rates. Current efforts are focused on the reach at the barrier where sediment transport occurs only when river flow exceeds 113 m3/s and the barrier gates are lowered. Reach bathymetry is measured after each transport event and sequential data sets differenced to estimate the minimum sediment transport volume past RKm 34 with each high flow and over each water year. Hydrophones have been installed 300 meters downstream of the barrier to monitor gravel transport. The hydrophone signal will be correlated to the measured bathymetric change over the barrier reach.
465. Pelto (2018) How unusual was 2015 in the 1984-2015 period of the North Cascade Glacier annual mass balanace?
     In 1983, the North Cascade Glacier Climate Project (NCGCP) began the annual monitoring of the mass balance on 10 glaciers throughout the range, in order to identify their response to climate change. Annual mass balance (Ba) measurements have continued on seven original glaciers, with an additional two glaciers being added in 1990. The measurements were discontinued on two glaciers that had disappeared and one was that had separated into several sections. This comparatively long record from nine glaciers in one region, using the same methods, offers some useful comparative data in order to place the impact of the regional climate warmth of 2015 in perspective. The mean annual balance of the NCGCP glaciers is reported to the World Glacier Monitoring Service (WGMS), with two glaciers, Columbia and Rainbow Glacier, being reference glaciers. The mean Ba of the NCGCP glaciers from 1984 to 2015, was -0.54 m w.e.a^-1 (water equivalent per year), ranging from -0.44 to -0.67 m w.e.a^-1 for individual glaciers. In 2015, the mean Ba of nine North Cascade glaciers was -3.10 m w.e., the most negative result in the 32-year record. The correlation coefficient of Ba was above 0.80 between all North Cascade glaciers, indicating that the response was regional and not controlled by local factors. The probability of achieving the observed 2015 Ba of -3.10 is 0.34%.
464. Radic et al. (2008) Analysis of scaling methods in deriving future volume evolutions of valley glaciers
     Volume–area scaling is a common tool for deriving future volume evolutions of valley glaciers and their contribution to sea-level rise. We analyze the performance of scaling relationships for deriving volume projections in comparison to projections from a one-dimensional ice-flow model. The model is calibrated for six glaciers (Nigardsbreen, Rhonegletscher, South Cascade Glacier, Sofiyskiy glacier, midre Lovénbreen and Abramov glacier). Volume evolutions forced by different hypothetical mass-balance perturbations are compared with those obtained from volume–area (V-A), volume–length (V-L) and volume–area–length (V-A-L) scaling. Results show that the scaling methods mostly underestimate the volume losses predicted by the ice-flow model, up to 47% for V-A scaling and up to 18% for V-L scaling by the end of the 100 year simulation period. In general, V-L scaling produces closer simulations of volume evolutions derived from the ice-flow model, suggesting that V-L scaling may be a better approach for deriving volume projections than V-A scaling. Sensitivity experiments show that the initial volumes and volume evolutions are highly sensitive to the choice of the scaling constants, yielding both over- and underestimates. However, when normalized by initial volume, volume evolutions are relatively insensitive to the choice of scaling constants, especially in the V-L scaling. The 100 year volume projections differ within 10% of initial volume when the V-A scaling exponent commonly assumed, γ = 1.375, is varied by −30% to +45% (γ = [0.95, 2.00]) and the V-L scaling exponent, q = 2.2, is varied by −30% to +45% (q = [1.52, 3.20]). This is encouraging for the use of scaling methods in glacier volume projections, particularly since scaling exponents may vary between glaciers and the scaling constants are generally unknown.
463. Vallance and Sisson (2022) Geologic field-trip guide to volcanism and its interaction with snow and ice at Mount Rainier, Washington
     Mount Rainier is the Pacific Northwest's iconic volcano. At 4,393 meters and situated in the south-central Cascade Range of Washington State, it towers over cities of the Puget Lowland. As the highest summit in the Cascade Range, Mount Rainier hosts 26 glaciers and numerous permanent snow fields covering 87 square kilometers and having a snow and ice volume of about 3.8 cubic kilometers. It remains by far the most heavily glacier-clad mountain in the conterminous United States despite having lost about 14 percent of its ice volume between 1970 and 2008. Five major rivers head at Mount Rainier—the White, Carbon, Puyallup, Nisqually, and Cowlitz Rivers. Because Mount Rainier is situated west of the Cascade Range crest, all of these rivers eventually turn and drain westward. The Puget Lowland, situated west to northwest of Mount Rainier, is the Pacific Northwest's most densely populated area, including Seattle, Tacoma, and Olympia. The Puget Lowland is now home to a population of more than 4.5 million and a vibrant economy. Mount Rainier is one of the most hazardous volcanoes in the United States, not so much because of its explosivity, but rather because of its frequent eruptions, its propensity to produce voluminous far-traveled lahars, and its proximity to large population centers of the Puget Lowland. Steep-sided, glacially carved valleys serve as lahar conduits, and even mild eruptions commonly produced large lahars that traveled into areas now populated by hundreds of thousands of people. This guide describes a five-day field trip to view the geology of Mount Rainier as it relates to volcanism and its interaction with snow and ice. Day 1 will focus on lahars in the White River valley. We will drive to Enumclaw, Washington, to begin the day then work our way back upvalley toward Mount Rainier. Day 2 concentrates on geology of the Sunrise-Glacier Basin area within Mount Rainier National Park. As part of day 2 activities, we will hike about 10 miles from Sunrise to the top of Burroughs Mountain, down into Glacier Basin, and be picked up at White River Campground. On day 3 we will pack up and move to Paradise, stopping to examine geology along Stevens Canyon Road. We will hike from Paradise along the Golden Gate Trail and eventually eastward to the former Paradise Ice Caves area (the ice caves have melted out). Day 4 involves hiking from Comet Falls trailhead to Mildred Point and return (~7 miles; 11 km), examining geology along the way. During the first half of day 5, we will visit sites on the south side of Mount Rainier to study lahar deposits, then return to the tour origin.

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The U.S. Geological Survey and Pacific Northwest Seismic Network (PNSN) continue to monitor these volcanoes closely and will issue additional updates and changes in alert level as warranted.

Website Resources

For images, graphics, and general information on Cascade Range volcanoes: https://www.usgs.gov/observatories/cvo
For seismic information on Oregon and Washington volcanoes: http://www.pnsn.org/volcanoes
For information on USGS volcano alert levels and notifications: https://www.usgs.gov/programs/VHP/volcano-notifications-deliver-situational-information

Jon Major, Scientist-in-Charge, Cascades Volcano Observatory, jjmajor@usgs.gov

General inquiries: vhpweb@usgs.gov
Media: Ryan McClymont, PIO, USGS Office of Communications and Publishing rmcclymont@usgs.gov