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USGS2019

Results from the Department of the Interior Strategic Sciences Group Technical Support for the 2018 Kīlauea Eruption

On May 3, 2018 Hawai'i’s Kīlauea volcano erupted, ultimately covering 35 square kilometers (13.5 square miles) of land in lava, destroying over 700 homes in multiple subdivisions, and displacing over 2500 residents in the Puna District on the southeast flank of the volcano. Simultaneously, Kīlauea’s summit experienced its largest collapse in 200 years, with a total of 500 meters (1,640 feet) subsidence and tens of earthquakes each day rattling surrounding communities. These simultaneous events impacted residential, agricultural, business, tourist, and scientific areas. Hawai'i Volcanoes National Park closed, slowing tourism and the local economy. The building housing the United States Geological Survey (USGS) Hawai'ian Volcano Observatory also closed, displacing scientists responsible for monitoring the erupting volcano. The eruption lasted 107 days, one of the longest eruptions in recent history in lower Puna. Throughout the eruption, uncertainty regarding the duration of the event, its extent, and total damage remained high. This uncertainty led to social tensions and fatigue across the affected community, responders, and local officials. At the direction of the USGS Director, serving as the Science Advisor to the Secretary of the of the Interior, the Department of the Interior (DOI, hereafter also referred to as “the Department”) Strategic Sciences Group (SSG) convened a multidisciplinary group of 13 experts in Hilo, Hawai'i, on July 17-19, 2018. The SSG was charged with considering the cascading short- and long-term social, economic, and environmental consequences of the 2018 Kīlauea eruption to DOI resources, employees, and facilities as well as to the surrounding communities. Established in 2012, the SSG is designed to complement ongoing response efforts by providing strategic science to identify potential social, environmental, and economic consequences and potential interventions during a crisis event affecting Departmental resources. This activation of the SSG was funded by the USGS. It was the first official activation of the SSG since it supported Hurricane Sandy recovery in 2013 and provided the unique opportunity to test new methods, including bolstering the social science expertise on the team and interacting directly with stakeholders before, during, and after deployment. The SSG Kīlauea Team developed three scenarios focused on 1) the impacts of continued seismicity and deformation at the summit; 2) vog (volcanic smog); and 3) the eruption in the lower East Rift Zone. Across all scenarios, areas of concern included human health (physical and mental); biosecurity (for example, protecting threatened and endangered species); infrastructure (impacts caused by seismic activity, vog, and lava); communications (internal and public-facing); long-term planning (related to tourism, access, housing); and ongoing needs for community engagement and empowerment. The SSG Kīlauea Team identified 59 potential actions for mitigation. Highlights of these actions were delivered to stakeholders during briefings in August and September 2018. Examples of potential actions included: ● Seize opportunities to develop new partnerships within and outside of DOI to address facilities issues caused by seismic damage and park closure. ● Educate community members and new workers to increase early detection of invasive species and establish new wash stations to address biosecurity threats to the park posed by more frequent commuting from new temporary Hilo locations. ● Create a "vog officer" position to ensure coordination and consistency in communication about vog hazards across federal, state, and county agencies. It is important to note that the potential actions are suggestions and are not intended to be prescriptive. The SSG uses “blue sky thinking” when developing these potential actions to encourage creative approaches to problem solving. In some cases, some of the suggested potential actions derived by the SSG are actions that were already underway, or already under consideration and helped to affirm 3 activities by different stakeholders. In other cases, the actions may be new ideas. Some were applicable to immediate response, while others are more relevant to long-term recovery. This report details the results from the July 2018 activation of the SSG. It includes background on Kīlauea and the 2018 eruption, an overview of SSG methodology, and a complete list of the potential actions to mitigate cascading consequences identified by the SSG. Importantly, Appendix 4 includes several rapidly assembled “issue papers” on a variety of topics for consideration for recovery and future preparedness and response activities. This report is designed to be used by both the Department and more broadly by partners, including the Federal Emergency Management Agency, Hawai'i County, Hawai'i Department of Health, and the Hawai'i Emergency Management Agency.

Hawaii↗
USGS2012

Lateral and vertical channel movement and potential for bed-material movement on the Madison River downstream from Earthquake Lake, Montana

The 1959 Hebgen Lake earthquake caused a massive landslide (Madison Slide) that dammed the Madison River and formed Earthquake Lake. The U.S. Army Corps of Engineers excavated a spillway through the Madison Slide to permit outflow from Earthquake Lake. In June 1970, high streamflows on the Madison River severely eroded the spillway channel and damaged the roadway embankment along U.S. Highway 287 downstream from the Madison Slide. Investigations undertaken following the 1970 flood events concluded that substantial erosion through and downstream from the spillway could be expected for streamflows greater than 3,500 cubic feet per second (ft 3 /s). Accordingly, the owners of Hebgen Dam, upstream from Earthquake Lake, have tried to manage releases from Hebgen Lake to prevent streamflows from exceeding 3,500 ft 3 /s measured at the U.S. Geological Survey (USGS) gaging station 0638800 Madison River at Kirby Ranch, near Cameron, Montana. Management of flow releases from Hebgen Lake to avoid exceeding the threshold streamflow at USGS gaging station 06038800 is difficult, and has been questioned for two reasons. First, no road damage was reported downstream from the Earthquake Lake outlet in 1993, 1996, and 1997 when streamflows exceeded the 3,500-ft 3 /s threshold. Second, the 3,500-ft 3 /s threshold generally precludes releases of higher flows that could be beneficial to the blue-ribbon trout fishery downstream in the Madison River. In response to concerns about minimizing streamflow downstream from Earthquake Lake and the possible armoring of the spillway, the USGS, in cooperation with the Madison River Fisheries Technical Advisory Committee (MADTAC; Bureau of Land Management; Montana Department of Environmental Quality; Montana Fish, Wildlife and Parks; PPL-Montana; U.S. Department of Agriculture Forest Service - Gallatin National Forest; and U.S. Fish and Wildlife Service), conducted a study to determine movement of the Madison River channel downstream from Earthquake Lake and to investigate the potential for bed material movement along the same reach. The purpose of this report is to present information about the lateral and vertical movement of the Madison River from 1970 to 2006 for a 1-mile reach downstream from Earthquake Lake and for Raynolds Pass Bridge, and to provide an analysis of the potential for bed-material movement so that MADTAC can evaluate the applicability of the previously determined threshold streamflow for initiation of damaging erosion. As part of this study channel cross sections originally surveyed by the USGS in 1971 were resurveyed in 2006. Incremental channel-movement distances were determined by comparing the stream centerlines from 14 aerial photographs taken between 1970 and 2006. Depths of channel incision and aggregation were determined by comparing the 2006 and 1971 cross-section and water-surface data. Particle sizes of bed and bank materials were measured in 2006 and 2008 using the pebble-count method and sieve analyses. A one-dimensional hydraulic-flow model (HEC-RAS) was used to calculate mean boundary-shear stresses for various streamflows; these calculated boundary-shear stresses were compared to calculated critical-shear stresses for the bed materials to determine the potential for bed-material movement. A comparison of lateral channel movement distances with annual peak streamflows shows that streamflows higher than the 3,500-ft 3 /s threshold were followed by lateral channel movement except from 1991 to 1992 and possibly from 1996 to 1997. However, it was not possible to discern whether the channel moved gradually or suddenly, or in response to one peak flow, to several peak flows, or to sustained flows. The channel moved between 2002 and 2005 even when streamflows were less than the threshold streamflow of 3,500 ft 3 /s. Comparisons of cross sections and aerial photographs show that the channel has moved laterally and incised and aggraded to varying degrees. The channel has developed meander bends and has incised as much as 5–12 feet (ft) through the upstream part of the Madison Slide (cross sections 1400–800). Near cross section 800, the stream has eroded into the steep right bank between the stream and the road where fill was mechanically placed after 1970. Channel movement also was noted downstream from the Madison Slide. Near Raynolds Pass Bridge, about 3 miles (mi) downstream from Earthquake Lake, elevations across the channel have changed by -1.4 ft to +1.9 ft, but these changes were local in nature and could represent a few rocks or depressions in the bed. Overall, it does not appear that the materials eroded from the Madison Slide are causing aggradation in the subreach near the Raynolds Pass Bridge. Comparisons of critical shear stresses to mean boundary-shear stresses indicate that the D50 particle sizes (median size) along the right side of the bed between cross sections 400 and 500 and along the right side of the bed between cross sections 1300 and 1400 could move at the threshold streamflow. In contrast, most of the D84 particle sizes at those two locations probably will not move at the threshold streamflow. This lack of movement for the larger particles at the threshold streamflow could lead to further armoring of the bed as the D50 and smaller-sized particles are removed from the bed and transported downstream. The Shields parameter values from 0.04 to 0.08 that were used to calculate critical shear stresses could be conservative for a high-gradient stream such as the Madison. A higher, less conservative, Shields parameter would result in higher critical shear stresses, meaning that higher streamflows would be required to move material than those reported herein. In addition, because materials in the channel thalweg are exposed to higher boundary-shear stresses than the materials along the sides of the channel, larger, more erosion-resistant materials likely exist in the deeper parts of the channel where high-flow depths and velocities prevented sediment sampling. Movement of these materials might require higher critical shear stresses than estimated in this report. Characterization of sediment sizes in the center of the stream and observation of bed-material movement for a range of streamflows could provide information to help refine the Shields parameter and critical-shear stress estimates for bed materials in the Madison River downstream from Earthquake Lake. Furthermore, resurveying cross sections and water-surface elevations more frequently (either annually or after high streamflows) could better define the relation between streamflow and lateral and vertical channel movement.

Montana↗
USGS2015

Real-time validation of the Dst Predictor model

The Dst Predictor model, which has been running real-time in the Space Weather Analysis and Forecast System (SWAFS), provides 1-hour and 4-hour forecasts of the Dst index. This is useful for awareness of impending geomagnetic activity, as well as driving other real-time models that use Dst as an input. In this report, we examine the performance of this forecast model in detail. When validating indices it should be noted that performance is only with respect to a reference index as they are derived quantities assumed to reflect a state of the magnetosphere that cannot be directly measured. In this case U.S. Geological Survey (USGS) Definitive Dst is the reference index (Section 3). Whether or not the model better reflects the actual activity level is nearly impossible to discern and is outside the scope of this report. We evaluate the performance of the model by computing continuous predictant skill scores against USGS Definitive Dst values as “observations” (Section 4.2). The two sets of data are not well-correlated for both 1-hour and 4-hour forecasts. The Dst Predictor Prediction Efficiency for both the 1- and 4-hour forecasts suggests poor performance versus the climatological mean. However, the skill score against a nowcast persistence model is positive, suggesting value added by the Dst Predictor model. We further examine statistics for storm times (Section 4.3) with similar results: nowcast persistence performs worse than Dst Predictor. Dst Predictor is superior to the nowcast persistence model for the metric used in this study. We recommend continued use of the DstPredictor model for 1-and4-hour Dst predictions along with active study of other Dst forecast models that do not rely on nowcast inputs (Section 6). The lack of certified requirements makes further recommendations difficult. A study of how the error in Dst translates to error in models and a better understanding of operational needs for magnetic storm warning are needed to determine such requirements. Nowcast persistence is often hard to beat for short term forecasts and specification and Dst Predictor clearly performs well against that standard (with 1-hour and 4-hour skill-scores of 0.233 and 0.485 respectively), although poor in absolute terms (with1-hourand4-hour prediction efficiencies of-64.6and-43.1, respectively).

Air Force Research Laboratory Technical Report↗
USGS2021

Evaluation of a “trace” plant density score in LTRM vegetation monitoring

The Long Term Resource Monitoring (LTRM) element of the Upper Mississippi River Restoration program employs a harvest method for sampling submersed aquatic vegetation (SAV) whereby a rake is dragged ~1.5 m over the substrate and plant materials are retrieved. “Plant density” (PD) scores indicate SAV abundance and are based on the amount of plant material collected on the teeth of the rake. Standard PD scores are ordered, whole numbers from 0 (no SAV on the rake) to 5 (80-100% of rake teeth full) and are assigned at each subsite for all species combined and for each individual species. In LTRM monitoring between 1998 and 2018, ~73% of non-zero, all-species-combined PD scores were 1s, and ~89% of individual SAV species were 1s. The preponderance of PD = 1 scores along with the wide range of fresh mass represented by PD = 1 (quantified in Drake and Lund 2020) limits inference about SAV abundance from LTRM monitoring data. Field personnel noted that small plant fragments comprised a substantial fraction of PD = 1 observations and proposed a modification of the existing LTRM methods where PD = 1 was subdivided to include “trace” scores to represent such small fragments. Trace was defined as PD = 0.08, indicating a maximum of 1 of 13 gaps in the sampling rake filled to the level of an original PD = 1. Amounts of plant material greater than PD = 0.08 and up to the original score of 1 were defined PD = +1. This study used field data collected in 2018 (scoring and fresh weights of scored plant materials) from 136 vegetated sites in Pools 4, 8 and 13 to evaluate the proposed subdivision and to examine among-pool differences in PD data. In the study data, 33% of all-species-combined observations and 69% of species (grouped by morphology) that would previously have received a score of 1 were classified as PD = 0.08. PD scores of 0.08, +1, and 2-3 represented statistically distinct amounts of fresh mass in rake samples. There were systematic differences in the mass of SAV reflected by PD score based on plant morphology and species composition. The mean fresh mass of plant materials assigned a given PD score varied among the three pools, suggesting bias attributable to personnel. To reduce this bias in future data collection efforts, the field crews incorporated a calibration of plant density scores in annual field training. The results presented here describe how including a trace PD score in LTRM data collection improves the description of SAV abundance and consequently estimates of biomass from those PD scores. LTRM vegetation crews have recorded trace scores in annual sampling since 2019 as extra information (i.e. which does not change the LTRM data stream as 0.08 and +1 scores can still be combined for PD=1). Trace data are not currently available to outside users through the LTRM data browser but are available from vegetation component personnel upon request.

Long Term Resource Monitoring Technical Report↗