2019 Supplemental Appropriations Activities
The Additional Supplemental Appropriations for Disaster Relief Act of 2019 (H.R. 2157) was signed by the President on June 6, 2019. The USGS received $98.5 million to support recovery and rebuilding activities in the wake of the 2018 Kīlauea volcano eruption, Hurricanes Florence and Michael, the Anchorage earthquake, and California wildfires.
USGS activities funded under the FY2019 Additional Supplemental Appropriations for Disaster Relief Requirements Act include:
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- New Hawaiian Volcano Observatory (HVO)
- Response Activities, Equipment Repair, and Hardening from the Kīlauea eruption
- Geologic Investigations of the Kīlauea Summit Collapse
- Equipment Repair and Replacement from Hurricanes Florence and Michael
- Coastal Hazard Assessments and Forecasts from Hurricane Florence
- Assessment of Landslide and Debris-Flow Impacts from California Wildfires
- Fire Behavior Models: Enhanced Support for Recovery of U.S. Department of the Interior (DOI) Lands
- Equipment Replacement and Geologic Investigations Related to the Alaska Earthquake
- Acquisition and Publication of 3D Elevation Program (3DEP) Lidar for Hurricanes and Wildfires
USGS Factsheet: 2019 Disaster Relief Act: USGS Recovery Activities
Related
Filter Total Items: 38
Topobathymetric Model of the Coastal Georgia, 1851 to 2020 Topobathymetric Model of the Coastal Georgia, 1851 to 2020
To support Hurricane Florence impact modeling of storm-induced flooding and sediment transport, the U.S. Geological Survey (USGS) Coastal National Elevation Database (CoNED) Applications Project has created an integrated 1-meter topobathymetric digital elevation model (TBDEM) for coastal Georgia. High-resolution coastal topobathymetric data are required to characterize flooding, storms...
Earthquake triggered ground failure associated with the M7.1 2018 southcentral Alaska Earthquake (ver. 2.0, December 2023) Earthquake triggered ground failure associated with the M7.1 2018 southcentral Alaska Earthquake (ver. 2.0, December 2023)
The November 30, 2018, magnitude (Mw) 7.1 Anchorage, Alaska earthquake triggered substantial ground failure throughout Anchorage and surrounding areas (Grant et al., 2020; Jibson et al., 2020). The earthquake was an intraslab event with a focal depth of about 47 km and an epicenter about 16 km north of the city of Anchorage. Peak ground accelerations reached ∼30% g. Despite the...
Aerial Imagery of the North Carolina Coast: 2020-02-08 to 2020-02-09 Aerial Imagery of the North Carolina Coast: 2020-02-08 to 2020-02-09
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Aerial Imagery of the North Carolina Coast: 2020-05-08 to 2020-05-09 Aerial Imagery of the North Carolina Coast: 2020-05-08 to 2020-05-09
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Coast Train--Labeled imagery for training and evaluation of data-driven models for image segmentation Coast Train--Labeled imagery for training and evaluation of data-driven models for image segmentation
Coast Train is a library of images of coastal environments, annotations, and corresponding thematic label masks (or 'label images') collated for the purposes of training and evaluating machine learning (ML), deep learning, and other models for image segmentation. It includes image sets from both geospatial satellite, aerial, and UAV imagery and orthomosaics, as well as non-geospatial...
Topobathymetric Model of the Coastal Carolinas, 1851 to 2020 Topobathymetric Model of the Coastal Carolinas, 1851 to 2020
To support Hurricane Florence impact modeling of storm-induced flooding and sediment transport, the U.S. Geological Survey (USGS) Coastal National Elevation Database (CoNED) Applications Project has created an integrated 1-meter topobathymetric digital elevation model (TBDEM) for coastal North Carolina, and South Carolina. High-resolution coastal topobathymetric data are required to...
Aerial Imagery of the North Carolina Coast: 2019-11-26 Aerial Imagery of the North Carolina Coast: 2019-11-26
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Aerial Imagery of the North Carolina Coast: 2019-10-11 Aerial Imagery of the North Carolina Coast: 2019-10-11
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Aerial Imagery of the North Carolina Coast: 2019-09-08 to 2019-09-13, Post-Hurricane Dorian Aerial Imagery of the North Carolina Coast: 2019-09-08 to 2019-09-13, Post-Hurricane Dorian
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Aerial Imagery of the North Carolina Coast: 2019-08-30 and 2019-09-02, Pre-Hurricane Dorian Aerial Imagery of the North Carolina Coast: 2019-08-30 and 2019-09-02, Pre-Hurricane Dorian
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Storm-Induced Overwash Extent Storm-Induced Overwash Extent
The Coastal Change Hazards Technical Capabilities and Applications project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation’s coastlines. This data release defines the alongshore extent of overwash deposits, determined from aerial photograph analysis, attributed to coastal processes during storm events. Note: This data release was...
Water-level data for the crater lake at the summit of Kilauea Volcano, Island of Hawai'i, 2019-2020 Water-level data for the crater lake at the summit of Kilauea Volcano, Island of Hawai'i, 2019-2020
During 2018, Kilauea Volcano, on the Island of Hawaiii, had a large effusive eruption (~1 cubic kilometer of lava) on the lower East Rift Zone that caused widespread destruction (Neal and others, 2019; Dietterich and others, 2021). This lower flank eruption was accompanied by one of the largest collapses of the summit caldera in two hundred years, with portions of the caldera floor...
Filter Total Items: 56
Modeled coastal-ocean pathways of land-sourced contaminants in the aftermath of Hurricane Florence Modeled coastal-ocean pathways of land-sourced contaminants in the aftermath of Hurricane Florence
Extreme precipitation during Hurricane Florence, which made landfall in North Carolina in September 2018, led to breaches of hog waste lagoons, coal ash pits, and wastewater facilities. In the weeks following the storm, freshwater discharge carried pollutants, sediment, organic matter, and debris to the coastal ocean, contributing to beach closures, algae blooms, hypoxia, and other...
Authors
Melissa Moulton, Joseph B. Zambon, Zuo Xue, John C. Warner, Daoyang Bao, Dongxiao Yin, Zafer Defne, Ruoying He, Christie Hegermiller
Slowly but surely: Exposure of communities and infrastructure to subsidence on the US east coast Slowly but surely: Exposure of communities and infrastructure to subsidence on the US east coast
Coastal communities are vulnerable to multihazards, which are exacerbated by land subsidence. On the US east coast, the high density of population and assets amplifies the region's exposure to coastal hazards. We utilized measurements of vertical land motion rates obtained from analysis of radar datasets to evaluate the subsidence-hazard exposure to population, assets, and infrastructure...
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Leonard O. Ohenhen, Manoochehr Shirzaei, Patrick L. Barnard
The 2023 US 50-State National Seismic Hazard Model: Overview and implications The 2023 US 50-State National Seismic Hazard Model: Overview and implications
The US National Seismic Hazard Model (NSHM) was updated in 2023 for all 50 states using new science on seismicity, fault ruptures, ground motions, and probabilistic techniques to produce a standard of practice for public policy and other engineering applications (defined for return periods greater than ∼475 or less than ∼10,000 years). Changes in 2023 time-independent seismic hazard...
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Mark D. Petersen, Allison Shumway, Peter M. Powers, Edward H. Field, Morgan P. Moschetti, Kishor S. Jaiswal, Kevin R. Milner, Sanaz Rezaeian, Arthur D. Frankel, Andrea L. Llenos, Andrew J. Michael, Jason M. Altekruse, Sean Kamran Ahdi, Kyle Withers, Charles Mueller, Yuehua Zeng, Robert E. Chase, Leah M. Salditch, Nico Luco, Kenneth S. Rukstales, Julie A. Herrick, Demi Leafar Girot, Brad T. Aagaard, Adrian Bender, Michael L. Blanpied, Richard W. Briggs, Oliver S. Boyd, Brandon Clayton, Christopher DuRoss, Eileen L. Evans, Peter J. Haeussler, Alexandra Elise Hatem, Kirstie Lafon Haynie, Elizabeth H. Hearn, Kaj M. Johnson, Zachary Alan Kortum, N. Simon Kwong, Andrew James Makdisi, Henry Mason, Daniel McNamara, Devin McPhillips, P. Okubo, Morgan T. Page, Frederick Pollitz, Justin Rubinstein, Bruce E. Shaw, Zheng-Kang Shen, Brian Shiro, James Andrew Smith, William J. Stephenson, Eric M. Thompson, Jessica Ann Thompson Jobe, Erin A. Wirth, Robert C. Witter
Global projections of storm surges using high-resolution CMIP6 climate models Global projections of storm surges using high-resolution CMIP6 climate models
In the coming decades, coastal flooding will become more frequent due to sea-level rise and potential changes in storms. To produce global storm surge projections from 1950 to 2050, we force the Global Tide and Surge Model with a ∼25-km resolution climate model ensemble from the Coupled Model Intercomparison Project Phase 6 High Resolution Model Intercomparison Project (HighResMIP). This...
Authors
Sanne Muis, Jeroen C. J. H. Aerts, Jose A. A. Antolinez, Job C. Dullaart, Trang Minh Duong, Li H. Erikson, Rein J. Haarsma, Maialen Irazoqui Apecechea, Matthias Mengel, Dewi Le Bars, Andrea C. O'Neill, Roshanka Ranasinghe, Malcolm J. Roberts, Martin Verlaan, Philip J. Ward, Kun Yan
Forecasting the inundation of postfire debris flows Forecasting the inundation of postfire debris flows
In the semi-arid regions of the western United States, postfire debris flows are typically runoff generated. The U.S. Geological Survey has been studying the mechanisms of postfire debris-flow initiation for multiple decades to generate operational models for forecasting the timing, location, and magnitude of postfire debris flows. Here we discuss challenges and progress for extending...
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Katherine R. Barnhart, Ryan P Jones, David L. George, Francis K. Rengers, Jason W. Kean
Runout model evaluation based on back-calculation of building damage Runout model evaluation based on back-calculation of building damage
We evaluated the ability of three debris-flow runout models (RAMMS, FLO2D and D-Claw) to predict the number of damaged buildings in simulations of the 9 January 2019 Montecito, California, debris-flow event. Observations of building damage after the event were combined with OpenStreetMap building footprints to construct a database of all potentially impacted buildings. At the estimated...
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Katherine R. Barnhart, Jason W. Kean
Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards
The steep, tectonically active terrain along the Central California (USA) coast is well known to produce deadly and destructive debris flows. However, the extent to which fire affects debris-flow susceptibility in this region is an open question. We documented the occurrence of postfire debris floods and flows following the landfall of a storm that delivered intense rainfall across...
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Matthew A. Thomas, Jason W. Kean, Scott W. McCoy, Donald N. Lindsay, Jaime Kostelnik, David B. Cavagnaro, Francis K. Rengers, Amy E. East, Jonathan Schwartz, Douglas P. Smith, Brian D. Collins
A model integrating satellite-derived shoreline observations for predicting fine-scale shoreline response to waves and sea-level rise across large coastal regions A model integrating satellite-derived shoreline observations for predicting fine-scale shoreline response to waves and sea-level rise across large coastal regions
Satellite-derived shoreline observations combined with dynamic shoreline models enable fine-scale predictions of coastal change across large spatiotemporal scales. Here, we present a satellite-data-assimilated, “littoral-cell”-based, ensemble Kalman-filter shoreline model to predict coastal change and uncertainty due to waves, sea-level rise (SLR), and other natural and anthropogenic...
Authors
Sean Vitousek, Kilian Vos, Kristen D. Splinter, Li H. Erikson, Patrick L. Barnard
Relative contributions of water-level components to extreme water levels along the US Southeast Atlantic Coast from a regional-scale water-level hindcast Relative contributions of water-level components to extreme water levels along the US Southeast Atlantic Coast from a regional-scale water-level hindcast
A 38-year hindcast water level product is developed for the U.S. Southeast Atlantic coastline from the entrance of Chesapeake Bay to the southeast tip of Florida. The water level modelling framework utilized in this study combines a global-scale hydrodynamic model (Global Tide and Surge Model, GTSM-ERA5), a novel ensemble-based tide model, a parameterized wave setup model, and...
Authors
Kai Alexander Parker, Li H. Erikson, Jennifer Anne Thomas, Cornelis M. Nederhoff, Patrick L. Barnard, Sanne Muis
Rapid modeling of compound flooding across broad coastal regions and the necessity to include rainfall driven processes: A case study of Hurricane Florence (2018) Rapid modeling of compound flooding across broad coastal regions and the necessity to include rainfall driven processes: A case study of Hurricane Florence (2018)
In this work, we show that large-scale compound flood models developed for North and South Carolina, USA, can skillfully simulate multiple drivers of coastal flooding as confirmed by measurements collected during Hurricane Florence (2018). Besides the accuracy of representing observed water levels, the importance of individual processes was investigated. We demonstrate that across the...
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Tim Leijnse, Cornelis M. Nederhoff, Jennifer Anne Thomas, Kai Alexander Parker, Maarten van Ormondt, Li H. Erikson, Robert T. McCall, Ap van Dongeren, Andrea C. O'Neill, Patrick L. Barnard
User needs assessment for postfire debris-flow inundation hazard products User needs assessment for postfire debris-flow inundation hazard products
Debris flows are a type of mass movement that is more likely after wildfires, and while existing hazard assessments evaluate the rainfall intensities that are likely to trigger debris flows, no operational hazard assessment exists for identifying the areas where they will run out after initiation. Fifteen participants who work in a wide range of job functions associated with southern...
Authors
Katherine R. Barnhart, Veronica Romero, Katherine R. Clifford
A 1.2 billion pixel human-labeled dataset for data-driven classification of coastal environments A 1.2 billion pixel human-labeled dataset for data-driven classification of coastal environments
The world’s coastlines are spatially highly variable, coupled-human-natural systems that comprise a nested hierarchy of component landforms, ecosystems, and human interventions, each interacting over a range of space and time scales. Understanding and predicting coastline dynamics necessitates frequent observation from imaging sensors on remote sensing platforms. Machine Learning models...
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Daniel D. Buscombe, Phillipe Alan Wernette, Sharon Fitzpatrick, Jaycee Favela, Evan B. Goldstein, Nicholas Enwright
Related
Filter Total Items: 38
Topobathymetric Model of the Coastal Georgia, 1851 to 2020 Topobathymetric Model of the Coastal Georgia, 1851 to 2020
To support Hurricane Florence impact modeling of storm-induced flooding and sediment transport, the U.S. Geological Survey (USGS) Coastal National Elevation Database (CoNED) Applications Project has created an integrated 1-meter topobathymetric digital elevation model (TBDEM) for coastal Georgia. High-resolution coastal topobathymetric data are required to characterize flooding, storms...
Earthquake triggered ground failure associated with the M7.1 2018 southcentral Alaska Earthquake (ver. 2.0, December 2023) Earthquake triggered ground failure associated with the M7.1 2018 southcentral Alaska Earthquake (ver. 2.0, December 2023)
The November 30, 2018, magnitude (Mw) 7.1 Anchorage, Alaska earthquake triggered substantial ground failure throughout Anchorage and surrounding areas (Grant et al., 2020; Jibson et al., 2020). The earthquake was an intraslab event with a focal depth of about 47 km and an epicenter about 16 km north of the city of Anchorage. Peak ground accelerations reached ∼30% g. Despite the...
Aerial Imagery of the North Carolina Coast: 2020-02-08 to 2020-02-09 Aerial Imagery of the North Carolina Coast: 2020-02-08 to 2020-02-09
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Aerial Imagery of the North Carolina Coast: 2020-05-08 to 2020-05-09 Aerial Imagery of the North Carolina Coast: 2020-05-08 to 2020-05-09
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Coast Train--Labeled imagery for training and evaluation of data-driven models for image segmentation Coast Train--Labeled imagery for training and evaluation of data-driven models for image segmentation
Coast Train is a library of images of coastal environments, annotations, and corresponding thematic label masks (or 'label images') collated for the purposes of training and evaluating machine learning (ML), deep learning, and other models for image segmentation. It includes image sets from both geospatial satellite, aerial, and UAV imagery and orthomosaics, as well as non-geospatial...
Topobathymetric Model of the Coastal Carolinas, 1851 to 2020 Topobathymetric Model of the Coastal Carolinas, 1851 to 2020
To support Hurricane Florence impact modeling of storm-induced flooding and sediment transport, the U.S. Geological Survey (USGS) Coastal National Elevation Database (CoNED) Applications Project has created an integrated 1-meter topobathymetric digital elevation model (TBDEM) for coastal North Carolina, and South Carolina. High-resolution coastal topobathymetric data are required to...
Aerial Imagery of the North Carolina Coast: 2019-11-26 Aerial Imagery of the North Carolina Coast: 2019-11-26
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Aerial Imagery of the North Carolina Coast: 2019-10-11 Aerial Imagery of the North Carolina Coast: 2019-10-11
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Aerial Imagery of the North Carolina Coast: 2019-09-08 to 2019-09-13, Post-Hurricane Dorian Aerial Imagery of the North Carolina Coast: 2019-09-08 to 2019-09-13, Post-Hurricane Dorian
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Aerial Imagery of the North Carolina Coast: 2019-08-30 and 2019-09-02, Pre-Hurricane Dorian Aerial Imagery of the North Carolina Coast: 2019-08-30 and 2019-09-02, Pre-Hurricane Dorian
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM)...
Storm-Induced Overwash Extent Storm-Induced Overwash Extent
The Coastal Change Hazards Technical Capabilities and Applications project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation’s coastlines. This data release defines the alongshore extent of overwash deposits, determined from aerial photograph analysis, attributed to coastal processes during storm events. Note: This data release was...
Water-level data for the crater lake at the summit of Kilauea Volcano, Island of Hawai'i, 2019-2020 Water-level data for the crater lake at the summit of Kilauea Volcano, Island of Hawai'i, 2019-2020
During 2018, Kilauea Volcano, on the Island of Hawaiii, had a large effusive eruption (~1 cubic kilometer of lava) on the lower East Rift Zone that caused widespread destruction (Neal and others, 2019; Dietterich and others, 2021). This lower flank eruption was accompanied by one of the largest collapses of the summit caldera in two hundred years, with portions of the caldera floor...
Filter Total Items: 56
Modeled coastal-ocean pathways of land-sourced contaminants in the aftermath of Hurricane Florence Modeled coastal-ocean pathways of land-sourced contaminants in the aftermath of Hurricane Florence
Extreme precipitation during Hurricane Florence, which made landfall in North Carolina in September 2018, led to breaches of hog waste lagoons, coal ash pits, and wastewater facilities. In the weeks following the storm, freshwater discharge carried pollutants, sediment, organic matter, and debris to the coastal ocean, contributing to beach closures, algae blooms, hypoxia, and other...
Authors
Melissa Moulton, Joseph B. Zambon, Zuo Xue, John C. Warner, Daoyang Bao, Dongxiao Yin, Zafer Defne, Ruoying He, Christie Hegermiller
Slowly but surely: Exposure of communities and infrastructure to subsidence on the US east coast Slowly but surely: Exposure of communities and infrastructure to subsidence on the US east coast
Coastal communities are vulnerable to multihazards, which are exacerbated by land subsidence. On the US east coast, the high density of population and assets amplifies the region's exposure to coastal hazards. We utilized measurements of vertical land motion rates obtained from analysis of radar datasets to evaluate the subsidence-hazard exposure to population, assets, and infrastructure...
Authors
Leonard O. Ohenhen, Manoochehr Shirzaei, Patrick L. Barnard
The 2023 US 50-State National Seismic Hazard Model: Overview and implications The 2023 US 50-State National Seismic Hazard Model: Overview and implications
The US National Seismic Hazard Model (NSHM) was updated in 2023 for all 50 states using new science on seismicity, fault ruptures, ground motions, and probabilistic techniques to produce a standard of practice for public policy and other engineering applications (defined for return periods greater than ∼475 or less than ∼10,000 years). Changes in 2023 time-independent seismic hazard...
Authors
Mark D. Petersen, Allison Shumway, Peter M. Powers, Edward H. Field, Morgan P. Moschetti, Kishor S. Jaiswal, Kevin R. Milner, Sanaz Rezaeian, Arthur D. Frankel, Andrea L. Llenos, Andrew J. Michael, Jason M. Altekruse, Sean Kamran Ahdi, Kyle Withers, Charles Mueller, Yuehua Zeng, Robert E. Chase, Leah M. Salditch, Nico Luco, Kenneth S. Rukstales, Julie A. Herrick, Demi Leafar Girot, Brad T. Aagaard, Adrian Bender, Michael L. Blanpied, Richard W. Briggs, Oliver S. Boyd, Brandon Clayton, Christopher DuRoss, Eileen L. Evans, Peter J. Haeussler, Alexandra Elise Hatem, Kirstie Lafon Haynie, Elizabeth H. Hearn, Kaj M. Johnson, Zachary Alan Kortum, N. Simon Kwong, Andrew James Makdisi, Henry Mason, Daniel McNamara, Devin McPhillips, P. Okubo, Morgan T. Page, Frederick Pollitz, Justin Rubinstein, Bruce E. Shaw, Zheng-Kang Shen, Brian Shiro, James Andrew Smith, William J. Stephenson, Eric M. Thompson, Jessica Ann Thompson Jobe, Erin A. Wirth, Robert C. Witter
Global projections of storm surges using high-resolution CMIP6 climate models Global projections of storm surges using high-resolution CMIP6 climate models
In the coming decades, coastal flooding will become more frequent due to sea-level rise and potential changes in storms. To produce global storm surge projections from 1950 to 2050, we force the Global Tide and Surge Model with a ∼25-km resolution climate model ensemble from the Coupled Model Intercomparison Project Phase 6 High Resolution Model Intercomparison Project (HighResMIP). This...
Authors
Sanne Muis, Jeroen C. J. H. Aerts, Jose A. A. Antolinez, Job C. Dullaart, Trang Minh Duong, Li H. Erikson, Rein J. Haarsma, Maialen Irazoqui Apecechea, Matthias Mengel, Dewi Le Bars, Andrea C. O'Neill, Roshanka Ranasinghe, Malcolm J. Roberts, Martin Verlaan, Philip J. Ward, Kun Yan
Forecasting the inundation of postfire debris flows Forecasting the inundation of postfire debris flows
In the semi-arid regions of the western United States, postfire debris flows are typically runoff generated. The U.S. Geological Survey has been studying the mechanisms of postfire debris-flow initiation for multiple decades to generate operational models for forecasting the timing, location, and magnitude of postfire debris flows. Here we discuss challenges and progress for extending...
Authors
Katherine R. Barnhart, Ryan P Jones, David L. George, Francis K. Rengers, Jason W. Kean
Runout model evaluation based on back-calculation of building damage Runout model evaluation based on back-calculation of building damage
We evaluated the ability of three debris-flow runout models (RAMMS, FLO2D and D-Claw) to predict the number of damaged buildings in simulations of the 9 January 2019 Montecito, California, debris-flow event. Observations of building damage after the event were combined with OpenStreetMap building footprints to construct a database of all potentially impacted buildings. At the estimated...
Authors
Katherine R. Barnhart, Jason W. Kean
Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards
The steep, tectonically active terrain along the Central California (USA) coast is well known to produce deadly and destructive debris flows. However, the extent to which fire affects debris-flow susceptibility in this region is an open question. We documented the occurrence of postfire debris floods and flows following the landfall of a storm that delivered intense rainfall across...
Authors
Matthew A. Thomas, Jason W. Kean, Scott W. McCoy, Donald N. Lindsay, Jaime Kostelnik, David B. Cavagnaro, Francis K. Rengers, Amy E. East, Jonathan Schwartz, Douglas P. Smith, Brian D. Collins
A model integrating satellite-derived shoreline observations for predicting fine-scale shoreline response to waves and sea-level rise across large coastal regions A model integrating satellite-derived shoreline observations for predicting fine-scale shoreline response to waves and sea-level rise across large coastal regions
Satellite-derived shoreline observations combined with dynamic shoreline models enable fine-scale predictions of coastal change across large spatiotemporal scales. Here, we present a satellite-data-assimilated, “littoral-cell”-based, ensemble Kalman-filter shoreline model to predict coastal change and uncertainty due to waves, sea-level rise (SLR), and other natural and anthropogenic...
Authors
Sean Vitousek, Kilian Vos, Kristen D. Splinter, Li H. Erikson, Patrick L. Barnard
Relative contributions of water-level components to extreme water levels along the US Southeast Atlantic Coast from a regional-scale water-level hindcast Relative contributions of water-level components to extreme water levels along the US Southeast Atlantic Coast from a regional-scale water-level hindcast
A 38-year hindcast water level product is developed for the U.S. Southeast Atlantic coastline from the entrance of Chesapeake Bay to the southeast tip of Florida. The water level modelling framework utilized in this study combines a global-scale hydrodynamic model (Global Tide and Surge Model, GTSM-ERA5), a novel ensemble-based tide model, a parameterized wave setup model, and...
Authors
Kai Alexander Parker, Li H. Erikson, Jennifer Anne Thomas, Cornelis M. Nederhoff, Patrick L. Barnard, Sanne Muis
Rapid modeling of compound flooding across broad coastal regions and the necessity to include rainfall driven processes: A case study of Hurricane Florence (2018) Rapid modeling of compound flooding across broad coastal regions and the necessity to include rainfall driven processes: A case study of Hurricane Florence (2018)
In this work, we show that large-scale compound flood models developed for North and South Carolina, USA, can skillfully simulate multiple drivers of coastal flooding as confirmed by measurements collected during Hurricane Florence (2018). Besides the accuracy of representing observed water levels, the importance of individual processes was investigated. We demonstrate that across the...
Authors
Tim Leijnse, Cornelis M. Nederhoff, Jennifer Anne Thomas, Kai Alexander Parker, Maarten van Ormondt, Li H. Erikson, Robert T. McCall, Ap van Dongeren, Andrea C. O'Neill, Patrick L. Barnard
User needs assessment for postfire debris-flow inundation hazard products User needs assessment for postfire debris-flow inundation hazard products
Debris flows are a type of mass movement that is more likely after wildfires, and while existing hazard assessments evaluate the rainfall intensities that are likely to trigger debris flows, no operational hazard assessment exists for identifying the areas where they will run out after initiation. Fifteen participants who work in a wide range of job functions associated with southern...
Authors
Katherine R. Barnhart, Veronica Romero, Katherine R. Clifford
A 1.2 billion pixel human-labeled dataset for data-driven classification of coastal environments A 1.2 billion pixel human-labeled dataset for data-driven classification of coastal environments
The world’s coastlines are spatially highly variable, coupled-human-natural systems that comprise a nested hierarchy of component landforms, ecosystems, and human interventions, each interacting over a range of space and time scales. Understanding and predicting coastline dynamics necessitates frequent observation from imaging sensors on remote sensing platforms. Machine Learning models...
Authors
Daniel D. Buscombe, Phillipe Alan Wernette, Sharon Fitzpatrick, Jaycee Favela, Evan B. Goldstein, Nicholas Enwright