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394 results for “hazard”
Post-fire flood hazard model (PF2HazMo) version 1.0.0: Model scripts and parameterization and validation data
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Comparing first street foundation and PRIMo flood hazard data across the Los Angeles metropolitan region
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Data from: Compound post-fire flood hazards considering infrastructure sedimentation
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Potential rapidly moving landslide hazards in Western Oregon, clipped to Andrews Experimental Forest, 1999 to 2002
Landslides are a serious geologic hazard, threatening public safety, natural resources, and infrastructure, and costing millions of dollars for repairs each year in Oregon. This map of areas where rapidly moving landslides pose hazards in western Oregon is part of the State's attempt to protect lives and property. The overview map delineates zones that are prone to landslide hazards, especially rapidly moving landslides. These zones provide information to local governments about property that might require more site-specific evaluation. The map is in digital format and was produced with data at a scale of 1:24,000 (1 in. = 2,000 ft). Creation of the map involved the use of Geographic Information System (GIS) modeling, checking and calibrating with limited field evaluations, and comparing with historic landslide inventories. The extent and severity of the hazard posed by rapidly moving landslides varies considerably across western Oregon. In general, the most hazardous areas are mountainous terrains, which are usually sparsely populated, especially drainage channels and depositional fans associated with debris flows. Where hazard areas intersect with human development, use of the map can help to assess the risk and prioritize risk-reduction activities. Various options are available to reduce the risk of landslide losses. Risk-reduction activities can include engineering solutions, public education, warning systems, temporary road closures and evacuation, land use regulation, and many other options. Although this project addresses a range of rapidly moving landslides, this map is not a compilation of all possible landslide hazards.
Foraging in competitive and hazardous environments
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Adaptation time to magnified flood hazards underestimated when derived from tide gauge records [dataset]
<p>This dataset contains the data supporting the manuscript Lambert et al., Adaptation time to magnified flood hazards underestimated when derived from tide gauge records, submitted to Environmental Research Letters.</p> <p>All files contain two main variables:<br> AF is the amplification factor as a function of [station, time, scenario]<br> DT is the doubling time as a function of [station, scenario]</p> <p>Note that these files contain data of all 299 available stations, rather than the subset of 130 presented in the manuscript.</p> <p>Filenames:<br> diss_AWL.nc Average Water Level at dissipative beaches<br> diss_IWL.nc Instantaneous Water Level at dissipative beaches<br> grd_AWL.nc Average Water Level at gentle rocky dikes<br> grd_IWL.nc Instantaneous Water Level at gentle rocky dikes<br> harbour.nc Average and Instantaneous Water Level at harbours, excluding wave contributions<br> srd_AWL.nc Average Water Level at steep rocky dikes<br> srd_IWL.nc Instantaneous Water Level at steep rocky dikes<br> ssb_AWL.nc Average Water Level at steep sandy beaches<br> ssb_IWL.nc Instantaneous Water Level at steep sandy beaches<br> tidegauge.nc Tide gauge-based analysis</p>
Solotvyno hazard & risk maps_ImProDiReT-783232_EN
<p>As a result of the analysis of geological natural environment of Solotvyno, several natural and anthropogenic processes those are potentially dangerous for the population have been identified: karst and suffosion (subsidence, sinkholes, collapses), seasonal and flash floods, flooding, slope erosion, landslides.</p> <p>A set of hazards / risk maps has been elaborated based on expert complex assessment of the natural and anthropogenic hazardous processes manifestations:</p> <p>1. Inventory map of hazardous technogenic-geological and engineering-geological processes manifestations and phenomena for Solotvyno</p> <p>2. Zonation of the hazardous technogenic-geological and engineering-geological processes manifestations;</p> <p>3. Specific land use for Solotvyno;</p> <p>4. Category of land for Solotvyno (according to StateGeoCadastre data);</p> <p>5. Risk Map of Natural and Natural-Antropogenic Hazards for Solotvyno;</p> <p>6. Risk Map of Natural and Natural-Antropogenic Hazards for Solotvyno (with critical infrastructure objects).</p> <p> </p>
Livestock and kangaroo grazing have little effect on biomass and fuel hazard in semi-arid woodlands
<ol> <li>Using livestock grazing as a tool to manage biomass and reduce fuel hazard has gained widespread popularity, but examples from across the globe demonstrate that it often yields mixed, context-dependent results. Grazing has potential to deliver practical solutions in systems where grazing reduces not only biomass but also reduces fuel hazard by altering vegetation connectivity or composition.</li> <li>We assessed the extent to which recent rainfall, rabbit and kangaroo grazing and recent and historic livestock grazing alters and accounts for variation in above-ground biomass, biomass composition and fuel hazard ratings across three broad communities in eastern Australia. We used nested linear models to assess biomass in three vertical vegetation strata, that matched the strata assessed in the Overall Fuel Hazard Assessment guide (i.e. litter/surface fuel; groundstorey vegetation/near surface fuel; and midstorey vegetation/elevated fuel) and Ordinal Logistic Regression to assess categorical fuel hazard ratings.</li> <li>Only recent kangaroo grazing reduced groundstorey biomass across all communities. Kangaroo grazing altered litter mass and significantly reduced surface fuel hazard in one community. Recent livestock grazing did not reduce fuel hazard, and despite significantly reducing half of our measures of biomass, these were not practical reductions. For instance, livestock grazing significantly reduced litter mass, however our model predicts that doubling our assessment of livestock grazing intensity only reduces total litter mass by 0.8 %, or 8 kg per hectare in landscapes where average litter loads ranged from 3,600 to 12,600 kg per hectare. Furthermore, long-term livestock grazing increased shrub biomass and in one community this increased elevated fuel hazard. There were few effects of rabbits. The effects of rainfall on biomass were up to an order of magnitude greater than any effects due to grazing.</li> <li> <i>Synthesis and applications:</i> Our data suggest that management practices that seek to use livestock grazing to reduce biomass in these systems will not achieve practical reductions in biomass and or fuel hazard.</li> </ol>
Quantifying the erasure of earthquake surface ruptures from desert landscapes: Implications for seismic hazard assessment
<p><strong>Original Landscapes</strong></p> <p>DEMs of ~120x140m landscapes clipped from:</p> <p>R1-10 = 2019 M7.1 Ridgecrest earthquake, 2019 lidar (Hudnut et al., 2020), and </p> <p>E1-10 = 2010 M7.2 El Mayor-Cucapah earthquake, 2010 lidar (OpenTopography, 2010).</p> <p>Example: "E5.asc"</p> <p> </p> <p><strong>Degraded Landscapes</strong></p> <p>Linearly diffused using <em>Landlab </em>(Hobley et al., 2017; Barnhart et al., 2020) at timesteps (100, 1000, 5000, 10000 yr) using a <em>k</em> of 1 m^2/kyr.</p> <p>Example: "e5_1000_001_eroded.asc"</p> <p> </p> <p><strong>Mapped Faults Shapefiles </strong>- E1_10_shps & R1_10_shps</p> <p>Faults mapped on each degraded landscape using a systematic mapping process (Scott et al., 2023; Adam, 2023)</p> <p> </p> <p><strong>Ridgecrest DEM</strong> - rc_7_1_0424_utm.tif</p> <p>0.014 m/pix DEM of a portion of the 2019 M7.1 Ridgecrest earthquake rupture, from 6 April 2024. Created from Structure from Motion using drone images. </p> <p> </p> <p><strong>Degradation and analysis python code</strong> - landscape_evolution_earthquake_ruptures-main.zip</p> <p>A set of scripts to simulate the effect of surface processes on surface ruptures and quantify the information loss associated with landscape evolution over time. Includes options to simulate surface processes with linear and non-linear diffusion, implemented using open-access code landlab.</p> <p> </p> <p><strong>References</strong></p> <p>Adam, R. (2023). Evaluation of remote mapping of active fault traces. Arizona State University.</p> <p>Barnhart, K.R., Hutton, E.W.H., Tucker, G.E., Gasparini, NM., Istanbulluoglu, E., Hobley, D.E.J., Lyons, N.J., Mouchene, M., Nudurupati, S.S., Adams, J.M., Bandarogoda, C., 2020, Short communication: Landlab v2.0: A software package for Earth surface dynamics: Earth Surface Dynamics Discussions, doi: 10.5194/esurf-2020-12.</p> <p>Hobley, D.E.J., Adams, J.M., Nudurupati, S.S., Hutton, E.W.H. Gasparini, N.M., Istanbulluoglu, E., and Tucker, G.E., 2017, Creative computing with Landlab: an open-source toolkit for building, coupling, and exploring two-dimensional numerical models of Earth-surface dynamics: Earth Surface Dynamics, v. 5, n. 1, p. 21-46, doi: 10.5194/esurf-5-21-2017.</p> <p>Hudnut, K.W., B. Brooks, K. Scharer, J.L. Hernandez, T.E. Dawson, M.E. Oskin, R. Arrowsmith, C.A. Goulet, K. Blake, M.L. Boggs, S. Bork, C.L. Glennie, J.C. Fernandez-Diaz, A. Singhania, D. Hauser, S. Sorhus (2020). 2019 Ridgecrest, CA Post-Earthquake Lidar Collection. National Center for Airborne Laser Mapping (NCALM). Distributed by OpenTopography. https://doi.org/10.5069/G9W0942Z.. Accessed: 2024-11-25 </p> <p>Opentopography; El Mayor-Cucapah Earthquake (4 April 2010) Rupture LiDAR Scan. Distributed by OpenTopography. https://doi.org/10.5069/G9TD9V7D . Accessed: 2024-11-25</p> <p>Scott, C., Adam, R., Arrowsmith, R., Madugo, C., Powell, J., Ford, J., Gray, B., Koehler, R., Thompson, S., Sarmiento, A., Dawson, T., Kottke, A., Young, E., Williams, A., Kozaci, O., Oskin, M., Burgette, R., Streig, A., Seitz, G., … Ingersoll, S. (2023). Evaluating how well active fault mapping predicts earthquake surface-rupture locations. Geosphere. https://doi.org/10.1130/GES02611.1</p>
Data and codes for Landslide hazard spatiotemporal prediction based on data-driven models: Estimating where, when and how large landslide may be
<p>Data and codes for Landslide hazard spatiotemporal prediction based on data-driven models: Estimating where, when and how large landslide may be</p>
D2.1 MIRACA Climate Hazard Database
<p><span>The MIRACA Climate Hazard Database is a collection of meteorological, geological and hidrological hazards datasets and indicators at a Pan-European and global level. This dabase is the Deliverable 1.2 of the MIRACA Project (Multi-hazard infrastructure Risk Assessment for Climate Adaptation).</span></p>
Data for 'Global Assessment of Interannual Hazard Variability in Coastal Urban Areas and Ecosystems'
<p>This dataset supports Odériz et al. (2024). 'Global Assessment of Interannual Hazard Variability in Coastal Urban Areas and Ecosystems'</p>
Processed files used for OQ based tsunami loss modelling using HPC based inundation and emulators(Part-IV OQ Simulation and Emulation Hazard Dataset)
<div> <div>This dataset is related to the main Zenodo repository: https://doi.org/10.5281/zenodo.13738078</div> <br> <div>This dataset contains some of the processed OpenQuake files covering tsunami inundation depth hazard using simulation results and emulation results discussed in the article - "Towards Using Machine Learning Emulation for Probabilistic Inundation Mapping: Multiple Earthquake Sources and Near-field Effects with project repo - https://github.com/naveenragur/ML4SicilyTsunami/tree/ptha_emulators.</div> <div> </div> <div>The risk calculation and procedure is available in the main repo: <a href="https://github.com/naveenragur/ML4SicilyTsunami/tree/main-dev/risk">https://github.com/naveenragur/ML4SicilyTsunami/tree/main-dev/risk </a></div> <div> </div> <br> <div>The processed files for the test locations of Catania(CT) are provided in compressed gzip files(.gz):</div> <br> <div>Processed hazard information used to prepare and run OQ event based risk analysis are as below,</div> <div> -<strong>hazard.tar.gz </strong>- preliminary numpy files with sitcol, eventid and hazard magnitude info</div> <div> -<strong>loss.tar.gz</strong> -final hdf5 files with both event hazard and site info</div> <br> <div>The filename follows the nomenclature with:</div> </div> <div>ML4SicilyTsunami/risk/loss/tsunami_prob_892.hdf5<br>ML4SicilyTsunami/risk/loss/tsunami_prob_1658.hdf5<br>ML4SicilyTsunami/risk/loss/tsunami_prob_3454.hdf5<br>ML4SicilyTsunami/risk/loss/tsunami_prob_7071.hdf5<br>ML4SicilyTsunami/risk/loss/tsunami_prob_true.hdf5</div> <div><br> <div> <div>More information on the attached readme, see project structure and code is available at:</div> <div><strong>https://github.com/naveenragur/ML4SicilyTsunami/tree/ptha_emulators</strong></div> <div><strong>https://github.com/naveenragur/ML4SicilyTsunami/tree/main-dev/risk</strong></div> <div><strong>https://github.com/naveenragur/OQ-Tsunami</strong></div> </div> </div>
UK climate hazard and climate change adaptation resources for heritage
<p><span>This dataset (.xlsx) is a compendium of climate change hazard data and adaptation resources for cultural heritage. It was created by JBA Consulting for Historic England and is accompanied by a <a href="https://historicengland.org.uk/research/results/reports/16-2024">research report</a> which provides the background, methodology, and results of the project. One aim of the project was to identify and compile climate hazard resources (data and tools) that could assist those managing the UK historic environment, with specific attention paid to data availability, spatial resolution, and format. </span></p> <p><span> </span><span>The project identified 73 datasets and 38 tools. The datasets were linked to relevant climate hazards from a standardised hazard vocabulary (<a href="../records/10868587">Thomas, 2024</a>). The attached pdf file provides further details on how to use the dataset. Further information can be found in the report, and questions can be addressed to Kate Guest at <a href="mailto:Kate.Guest@HistoricEngland.org.uk">Kate.Guest@HistoricEngland.org.uk</a>. </span></p>
Determination of Natural Radioactivity Levels and Associated Radiation Hazard Indices of Wheat Flour Samples From Selected Ethiopian Markets.
<p>Wheat flour is a nutrient-dense food that is commonly consumed by various age groups in Ethiopia. In this study, natural radioactivity levels of <sup>226</sup>Ra, <sup>232</sup>Th, and <sup>40</sup>K, as well as the related dangerous radiological characteristics, were successfully measured on 10 different brands of wheat flour samples using high-purity germanium (HPGe) gamma-ray spectrometry. Average activity concentrations of <sup>226</sup>Ra, <sup>232</sup>Th, and <sup>40</sup>K in wheat flour are found to be 0.26<strong> ±</strong>0.07 Bq.kg<sup>-1</sup>, 1.54<strong> ± </strong>0.43 Bq.kg<sup>-1</sup>, and 59.79<strong>±</strong>3.65 Bq.kg<sup>-1</sup>, respectively. Moreover, the average values of the corresponding radiological parameters, Ra<sub>eq</sub>, H<sub>int</sub>, and annual effective dose (E<sub>ave</sub>) (sum), were also found to be 7.07±0.96 Bq.kg<sup>-1</sup>, 0.019±0.003, and 0.109±0.019 mSvy<sup>-1</sup>, respectively. When the obtained results for all of the samples were compared to the internationally accepted norms, they were found to be below the permissible world average values. Furthermore, the lifetime cancer risk was discovered to be substantially below the permissible limit. According to the study, the risk of absorbing natural radionuclides from wheat flour consumption is negligible. The findings can be used to develop radiation protection rules and regulations for the use of wheat flour in food production and processing.</p>
Assessment of Natural Radioactivity Levels and Estimation of Radiological Hazards in Building Materials Commonly Used in Ethiopian Constructions.
<p>Natural radionuclide activity concentrations were measured in ceramic, gypsum, and brick samples from manufacturers, dealers, and construction sites in and around Addis Ababa, Ethiopia, using an HPGe detector. The study's main objectives were to assess the building material activity and health impacts. Average activity concentrations (Bq.kg<sup>-1</sup>) for <sup>226</sup>Ra in ceramic, gypsum, and brick samples were obtained as 81.19 ± 1.88, 1.34 ± 0.17, and 39.83 ± 1.21, respectively. Respective values of <sup>232</sup>Th were obtained as 166.12 ± 4.20, 0.68 ± 0.18, and 103.71 ± 3.29 and concentrations of <sup>40</sup>K were found to be 755.06 ± 16.10,15.42 ± 1.97, and 921.22 ± 24.90, respectively. Some of the materials that were tested, especially the ceramic sample, had slightly higher concentrations of radionuclides. In all samples except ceramic, Ra<sub>eq </sub>was < 370 Bq.kg<sup>-1</sup>, which is the recommended limiting dose for bulk medium. Furthermore, the corresponding radiological parameters, absorbed dose, annual effective dose equivalent, excess lifetime cancer risk (ELCR), internal (H<sub>in</sub>) and external (H<sub>ex</sub>) hazard indexes, gamma index (Iγ), and alpha index (Iα) were determined. The ELCR average values in this study are slightly higher than the global average, and the indoor and outdoor absorbed dose rates are greater than the limiting criteria of 84 and 59 nGyh<sup>-1</sup>. Therefore, especially for ceramic samples, it is important to assess their radiation potential and should be utilized in a controlled manner to decrease gamma exposure to inhabitants. Finally, the computed data could be used as a baseline to look at any radiological contamination caused by construction materials in the future.</p>
Preventing Struck-by Hazards: Defying Risk-habituation via Virtual Accident Simulation
<p>Repeated exposure to struck-by hazards in road work zones generates workers’ habituation to risks related to those hazards, a key contributor to accidents in road work zones. Thus, analyzing the development of risk habituation and providing proper intervention are crucial to preventing accidents in road work zones. In this context, this study employs a virtual reality (VR) environment as a behavioral intervention tool to investigate its effect on mitigating a decline in workers’ vigilance with habituation to hazards in workplaces. A virtual environment that simulates a road maintenance task was developed and used to repeatedly expose subjects to struck-by hazards in road construction sites. A VR accident was simulated in response to the emergence of habituation to hazards within the virtual environment. The intervention effect was investigated to analyze the frequency and threshold of subjects’ vigilant behaviors. The results indicated that the developed VR environment evoked a decline in subjects’ attentiveness as a result of risk habituation within a relatively short period of experiment time, and the simulated VR accidents generated a sustained effect in reducing risk habituation. The findings of this study provide the understanding of how workers’ risk habituation can be observed using VR and how a behavioral intervention in a VR environment can reduce risk habituation to repeatedly exposed workplace hazards.</p>
MPS19 seismic hazard model of Italy results
<p><em>The MPS19 model is the result of the activities performed by the Seismic Hazard Center at INGV (Centro Pericolosità Sismica - CPS) in the framework of the 2015-2019 DPC-INGV B1 agreements. The documentation of the whole work is presented in Meletti et al. (2021). Details on the earthquake rupture forecasts are reported in Visini et al. (2021). Details on the ground motion models are reported in Lanzano et al. (2020).</em></p> <p><em>Data are free for the users, by reporting the following citation: <strong>Meletti C., Marzocchi W., D'Amico V., Lanzano G., Luzi L., Martinelli F., Pace B., Rovida A., Taroni M., Visini F. & the MPS19 Working Group, 2022. MPS19 seismic hazard model of Italy results. DOI: 10.5281/zenodo.7032251</strong></em></p> <p><em>In each file, the different sheets list the mean values and the values corresponding to 84th, 16th, 97.5th and 2.5th percentiles for the spectral acceleration, contained in the filename. Values are computed for 10 probabilities of exceedance in 50 years (as reported in the column name) and for rocky soil (class A of the Eurocode 8). Values represent the geometric mean of the horizontal components of the shaking. Values are computed on a regular grid 0.05 degrees spaced, covering the Italian territory.</em></p>
Probabilistic Fault Displacement Hazard Assessment materials
<p>The models, data, and information provided here were created as part of the Fault Displacement Hazard Initiative. We provide the Electronic Supplement for Chiou et al., 2023, CDF Fortran subroutines; the ArcGIS least-cost path (LCP) model and implementation guide, LCP MATLAB and Python scripts, and the LCP for 75 events in a shapefile and KMZ format for Thomas et al., 2023; and the Fortran code for Chiou et al. in review for Earthquake Spectra. </p>
Urban heat hazard in the Global South
<p>This dataset includes various estimates of fine-grained outdoor heat hazard and vegetation metrics for cities in the Global South, and also for U.S. cities.<br><br>Extent of urban clusters based on the Global Human Settlement Layer (GHSL; RWI_ALL_v2.geojson), European Space Agency Climate Change Initiative (ESACCI; RWI_ALL_GLOB_v2.geojson) land cover data, and U.S. urbanized areas (GLOB_distance_US.geojson) in geojson format.</p> <p>The geojsons and data tables have several environmental and socioeconomic variables by grid and census tract (for the U.S.).<br><br>The variables are:</p> <p>AT_max: 10-year (2010-2019) average maximum annual air temperature<br>AT_max_summ: 10-year (2010-2019) average maximum summer air temperature<br>AT_min: 10-year (2010-2019) average minimum annual air temperature<br>AT_min_summ: 10-year (2010-2019) average minimum summer air temperature<br>All_area: Area of the grid or census tract<br>EVI: Mean 10-year (2010-2019) Enhanced Vegetation Index<br>Grass_area: Area of grassland for ~2020 from the ESA WorldCover dataset<br>ID: ID of urban cluster (U.S. urbanized areas havr a 'NAME' for the urbanized area instead)<br>LST_day: 10-year (2010-2019) average daytime annual land surface temperature from MODIS Aqua<br>LST_day_summ: 10-year (2010-2019) average daytime summer land surface temperature from MODIS Aqua<br>LST_night: 10-year (2010-2019) average nighttime annual land surface temperature from MODIS Aqua<br>LST_night_summ: 10-year (2010-2019) average nighttime summer land surface temperature from MODIS Aqua<br>PM25: 10-year (2010-2019) average particulate matter below 2.5 micron (not used in paper)<br>Pop: Population of grid or census tract<br>REGION_WB: World Bank region<br>SUBREGION: World Bank subregion (not used in paper)<br>Tree: 10-year (2010-2019) average tree percentage from MODIS continuous vegetation fields<br>Tree_area: Area of trees for ~2020 from the ESA WorldCover dataset<br>Veg: 10-year (2010-2019) average non-tree vegetation percentage from MODIS continuous vegetation fields<br>error: Error in Relative Wealth Index<br>rwi: relative Wealth Index</p> <p> </p> <p>In addition to these, the 'distance' files include a column for distance of the grids or census tract from the centroid of the cluster in belongs to.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.