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48 results for “flood risk”
Distribution records: Reconciling biodiversity conservation and flood risk reduction: the new strategy for freshwater protected areas
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A data science approach to climate change risk assessment applied to pluvial flood occurrences for the United States and Canada (Supplementary Material)
<p>This resource is tied to manuscript "A data science approach to climate change risk assessment applied to pluvial flood occurrences for the United States and Canada".</p> <p>It contains: (1) a PDF with additional details on the implementation of GLM, GAM and RF, summarized outputs for two models, a bias analysis of the CRCM and extensive tables from Section 5.2; (2) full outputs for two models; (3) high-resolution figures, and; (4) rasters for selected figures.</p> <p>**</p> <p>Version 2 adds a log-log version of Figure 9 and changes the main PDF file to remove blue section titles.</p>
Global Flood Proportional Economic Loss Risk Deciles
The Global Flood Proportional Economic Loss Risk Deciles is a 2.5 minute grid of flood hazard economic loss as proportions of Gross Domestic Product (GDP) per analytical Unit. Estimates of GDP at risk are based on regional economic loss rates derived from historical records of the Emergency Events Database (EM-DAT). Loss rates are weighted by the hazard's frequency and distribution. The methodology of Sachs et al. (2003) is followed to determine baseline estimates of GDP per grid cell. To better reflect the confidence surrounding the data and procedures, the range of proportionalities is classified into deciles, 10 class of an approximately equal number of grid cells of increasing risk. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
Global Flood Mortality Risks and Distribution
The Global Flood Mortality Risks and Distribution is a 2.5 minute grid of global flood mortality risks. Gridded Population of the World, Version 3 (GPWv3) data provided a baseline population per grid cell from which to estimate potential mortality risks due to flood hazard. Mortality loss estimates per flood event are calculated using regional, hazard-specific mortality records of the Emergency Events Database (EM-DAT) that span the 20 years between 1981 and 2000. Data regarding the frequency and distribution of flood hazard are obtained from the Global Flood Hazard Frequency and Distribution data set. In order to more accurately reflect the confidence associated with the data and the procedures, the potential mortality estimate range is classified into deciles, 10 classes of increasing hazard with an approximately equal number of grid cells per class, producing a relative estimate of flood-based mortality risks. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
Global Flood Total Economic Loss Risk Deciles
The Global Flood Total Economic Loss Risk Deciles is a 2.5 minute grid of global flood total economic loss risks. A process of spatially allocating Gross Domestic Product (GDP) based upon the Sachs et al. (2003) methodology is utilized. First the proportional contributions of subnational Units to their respective national GDP are determined using sources of various origins. The contribution rates are then applied to published World Bank Development Indicators to determine a GDP value for the subnational Unit. Once the national GDP has been spatially stratified into the smallest administrative Units available, GDP values for grid cells are derived using Gridded Population of the World, Version 3 (GPWv3) data of population distributions. A per capita contribution value is determined within each subnational Unit, and this value is multiplied by the population per grid cell. Once a GDP value has been determined on a per grid cell basis, then the regionally variable loss rate as derived from the historical records of EM-DAT is used to determine the total economic loss risks posed to a grid cell by flood hazards. The final surface does not present absolute values of total economic loss, but rather a relative decile (1-10 with increasing risk) ranking of grid cells based upon the calculated economic loss risks. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).
First Street Aggregated Flood Risk Summary Statistics Version 1.3
<p>This dataset includes <a href="https://firststreet.org/">First Street</a>'s aggregated flood risk summary statistics. The data is available in CSV format and is aggregated at the congressional district, county, and zip code level. The data allows you to compare FSF data with FEMA data. You can also view aggregated flood risk statistics for various modeled return periods (5-, 100-, and 500-year) and see how risk changes due to climate change (compare FSF 2020 and 2050 data). There are various <a href="https://floodfactor.com/">Flood Factor</a> risk score aggregations available including the average risk score for all properties (flood factor risk scores 1-10) and the average risk score for properties with risk (i.e. flood factor risk scores of 2 or greater). This is version 1.3 of the data and it covers the 48 contiguous United States. There will be updated versions to follow.</p> <p>If you are interested in acquiring First Street flood data, you can request to access the data <a href="https://firststreet.org/data-access/paid-access/?utm_source=Summary_Statistics_v1.3&utm_medium=Purchase_Data&utm_campaign=Zenodo#pricing-component">here</a>. More information on First Street's flood risk statistics can be found <a href="https://firststreet.org/data-access/getting-started-with-first-street-data/data-dictionary/?utm_source=Summary_Statistics_v1.3&utm_medium=Data_Dictionary&utm_campaign=Zenodo">here</a> and information on First Street's hazards can be found <a href="https://firststreet.org/data-access/getting-started-with-first-street-data/documentation-hazard-dictionary/?utm_source=Summary_Statistics_v1.3&utm_medium=Hazard_Dictionary&utm_campaign=Zenodo">here</a>.</p>
First Street Aggregated Flood Risk Summary Statistics Version 2.0
<p>This dataset includes <a href="https://firststreet.org/">First Street</a>'s aggregated flood risk summary statistics. The data is available in CSV format and is aggregated at the state, congressional district, county, and zip code level. The data allows you to compare FSF data with FEMA data. You can also view aggregated flood risk statistics for various modeled return periods (5-, 100-, and 500-year) and see how risk changes due to climate change (compare FSF 2020 and 2050 data). There are various <a href="https://floodfactor.com/">Flood Factor</a> risk score aggregations available including the average risk score for all properties (flood factor risk scores 1-10) and the average risk score for properties with risk (i.e. flood factor risk scores of 2 or greater). This is version 2.0 of the data and it covers the 50 United States and Puerto Rico. There will be updated versions to follow.</p> <p>If you are interested in acquiring First Street flood data, you can request to access the data <a href="https://firststreet.org/data-access/paid-access/?utm_source=Summary_Statistics_v1.3&utm_medium=Purchase_Data&utm_campaign=Zenodo#pricing-component">here</a>. More information on First Street's flood risk statistics can be found <a href="https://firststreet.org/data-access/getting-started-with-first-street-data/documentation-data-dictionaryv2/">here</a> and information on First Street's hazards can be found <a href="https://firststreet.org/data-access/getting-started-with-first-street-data/documentation-hazard-dictionary/?utm_source=Summary_Statistics_v1.3&utm_medium=Hazard_Dictionary&utm_campaign=Zenodo">here</a>.</p>
The data for "Entrapment risk precedes and is more fatal than instability risk in mountainous flash floods"
<p><span>The DEM and inundation depth data of the central area of Liulin Town were obtained by field measurement after the “8.12” flood event.</span></p>
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OpenNeuro
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