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32 results for “Flood impacts”
Timing of hydrologic anomalies direct impacts on migration traits in a flood pulse fishery system
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Flood Occurrence and Impact Models for Socioeconomic Applications over Canada and the United States (Supplementary Material)
<p>Supplementary Material to the manuscript entitled "Flood Occurrence and Impact Models for Socioeconomic Applications over Canada and the United States" by the same authors.</p>
Quantitative Assessment of the Impact of Future Land Use Changes on Flood Risk Using Remote Sensing, Machine Learning, and a Hydraulic Model
<p> </p> <p>The RF Machine learning code </p> <p>Topological, geomorphology, geology, metrological information of the Tajan watershed.</p> <p>Land use land cover images of the Tajan watershed</p> <p>River, transportation roads, villages map </p> <p>Global damage function datasets.</p>
Repeated failures of the giant Beshkiol landslide and its impact on the long-term Naryn Basin floodings, Kyrgyz Tien Shan.
<p>Drone video taken in 2022 showing the different study sites (Kyrgyz Tien Shan) :</p> <p>From 00:00:00 to 00:00:30 min, seconds : Beshkiol area with view on the basal contact of one of the secondary landslides and the upstream lake levels (shown in figure 4 and 5).</p> <p>From 00:00:31 to 00:01:27 min, seconds: Section overview on the cliff of Kok-Dhzar presented in figure 3.</p> <p>From 00:01:27 to 00:01:56 min, seconds: Kok-Dhzar village and landscape view with the sedimentary sequence and the alluvial fans.</p>
Future Riverine Flood Impacts for NUTS3 regions in Europe: GLOFRIS input to DIFI
<p>This dataset presents results of current and future riverine flood impact data for NUTS3 regions in Europe. The dataset has been developed following the methodology presented in Tiggeloven et al. (2020) and Mortensen et al. (In Review).</p><p>This dataset can be used to as direct input for the DIFI model as described in Tesselaar et al. (2023).</p><p>References:</p><p>Mortensen, E., Tiggeloven, T., Haer, T., van Bemmel, B., Bouwman, A., Ligtvoet, W., & Ward, P.J.: The potential for various riverine flood DRR measures at the global scale. <i>Journal of Coastal and Riverine Flood Risk</i>, In Review.</p><p>Tesselaar, M., Botzen, W.J.W., Aerts, J.C.J.H., Tiggeloven, T. (2023). Flood insurance is a driver of population growth in European floodplains. <i>Nature Communications (provisionally accepted)</i></p><p>Tiggeloven, T., De Moel, H., Winsemius, H. C., Eilander, D., Erkens, G., Gebremedhin, E., ... & Ward, P. J. (2020). Global-scale benefit–cost analysis of coastal flood adaptation to different flood risk drivers using structural measures. <i>Natural Hazards and Earth System Sciences</i>, <i>20</i>(4), 1025-1044.</p>
Data from: Plant traits of propagule banks and standing vegetation reveal flooding alleviates impacts of agriculture on wetland restoration
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Assessing the Impacts of Super Storm Flooding in the Transportation Infrastructure – Case Study: San Antonio, Texas
<p>Corresponding data set for Tran-SET Project No. 18HSTSA02. Abstract of the final report is stated below for reference:</p> <p>"Flooding are likely to increase worldwide due to climate change. Large storms, referred here as superstorms, defined as events with return period equal or larger than 100 years, can lead to an increase of property damages and loss of life. The ability to predict and plan for the impacts of superstorms on transportation infrastructure is key to mitigate future damages and losses. This study analyzed 51 combinations of future projections for representative concentration pathways (RCP) 4.5 and 8.5 scenarios, which were used to calculate future 1st and 3rd quartiles, median, minimum and maximum intensity-duration-frequency curves (IDF). A HEC-HMS and GSSHA models were built for Leon Creek and Upper San Antonio watersheds. HEC-RAS 1D and 2D were used to evaluate flooding in 20 bridges and the extent of flooded area and roads in both watersheds and to test flood control scenarios. Land use modification with 5, 10 and 15% of LID areas in the watersheds were simulated. The use of levees and altering channels were evaluated. In addition, we evaluated how an increasing the storage capacity of the Olmos Dam would contribute to reduce flood impacts downstream. Results show that the 3rd quartile of projected IDF is closest to the one originated with observed precipitation, which is likely to increase in the future. The near future (2025-2049) under RCP 4.5 scenario presented the greatest increase in intensity. HEC-HMS models showed that discharge peak will increase for all future periods under both scenarios, for the 100- and 500-years storms. Flood projections generated by GSSHA for 100- and 500-years and future precipitation showed that flooded area can increase significantly. For instance, the increase in flooded roads can be more than 80% in near future for 500-year storm in Leon Creek watershed. HEC-RAS analysis showed that all 20 analyzed bridges can be flooded with 500-years storm with climate change and 15 with the 100-year storm. Simulation showed that LID implementation and the elevation of the Olmos Dam’s crest were ineffective to protect transportation infrastructure. Enhancing cross-sections of the main channels and the use of levees can mitigate the impact in some bridges. This study illustrates the need for updates in the design criteria of current and future transportation infrastructure."</p>
ECFAS Pan-EU Impact Catalogue, D5.4 – Pan-EU flood maps catalogue - ECFAS project (GA 101004211), www.ecfas.eu
<p>The European Copernicus Coastal Flood Awareness System (ECFAS) project aimed at contributing to the evolution of the Copernicus Emergency Management Service (https://emergency.copernicus.eu/) by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS provides a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits.</p> <p>The ECFAS Proof-of-Concept development ran from January 2021 to December 2022. The ECFAS project was a collaboration between Scuola Universitaria Superiore IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and was funded by the <strong>European Commission H2020 Framework Programme</strong> within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services. </p> <p><em><strong>Reference literature:</strong></em></p> <p><strong><em>Duo, E., Montes, J., Le Gal, M., Fernández-Montblanc, T., Ciavola, P., and Armaroli, C.: Validated probabilistic approach to estimate flood direct impacts on the population and assets on European coastlines, Nat. Hazards Earth Syst. Sci., 25, 13–39, <a href="https://doi.org/10.5194/nhess-25-13-2025">https://doi.org/10.5194/nhess-25-13-2025</a>, 2025.</em></strong></p> <p><em>Montes, J., Duo, E., Souto, P., Gastal, V., Grigoriadis, D., Le Gal, M., Fernández-Montblanc, T., Delbour, S., Ieronymidi, E., Armaroli, C., and Ciavola, P.: Evaluating coastal flood impacts at the EU-scale: the ECFAS approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11295, <a href="https://doi.org/10.5194/egusphere-egu22-11295">https://doi.org/10.5194/egusphere-egu22-11295</a>, 2022.</em></p> <p><strong>Description of the files contained in the Dataset</strong></p> <p>The ECFAS Pan-EU Impact Catalogue collects impact layers associated to the flood scenarios contained in the ECFAS Pan-EU Flood Catalogue. To produce the Flood Catalogue, the coast was divided into geographic regions embracing similar oceanographic conditions, and subsequently into coastal sectors. The coastal sectors can be identified by its region index RXXX and its own index CSYYY. Impacts associated to the flood maps were calculated following the approach described in the technical document of the ECFAS Deliverable 5.3 Algorithms for Impact Assessment (ECFAS Impact Tool; Duo et al., 2021). The ECFAS Impact Tool was adapted to assess the affected population, the damage to buildings, roads and railways and the exposure of a variety of other assets (e.g. agriculture, points of interest, etc.) for the flood scenarios included in the ECFAS Flood Catalogue.</p> <p>The shapefile of the polygons defining the coastal sectors as defined for the catalogue implementation is included in the database.</p> <p><strong>The Pan-EU Impact Catalogue is associated with the following additional ECFAS products: </strong></p> <p><strong>- The ECFAS Pan-EU Flood Catalogue</strong></p> <p><strong>Flood Catalogue in Zenodo</strong>: Le Gal, M., Fernández Montblanc, T., Montes Pérez, J., Duo, E., Souto Ceccon, P.E., Cabrita, P., & Ciavola, P. (2022). ECFAS Pan-EU Flood Catalogue, D5.4 – Pan-EU flood maps catalogue - ECFAS project (GA 101004211), https://www.ecfas.eu/ (1.2) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.6778807">https://doi.org/10.5281/zenodo.6778807</a></p> <p><em><strong>Flood Catalogue Reference literature</strong>: Le Gal, M., Fernández-Montblanc, T., Duo, E., Montes Perez, J., Cabrita, P., Souto Ceccon, P., Gastal, V., Ciavola, P., and Armaroli, C.: A new European coastal flood database for low–medium intensity events, Nat. Hazards Earth Syst. Sci., 23, 3585–3602, <a href="https://doi.org/10.5194/nhess-23-3585-2023">https://doi.org/10.5194/nhess-23-3585-2023</a>, 2023.</em></p> <p><strong>- The ECFAS Impact Tool</strong></p> <p><strong>Impact Tool in Zenodo</strong>: Duo, E., Montes Pérez, J., and Souto-Ceccon, P.E. (2021). ECFAS Impact Tool, D5.3 – Algorithms for impact assessment - ECFAS project (GA 101004211), <a href="http://www.ecfas.eu/">www.ecfas.eu</a>, link: <a href="https://doi.org/10.5281/zenodo.5809296">https://doi.org/10.5281/zenodo.5809296</a></p> <p> </p> <p>The Impact Catalogue is accompanied by a technical document describing methods, datasets, structure, format and content of the ECFAS Flood and Impact Catalogues:</p> <p>- Duo, E., Le Gal, M., Souto Ceccon, P.E., Montes Pérez, J., 2022. <a href="https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5ee287a5d&appId=PPGMS">Technical document</a> on the ECFAS Flood and Impact Catalogue, D5.4 – Pan-EU flood maps catalogue - ECFAS project (GA 101004211). <a href="http://www.ecfas.eu/">www.ecfas.eu</a></p> <p> </p> <p>This ECFAS <strong>Impact Catalogue</strong> is made available under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/odbl/1.0/">http://opendatacommons.org/licenses/odbl/1.0/</a>. Any rights in individual contents of the Impact Catalogue are licensed under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/dbcl/1.0/">http://opendatacommons.org/licenses/dbcl/1.0/</a>.</p> <p>The <strong>technical document</strong> describing methods, datasets, structure, format and content of the ECFAS Flood and Impact Catalogues is made available under the <strong>Creative Commons Attribution 4.0 International License</strong>.</p> <p>*The size of the uncompressed dataset is 211 GB.</p> <p><em><strong>Disclaimer:</strong></em></p> <p>ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided.</p> <p>This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211</p> <p> </p>
Impact of storm propagation speed on coastal flood hazard induced by offshore storms in the North Sea
<p>This datasets include all numerical simulation results of the paper "Impact of storm propagation speed on coastal flood hazard induced by offshore storms in the North Sea".</p>
Investigating the Combined Impact of Climate Change and Land Use/Land Cover on Flood Vulnerability Using a Machine Learning Algorithm
<p>Using the uploaded code in preparation of the Flood vulnerability maps.</p><p> </p>
Investigating the Combined Impact of Climate Change and Land Use/Land Cover on Flood Vulnerability Using a Machine Learning Algorithm.
<p>The used data in the paper</p>
Investigating the Combined Impact of Climate Change and Land Use/Land Cover on Flood Vulnerability Using a Machine Learning Algorithm.
<p>Flood points and Meteorological data</p>
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