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4 results for “Flood impact assessment”
Dataset for the article "Development of an integrated socio-hydrological modeling framework for assessing the impacts of shelter location arrangement and human behaviors on flood evacuation processes"
<p>This dataset include the data needed to create the socio-hydrological model to simulate human evacuation processes via a transportation network before a flood hits the residential area. Source code, in JAVA, for generating households in the agent-based model are also provided. </p>
Quantitative assessment of the reservoir-induced and urbanization-induced impact on multivariate flood risk via a nonstationary vine Copula model
<p>Here we show the results of the characteristics of the floods at Huayuankou, Lanzhou and Toudaoguai gauges selected by AMS and POT mentod, respectively. Besides that, the inormation about the reservoirs and the imprevious layer in the control catchment of each station is also uploaded.</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>
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>
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