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Portable Roadway High Water Detection System for Driver Safety and Infrastructure Assessment [Supporting Dataset]
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2019-08-01
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Abstract:The state of Texas, local governments, and community groups are adopting several initiatives to address this problem. The main goal of this project is to develop an approach to enhance prediction and detection of roadway flooding and help efforts to prevent driving into flood roadways. The motivation of this work was initiated by the alarming number of vehicle related flood fatalities in Texas, mostly at low-water crossings. Texas leads the nation in the number of flood fatalities and about 77% of flood fatalities in Texas are motor vehicle-related. This percentage is much higher than the national percentage reported in several previous studies. Motor vehicle-related flood fatalities in Texas are generally correlated with monthly climate, topography, and population density. For example, about half of the fatalities caused by Hurricane Harvey were transportation-related. The presence of numerous low water crossings throughout Texas contribute to the higher recurrence rates of floods that pose a danger to vehicles. The research team has been challenged to identify effective measures to improve safety at low-water crossings. Therefore, the research team developed an approach that combines data analysis, modeling, and high water detection and communication to improve safety at low-water crossings. Researchers conducted the following tasks: literature review, vehicle-related flood fatality analysis, review of transportation fatalities cause by Hurricane Harvey, and proposed the design of a warning systems at low-water crossings that can detect and predict water depth and velocity at these locations. It was suggested that flood detection and warning can be significantly augment by using sensing technologies that can detect not only the water depth but also the water velocity in combination with a physically-based hydrologic modeling system that can provide forecasts of water depth and velocity at locations of interest. The results of the model and information of the sensors can be used to provide timely and adequate warning to approaching motorists that flooded roadway conditions exist further up the road. The total size of the described zip file is 11.5 MB. Files with the .xlsx extension are Microsoft Excel spreadsheet files. These can be opened in Excel or open-source spreadsheet programs. Docx files are document files created in Microsoft Word. These files can be opened using Microsoft Word or with an open source text viewer such as Apache OpenOffice. The OPT, OHL, OTL, PRJ, SUM, IN, OUT TFW, STO, XY, CIF, ELE, GST, LSF, MSK, SMT, IHL, CMF, PRO, IDX, XYS, GAG, and PRN files are all used to model hydraulics using the software Gridded Surface Subsurface Hydrologic Analysis, which is free to download.
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Content Notes:National Transportation Library (NTL) Curation Note: As this dataset is preserved in a repository outside U.S. DOT control, as allowed by the U.S. DOT's Public Access Plan (https://doi.org/10.21949/1503647) Section 7.4.2 Data, the NTL staff has performed NO additional curation actions on this dataset. The current level of dataset documentation is the responsibility of the dataset creator. NTL staff last accessed this dataset at its repository URL on 2022-11-11. If, in the future, you have trouble accessing this dataset at the host repository, please email NTLDataCurator@dot.gov describing your problem. NTL staff will do its best to assist you at that time.
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