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HYDROGRAMME DE CRUE
Published in CIGB ICOLD, Flood Evaluation and Dam Safety, 2018
Estimating the probable maximum precipitation (PMP) and determining the associated flood flow rates and volumes by transforming the precipitation to runoff. Examining the floodplain and stream to identify paleo-flood evidence such as high-water marks, boulder marks on trees or banks, debris lines, historical accounts by local residents, or geologic or geomorphologic evidence.
Use of Twitter in disaster rescue: lessons learned from Hurricane Harvey
Published in International Journal of Digital Earth, 2020
Volodymyr V. Mihunov, Nina S. N. Lam, Lei Zou, Zheye Wang, Kejin Wang
The study area for the Twitter user survey included 374 zip code areas affected by flooding during Hurricane Harvey, which span across 37 counties in Texas and 4 Louisiana Parishes (Figure 1). The affected zip code areas were identified from the U. S. Geological Survey (USGS) Summary Peaks point locations data (2017) and their flood inundation shapefiles (Watson et al. 2018b). For the Summary Peaks dataset (USGS 2017), USGS obtained 1258 water surface elevations through averaging 2123 field surveyed high-water marks that span across the entire study area (Watson et al. 2018a). High-water marks are evidence of water surface elevations such as flood debris trapped in tree branches and water stains on sides of the walls, that were preserved shortly after the flood with more permanent marks, and then documented and surveyed using hand-held Global Positioning System (GPS) devices (Watson et al. 2018a). Additionally, Watson et al. (2018b) used the USGS streamflow-gaging stations data to create 19 inundation maps that covered several smaller areas surrounding selected rivers and water bodies. We utilized these data sets to identify the 374 zip code areas that were affected by flooding for the Twitter user survey distribution.