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Inundation layers for the Pine Island Bayou for the August and September 2017 flood event in Texas
Hurricane Harvey made landfall near Rockport, Texas on August 25 as a category 4 hurricane with wind gusts exceeding 150 miles per hour. As Harvey moved inland the forward motion of the storm slowed down and produced tremendous rainfall amounts to southeastern Texas and southwestern Louisiana. Historic flooding occurred in Texas and Louisiana as a result of the widespread, heavy rainfall over an 8-day period in Louisiana in August and September 2017. Following the storm event, U.S. Geological Survey (USGS) hydrographers recovered and documented 2,123 high-water marks in Texas, noting location and height of the water above land surface. Many of these high-water marks were used to create flood-inundation maps for selected communities of Texas that experienced flooding in August and September, 2017. The mapped area boundary, flood inundation extents, and depth rasters were created to provide an estimated extent of flood inundation along the Pine Island Bayou within the communities of Hull, Daisetta, Sour Lake, Nome, Bevil Oaks, Rose Hill Acres, and the outskirts of Beaumont, Texas. These geospatial data include the following items: 1. bnd_pib; shapefile containing the polygon showing the mapped area boundary for the Pine Island Bayou flood maps, 2. hwm_pib; shapefile containing high-water mark points, 3. polygon_pib; shapefile containing mapped extent of flood inundation, derived from the water-surface elevation surveyed at high-water marks, and 4. depth_pib; raster file for the flood depths derived from the water-surface elevation surveyed at high-water marks. The upstream and downstream mapped area extent is limited to the upstream-most and downstream-most high-water mark locations. In areas of uncertainty of flood extent, the mapped area boundary is lined up with the flood inundation polygon extent. The mapped area boundary polygon was used to extract the final flood inundation polygon and depth raster from the water-surface elevation raster file. Depth raster files were created using the "Topo to Raster" tool in ArcMap (ESRI, 2012). These data show the area of inundation within communities along the Pine Island Bayou, Texas. This polygon shapefile was created to provide an extent of flood inundation along the Pine Island Bayou within communities in the counties of Jefferson, Hardin, Liberty, and Orange, Texas. The extent of the inundation map is a 68-mi reach of Pine Island Bayou through the communities of Hull, Daisetta, Sour Lake, Nome, Bevil Oaks, Rose Hill Acres, and the outskirts of Beaumont. The HWM elevation data from the USGS Short-tern Network (STN) was used to create the flood water-surface raster file (U.S. Geological Survey [USGS], 2018, Short-Term Network Data Portal: USGS flood information web page, accessed February 13, 2018, at https://water.usgs.gov/floods/FEV.). The water-surface raster was the basis for the creation of the final flood inundation polygon and depth layer to support the development of flood inundation map for the Federal Emergency Management Agency's (FEMA) response and recovery operations.
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Flood Inundation Maps for the Amite and Comite Rivers from State Highway 64 to U.S. Highway 190 – City of Central, Louisiana
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The State of Louisiana experienced widespread flooding during the extreme rainfall events of March and August 2016. The City of Central, Louisiana, which lies above the confluence of the Amite and Comite Rivers, is bordered on the East and West respectively by these rivers. The city had extensive damage from both events, in particular the August 2016 flood in which the river basins received up to 30 inches of documented rainfall. Many streamgages in the area recorded peak of record flood levels from the event. The US Geological Survey (USGS) in cooperation with the City of Central, created a digital flood inundation map library to depict estimated areal extents and depth of flooding along 14.5 and 20.2 mile reach lengths of the Amite and Comite Rivers. The maps were created using a 2-dimensional flow model calibrated to the March and August 2016 events as well as to the current stage-discharge ratings at USGS streamgaging stations 07377300 Amite River at Magnolia, Louisiana and 07378000 Comite River near Comite, Louisiana. The maps range from flood stage to the peak of record stage at the gaging stations. Annual peak flow data was analyzed to determine multiple flooding scenario possibilities between the two gages. This data release provides the ArcGIS files and metadata for these maps. In addition, the maps will be hosted by the USGS on an interactive web mapper accessible to the cooperator and the public at: https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program Use of the maps aids city officials and emergency managers in pre-planning for a flood event in areas such as road and bridge closures, staging of man power and materials, and estimation of affected population. The maps also aid the public in foreseeing their flood risk potential and helps them in their decision making regarding life and property.
Comite River Flood Map Files
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A slow-moving area of low pressure and a high amount of atmospheric moisture produced heavy rainfall across Louisiana and southwest Mississippi in August 2016. Over 31 inches of rain was reported in Watson, 30 miles northeast of Baton Rouge, over the duration of the event. The result was major flooding that occurred in the southern portions of Louisiana and included areas surrounding Baton Rouge and Lafayette along rivers such as the Amite, Comite, Tangipahoa, Tickfaw, Vermilion, and Mermentau. The U.S. Geological Survey (USGS) Lower Mississippi-Gulf Water Science Center operates many continuous, streamflow-gaging stations in the impacted area. Peak streamflows of record were measured at 10 locations, and seven other locations experienced peak streamflows ranking in the top 5 for the duration of the period of record. In August 2016, USGS personnel made fifty streamflow measurements at 21 locations on streams in Louisiana. Many of those streamflow measurements were made for the purpose of verifying the accuracy of the stage-streamflow relation at the associated gaging station. USGS personnel also recovered and documented 590 high-water marks after the storm event by noting the location and height of the water above land surface. Many of these high water marks were used to create twelve flood-inundation maps for selected communities of Louisiana that experienced flooding in August 2016. This data release provides the actual flood-depth measurements made in selected river basins of Louisiana that were used to produce the flood-inundation maps published in the companion product (Watson and others, 2017). Reference Watson, K.M., Storm, J.B., Breaker, B.K., and Rose, C.E., 2017, Characterization of peak streamflows and flood inundation of selected areas in Louisiana from the August 2016 flood: U.S. Geological Survey Scientific Investigations Report 2017–5005, 26 p., https://doi.org/10.3133/sir20175005.
Tickfaw River Flood Map Files
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A slow-moving area of low pressure and a high amount of atmospheric moisture produced heavy rainfall across Louisiana and southwest Mississippi in August 2016. Over 31 inches of rain was reported in Watson, 30 miles northeast of Baton Rouge, over the duration of the event. The result was major flooding that occurred in the southern portions of Louisiana and included areas surrounding Baton Rouge and Lafayette along rivers such as the Amite, Comite, Tangipahoa, Tickfaw, Vermilion, and Mermentau. The U.S. Geological Survey (USGS) Lower Mississippi-Gulf Water Science Center operates many continuous, streamflow-gaging stations in the impacted area. Peak streamflows of record were measured at 10 locations, and seven other locations experienced peak streamflows ranking in the top 5 for the duration of the period of record. In August 2016, USGS personnel made fifty streamflow measurements at 21 locations on streams in Louisiana. Many of those streamflow measurements were made for the purpose of verifying the accuracy of the stage-streamflow relation at the associated gaging station. USGS personnel also recovered and documented 590 high-water marks after the storm event by noting the location and height of the water above land surface. Many of these high water marks were used to create twelve flood-inundation maps for selected communities of Louisiana that experienced flooding in August 2016. This data release provides the actual flood-depth measurements made in selected river basins of Louisiana that were used to produce the flood-inundation maps published in the companion product (Watson and others, 2017). Reference Watson, K.M., Storm, J.B., Breaker, B.K., and Rose, C.E., 2017, Characterization of peak streamflows and flood inundation of selected areas in Louisiana from the August 2016 flood: U.S. Geological Survey Scientific Investigations Report 2017–5005, 26 p., https://doi.org/10.3133/sir20175005. First release: February 2017 Revised: April 2017 (ver. 1.1) Additionally, there is a revision history text file available on the main page that explains exactly what changed in the revision.
Flood Inundation Depth for a Flow of 3,080 cfs (stage 16) at Gage 14211500, Johnson Creek near Sycamore, Oregon (sycor 16.tif)
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The basis for these features is U.S. Geological Survey Scientific Investigation Report 2017-5024 Flood Inundation Mapping Data for Johnson Creek near Sycamore, Oregon. The domain of the HEC-RAS hydraulic model is a 12.9 mile reach of Johnson Creek from just upstream of SE 174th Avenue in Portland, Oregon to its confluence with the Willamette River. Some of the hydraulics used in the model were taken from Federal Emergency Management Agency, 2010, Flood Insurance Study, City of Portland, Oregon, Multnomah, Clackamas and Washington Counties, Volume 1 of 3, November 26, 2010. The Digital Elevation Model (DEM) utilized for the project was developed from LiDAR data flown in 2015 and provided by the Oregon Department of Geology and Mineral Industries. Bridge decks are generally removed from DEMs as standard practice. Therefore, these features may be shown as inundated when they are not. Judgement should be used when estimating the usefulness of a bridge during flood flow. Comparing the bridge to the surrounding ground can be more informative in this respect than simply looking at the bridge itself. Two model plans were used in the creation of the flood layers. The first is a stable model plan using unsteady flow in which the maximum streamflow is held in place for a long period of time (a number of days) in order to replicate a steady model using an unsteady plan. The stable model plan produced the areas of uncertainty contained in the sycor_breach.shp shapefile. The second is an unstable model plan that uses unsteady flow in which the full hydrograph (rising and falling limb) is represented based on the hydrograph shape of the December 2015 peak annual flood. The unstable model plan produced the flood extent polygons contained in the sycor.shp shapefile and the depth rasters and represents the best estimate of flood inundation for the given streamflow at U.S. Geological Survey streamgage 14211500.
Sea-level rise and high tide flooding inundation probability and depth statistics at De Soto National Memorial, Florida
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This dataset includes elevation-based probability and depth statistics for estimating inundation under various sea-level rise and high tide flooding scenarios in and around the National Park Service’s De Soto National Memorial. These datasets were developed using 1-m digital elevation model (DEM) from the 3D Elevation program. This data release includes results from analyses of two local sea-level rise scenarios for two-time steps — the Intermediate-Low and Intermediate-High for 2050 and 2100 from Sweet and others (2022). Additionally, this data release includes maps of inundation probability under the minor, moderate, and major high tide flooding thresholds defined by the National oceanic and Atmospheric Administration (NOAA). We estimated the probability of an area being inundated under a given scenario using Monte Carlo simulations with 1,000 iterations. For an individual iteration, each pixel of the DEM was randomly propagated based on the lidar data uncertainty, while the sea-level rise and high tide flooding water level estimates were also propagated based on uncertainty in the estimate (Sweet and others, 2022) and tidal datum transformation, respectively. Moreover, the probability of a pixel being inundated was calculated by summing the binary simulation outputs and dividing by 1,000. Following, probability was binned into the following classes: 1) Unlikely, probability ≤0.33; 2) Likely as not, probability >0.33 and ≤0.66; and 3) Likely, probability >0.66. Finally, depth statistics were only recorded when depth was equal to or greater than 0. We calculated the median depth, 25th percentile, 75th percentile, and interquartile range using all the pixels that met this criterion. When utilizing the depth statistics, it is important to also consider the probability of this pixel being flooded. In other words, the depth layers may show some depth returns, but the pixel may have rarely been inundated for the 1,000 iterations.
SIR2016-5029 cfwgoshor 7b: Flood Inundation Depth for a Flow of 46,800 cfs at the Gage Coast Fork Willamette River at Goshen, Oregon (Area of Uncertainty)
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The domain of the model is as follows: Row River from Dorena dam to the confluence with the Coast Fork; Coast Fork from Cottage Grove dam to the confluence with the Middle Fork; Silk Creek from River Mile 1.7 to the confluence with the Coast Fork. The basis for these features is the Willamette Flood Insurance Study – Phase One (2013). The hydraulics and hydrology for the FIS were reused in the production of these polygons; the reports and information associated with the FIS are applicable to this product. The Digital Elevation Model (DEM) utilized for the Willamette FIS submittal was produced by combining multiple overlapping topographic surveys for the Middle Fork and Coast Fork of the Willamette River. This DEM was created from four sources: LiDAR of the Springfield area that was flown in 2008, LiDAR of Silk Creek that was flown in 2011, LiDAR of Fall Creek that was flown in 2012, and photogrammetry of the Middle Fork and Coast Fork of the Willamette River that was flown in 2004. In areas where no high-resolution elevation data were available, USGS National Elevation Dataset (NED) data were used to supplement the DEM. The shapefiles Hi_Res_Extents.shp and Low_Res_Extents.shp define the limits of these areas. The horizontal datum of the DEM is NAD 1983 State Plane-Oregon South HARN with units of International Feet (NAD83). The vertical datum of the elevation model is NAVD 1988 with units of international feet (NAVD-88). In addition, some areas show surveyed bathymetry within the channel. These can be noted by the sharp increase in apparent depth, creating a stripe across the depth grid when compared to the LiDAR data, which represents the water surface elevation at the time of the aerial data collection. Bridge decks are generally removed from DEMs as standard practice. Therefore, these features may be shown as inundated when they are not. An effort to clip flood extents on bridge decks was made, but judgement should be used when estimating the usefulness of a bridge during flood flow. Comparing the bridge to the surrounding ground can be more informative in this respect than simply looking at the bridge itself. The features and depth grids stop as the Coast Fork approaches the Middle Fork on the northern end of the reach. See cfwgoshOR_breach.shp for information regarding this file. This represents the depth grid for the 46,800 cfs profile.
Sea-level rise and high tide flooding inundation probability and depth statistics at Biscayne National Park, Florida
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This dataset includes elevation-based probability and depth statistics for estimating inundation under various sea-level rise and high tide flooding scenarios in and around the National Park Service’s Biscayne National Park. For information on the digital elevation model (DEM) source used to develop these datasets refer to the corresponding spatial metadata file (Danielson and others, 2023). This data release includes results from analyses of two local sea-level rise scenarios for two-time steps — the Intermediate-Low and Intermediate-High for 2040 and 2080 from Sweet and others (2022). Additionally, this data release includes maps of inundation probability under the minor, moderate, and major hight tide flooding thresholds. We estimated the probability of an area being inundated under a given scenario using Monte Carlo simulations with 1,000 iterations. For an individual iteration, each pixel of the DEM was randomly propagated based on the lidar data uncertainty, while the sea-level rise and high tide flooding water level estimates were also propagated based on uncertainty in the estimate (Sweet and others, 2022) and tidal datum transformation. Moreover, the probability of a pixel being inundated was calculated by summing the binary simulation outputs and dividing by 1,000. Following, probability was binned into the following classes: 1) Unlikely, probability ≤0.33; 2) Likely as not, probability >0.33 and ≤0.66; and 3) Likely, probability >0.66. Finally, depth statistics were only recorded when depth was equal to or greater than 0. We calculated the median depth, 25th percentile, 75th percentile, and interquartile range using all the pixels that met this criterion. When utilizing the depth statistics, it is important to also consider the probability of this pixel being flooded. In other words, the depth layers may show some depth returns, but the pixel may have rarely been inundated for the 1,000 iterations.
Hurricane Matthew Overwash Extents
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The National Assessment of Coastal Change Hazards project exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the southeast coast of the United States from Florida to North Carolina and attributed to coastal processes during [Atlantic Basin] Hurricane Matthew, which made landfall in the U.S. on October 8, 2016.
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