This collection is for datasets of flood depths, flood extents, high water marks, streamflow, damages recorded, aerial oblique photos, and related subjects. This includes both forecast and observed data. These were primarily obtained from national agencies such as NOAA (weather related), USGS (surface water related), FEMA (surface water and damage related), and Civil Air Patrol (aerial photos).

Note on November 2023 updates: due to numerous updates among the resources linked below, this collection has been updated to point to the most recent resources.

The main objective is to segment images acquired be a small UAV (sUAV) at the area on Houston, Texas. These images were acquired in order to assess the damages on residential and public properties after Hurricane Harvey. In total, there are 25 categories to segment that are provided below.

0: Background 1: Property Roof 2: Secondary Structure 3: Swimming Pool 4: Vehicle 5: Grass 6: Trees / Shrubs 7: Solar Panels 8: Chimney 9: Street Light 10: Window 11: Satellite Antenna 12: Garbage Bins 13: Trampoline 14: Road/Highway 15: Under Construction / In Progress Status 16: Power Lines & Cables 17: Water Tank / Oil Tank 18: Parking Area - Commercial 19: Sports Complex / Arena 20: Industrial Site 21: Dense Vegetation / Forest 22: Water Body 23: Flooded 24: Boat

This resource describes a dataset of gridded depth at horizontal resolution of 3 meters, published as an Esri ArcGIS geodatabase on November 15, 2017 by FEMA. This dataset is no longer accessible from FEMA, but is now uploaded to this HydroShare resource in the contents list. This product utilized Triangulated Irregular Network (TIN) interpolation, four quality assurance measures (identifying dips, spikes, duplication, and inaccurate/unrealistic measurements). High Water Marks were obtained from the Harris County Flood Control District (HCFCD), US Geological Survey (USGS), and other inspection data. Elevation data comprised a mosaic of 3 meter resampled elevations from 1M & 3M LiDAR, and IFSAR data. One section of the IfSAR data was found to be erroneous, and replaced with a blended 10 meter section. [This method description was from correspondence January 22, 2018, from Mark English, GeoSpatial Risk Analyst, FEMA Region VIII, Mitigation Division.]

See FEMA's Natural Disasters data site [1] for additional HWM-based depth grids and inundation polygons: - Harris County Areas of Interest (AOIs) and Inundation Boundaries - Harris County Depth Grids - Aransas, Nueces, and San Patricio Coastal Depth Grids and Boundaries

Some of the data available below in the contents list is from the FIMA NHRAP program, which is no longer available from FEMA, as of the summer of 2019.

FEMA notes on these Modeled Preliminary Observations: o Based on observed Water Levels at stream gauges interpolated along rivers, downsampled to 5m resolution DEM o Depth grids updated with new observed peak crest as they become available o Will include High Water Mark information as it becomes available o Extents validated with remote sensing o Use for determining damage levels on specific structures

References: [1] FEMA Harvey data [https://disasters.geoplatform.gov/publicdata/NationalDisasters/2017/HurricaneHarvey/Data/] [link is no longer accessible]

This refined map was created to help assess possible spread of nonindigenous aquatic species distributions due to flooding associated with Hurricane Harvey. Storm surge and flood events can assist expansion and dissemination of nonindigenous aquatic species through the connection of adjacent watersheds, backflow of water upstream of impoundments, increased downstream flow, and creation of freshwater bridges along coastal regions. This map will help natural resource managers determine potential new locations for individual species, or to develop a watch list of possible new species within a watershed. These data include a subset of data from the Nonindigenous Aquatic Species Database, that fall within the general area of the 2017 Hurricane Harvey flooding.

During and after Hurricane Harvey, the US Geological Survey recorded high water marks across southeast Texas, as they do for every major storm. The files in this dataset provide 2123 high water marks for Hurricane Harvey flooding, among 1258 sites. These files were downloaded following the steps below. If you'd like to check the original sources again, or search for HWM for a different storm, you may find these directions helpful.

Finding, Downloading and Filtering USGS High Water Marks (HWM) 1. Visit USGS website: https://water.usgs.gov/floods/history.html, which lets you… 2. Click on Hurricane Harvey: https://www.usgs.gov/harvey, which lets you… 3. Click on green button Get Data: https://stn.wim.usgs.gov/fev/#HarveyAug2017 4. In left margin menu of resulting page, click a second Get Data link. This will open up the remaining options below. 5. Click each data type you want, such as High-Water Mark, Peak Summary, or Sensor Data. It’s only csv or REST (json or xml).

• I downloaded the HWM as csv, opened in Excel, clicked the Sort & Filter tool in Excel toolbar, clicked Filter, then filtered on "Harvey Aug 2017” in the popup list for column E (Event Name). I saved the result to a new spreadsheet which now has 2123 records, plus column labels in row 1.

• To understand the fields or columns of this table, see HWM_Peaks_Sensors_Data_Dictionary_20180329.xslx in the contents below.

Feature Class of the High Water Marks taken by Harris County Flood Control District's Hydrologic Operation team after a flooding event (August 27, 2017).

This dataset contains the tweet ids of 35,596,281 tweets related to Hurricanes Irma and Harvey. They were collected during these events from the Twitter API using Social Feed Manager. These tweet ids are broken up into 2 collections. Each collection was collected using the POST statuses/filter method of the Twitter Stream API. The collections are: Hurricane Irma: irma_filter_tweet_ids.txt Hurricane Harvey: harvey_filter_tweet_ids.txt There is a README.txt file for each collection containing additional documentation on how it was collected. The GET statuses/lookup method supports retrieving the complete tweet for a tweet id (known as hydrating). Tools such as Twarc or Hydrator can be used to hydrate tweets. Per Twitter’s Developer Policy, tweet ids may be publicly shared for academic purposes; tweets may not. Questions about this dataset can be sent to sfm@gwu.edu. George Washington University researchers should contact us for access to the tweets.

We at HARC are grateful to Houston Endowment for their support in the development of this project. Hurricane Harvey brought record rainfall to Houston; the resulting flooding led to regional devastation, impacting lives, homes and livelihoods. The storm also had numerous environmental impacts. The Houston Advanced Research Center (HARC) mobilized swiftly to acquire and process data and information about the flooding and related impacts, such as storm-related spills, pollutants, Superfund impacts, water quality, air quality, and power generation. The resulting analysis is shown through narrative summaries, maps, and infographics in this story map, “Summarizing Hurricane Harvey’s Environmental Impacts”. For general feedback on this application, please contact us at harcgis@harcresearch.org.

HARC would like to thank the following organizations for providing data used within this story map:

• National Oceanic and Atmospheric Administration
  
• United States Geological Survey
  
• National Weather Service
  
• Vieux Inc.
  
• Texas Parks & Wildlife Department
  
• Texas Commission on Environmental Quality
  
• Environmental Defense Fund
  
• Environmental Protection Agency
  
• U.S. Coast Guard National Response Center
  
• Federal Emergency Management Agency
  
• Department of Energy
  
• Electric Reliability Council of Texas (ERCOT)
  
• Texas A&M University, Department of Soil and Crop Sciences
  
• University of Houston - Clear Lake, College of Science and Engineering
  
• Texas General Land Office – Beach Watch Program
  
• Galveston Bay Foundation
  
• Texas A&M University Galveston – Department of Marine Biology
  
• City of Houston Health Department via Urban Data Platform (Kinder Institute)

Urban flooding from extreme precipitation has emerged as a major threat to metropolitan regions of the United States. There is a pressing need for flood inundation forecasts capable of meeting emergency response needs for public safety and damage reduction from the household scale upwards to the entire region.

Leveraging the computational efficiency of the numerical hydrodynamic model PRIMo (University of California Irvine), we present a flood inundation forecasting system that ingests short-range quantitative precipitation forecast data provided by the National Weather Service, 3 m resolution topographic data available from the 3D Elevation Program of the United States Geologic Survey, and other data to simulate flooding at fine-resolution (3 m) at the county/regional scale, and inform emergency management at household scales.

With an application to Metropolitan Houston and 5-day simulations of Hurricane Harvey, the forecast system is shown to capture flood peaks with a mean absolute error (MAE) of 0.86 m, hourly streamflow stage is captured with a median MAE and Nash Sutcliffe Efficiency (NSE) of 0.90 m and 0.41, respectively, and high water marks (HWMs) are captured with a MAE of 0.77 m. The forecast system also achieves hit rates of 90% and 73% predicting 3-1-1- distress calls and FEMA property damage claims, respectively, based on simulated flood depth. Based on fast model speeds made possible by upscaling and parallel computing, these results demonstrate the potential to operationally forecast flood inundation and its impacts in the U.S. for emergency management.

This dataset contains a Hurricane Harvey hindcast as well as three forecast scenarios at 3 m linear resolution using different levels of PRIMo's computational grid upscaling technology. The data represents maximum accumulated flood depths over the period August 26 2017 - August 30 2017 as a result of heavy precpitation and storm surge. The spatial extent of the flood hazard layers is approximately 9,000 km² encompassing Harris County, Texas.

This lidar dataset was collected as part of an NCALM Rapid Response Project for Inci Gunerlap at Texas A&M University. Data collection covers and area of ~69 km² along the Mission River in Refugio, Texas after Hurricane Harvey.

Note that this project utilized three laser channels during its data collection. Each of the returns contained on the LAS tiles are encoded with a laser channel value. The values used are 1 (1550 nm), 2 (1064 nm), and 3 (532 nm), and are stored in the \"User Data\" record of the Point Data records in the LAS file.

Publications associated with this dataset can be found at NCALM's Data Tracking Center

Twitter dataset about Hurricane Harvey

This point dataset represents high water mark observations made by USGS field staff after Hurricane Harvey in Sept 2017 (Sept 9 - Oct 10).

This resource contains shapefiles for FEMA Damage Assessments, Auto Claims, Property Claims, and geodatabases for Hazus windfield data, publicly available here [see NOTE 1].
Damage assessments are organized in daily map layers. These appear to be cumulative, but some days' records do not include all the previous days' records. - Aug 27, 2017: Coastal damage assessments (26,027 records) - Aug 28: Damage assessments (78,218) - Aug 29: Damage assessments (115,412) - Aug 30: Damage assessments (137,754) - Aug 31: Damage assessments (161,366) - Sep 02: Damage assessments (156,099) A document is provided that explains the damage assessment methodology.

Auto and Property Claims are each in a single shapefile, containing all records from Aug 25-Sep 08: - Auto claims, Aug 25-Sep 08 (203, 312 records) - Property claims, Aug 25-Sep 08 (226,167) These identify location, date and type of loss. These are all claims submitted during this period, which may include damages not caused by Hurricane Harvey.

Other damage assessments and inundation depth grids are available at the FEMA Natural Hazard Risk Assessment Program (NHRAP) [2]. These include: - Windfield contours [3] - PDC Hazus Wind Adv26 (Hurrevac) [4] - PDC Hazus Windfield geodatabases for Harvey [5]

References NOTE 1: As of the summer of 2019, FEMA damage data was reorganized and moved to new URLs, which affected references [1,2,3,4,5]. Most of these data sources have been moved to https://disasters.geoplatform.gov/publicdata/NationalDisasters/2017/HurricaneHarvey/Data/. Some of the original datasets are no longer available from FEMA. The original and current datasets are available for download below in the contents list.

[1] FEMA Damage Assessments [https://disasters.geoplatform.gov/publicdata/NationalDisasters/2017/HurricaneHarvey/Data/DamageAssessments/] [2] FEMA Natural Hazard Risk Assessment Program (NHRAP) [link no longer available] [3] Harvey_WindSpeedContours.zip, see contents list below. [4] PDC_HAZUS_Damage_Loss_Assessment_ADV26_26AUG17_2100UTC.PDF, see contents list below. [5] PDC_HarveyResults.gdb.zip and PDC_HarveyWindfield.gdb.zip from [https://disasters.geoplatform.gov/publicdata/NationalDisasters/2017/HurricaneHarvey/Data/Hazus/PDC/Wind/], also in contents list below.

This map serves as the base location to store key layers for tropical impacts. Having all the layers in one place to develop StoryMaps, graphics, and situational awareness for tropical events. Individual layers with custom settings can be saved in this folder as well to access in other tools. This map as every map is a work in progress.

Estimated to be the costliest natural disaster in U.S. history, Hurricane Harvey left many people with a difficult decision: should I leave my home or wait out the storm? With numerous warnings from local and federal agencies, thousands chose to heed hurricane advisories and evacuate their homes. Three main questions about movement arise when thinking about evacuations:Where did people leave?Where did people go?And who decided to stay?Utilizing Teralytics data aggregated from billions of signals obtained daily from cell towers and other unique sources, Esri created a map that attempts to answer these three questions.

Quick Start This is a collection of flood datasets to support hydrologic research for Hurricane Harvey, August-September 2017. The best way to start exploring this collection is by opening the Hurricane Harvey 2017 Story Map [2]. It has separate sections for the different content categories, and links to the relevant HydroShare resources within this collection.

More Details This is the root collection resource for management of hydrologic and related data collected during Hurricane Harvey on the Texas-Louisiana Gulf coast. This collection holds numerous composite resources comprising streamflow forecasts, inundation polygons and depth grids, flooding impacts, elevation grids, high water marks, and numerous other related information sources. Texas address points are included to support estimating storm and flood impacts in terms of structures within an affected area.

The data providers for this collection are the Texas Division of Emergency Management, NOAA National Weather Service, NOAA National Hurricane Center, NOAA National Water Center, FEMA, 9-1-1 emergency communications agencies, and many others. Esri and Kisters also provided invaluable tools, data and geoprocessing services to support the initial data production, and these are included or referenced.

User-contributed resources from 2017 US Hurricanes may also be shared with The CUAHSI 2017 Hurricane Data Community group [1] to make them accessible to interested researchers, Anyone may join this group.

An ArcGIS Story Map [2] has been created which provides example data views and interactive access to this collection.

This collection has been produced by work on a US National Science Foundation RAPID Award "Archiving and Enabling Community Access to Data from Recent US Hurricanes" [3].

References [1] CUAHSI 2017 Hurricane Data Community group [https://www.hydroshare.org/group/41] [2] Hurricane Harvey 2017 Archive Story Map [https://arcg.is/1rWLzL0] [3] NSF RAPID Grant [https://nsf.gov/awardsearch/showAward?AWD_ID=1761673]

The following resource contains the data and code that were used for the study described in the abstract below. Hurricane Harvey produced unprecedented flooding that altered flood frequency statistics near Houston. While Harvey could have made landfall elsewhere along the Gulf coast, traditional flood frequency methodologies only consider the risk of Harvey in the region that it hit. This may be a significant shortcoming of flood frequency methodologies as the intensity of Harvey was greater due to climate change; therefore, Harvey may be more indicative of future hurricanes than other historical observations. This study addresses this shortcoming by investigating what effect Harvey would have had on flood frequency statistics if it had made landfall elsewhere. This was done by shifting spatial rainfall data to probable alternative landfall locations in two separate geomorphologic regions adjacent to the Texas coast and using synthetic unit hydrographs to create a simulated set of peakflows. These simulated peakflows were then used to evaluate the impact of Harvey in these new locations using Log Pearson III and Regional Flood Frequency Analyses. Log Pearson III analyses with simulated Harvey streamflows produced 100-year peakflows that were, on average, 21.4% – 63.9% higher than analyses that only used historical records. A similar Regional Flood Frequency analysis in the central coastal geomorphologic region of Texas showed that predictive equations, based upon basin area and shape factor, had an average increase of 17.7% in the 100-year peak discharge. This study demonstrates that contemporary storms, whose intensities are increased by climate change, may have similar impacts on flood frequency statistics and regional regression equations in other regions within their probabilistic landfall path.

This map serves as the base location to store key layers for tropical impacts. Having all the layers in one place to develop StoryMaps, graphics, and situational awareness for tropical events. Individual layers with custom settings can be saved in this folder as well to access in other tools. This map as every map is a work in progress.

Oblique and nadir imagery was acquired following Hurricane Harvey in August and September 2017. The aerial photography missions were conducted by the NOAA Remote Sensing Division. The images were acquired from an altitude of 2500 to 5000 feet, using a Trimble Digital Sensor System (DSS).