DOI: 10.5061/dryad.d7wm37q5d
title: Capturing local nuisance flooding events with HOBO pendant G data loggers in Key West, Florida US

description: Flooding impacts social, economic, and landscape systems globally.
 Changing climate and growing coastal populations exacerbate the outcomes
 of environmental hazards. Due to the spatial variability in exposure and
 vulnerability, coastal flooding must be understood at high spatial and
 temporal resolutions. This paper presents a novel deployment technique
 using inexpensive accelerometers to measure local floods. The technique is
 tested in Key West, FL, USA using storm drains to deploy HOBO pendant G
 data loggers. The feasibility of the method is tested by a team of local
 stakeholders and researchers through four deployments between July 2019 –
 November 2021. All deployments resulted in 22 sensors successfully
 recording data, with 15 of these sensors recording flooding. Sensors
 captured an average of 13.58 inundation events causing the storm drains to
 be inundated on average 12.07% of the deployment time. Measured inundation
 events coincide with local National Oceanic and Atmospheric Administration
 (NOAA) water level measurements of high tides, which shows that high-tide
 inundation is captured by the accelerometers. Accelerometers are easy to
 deploy and accurately capture the duration of local flooding. Access to an
 effective and inexpensive sensor for measuring flood events can increase
 opportunities to measure local-scale hazards and collect important
 information with participation by interested parties (e.g., local
 governments, homeowners, schools etc.). The ease of use and successful
 recording of loggers can give communities access to flooding data, and in
 turn, increase their capacity to make data-informed decisions surrounding
 sea level rise adaptation. 
description: The research team — which includes a Key West municipal employee,
 researchers from Northeastern University and researchers from the United
 States Naval Academy — use HOBO pendant G data loggers to collect flooding
 data in Key West. The loggers record acceleration and angular displacement
 (tilt) in three dimensions, allowing for characterization of
 three-dimensional motion. For nuisance flooding, the acceleration and tilt
 are used to record localized flood events since rising water changes the
 orientation of the buoyant sensors, causing angular displacement and a
 change in the axis experiencing gravitational acceleration. Storm drains
 were selected for deployments, providing publicly accessible areas that
 were both prone to frequent inundation and fixed locations for sensor
 deployment. Using knowledge of previous flooding events and local
 expertise, 14 total deployment locations were selected. Each location has
 a publicly accessible storm drain to attach the loggers. The research team
 deployed loggers four different times over the period from July 2019 –
 November 2021. Loggers were programmed to record continuously after a
 user-specified launch time and sampling rates were specified such that
 loggers recorded measurements every one minute for the first two
 deployments and every five minutes for the third and fourth
 deployments.  The sum acceleration and the tilt in all
 three dimensions were downloaded through HOBOware v3.7.21, exported as
 .csv files and uploaded to RStudio v1.4.1717. Times at which a sensor
 recorded a flooding event was identified using tilt in the x-direction and
 z-direction. 
description: All data files are saved as .csv from the HOBOware v3.7.21. The
 code was created using RStudio v1.4.1717. 
description: # Capturing local nuisance flooding events with HOBO pendant G data
 loggers in Key West, Florida US Stakeholder Driven Sensor Deployments to
 Characterize Nuisance Flood Inundation and Duration in Key West Florida We
 test a novel deployment technique using inexpensive accelerometers to
 measure local floods in Key West, FL, USA using storm drains to deploy
 HOBO pendant G data loggers. The feasibility of the method is tested by a
 team of local stakeholders and researchers through four deployments
 between July 2019 - November 2021. All deployments resulted in 22 sensors
 successfully recording data, with 15 of these sensors recording flooding.
 ## Description of the Data and file structure The sum acceleration and the
 tilt in all three dimensions were downloaded through HOBOware v3.7.21,
 exported as .csv files and uploaded to RStudio v1.4.1717 for processing.
 Times at which a sensor recorded a flooding event were identified using
 tilt in the x-direction and z-direction. A .csv file is created for each
 logger during each deployment, resulting in 27 accelerometer data files.
 The Accelerometer data files are labeled as [sensor ID]_[deployment].csv
 NOTE: There are two Accelerometer data files that were deployed
 differently from the rest, and therefore not included in the final report.
 The two files are included in this database as
 'Garrison_Blight_20197221_NOTSTUDIED' and
 'Key_West_Blight_20498054_NOTSTUDIED'. The location of the
 deployment and the accelerometer IDs are included in the data file name.
 The R code to read and analyze the Accelerometer data files is called
 "WL_Data.R" Several supplemental data files were created to use
 within R analysis and plotting: 1\) FloodingEvents.csv is the number of
 times and total minutes inundated each location floods for each
 deployment. The .csv also includes the minor, moderate, and major flood
 events denoted by the NOAA Key West Water Level station. These numbers
 were calculated within R (under section ##### Time inundated #####) and
 manually entered into the .csv file. A flooding per minute deployed was
 calculated to compare flooding events across the various deployment times.
 Empty cells within the table are instances where sensors were either not
 deployed at a location or not recovered from the location. 2\)
 DeploymentLocations.csv is the 14 locations of accelerometer deployments.
 Deployment locations were mapped in ArcGIS Pro 2.4.0 using the latitude
 and longitude collected during deployments. The distance to the closest
 NOAA tidal station, the distance to the closest coastline or canal, and
 the elevation were determined for each deployment location The elevation
 of each deployment location was collected from a digital elevation model
 from NOAA’s National Geophysical Data Center, which provided elevation
 with a resolution of one-third arc-second (10 m) with reference to the
 vertical tidal datum of Mean High Water (MHW) and horizontal datum of
 World Geodetic Systems 1984 (National Geophysical Data Center, 2019). 3\)
 Location_HighTideTiming.csv has the difference between a NOAA high tide
 and the onset of a flood event, and a NOAA high tide and the end of a
 flood event for each location. This information was manually collected and
 put into a .csv from the R Data frames "StartWL" and
 "EndWL" created in the R code. Empty cells in the table are
 instances where there was no flood recorded at that station for that
 deployment period either due to no flood recorded, or due to no
 accelerometer at the site.  4\) Dep_Floods.xlsx is a workbook of the start
 and end timing of each flood event for each deployment. The data for the
 timing of the flood events was downloaded from R and manually checked for
 flooding events and for the closest NOAA high tide. This workbook is the
 final product of manually checking each flood event and matching it to the
 closest NOAA high tide. This process was used to double check the code
 that labeled flooding start and end events. Multible tables were created
 within the tabs of the excel workbook. Spaces throughout the sheet
 indicate a new table.  Several figures were created to check the data
 throughout the process and uploaded as supplementary files. ##
 Abbreviation Definitions/ Code Book: WL = water level in meters MLLW =
 mean low low water in meters MHHW = mean high high water in meters MHW =
 mean high water in meters GMT = Greenwich mean time EDT = Eastern Daylight
 Time SumAcc = sum acceleration - given by the sensors through HOBOware -
 in meters per second squared OTD = Onset Time Difference - the difference
 between the time of flooding onset from the NOAA high tide in hours.
 Deployment number is displayed as \_1, \_2, \_3, and \_4.  ETD = End Time
 Difference - the difference between the time of flooding end from the NOAA
 high tide in hours. Deployment number is displayed as \_1, \_2, \_3, and
 \_4.  NOAA_Dist = NOAA tidal station distance in meters Elev = Elevation -
 deployment location elevation in meters FIRM = Flood Insurance Rate Map
 FLD_Zone = Flood zone SE_flooding = Start/End Flooding H_timedif = High
 tide time difference in hours