Capturing local nuisance flooding events with HOBO pendant G data loggers in Key West, Florida US
Data files
Apr 15, 2024 version files 30.59 MB
Abstract
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.
README: 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
Methods
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.
Usage notes
All data files are saved as .csv from the HOBOware v3.7.21. The code was created using RStudio v1.4.1717.