http://lod.bco-dmo.org/id/dataset/971943
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2025-08-05
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Continuously monitored water quality parameters from three open-water sites in a tidal salt marsh channel in New Jersey, USA from June 2021 to June 2024
2025-08-08
publication
2025-08-08
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2025-08-12
publication
https://doi.org/10.26008/1912/bco-dmo.971943.1
Hilary I. Palevsky
Boston College
principalInvestigator
Emily J. Chua
Boston College
principalInvestigator
Kristen E. Fogaren
Boston College
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Chua, E. J., Supino, J., Fogaren, K. E., Palevsky, H. I. (2025) Continuously monitored water quality parameters from three open-water sites in a tidal salt marsh channel in New Jersey, USA from June 2021 to June 2024. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2025-08-08 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.971943.1 [access date]
Marsh channel monitoring data Dataset Description: Methods and Sampling: <p>This dataset follows the methodology described in Chua et al. (2025). Continuous water quality monitoring was conducted at three observational open-water platforms located within the main marsh channel of SMIIL. Each platform was outfitted with Aqua TROLL 600 multiparameter sondes (In-Situ Inc.), configured to measure a suite of environmental variables including water depth, temperature, salinity, dissolved oxygen (DO), pH, chlorophyll a fluorescence, turbidity. Two sondes were mounted on a fixed pole at each platform and deployed near the bottom of the water column (in water depths &lt;2 m). Salinity, temperature, DO, and pH were measured in duplicate to ensure data quality and redundancy. Each sonde was also configured with either a chlorophyll a or turbidity sensor, allowing coverage of all target variables across platforms. Sondes were retrieved and replaced with pre-cleaned, newly calibrated sondes every 4–12 weeks. Data were downloaded during each maintenance visit using the VuSitu Mobile App (In-Situ Inc.). Although sondes were initially configured for remote telemetry, persistent data dropout issues led to a switch to internal data logging by June 2022. Discrete surface water samples for DO, dissolved inorganic carbon (DIC), and total alkalinity (TA) were also collected during maintenance visits, starting in September 2022 <em>(</em>Supino et al., 2025). These samples were used to validate the Aqua TROLL DO and pH data (see Data Procession section).</p>
<p>Meteorological data were also collected at SMIIL to complement the water quality dataset. A ResponseONE™ Weather Transmitter (R.M. Young Company) measured wind speed and direction, air temperature, relative humidity, and atmospheric pressure. Due to data transmission issues, this record only spans September 2021–May 2023. Additionally, a nearby HOBO water level logger (Onset Computer Corp.) recorded air temperature and atmospheric pressure from August 2022–June 2024. Data from both sensors were combined to produce a continuous record of air temperature and atmospheric pressure spanning the full duration of water quality measurements. To estimate surface wind speed over the study period, hourly 10-m u- and v-component wind data were obtained from the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5; Hersbach et al., 2023) for the grid cell closest to 39.04<sup>o</sup>N, 74.79<sup>o</sup>W. The ERA5-derived wind speeds were used in subsequent analyses due to their close agreement with field measurements from the ResponseONE™ station.</p>
Funding provided by U.S. Army Engineer Research and Development Center (ERDC) Award Number: W912HZ2020061–RA3
completed
Hilary I. Palevsky
Boston College
617-552-4936
Boston College Dept of Earth and Environmental Sciences 140 Commonwealth Ave
Chestnut Hill
MA
02467
USA
palevsky@bc.edu
pointOfContact
Emily J. Chua
Boston College
emily.chua@bc.edu
pointOfContact
Kristen E. Fogaren
Boston College
Boston College Department of Earth and Environmental Sciences
kristen.fogaren@bc.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
datetime_utc
site
lat
lon
depth
salinity
temperature
DOconc
DOsat
pH
chla
turbidity
Tair
rhumid
patm
wspd
ResponseONE™ Weather Transmitter (R.M. Young Company)
Aqua TROLL 600 multiparameter sondes (In-Situ Inc.)
HOBO water level logger (Onset Computer Corp.)
theme
None, User defined
ISO_DateTime_UTC
site
latitude
longitude
depth
salinity
water temperature at measurement depth
dissolved Oxygen
Dissolved oxygen (percent)
pH
chlorophyll a
turbidity
air temperature
humidity
barometric pressure
relative wind speed
featureType
BCO-DMO Standard Parameters
Automated Weather Station
Multi Parameter Portable Meter
Water Level Sensor
instrument
BCO-DMO Standard Instruments
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Sediment transport and water quality in watersheds and coastlines of the United States
https://osprey.bco-dmo.org/project/962228
Sediment transport and water quality in watersheds and coastlines of the United States
<p>Salt marshes are highly productive, dynamic coastal environments that experience large fluctuations in biogeochemical parameters such as dissolved oxygen and pH in response to both natural forcings and anthropogenic impacts. At present, we have a limited understanding of the magnitude of biogeochemical variability in coastal habitats, hindering our ability to predict how they will respond in the future to episodic events and long-term change. This incomplete picture owes to a lack of sustained water quality measurements in coastal and estuarine systems worldwide.</p>
<p>This project investigates biogeochemical cycling in the Seven Mile Island Innovation Laboratory (SMIIL), a network of tidal marshes and channels in coastal New Jersey that is a site of historic and contemporary dredging and a testbed for marsh restoration techniques such as beneficial use of dredged sediment. It leverages multiple data sets of continuous, high-frequency (10-minute) measurements of physical and biogeochemical parameters, including water depth, temperature, salinity, dissolved oxygen, pH, chlorophyll a, and turbidity, as well as precipitation, wind speed, wind direction, temperature, relative humidity, and atmospheric pressure data. Two long-term biogeochemical sensor data sets, comprising a three-year time series at three sites in the main marsh channel (from June 2021–June 2024) and 1-2 year time series at six distinct salt ponds (August 2022–June 2024), were collected. Additionally, short-term (~months long) dredging and sediment placement monitoring data were collected at five different locations in 2022 and 2023. Data collection was designed to capture a variety of natural (diel, tidal, seasonal, storm-related) and human-created (sediment dredging and placement) conditions. Factory-calibrated biogeochemical sensors were field calibrated and maintained every 4 to 12 weeks. Discrete samples for dissolved oxygen, total alkalinity, and dissolved inorganic carbon were collected at the start and end of each sensor deployment for additional sensor calibration and validation. Altogether, our high-quality, multiyear dataset provides critical insights into the inherent variability of biogeochemical conditions in temperate salt marshes on diel and seasonal timescales, as well as how they may respond to transient events (e.g., storms, dredging activities) and over the longer term.</p>
SMIIL Water Quality
largerWorkCitation
project
eng; USA
oceans
-74.78825
-74.76549
39.04401
39.10316
2021-06-29
2024-06-04
Coastal New Jersey (Seven Mile Island Innovation Lab)
0
BCO-DMO catalogue of parameters from Continuously monitored water quality parameters from three open-water sites in a tidal salt marsh channel in New Jersey, USA from June 2021 to June 2024
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/972267.rdf
Name: datetime_utc
Units: unitless
Description: <p>Sampling date and time in UTC format (mm/dd/yyyy hh:mm:ss)</p>
http://lod.bco-dmo.org/id/dataset-parameter/972269.rdf
Name: site
Units: unitless
Description: <p>Sampling site within marsh; North, South, or Gull (around Gull Island)</p>
http://lod.bco-dmo.org/id/dataset-parameter/972270.rdf
Name: lat
Units: decimal degree
Description: <p>Sampling location latitude, south is negative</p>
http://lod.bco-dmo.org/id/dataset-parameter/972272.rdf
Name: lon
Units: decimal degree
Description: <p>Sampling location longitude, west is negative</p>
http://lod.bco-dmo.org/id/dataset-parameter/972274.rdf
Name: depth
Units: meters
Description: <p>Cleaned sampling depth from the Aqua TROLL sensor</p>
http://lod.bco-dmo.org/id/dataset-parameter/972276.rdf
Name: salinity
Units: psu
Description: <p>Cleaned salinity from the Aqua TROLL sensor</p>
http://lod.bco-dmo.org/id/dataset-parameter/972277.rdf
Name: temperature
Units: degrees Celsius
Description: <p>Cleaned temperature from the Aqua TROLL sensor</p>
http://lod.bco-dmo.org/id/dataset-parameter/972278.rdf
Name: DOconc
Units: μmol/L
Description: <p>Cleaned Dissolved oxygen concentration from the Aqua TROLL sensor</p>
http://lod.bco-dmo.org/id/dataset-parameter/972279.rdf
Name: DOsat
Units: percent (%)
Description: <p>Dissolved oxygen percent saturation, calculated from the cleaned DO concentration, salinity, and temperature data</p>
http://lod.bco-dmo.org/id/dataset-parameter/972280.rdf
Name: pH
Units: pH Scale
Description: <p>Cleaned pH from the Aqua TROLL sensor</p>
http://lod.bco-dmo.org/id/dataset-parameter/972281.rdf
Name: chla
Units: Relative Fluorescence Units (RFU)
Description: <p>Cleaned chlorophyll a from the Aqua TROLL sensor</p>
http://lod.bco-dmo.org/id/dataset-parameter/972282.rdf
Name: turbidity
Units: Nephelometric Turbidity Unit (NTU)
Description: <p>Cleaned turbidity from the Aqua TROLL sensor</p>
http://lod.bco-dmo.org/id/dataset-parameter/972283.rdf
Name: Tair
Units: degrees Celsius
Description: <p>Air temperature combined from ResponseONE Weather Transmitter and HOBO water level logger</p>
http://lod.bco-dmo.org/id/dataset-parameter/972284.rdf
Name: rhumid
Units: percent (%)
Description: <p>Relative humidity from ResponseONE Weather Transmitter</p>
http://lod.bco-dmo.org/id/dataset-parameter/972285.rdf
Name: patm
Units: hPa
Description: <p>Atmospheric pressure combined from ResponseONE Weather Transmitter and HOBO water level logger</p>
http://lod.bco-dmo.org/id/dataset-parameter/972286.rdf
Name: wspd
Units: m/s
Description: <p>10-meter wind speed calculated from ERA5</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
62404938
https://darchive.mblwhoilibrary.org/server/api/core/bitstreams/30587389-fbc9-4392-b32f-9c2aa99d4fb8/content
download
https://doi.org/10.26008/1912/bco-dmo.971943.1
download
onLine
dataset
<p>This dataset follows the methodology described in Chua et al. (2025). Continuous water quality monitoring was conducted at three observational open-water platforms located within the main marsh channel of SMIIL. Each platform was outfitted with Aqua TROLL 600 multiparameter sondes (In-Situ Inc.), configured to measure a suite of environmental variables including water depth, temperature, salinity, dissolved oxygen (DO), pH, chlorophyll a fluorescence, turbidity. Two sondes were mounted on a fixed pole at each platform and deployed near the bottom of the water column (in water depths &lt;2 m). Salinity, temperature, DO, and pH were measured in duplicate to ensure data quality and redundancy. Each sonde was also configured with either a chlorophyll a or turbidity sensor, allowing coverage of all target variables across platforms. Sondes were retrieved and replaced with pre-cleaned, newly calibrated sondes every 4–12 weeks. Data were downloaded during each maintenance visit using the VuSitu Mobile App (In-Situ Inc.). Although sondes were initially configured for remote telemetry, persistent data dropout issues led to a switch to internal data logging by June 2022. Discrete surface water samples for DO, dissolved inorganic carbon (DIC), and total alkalinity (TA) were also collected during maintenance visits, starting in September 2022 <em>(</em>Supino et al., 2025). These samples were used to validate the Aqua TROLL DO and pH data (see Data Procession section).</p>
<p>Meteorological data were also collected at SMIIL to complement the water quality dataset. A ResponseONE™ Weather Transmitter (R.M. Young Company) measured wind speed and direction, air temperature, relative humidity, and atmospheric pressure. Due to data transmission issues, this record only spans September 2021–May 2023. Additionally, a nearby HOBO water level logger (Onset Computer Corp.) recorded air temperature and atmospheric pressure from August 2022–June 2024. Data from both sensors were combined to produce a continuous record of air temperature and atmospheric pressure spanning the full duration of water quality measurements. To estimate surface wind speed over the study period, hourly 10-m u- and v-component wind data were obtained from the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5; Hersbach et al., 2023) for the grid cell closest to 39.04<sup>o</sup>N, 74.79<sup>o</sup>W. The ERA5-derived wind speeds were used in subsequent analyses due to their close agreement with field measurements from the ResponseONE™ station.</p>
Specified by the Principal Investigator(s)
<p>Water quality data were processed using MATLAB (MathWorks) version&nbsp;R2023b. Time and depth corrections were applied to each deployment to account for instrument offsets, and all deployments were merged into a continuous time series. Quality control procedures were based on protocols adapted from the U.S. Integrated Ocean Observing System (IOOS) Quality Assurance/Quality Control of Real-Time Oceanographic Data (QARTOD) recommendations (Integrated Ocean Observing System, 2018; Palevsky et al., 2023). Data for depth, temperature, salinity, DO concentration, pH, turbidity, and chlorophyll <em>a</em> were subjected to a combination of manual and automated quality checks as follows.</p>
<p>First, the depth time series for each sonde/platform was manually inspected and “human-in-the-loop” (HITL) annotations were created to document known and identified bad data. Points flagged by HITL review were compared to service trip logs to diagnose the cause of bad data (e.g., from power or communications disruptions or when the sensor was out of water between deployments). Flagged points that arose from data dropouts or when the sonde was out of water were removed from further analysis for all parameters (not just depth). Next, a gross range test was performed to check whether data were within reasonable ranges for a specified parameter. Parameter-specific selection of gross range limits (Table 1) was guided by Aqua TROLL sensor output ranges, expert judgement, and local knowledge. Points that exceed these thresholds were flagged and removed as bad data. Then, a spike test was performed to evaluate whether a data point exceeded a threshold relative to adjacent points. The absolute value of the spike was tested to catch both positive and negative spikes. Parameter-specific spike test thresholds (Table 1) were selected by assessing the frequency distribution of the absolute difference between a point and the average of its nearest neighbor points for the parameter in question. For both the gross range and spike tests, the thresholds were kept consistent for a given parameter between open-water platforms. Following these initial quality control tests, the data were retimed to 10-minute bins to resolve irregular sampling times.</p>
<p>Following initial QC, a moving median test was applied to detect outliers in the remaining datasets (Leys et al., 2013). This test was not performed for depth or temperature because of the large diel oscillations in these parameters. A 25-hour moving window median was calculated, and then the absolute deviation of each value from the moving median was obtained. An upper median absolute deviation (MAD) was obtained as the median of the deviations above the moving median, and a lower MAD for the deviations below. This double MAD approach was employed because the data distributions for all of the parameters were asymmetric (Tan et al., 2022). Points that exceeded ±3 respective MADs from the moving median were flagged and excluded from further analysis.&nbsp;</p>
<p>For parameters measured in duplicate (salinity, temperature, DO concentration, and pH), datasets were compared to produce a single, final quality-controlled time series. To assist this assessment, the absolute difference between duplicate datasets for a parameter was found for each time point and highlighted if it exceeded a certain threshold. The data were then visually examined and the “best guess” data was determined on a deployment-by-deployment basis. Several general principles were used to guide this selection. If the individual time series were offset for no apparent reason, and neither appeared to match up better with the previous and next deployment, then the mean time series was chosen (for salinity only, because the data were extremely noisy, the mean of the 24-hour moving median was used). If there were clear differences between duplicates for a given deployment (e.g., the individual time series were offset and one clearly did not match up with the previous and next deployments; one time series diverged from the other; or only one sonde had a complete record for that deployment), then the data from the “better” sensor was used. Data between related parameters were compared to aid this assessment (e.g., if pH dropped to relatively low values, the DO data were consulted to see if it coincided with a period of hypoxia or anoxia).</p>
<p>To further help in determining the best guess data, discrete Winkler samples were compared to the DO data, and DIC/TA samples were used to evaluate the pH data <em>[reference discrete sample dataset in this project]</em>. Discrete salinity samples were occasionally available for spot-checking. For the pH comparison, Aqua TROLL pH data were converted to hydrogen ion concentrations ([H+]) rather than evaluated on a logarithmic scale. Accordingly, the DIC and TA values were used to calculate discrete [H+] values using the CO2SYSv3 MATLAB program (Lewis &amp; Wallace, 1998; Sharp, 2023; Van Heuven et al., 2011). Errors in the CO<sub>2</sub> system variables were propagated to estimate errors in the calculated [H+] (Orr et al., 2018). The discrete values were used to help guide judgment in two cases: 1) determining which of the duplicate sensors was better performing when they differed, and 2) correcting for offsets in the sensor data when offsets were observed at both the beginning and end of a deployment. While the discrete sample data were useful additions to help inform the duplicate sensor check, they were evaluated on a deployment-by-deployment basis and as few adjustments as possible were made, because of uncertainty in the discrete measurements themselves as well as potential spatial mismatch in the water mass sampled and the sonde location. Moreover, the discrete sample coverage did not span the entire open-water platform time series, and therefore were only applicable to certain deployments in the last two years of measurements.</p>
<p>Because the Aqua TROLL sondes produce DO concentration values based on the measured pressure, temperature, and salinity, any errors in these measurements will propagate into the output DO values. To address this, DO concentration values were recalculated prior to duplicate comparison based on the salinity and depth compensation equations of Aanderaa Data Instruments AS (2017) using the final quality-controlled depth, temperature, and salinity time series. DO % saturation was calculated by normalizing the measured DO concentration to the saturation DO concentration (DO % saturation = DO<sub>measured</sub> / DO<sub>sat</sub> ×100%), where DO<sub>sat</sub> was calculated as a function of the final quality-controlled temperature and salinity (Garcia &amp; Gordon, 1992).</p>
<p>Turbidity and chlorophyll <em>a</em>, which were only available from single sensors at a platform, were reviewed further for final manual removals. This final manual inspection was necessary to address known issues of biofouling, which strongly affects the performance of these optical sensors by obscuring the sensor and causing sustained upward drift and excessive noise (Palevsky et al., 2023), and which was not fully remedied by the prior quality control tests. All of the open-water platform sondes experienced heavy biofouling year-round; a recent study conducted at the SMIIL site also reported pronounced biofouling that impacted turbidity sensor performance (Perkey et al., 2024). Here, cross-platform data were examined on a deployment-by-deployment basis for evidence of biofouling, and suspect data were removed, resulting in the removal of large periods of data.</p>
<p>Table 1. Thresholds for the initial data quality control tests for the parameters specified. Data exceeding these thresholds were flagged as suspect and removed prior to subsequent quality control tests.</p>
<table>
<tbody>
<tr>
<td><strong>Parameter</strong></td>
<td>
<p><strong>Gross Range Test Limits</strong></p>
<p><strong>(lower, upper)</strong></p>
</td>
<td>
<p><strong>Spike Test</strong></p>
<p><strong>Threshold</strong></p>
</td>
</tr>
<tr>
<td>&nbsp;Depth (m)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</td>
<td>(0, 5)</td>
<td>0.1</td>
</tr>
<tr>
<td>Temperature (<sup>o</sup>C)</td>
<td>(-2, 35)</td>
<td>1</td>
</tr>
<tr>
<td>DO conc (μmol/L)</td>
<td>(0, 650)</td>
<td>50</td>
</tr>
<tr>
<td>Salinity (psu)</td>
<td>(10, 50)</td>
<td>10</td>
</tr>
<tr>
<td>pH</td>
<td>(6, 9)</td>
<td>0.25</td>
</tr>
<tr>
<td>Turbidity (NTU)</td>
<td>(0, 350)</td>
<td>50</td>
</tr>
<tr>
<td>Chl a (RFU)</td>
<td>(0, 100)</td>
<td>10</td>
</tr>
</tbody>
</table>
Specified by the Principal Investigator(s)
- Imported "gull_finalDataset.csv", "north_finalDataset.csv", and "south_finalDataset.csv" into the BCO-DMO system, replacing NaN with blanks
- Concatenated all three files, adding a column for "site", which is what delineated the three files
- Converted datetime to ISO 8601 format YYYY-MM-DDTHH:MM:SSZ
- Exported file as "971943_v1_marsh_channel_monitoring.csv"
Specified by BCO-DMO Data Managers
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
ResponseONE™ Weather Transmitter (R.M. Young Company)
ResponseONE™ Weather Transmitter (R.M. Young Company)
PI Supplied Instrument Name: ResponseONE™ Weather Transmitter (R.M. Young Company) PI Supplied Instrument Description:Meteorological data were also collected at SMIIL to complement the water quality dataset. A ResponseONE™ Weather Transmitter (R.M. Young Company) measured wind speed and direction, air temperature, relative humidity, and atmospheric pressure. Due to data transmission issues, this record only spans September 2021–May 2023. Instrument Name: Automated Weather Station Instrument Short Name:AWS Instrument Description: Land-based AWS systems are designed to record meteorological information. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/102/
Aqua TROLL 600 multiparameter sondes (In-Situ Inc.)
Aqua TROLL 600 multiparameter sondes (In-Situ Inc.)
PI Supplied Instrument Name: Aqua TROLL 600 multiparameter sondes (In-Situ Inc.) PI Supplied Instrument Description:Water quality measurements were collected using Aqua TROLL 600 multiparameter sondes (In-Situ Inc.). Each sonde was equipped with sensors to measure depth, temperature, salinity, temperature, DO, and pH. In addition, each sonde included either a chlorophyll a fluorescence sensor or a turbidity sensor. Prior to each deployment, all sensors were calibrated in the laboratory according to the manufacturer’s protocols, including multipoint calibrations with certified standard solutions where applicable. Instrument Name: Multi Parameter Portable Meter Instrument Short Name: Instrument Description: An analytical instrument that can measure multiple parameters, such as pH, EC, TDS, DO and temperature with one device and is portable or hand-held.
HOBO water level logger (Onset Computer Corp.)
HOBO water level logger (Onset Computer Corp.)
PI Supplied Instrument Name: HOBO water level logger (Onset Computer Corp.) PI Supplied Instrument Description: Additionally, a nearby HOBO water level logger (Onset Computer Corp.) recorded air temperature and atmospheric pressure from August 2022–June 2024. Instrument Name: Water Level Sensor Instrument Short Name: Instrument Description: For measuring water level in fresh and salt water including tanks, wells, rivers, and the ocean.