Data is currently preliminary and likely to undergo additional QAQC steps
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Two data sets are included: (1) sensor and calculated data and (2) modeled stream metabolism estimates.
Sampling was conducted at sites in East Fork Poplar Creek by members of Oak Ridge National Laboratory’s WaDE Science Focus Area. Data from Theme 3 (9 sites) and Theme 2 (2 sites) are provided.
East Fork Poplar Creek in Oak Ridge, TN, USA, Roane and Anderson Counties. 12-digit hydrologic unit code: 060102070302.
| Site.Name.Normalized | Lat | Long | Altitude.Estimated.m |
|---|---|---|---|
| EFK5.4 | 35.96648 | -84.3581 | 230 |
| EFK7.9 | 35.96937 | -84.3464 | 234 |
| GumHollow | 35.97553 | -84.3356 | 237 |
| EFK10.0 | 35.97628 | -84.3355 | 237 |
| EFK11.3 | 35.98249 | -84.3274 | 240 |
| EFK13.8 | 35.99250 | -84.3153 | 245 |
| MillBranch | 35.99629 | -84.3032 | 249 |
| EFK16.2 | 35.99888 | -84.3001 | 250 |
| EFK18.2 | 36.00642 | -84.2810 | 254 |
| EFK20.0 | 36.00951 | -84.2685 | 256 |
| Downtown | 36.00974 | -84.2677 | 256 |
The Theme 3 sites were established in 2023 by Oak Ridge National Laboratory as part of the WaDE Science Focus Area. Theme 2 sites were established prior to 2023, however data from these sites is only provided for the time period that overlaps with when Theme 3 sites were active.
This work was funded by the U.S. Department of Energy, Office of Science, Biological and Environmental Research, Environmental Systems Science (ESS) Program, supporting the Watershed Dynamics and Evolution Science Focus Area (WaDE SFA).
Forthcoming. Please contact Marie Kurz prior to using any of this data in a publication.
Variables measured by sensors at Theme 3 sites were collected with two co-deployed underwater sensors: miniDOT (water temperature and dissolved oxygen) and CTD (water temperature, water pressure, and specific conductance) sensors. Air temperature and pressure is accessed from a nearby NOAA ASOS weather station.
Theme 2 site data are collected from sonde data (water temperature, dissolved oxygen, specific conductance, and depth). Additional meta-data is available elsewhere for these sites.
A visualization of theme 3 data is available (mean hourly, to speed processing) here: preliminarywadedata.shinyapps.io/Shiny_AllData. Contact Jonny Behrens for a password.
Each variable are reported in a comma separated file (.csv). Missing values are reported as NA.
| Flag | Flag description |
|---|---|
| REMOVE | Data is not real and replaced with “NA”. A known issue precludes its use (e.g., sensor out of water or not deployed at correct site) |
| Bad Data | Data is unreliable and should not be used in analyses. Issue with data is strongly inferred (e.g., sensor malfunction, cleaning, or calibration) |
| Questionable | The quality of the data cannot be verified. Use with caution. |
| Interesting | Data has unexpected values but is likely quality data. |
| No Flag | No quality concerns have been identified. |
This dataset covers water years 2024 and 2025, which begins on 1 October each year and ends 30 September each year. On-going data collection is underway for water year 2026, and is provided as it become available. Data are recorded in 15-minute intervals.
A PME miniDOT logger measures water temperature and dissolved oxygen. An error term (Q) is also reported by the instrument.
A VanEssen CTD-Diver measures water temperature, water depth, and specific conductance. Both sensors are installed in cinder blocks that are fully submerged underwater on the streambed at each site.
The Q term reported by the miniDOT provides a quality check for the optical sensor used to measure dissolved oxygen.
“Q is the ratio of the [DO] as determined from emission intensity to the [DO] as determined by emission lifetime. [DO] should be the same no matter which measurement technique is used. So [DOlifetime] = [DOintensity] and therefore [DOlifetime]/[DOintensity] = Q is ideally 1.0. In practice miniDOTs report Q to very close to 1.0.”
Source: PME: q-measurement-found-in-minidot.
The sensitivity reported by the manufacturer is provided below.
| Parameter | SensitivitySensor | Accuracy | Precision |
|---|---|---|---|
| DO_mgL | miniDOT | ± 5% of measure or ± 0.3 mg/L, whichever is larger | 0.001 mg/L |
| DO_sat | miniDOT | ± 5% of measure or ± 0.3 mg/L, whichever is larger | 0.001 mg/L |
| Pressure_Water_cmH2O | CTD | ± 0.5 cmH20 | 0.2 cmH20 |
| SpC_uScm | CTD | ± 1% of measure | 0.1% of measure |
| Temp_C_CTD | CTD | ± 0.1 degrees C | 0.01 degrees C |
| Temp_C_miniDOT | miniDOT | ± 0.1 degrees C | ± 0.1 degrees C |
Raw sensor data underwent automated and manual QAQC. When possible, data is preserved and marked with flags to enable users the ability to make decisions on what to include in their analyses.
We automatically flag data as “questionable” if any of the follow criteria are met.
During the period of sensor maintenance, time points are removed (~ 1 hour) and the gap is linearly interpolated.
Manually we also flag for various things observed. For example, when the sensor block is known or expected to be out of water, when biofouling of the miniDOT is expected, and during maintenance. When possible, we only flag the impacted sensor (e.g., if biofouling occurred, only DO data is flagged).
Detailed information is available alongside previously published datasets. Details forthcoming.
There are four calculated measures. The include: site-specific air pressure, dissolved oxygen in percent saturation, depth at the location of sensor deployment, stage height.
Air pressure and air temperature data were downloaded from a nearby NOAA weather station in Oak Ridge, WBAN:53868. Data is sourced from the NOAA Local Climatological Data, Version 2. The station is located at lat: 36.023 and long: -84.2337.
Functionally, the air pressure at the ASOS weather station is slightly different (~2-5 cmH2O) relative to other sites, given different altitudes. This is important, as that could introduce ~10-20% error to our estimate of water depth at some sites, if not calculated at each site specifically.
Thus, the air pressure at each site, approximately above the water surface, is estimated by correcting the air pressure measured by the ASOS weather station in Oak Ridge, TN for each site’s altitude. Altitude for each site was estimated based on the lowest elevation reported for the watershed draining to the site, using NHDPlus V2 NEDSnapshot DEM that was accessed through the Shroud Center’s Model My Watershed tool.
Sub-hourly NOAA data is transmuted to every minute and filtered to the 15 minute timestep to be consistent with the timestep of the CTDs.
Gaps in station pressure, when station altimeter is reported, are filled per NOAA methods.
The air pressure for each site is calculated by correcting the ASOS Oak Ridge NOAA station data to the altitude of the site of interest, per Equations 1 and 2. These equations are a simplified calculation that is used by streamMetabolizer, with site specific parameters. They are adapted from the second equation provided on this page.
A few assumptions were made for these analyses
For each time-step, at each site, we estimate the theoretical concentration of dissolved oxygen (mg/L) if the water was 100% saturated. This is the equilibrium concentration of DO at a given water temperature, site-specific air pressure, and altitude, assuming complete mixing of the water with the atmosphere.
LakeMetabolizer::o2.at.sat.base() is used
to calculate this value independently at each timestep at each siteWe divide the actual measured DO (mg/L) by the equilibrium concentration and multiply by 100 (to get a percent). This gives the dissolved oxygen in percent saturation.
Water depth was measured by subtracting the calculated site-specific air pressure from the water pressure measured by CTD sensor.
A stage height was approximated from the raw water depth. The sensor location moved at sites throughout the timeseries due to sensor cleaning, sensor re-positioning, or disturbance during disruptive flow events. Therefore, an approximate stage depth is calculated, relative to where the sensor was first deployed in the streambed. The stage height is manually estimated based on known and identified periods when the sensor block shifted.
Each variable is reported in a comman separated file (.csv).
Data inputs into streamMetabolizer include 2 parameters discussed in
the “sensor and calculated data” section: dissolved oxygen (percent
saturation) and water temperature. Light and depth are calculated with
the streamPULSE::prep_metabolism R function, by using
site-specific lat/long and discharge, respectively.
We estimated discharge at each site by …
Modeled estimates of daily metabolism underwent automated and manual QAQC. When possible, data is preserved and marked with flags to enable users the ability to make decisions on what to include in their analyses.
Data that used for streamMetabolizer was processed per the previously
outlined protocols. All time steps marked with “bad” or “remove” flags
were excluded from analysis, and replaced with NA. When data was
missing, it was linearly interpolated for gaps up to 3 hours in length
using the prep_metabolism function in the streamPULSE R
package. The same package was used to estimate PAR (above the canopy)
for each site and areal depth. NOTE: the PAR estimated for
streamMetabolizer should not be used for other analyses, as it is not an
estimate of light reaching the stream surface. Contact Jonny Behrens for
modeled estimates of PAR at the stream surface (with the R package
streamlight).
We chose to include flagged data with “questionable” or “interesting” to allow for the metabolism model to run, even with imperfect data. As described further below in the output QAQC, on days with this flagged data, caution should be used when interpreting those results. For example, if there is clear biofouling (DO will be flagged), metabolism estimates may not be trustworthy.
For detailed information on how the streamMetabolizer bayes model was set-up, contact Jonny Behrens. In brief summary, K600 priors were binned into 6 bins and 1000 burnin steps and 1000 saved steps were used.
Daily estimates were automatically flagged based on the following criteria. We group these into two categories: Reject and Questionable. It is encouraged that days marked with “reject” are excluded from all analyses. Days marked with “questionable” could be used in some analyses, depending on tolerance of error.
Days are marked as “rejected” for one of the following reasons:
Days are marked as “questionable” for one of the following reasons:
When the model does not have sufficient input data to model a day, it will not attempt to model GPP, ER, K600, and DO. For these days, “NA” is provided instead of any numeric value.
Different analyses may approach our flagged data in different ways. A few recommendations, though not required, are encouraged based on what has been previously done in the literature.
Do not include any days in analysis (even if they have numbers) if flagged with “bad”, “remove”, or “reject”. Effectively, they should be replaced with “NA”, as the output of the model indicates the failure of the model and not a defendable estimate of GPP, ER, or K600. The model’s fundamental assumptions are violated (e.g., high variability in discharge), the model struggled to reliably reach finality (high Rhat), or the model did not reach a biologically real solution even though the model may have “certainty” in the output (unrealistic GPP or ER).
For “questionable: unrealistic GPP or ER” flagged days, the measured values could be replaced with 0 since they are close to that value (and the 2.5% - 97.5% range likely includes 0). The “actual” GPP or ER likely is close to 0, though of course one should be cautious. This is particularly important for sites where anoxic or suboxic conditions are common, and thus GPP may either be close to 0 or not measurable. Filtering out all those days could remove quite a bit of data inadvertently.
All other days labeled “questionable” should be considered on a case by case basis.
Plans as of 2026-02-02: