ABSTRACT:

The following standard operating procedure (SOP) was created for the the Aquatic Intermittency effects on Microbiomes in Streams (AIMS), an NSF EPSCoR funded project (OIA 2019603) seeking to explore the impacts of stream drying on downstream water quality across Kansas, Oklahoma, Alabama, Idaho, and Mississippi. AIMS integrates datasets on hydrology, microbiomes, macroinvertebrates, and biogeochemistry in three regions (Mountain West, Great Plains, and Southeast Forests) to test the overarching hypothesis that physical drivers (e.g., climate, hydrology) interact with biological drivers (e.g., biogeochemistry, microbial and macroinvertebrate communities) to control water quality in intermittent streams. An overview of the AIMS project can be found here: https://youtu.be/HDKIBNEnwdM

This protocol will detail the process for collecting and storing benthic macroinvertebrates collected at AIMS sites. Benthic macroinvertebrates will be collected during regular sensor maintenance (Approach 1), during seasonal synoptics (Approach 2), and during the synoptic sampling (Approach 3). A video was created to detail this sampling method (https://www.youtube.com/watch?v=6niLLGBOoeU). Most samples were collected for DNA metabarcoding, although some samples were set aside for abundance data. From this SOP, the following data types will be created: Macroinvertebrate DNA sequences, presence / absence data, abundance data [AIMS rType: MACR]

ABSTRACT:

The following standard operating procedure (SOP) was created for the the Aquatic Intermittency effects on Microbiomes in Streams (AIMS), an NSF EPSCoR funded project (OIA 2019603) seeking to explore the impacts of stream drying on downstream water quality across Kansas, Oklahoma, Alabama, Idaho, and Mississippi. AIMS integrates datasets on hydrology, microbiomes, macroinvertebrates, and biogeochemistry in three regions (Mountain West, Great Plains, and Southeast Forests) to test the overarching hypothesis that physical drivers (e.g., climate, hydrology) interact with biological drivers (e.g., biogeochemistry, microbial and macroinvertebrate communities) to control water quality in intermittent streams. An overview of the AIMS project can be found here: https://youtu.be/HDKIBNEnwdM

This protocol details the process for collecting, storing, and routing primary samples for the Microbiome theme. Material for microbiome data analysis from four microhabitat types, i) water, ii) epilithon, iii) benthic sediment, and iv) leaf litter, will be collected during the distributed seasonal sampling (AIMS Approach 2), synoptic sampling (AIMS Approach 3), and the flow manipulation experiment (AIMS Approach 4). All samples will be collected using sterile technique, then subsampled and preserved appropriately for the following downstream laboratory analyses: a) extracellular enzyme activity analysis, b) DNA extraction for 16S rRNA gene and ITS library sequencing and quantitative PCR, c) chlorophyll-a and ash-free dry mass. Those laboratory analyses will be detailed in separate SOPs. This protocol will also include directions for measurement of stream habitat characteristic measurements that are not already covered by biogeochemical and hydrological data collection.
From this SOP, the following data types will be created: field meta-data, extracellular enzyme activity analysis, DNA extraction for 16S rRNA gene and ITS library sequencing and quantitative PCR, chlorophyll-a and ash-free dry mass [AIMS data types: MIME, EEAS, DNAB, DNAF, CHLA, AFDM].

ABSTRACT:

The following standard operating procedure (SOP) was created for the the Aquatic Intermittency effects on Microbiomes in Streams (AIMS), an NSF EPSCoR funded project (OIA 2019603) seeking to explore the impacts of stream drying on downstream water quality across Kansas, Oklahoma, Alabama, Idaho, and Mississippi. AIMS integrates datasets on hydrology, microbiomes, macroinvertebrates, and biogeochemistry in three regions (Mountain West, Great Plains, and Southeast Forests) to test the overarching hypothesis that physical drivers (e.g., climate, hydrology) interact with biological drivers (e.g., microbes, biogeochemistry) to control water quality in intermittent streams. An overview of the AIMS project can be found here: https://youtu.be/HDKIBNEnwdM

This protocol details the process for setting up, testing, deploying, downloading, relaunching, and retrieving STIC sensors to assess the presence and absence of surface water. These sensors will be used throughout the nine focal watersheds to get a spatially distributed view of stream drying patterns (AIMS Approach 1) and will inform locations for distributed seasonal sampling (AIMS Approach 2).

The "living" version of this SOP can be found on Google Docs: https://docs.google.com/document/d/1_GOR5HyaH7kxzvBhT6yi1ajTyhBhfVRI9UGYjQ043qI/edit?tab=t.0

Also included in this resource are field sheets, used when STICs were collected to record site, serial number, timing of collection, and other information important for STIC processing.

From this SOP, the following data types will be created: Time series of temperature and conductivity. [AIMS rTypes: STIC]

ABSTRACT:

The following standard operating procedure (SOP) was created for the the Aquatic Intermittency effects on Microbiomes in Streams (AIMS), an NSF EPSCoR funded project (OIA 2019603) seeking to explore the impacts of stream drying on downstream water quality across Kansas, Oklahoma, Alabama, Idaho, and Mississippi. AIMS integrates datasets on hydrology, microbiomes, macroinvertebrates, and biogeochemistry in three regions (Mountain West, Great Plains, and Southeast Forests) to test the overarching hypothesis that physical drivers (e.g., climate, hydrology) interact with biological drivers (e.g., microbes, biogeochemistry) to control water quality in intermittent streams. An overview of the AIMS project can be found here: https://youtu.be/HDKIBNEnwdM

This protocol will detail the process for calibrating and launching STIC (Stream Temperature Intermittency & Relative Conductivity) sensors.

The "living" version of this SOP can be found on Google Docs: https://docs.google.com/document/d/1gTZ5MecE8Xjp6ymhH4rB92V_i1lH93Jv/edit

From this SOP, the following data types will be created: Time series of temperature and conductivity. [AIMS rTypes: STIC]

ABSTRACT:

The following standard operating procedure (SOP) was created for the the Aquatic Intermittency effects on Microbiomes in Streams (AIMS), an NSF EPSCoR funded project (OIA 2019603) seeking to explore the impacts of stream drying on downstream water quality across Kansas, Oklahoma, Alabama, Idaho, and Mississippi. AIMS integrates datasets on hydrology, microbiomes, macroinvertebrates, and biogeochemistry in three regions (Mountain West, Great Plains, and Southeast Forests) to test the overarching hypothesis that physical drivers (e.g., climate, hydrology) interact with biological drivers (e.g., microbes, biogeochemistry) to control water quality in intermittent streams. An overview of the AIMS project can be found here: https://youtu.be/HDKIBNEnwdM.

This protocol details the process for measuring streamflow within the stream network focused largely on low-flow conditions using dilution gaging techniques.

Also included in this resource is the AIMS datasheet used when taking measurements in the field.

The "living" version of this SOP is available on Google Docs: https://docs.google.com/document/d/18mvs_aAr677eQDrwUuassMTWmjggSQxVkmkr0vgF0J4/edit?tab=t.0

From this SOP, the following data types will be created: stream width, depth, discharge (AIMS rTypes created: ENVI, DISC).

ABSTRACT:

This resource includes static environmental data collected for the sensor and sampling locations in the Gibson Jack Watershed located near Pocatello, ID. Gibson Jack Creek (outlet location: 42.7853, -112.4446) drains 1620 ha of the US Forest Service Research Natural Area within the Caribou National Forest. Predominantly forested with deciduous trees, sub-apline fir, Douglas fir, and with woody shrubs, sagebrush, and grasses, Gibson Jack spans an elevation range of 1555-2130 m, and has an mean annual temperature and precipitation of 6.5°C and 614.5 mm/yr, respectively. Gibson Jack spans the rain to snow transition with rainfall occurring at the lower elevations and snowfall at the upper elevations. Gibson Jack Creek drains to the Portnuef River and is heavily recreated by the local community.

Further information for all data fields can be found in the "Data Types" tab of this file. In short, this resource contains data for sites across a suite of sensor types, denoted by the sublocation field. These sublocations include:
- "SW" -- a site where regular surface water sampling occured, and contained a stilling well to record stream water level

This resource was created using geospatial analyses using publicly available topographic data (Digital Elevation Models, DEMs from the USGS National Map Downloader v2.0; https://apps.nationalmap.gov/downloader/).
Site locations GPS coordinates were collected using a eMLID Reach RX multi-band RTK rover.
Elevation was extracted from a DEM. All additional environmental data were derived from this DEM using whitebox functions for topographic and stream network analysis (Wu & Brown, 2022) in R version 4.4.0 (R Core Team, 2024).

Approach 1 site is GSS01
Approach 2 sites indicated by GPZ
Approach 3 sites are listed as GBJ or STIC

ABSTRACT:

Johnston Draw is a 1.8-km2 watershed in southwestern Idaho, USA (outlet location: 43.1226, -116.776) located within the Reynolds Creek Critical Zone Observatory in western Idaho, a research center with cattle grazing. Elevation ranges from approximately 1490m to 1850m. The mean annual precipitation in the watershed is 550 mm/yr with rainfall occurring at the lower elevations and snowfall, resulting in large drifts, at the higher elevations (Godsey et al., 2018). Mean annual temperatures range from 8.9C at the bottom of watershed and 4.7C near the top.

Citations:

Bilbrey, E.M. 2024. Quantifying Dissolved Organic Carbon Patterns and the Impact of Stream Network Connectivity on Export From Semi-Arid Intermittent Watersheds. Idaho State University. https://www.proquest.com/docview/3079012638/abstract/4FAB29E7230542A8PQ/1.
Godsey, S.E., Marks, D., Kormos, P.R., Seyfried, M.S., Enslin, C.L., Winstral, A.H., McNamara, J.P., Link, T.E. 2018. Eleven years of mountain weather, snow, soil moisture and streamflow data from the rain–snow transition zone—The Johnston draw catchment, Reynolds Creek Experimental Watershed and Critical Zone Observatory, USA. Earth Systems Science Data Vol. 10: 1207-1216.

Further information for all data fields can be found in the "Data Types" tab of this file. In short, this resource contains data for sites across a suite of sensor types, denoted by the sublocation field. These sublocations include:
- "SW" -- a site where regular surface water sampling occured, and contained a stilling well to record stream water level

This resource was created using geospatial analyses using publicly available topographic data (Digital Elevation Models, DEMs from the USGS National Map Downloader v2.0; https://apps.nationalmap.gov/downloader/).
Site locations GPS coordinates were collected using a eMLID Reach RX multi-band RTK rover.
Elevation was extracted from a DEM. All additional environmental data were derived from this DEM using whitebox functions for topographic and stream network analysis (Wu & Brown, 2022) in R version 4.4.0 (R Core Team, 2024).

Approach 1 site is JSS01
Approach 2 sites indicated by JPZ (Pressure Transducers)
Additional sites (STICS) indicated by JDR

ABSTRACT:

Environmental data from AIMS research locations at Shane Creek, Kansas. Full description in 'Metadata' tab of excel data file.

Shane Creek, located north of Kings Creek in the Konza Prairie Biological Station (outlet location: 39.11522, -96.55838; 434 ha), is a native tallgrass prairie located in the Konza Prairie Biological Station, a long term ecological research station that has been in operation since 1980. Shane’s Creek is annually cattle-grazed and burned every three years. Konza is located in the Flint Hills of northern Kansas. In 2023, the outlet of the stream wet up in March and dried down in July; in 2024, the outlet of the stream wet up in March and dried down in September. Average annual precipitation for this site is 35.62 inches.

Further information for all data fields can be found in the "Data Types" tab of this file. In short, this resource contains data for sites across a suite of sensor types, denoted by the sublocation field. These sublocations include:
- "SW" -- a site where regular surface water sampling occurred, and contained a stilling well to record stream water level

This resource was created using geospatial analyses using publicly available topographic data (Digital Elevation Models, DEMs from the USGS National Map Downloader v2.0; https://apps.nationalmap.gov/downloader/).
Site locations GPS coordinates were collected using a eMLID Reach RX multi-band RTK rover.
Elevation was extracted from a DEM. All additional environmental data were derived from this DEM using whitebox functions for topographic and stream network analysis (Wu & Brown, 2022) in R version 4.4.0 (R Core Team, 2024).

Approach 1 site is outlet site, with a STIC, pressure transducer loggers, and YSI EXO and S::CAN
Approach 2 sites long term monitoring, equipped with pressure transducers and STICs
Additional sites with STICs

ABSTRACT:

Environmental data from AIMS research locations at Youngmeyer Ranch, Kansas. Full description in 'Metadata' tab of excel data file.

Youngmeyer Ranch is located in Elk County, KS (outlet location: 37.56442, -96.49106) and managed by Witchita State University and owned by the Youngmeyer Trust. The ranch is roughly 1902 ha of grassland prairie used predominantly for cattle grazing and is burned every 1-2 years. A tributary of the Elk River, specifically the south branch of the Elk River headwaters, elevation at Youngmeyer ranges from 373-488 m with mean annual temperature of 13.7°C and mean annual precipitation of 979mm. This site is geologically constructed of Permian age limestone and shale with layers of chert below silty clay loam soils (Houseman et al. 2016). This site is predominantly grassland composed of the same dominant grasses as Konza Prairie, with scattered black oaks (Q. veluntina) along the creeks (Houseman et al. 2016).

Houseman, G. R., M. S. Kraushar, and C. M. Rogers. 2016. The Wichita State University biological field station: Bringing breadth to research along the precipitation gradient in Kansas. Transactions of the Kansas Academy of Science 119(1):27-32.

Further information for all data fields can be found in the "Data Types" tab of this file. In short, this resource contains data for sites across a suite of sensor types, denoted by the sublocation field. These sublocations include:
- "SW" -- a site where regular surface water sampling occurred, and contained a stilling well to record stream water level

This resource was created using geospatial analyses using publicly available topographic data (Digital Elevation Models, DEMs from the USGS National Map Downloader v2.0; https://apps.nationalmap.gov/downloader/).
Site locations GPS coordinates were collected using a eMLID Reach RX multi-band RTK rover.
Elevation was extracted from a DEM. All additional environmental data were derived from this DEM using whitebox functions for topographic and stream network analysis (Wu & Brown, 2022) in R version 4.4.0 (R Core Team, 2024).

Approach 1 site is outlet site, with a STIC, pressure transducer loggers, and YSI EXO and S::CAN
Approach 2 sites long term monitoring, equipped with pressure transducers and STICs
Additional sites with STICs

ABSTRACT:

This study was conducted on the South Fork of the Kings Creek research watershed (outlet location: 39.092281, -96.58719) within Konza Prairie Biological Station (KBPS) near Manhattan (KS, USA). At the USGS gage located on the mainstem (06879560; est. 1979), Kings Creek is a 5th order intermittent stream draining 1059-ha of tallgrass prairie that is actively managed using controlled buns at varying frequencies (1-20 year return intervals) and grazing by bison or cattle. Kings Creek ranges in elevation from 338 to 430 m above sea level and drains into the Kansas River. The region is within a midwestern continental climate, with temperatures ranging from 4 to 22°C and mean annual precipitation averaging about 780 mm/yr.

This site lies within the Flint Hills ecoregion of eastern KS and northeastern OK, has a mean annual temperature of 11.7ºC (1983-2020), and 811 mm annual precipitation (1983-2020) with high interannual variability and an estimated 75% of annual precipitation occurring during late spring and early summer (Hayden 1998, Sadayappan et al. 2023). The AIMS study catchment, the South Fork of Kings Creek, is grazed by bison year-round, and includes sub-catchments with variable prescribed burn history, but the entire study area was burned in early April 2021. The riparian vegetation is deciduous gallery forest and the highest portion of the landscape is tallgrass prairie (Dodds et al. 2004) dominated by warm-season grasses, though woody encroachment has occurred in most subwatersheds (Sadayappan et al. 2023)*. The underlying bedrock of the Flint Hills ecotone is characterized as limestone, mudstone, and shale with predominately silty clay loam soils that rest atop (Hayden 1998, Vero et al. 2018).

This resource contains the YSI field data from AIMS approaches 1 (maintenance samples ~every 3 weeks), 2 (seasonal sampling), and 3 (syntopic sampling event) samplings at King's Creek. During sampling, a YSI Pro1030 Waterproof Handheld meter was placed in the stream and numbers were allowed to stabilize while water sampling took place. Data is not available when the site was dry - as noted by the flow_state column. In addition, some sampling events lacked a YSI handheld and data is therefore missing.

ABSTRACT:

Shane Creek, located north of Kings Creek in the Konza Prairie Biological Station (outlet location: 39.11522, -96.55838; 434 ha), is a native tallgrass prairie located in the Konza Prairie Biological Station, a long term ecological research station that has been in operation since 1980. Shane’s Creek is annually cattle-grazed and burned every three years. Konza is located in the Flint Hills of northern Kansas. In 2023, the outlet of the stream wet up in March and dried down in July; in 2024, the outlet of the stream wet up in March and dried down in September. Average annual precipitation for this site is 904.7 mm.
These data were collected in support of the sampling goals of the Aquatic Intermittency effects on Microbiomes in Streams (AIMS) Project. This study took place in Shane’s Creek (434 ha) at the Konza Prairie Biological Station, a long term ecological research station that has been in operation since 1980. Shane’s Creek is annually cattle-grazed and burned every three years. Konza is located in the Flint Hills of northern Kansas. In 2023, the outlet of the stream wet up in March and dried down in July; in 2024, the outlet of the stream wet up in March and dried down in September. Average annual precipitation for this site is 35.62 inches.

We constructed a wooden stream diversion structure halfway down a 380m reach containing four pools and three riffles above and below the structure. The structure had 4 1-foot diameter holes installed with PVC couplers. Four 130m corrugated flexible tubes were laid out from the diversion structure to the bottom of the impact reach. We deployed 20 STICs throughout the control and impact reach to quantify the extent of drying using rebar. Construction and preparation occurred in February and March, when the stream was dry, to minimize construction-related disturbances to the experimental sampling. Prior to experimental dry down, water was able to flow from upstream (control reach) to downstream (impact reach) through the holes. We obtained pre-dry down sampling to collect a reference point for both the control and impact reaches. These “pre-dry week X” samples were collected from April to mid-July due to multiple flooding events (April 25th, June 26th, and July 3rd) that disrupted the experimental setup and required redeployment of experimental structures and equipment. During the experimental dry down (“dry week X” samples), we attached the tubes to the couplers in the diversion structure. Flow was diverted around the impact reach into the downstream watershed for five weeks, during which we collected weekly samples. Following the final forced drying sampling, tubes were cut from their couplers to allow flow to resume in the impact reach (“re-wet week X” samples). After 6 hours, we performed day 0 re-wet sampling. Twenty four hours later, we performed day 1 re-wet sampling. One week later, the stream began to naturally dry down in both the control and impact reaches, and collected weekly natural dry down samples for two weeks (“natural dry down week X” samples).

This resource contains the YSI field data from AIMS approaches 1 (maintenance samples ~every 3 weeks), 2 (seasonal sampling), and 3 (syntopic sampling event) samplings at King's Creek. During sampling, a YSI Pro1030 Waterproof Handheld meter was placed in the stream and numbers were allowed to stabilize while water sampling took place. Data is not available when the site was dry - as noted by the flow_state column. In addition, some sampling events lacked a YSI handheld and data is therefore missing.

ABSTRACT:

Johnston Draw is a 1.8-km2 watershed in southwestern Idaho, USA (outlet location: 43.1226, -116.776) located within the Reynolds Creek Critical Zone Observatory in western Idaho, a research center with cattle grazing. Elevation ranges from approximately 1490m to 1850m. The mean annual precipitation in the watershed is 550 mm/yr with rainfall occurring at the lower elevations and snowfall, resulting in large drifts, at the higher elevations (Godsey et al., 2018). Mean annual temperatures range from 8.9C at the bottom of watershed and 4.7C near the top.

These data were collected in support of the sampling goals of the Aquatic Intermittency effects on Microbiomes in Streams (AIMS) Project. These sensors were set to collect temperature and conductivity data every 15 minutes. Each .csv file is associated with a single site for a single year.

Naming convention
Guide to interpreting file names using STIC_MW_JDR_JDR28_HS_.2023csv as an example:
- "STIC_MW_JDR_" = same for all sites, indicating it is STIC data from the Mountian West region and the Johnston Draw watershed.
- "JDR28" = site code, corresponding to the location of the STIC within the watershed
- "HS" = sublocation, corresponding to the placement of the STIC at that site. All data in this resource was collected from sensors with a "HS" sublocation, meaning the STIC was placed at a high spot in the stream thalweg, and a wet reading is interpreted as an indicator of flowing surface water connection within the stream network.
- "2023" = year of STIC data included in file.

Methodological details:
STIC sensors were deployed in 2021 following the methods described here: http://www.hydroshare.org/resource/c82a87a6c63445029d35131260241386
STIC sensors were calibrated following the methods described here: http://www.hydroshare.org/resource/9f2027c779d64149be32bdb9eede54f2
A detailed description of the processing and classification workflow is available in Zipper et al: https://eartharxiv.org/repository/view/4909/

Due to data logger errors, maintenance, etc. there are not data for all sites at all timesteps.

Further information for all data fields can be found in the "Data Types" tab of this ReadME. Sensors recorded relative conductivity (here, condUncal) and used in conjunction with multi-point lab calibration curves to calculate wetdry and SpC fields. The lowest point on the standard curve was water with an SpC of 0, which represented the lowest possible condUncal that would yield a "wet" value. This zero was used as a threshold, and wetdry was calculated such that anything below this threshold was "dry" (wetdry = 0) and anything above was "wet" (wetdry = 1). Additionally, the rest of the standard curve was used to build a relationship between condUncal and SpC, and this linear model was applied to the condUncal to calculate SpC.

The qual_rating flags are (Details in Zipper et al):
Excellent: STIC was (1) calibrated prior to deployment, and (2) stayed operational throughout 95% of the download period, and (3) was not displaced from streambed (i.e., the external electrodes were within 1 cm from stream bed at the time of download indicating minimal erosion/deposition), and (4) data from sensor roughly agree with field observations of wet/dry (i.e., >1000 Lux sensor reading on day of removal corresponds to field observations of water at STIC).
Good: (1) STIC stayed operational throughout the entire download period, and (2) the external electrodes were within 1 cm from stream bed at the time of download, and (3) data from sensor roughly agree with field observations of wet/dry, but (4) the STIC was not calibrated prior to deployment.
Fair: (1) STIC stayed operational throughout 75% or more of the download period, and (2) data roughly agree with field observations, and/or (3) the external electrodes were between 1-3 cm from streambed at the time of download.
Poor: (1) STIC stayed operational throughout less than 75% of the download period, and/or (2) the external electrodes were >3 cm from streambed at the time of download, and/or (3) data does NOT agree with field observations.
The QAQC flags are denoted as follows; if multiple flags were generated, they were concatenated:
NA : no flags, data passes checks
C : calibration curve yielded a negative value for SpC, changed to a value of 0 manually
O : SpC value is higher than the highest measured Calibration point, and is therefore off the calibration curve
D : wetdry reading flagged as a potential anomaly (i.e., short period of dry surrounded by long period of wet, calculated using a moving window z-score of condUncal values)
T : wetdry reading interpreted from temperature data

ABSTRACT:

Located near Pocatello, ID, Gibson Jack Creek (outlet location: 42.7853, -112.4446) drains 1620 ha of the US Forest Service Research Natural Area within the Caribou National Forest. Predominantly forested with deciduous trees, sub-apline fir, Douglas fir, and with woody shrubs, sagebrush, and grasses, Gibson Jack spans an elevation range of 1555-2130 m, and has an mean annual temperature and precipitation of 6.5°C and 614.5 mm/yr, respectively. Gibson Jack spans the rain to snow transition with rainfall occurring at the lower elevations and snowfall at the upper elevations. Gibson Jack Creek drains to the Portnuef River and is heavily recreated by the local community.

These data were collected in support of the sampling goals of the Aquatic Intermittency effects on Microbiomes in Streams (AIMS) Project. These sensors were set to collect temperature and conductivity data every 15 minutes. Each .csv file is associated with a single site for a single year.

Naming convention
Guide to interpreting file names using STIC_MW_GBJ_STIC65_HS_2024.csv as an example:
- "STIC_MW_GBJ_" = same for all sites, indicating it is STIC data from the Mountian West region and the Gibson Jack watershed.
- "STIC65" = site code, corresponding to the location of the STIC within the watershed
- "HS" = sublocation, corresponding to the placement of the STIC at that site. All data in this resource was collected from sensors with a "HS" sublocation, meaning the STIC was placed at a high spot in the stream thalweg, and a wet reading is interpreted as an indicator of flowing surface water connection within the stream network.
- "2024" = year of STIC data included in file.

Methodological details:
STIC sensors were deployed in 2021 following the methods described here: http://www.hydroshare.org/resource/c82a87a6c63445029d35131260241386
STIC sensors were calibrated following the methods described here: http://www.hydroshare.org/resource/9f2027c779d64149be32bdb9eede54f2
A detailed description of the processing and classification workflow is available in Zipper et al: https://eartharxiv.org/repository/view/4909/

Due to data logger errors, maintenance, etc. there are not data for all sites at all timesteps.

Further information for all data fields can be found in the "Data Types" tab of this ReadME. Sensors recorded relative conductivity (here, condUncal) and used in conjunction with multi-point lab calibration curves to calculate wetdry and SpC fields. The lowest point on the standard curve was water with an SpC of 0, which represented the lowest possible condUncal that would yield a "wet" value. This zero was used as a threshold, and wetdry was calculated such that anything below this threshold was "dry" (wetdry = 0) and anything above was "wet" (wetdry = 1). Additionally, the rest of the standard curve was used to build a relationship between condUncal and SpC, and this linear model was applied to the condUncal to calculate SpC.

The qual_rating flags are (Details in Zipper et al):
Excellent: STIC was (1) calibrated prior to deployment, and (2) stayed operational throughout 95% of the download period, and (3) was not displaced from streambed (i.e., the external electrodes were within 1 cm from stream bed at the time of download indicating minimal erosion/deposition), and (4) data from sensor roughly agree with field observations of wet/dry (i.e., >1000 Lux sensor reading on day of removal corresponds to field observations of water at STIC).
Good: (1) STIC stayed operational throughout the entire download period, and (2) the external electrodes were within 1 cm from stream bed at the time of download, and (3) data from sensor roughly agree with field observations of wet/dry, but (4) the STIC was not calibrated prior to deployment.
Fair: (1) STIC stayed operational throughout 75% or more of the download period, and (2) data roughly agree with field observations, and/or (3) the external electrodes were between 1-3 cm from streambed at the time of download.
Poor: (1) STIC stayed operational throughout less than 75% of the download period, and/or (2) the external electrodes were >3 cm from streambed at the time of download, and/or (3) data does NOT agree with field observations.
The QAQC flags are denoted as follows; if multiple flags were generated, they were concatenated:
NA : no flags, data passes checks
C : calibration curve yielded a negative value for SpC, changed to a value of 0 manually
O : SpC value is higher than the highest measured Calibration point, and is therefore off the calibration curve
D : wetdry reading flagged as a potential anomaly (i.e., short period of dry surrounded by long period of wet, calculated using a moving window z-score of condUncal values)
T : wetdry reading interpreted from temperature data