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:

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:

This resource includes hydrometric data collected within the Gibson Jack watershed, located in Pocatello, Idaho, USA in the northern Rocky Mountains. These data were collected with the purpose of assessing three-dimensional connectivity in an intermittent stream reach. Stage was measured via Onset U-20 water level loggers at 13 locations within the stream, riparian area, and adjacent hillslopes, and corrected for barometric pressure. For sites within the stream, stage was converted to a hydrograph via a stage-discharge relationship derived from occasional discharge measurements. Discharge measurements were made with a SonTek FlowTracker as well as using dilution gaging methods with an Onset U-24 electrical conductivity logger, which was used to quantify the breakthrough curve for known additions of salt. Local discharge gains and losses in flow along the stream network were calculated using the methods outlined in Payn et al. 2009. Precipitation was measured using a Texas Electronics Rain Gage (0.254mm) recorded by a Campbell Scientific CR1000 datalogger. Temperatures were also recorded at the stream sites using the Hobo U-24 sensors.