As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the glacial meltwater streams in that region. These tables contain data pertaining to continuous monitored water quality and quantity parameters measured with automatic recording devices on streams in this region. Specifically, this dataset describes the hydrology data for the Barltley Stream (Flume) for the seasons 1983-84 to 1984-85
Campbell CR10 dataloggers were used to record stream stage, water temperature, and conductivity in a network of stream gages. Stage is monitored with pressure transducers; PSS-1 and PS-2 models form Paroscientific Corporation, and Accubars from Sutron Corporation. The press ure transducers measure the backpressure in orifice lines set into or above controls in the stream channel. In addition, some of the sites monitor water temperature and conductivity with either USGS minimonitor probes, or Campbell temperature/conductivity probes. Ratings are developed for the stage/discharge relationship at each site by measuring streamflow with current meters or portable flumes, according to standard USGS methods. Datum corrections to the stage are determined by periodically surveying the elevation of the orifice line to the control and nearby reference marks. Calibrations for the temperature and conductivity are assessed by measuring these parameters with portable field meters while simultaneously noting the readings from the gage probes. Data is downloaded into Campbell storage modules, and retrieved into pcs. From there, the data is sent to a USGS computer, where time discrepancies are resolved, and the data is loaded into ADAPS, a database system developed in the USGS for maintaining and processing water data. A determination for each site as to when the stream was flowing and when it was not is made. For water temperature and conductivity, bad data is deleted. Variable shifts are determined based on field calibration measurements, and other indicators. The shifts are applied to the remaining good data inside of ADAPS. The data is pulled out of ADAPS, and reformatted for input into ORACLE. Cases of water temperature below reasonable values are set to lower limits. A quality code is assigned to every value. The resulting data is uploaded into the ORACLE and the McMurdo database. For stage/discharge, bad data is deleted. Survey data is reviewed to compute weir elevations and datum corrections. A rating curve is developed graphically, based on available data, and entered into ADAPS. All applicable shifts and datum corrections are entered into ADAPS. All corrections and ratings are run against the good stage data to compute the discharge at each recording interval. The data is pulled out of ADAPS, and reformatted for input into ORACLE. A quality code is assigned to every value. The resulting data is uploaded into ORACLE and the McMurdo database.
The 'discrete_stream_gauge' table was created by Harry House in early 1994. It was first stored in an INGRES database, but was converted to ORACLE format in early 1996. Modifications were generally made each year after the initial creation in the early part of the year. It was transferred to INSTAAR in late 1997, where it was stored in a Microsoft Access database, and presented on the web in ascii, comma delimited files. In October, 1999 Mike Gooseff submitted the 1997-98 data to Denise Steigerwald (the data manager) in ascii, comma delimited files. In order to prepare the files for use in an Oracle database as well as a geographic information system, Denise created a field for "strmgageid" (stream gage id), converted any time fields of 24:00 to 0:00 on the following day, combined the date and time fields into one date/time field, and separated the data into separate files for each station. Data which was previously presented according to decade collected is now presented according to location, and contains records from the start date of monitoring for a given stream gage. The resulting files are available through the links provided above. In order to make the data more relational / useful in Oracle and ArcInfo, and generate links between different data and metadata fields, a dataset code was added to these files Inigo San Gil introduced metadata enhancements following LTER guidelines in 2014, and migrated the metadata to the Drupal Ecological Information Management System