The Download You Thought Happened
The HOBO pendant logger at McFarland Top has been sitting at 1.2 meters depth since April. The crew visited in mid-July, downloaded what they thought was the full deployment, and moved to the next site. Back at the office, the data file opens and shows 47 days of good readings — then a gap from June 22nd to July 12th. The red light before download: nobody recorded whether it was observed. The download successful field was not logged. The crew member who did the visit doesn't recall.
The June 22nd to July 12nd gap falls exactly across the period of highest thermal stress in the summer snowmelt. It is the data that would have shown whether the North Fork thermoregulatory corridor held temperature below the 18°C juvenile steelhead threshold during low-flow conditions. That analysis is the reason the loggers are deployed. The gap makes it unusable.
A structured field check record — crew initials, logger ID, serial number, date/time, red-light before download confirmed or not, download successful or not — takes thirty seconds per site. It creates the accountability trail that turns a data gap into a known data gap with a visit record, rather than an inexplicable absence in a multi-year dataset.
What the Condition Field Catches
Logger condition — Submerged or Not fully submerged — is the field that flags compromised air temperature data from a water logger and missing thermal refuge data from a partially exposed unit.
A water temperature logger that is not fully submerged during a low-water August visit is recording air temperature during the hours it is exposed and water temperature when stream flow rises. The resulting record is a mixed signal that cannot be cleanly attributed to either medium without knowing the submersion history. The condition field, recorded at each visit, provides that history. A string of "Not fully submerged" entries across multiple late-summer visits is the metadata that makes the temperature record interpretable — or that correctly disqualifies it from trend analysis.
The Logger type field — Water temp, Air temp — seems redundant for a crew that installs and retrieves its own loggers. It is not redundant when the field sheet is reconciled against the deployment register at the end of the season and three loggers have been retrieved from locations where the deployment register shows the opposite type. Transposition errors during installation happen. The field sheet is the catch.
Thirty Seconds Per Site, Across Ninety Sites
The location list embedded in this template names every node in a multi-watershed temperature monitoring network across the Methow River system in north-central Washington: 20 Mile, 8 Mile, Bear, Beaver, Benson, Black Canyon, Buttermilk, Cub, Falls, Finley, Frazer, Goat, July, Libby, McFarland, Pearrygin, Ramsey, Squaw, Whiteface — top, bottom, air, pond, and tributary splits at each. Ninety-plus named deployment sites, each requiring a visit record that ties a crew member, a timestamp, a logger ID, a serial number, and a condition assessment to a specific geographic node on a specific date.
The Notes/observations field — hinted as "Visit type, flows, found floating, needs attention?" — is where the site-specific narrative goes that the structured fields cannot capture: the coyote that moved the anchor stake at Squaw Top, the unusually high turbidity at Benson South Fork that may indicate upstream erosion, the logger at Bear Bottom that was found floating after the mid-July pulse flow and was re-anchored with a heavier attachment.
Without a field check record, those observations are verbal, exchanged at the tailgate, and lost by the time the data is processed in November.