Methods
Summary
Temperature sensors will be deployed to optimize spatial sampling on a stream network across the range of known important predictors (Thomas Kincaid 2023), such as basin area, flow, and elevation (Som 2014). Specific stream network locations will be targeted for sensor triad clustering to optimize autocovariance parameter estimation.
At least 35 sites will be installed and monitored during the summer from spring (June 1st) to fall (October 1st). At each monitoring location loggers will be deployed in well mixed water, shade, and adequate depth to remain submerged for the summer low flow period. Temperature data will be collected at 30-minute intervals.
Data QC is required after the end of monitoring download of temperature data. In addition to the post-recovery data QC process (e.g., compare field visits, stream flow, and air temp against water temperature), automated checks should be used to identify potential errors (Sowder 2012). At a minimum, automated flags should include a thermal minimum and maximum of -1 oC and 25 oC, respectively, and two rapid thermal variations (hourly and daily). Prior to deployment, lab ambient and cold water (ice water) sensor drift check with a certified NIST reference thermometer is required over a 24-hour period to ensure temperature deviations do not exceed 0.5 oC.
Challenges
The main challenges we will face are critters (bear) tampering with the sensor housing, and sensors dewatering during low flows. Special attention to stream hydro morphology conditions during field installation will reduce the chance of sensors becoming dewatered, and PVC housings will keep bear from tampering with equipment.
Pre Analysis Plan
The field stream temperature data collected from the sensors will support entire landscape SSN stream temperature modeling
Protocols
This project has not yet shared any protocols.
