STICr: An open-source package and workflow for stream temperature, intermittency, and conductivity (STIC) data

Non-perennial streams constitute over half the world's stream miles but are not commonly included in streamflow monitoring networks. As a result, Stream Temperature, Intermittency, and Conductivity (STIC) loggers are widely used for characterizing flow presence or absence in non-perennial streams. To facilitate ‘FAIR’ (findable, accessible, interoperable, and reusable) stream intermittency science, we present an open-source R package, STICr, for processing STIC logger data. STICr includes functions to tidy data, calibrate sensors, classify data into wet/dry readings, and perform quality checks and validation. We also show a reproducible STICr-based workflow for an interdisciplinary project spanning multiple watersheds, years, and research groups. In South Fork Kings Creek (Konza Prairie, Kansas, USA), we show that stream intermittency is driven by the balance between monthly precipitation inputs, seasonal evapotranspiration fluxes, and underlying geology. Overall, STICr can be used to create FAIR stream intermittency data and enable advances in hydrologic and ecosystem science. • Stream intermittency datalogger output requires substantial processing. • The STICr R package provides functions to process, analyze, and QAQC this data. • We share a project-wide workflow for creating FAIR stream intermittency data. • In Kansas, STIC data reveal spatial stream intermittency response to geology. • Temporal stream intermittency linked to precipitation and ET at different time lags.