Assessing Subjectivity in Environmental Sensor Data Post Processing via a Controlled Experiment

Collection of high resolution, in situ data using environmental sensors is common in hydrology and other environmental science domains. Sensors are subject to drift, fouling, and other factors that can affect the quality of the measurements and their subsequent use for scientific analyses. The process by which sensor data are reviewed to verify validity often requires making edits in post processing to generate approved datasets. This quality control process involves decisions by technicians, data managers, or data users on how to handle problematic data. In this study, an experiment was designed and conducted where multiple participants performed quality control post processing on the same datasets using consistent guidelines and tools to assess the effect of individual technician on the resulting datasets. The effect of technician experience and training was also assessed by conducting the same procedures with a group of novices unfamiliar with the data and compared results to those generated by a group of experienced technicians. Results showed greater variability between outcomes for experienced participants, which we attribute to novice participants\u27 reluctance to implement unfamiliar procedures that change data. The greatest variability between participants\u27 results was associated with calibration events for which users selected different methods and values by which to shift results. These corrections resulted in variability exceeding the range of manufacturer-reported sensor accuracy. To reduce quality control subjectivity and variability, we recommend that monitoring networks establish detailed quality control guidelines and consider a collaborative approach to quality control in which multiple technicians evaluate datasets prior to publication

Persistent Urban Influence on Surface Water Quality via Impacted Groundwater

Growing urban environments stress hydrologic systems and impact downstream water quality. We examined a third-order catchment that transitions from an undisturbed mountain environment into urban Salt Lake City, Utah. We performed synoptic surveys during a range of seasonal baseflow conditions and utilized multiple lines of evidence to identify mechanisms by which urbanization impacts water quality. Surface water chemistry did not change appreciably until several kilometers into the urban environment, where concentrations of solutes such as chloride and nitrate increase quickly in a gaining reach. Groundwater springs discharging in this gaining system demonstrate the role of contaminated baseflow from an aquifer in driving stream chemistry. Hydrometric and hydrochemical observations were used to estimate that the aquifer contains approximately 18% water sourced from the urban area. The carbon and nitrogen dynamics indicated the urban aquifer also serves as a biogeochemical reactor. The evidence of surface water–groundwater exchange on a spatial scale of kilometers and time scale of months to years suggests a need to evolve the hydrologic model of anthropogenic impacts to urban water quality to include exchange with the subsurface. This has implications on the space and time scales of water quality mitigation efforts