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We investigated biogeochemistry along a 12-m hyporheic mesocosm that allowed for controlled testing of seasonal and spatial water quality changes along a flowpath with fixed geometry and constant flow rate. Water quality profiles of oxygen, carbon, and nitrogen were measured at 1-m intervals along the mesocosm over multiple seasons. dissolved oxygen (DO) and temperature profiles were monitored on 18 dates between May 2019 through August 2020. Grab samples to monitor profiles of carbon, nitrogen, and various other solutes along the mesocosm were collected in December 2019 and August 2020 to provide more comprehensive biogeochemical analyses at time points when the dissolved oxygen (DO) and temperature profiles were at or near the maximum seasonal differences. Mesocosm monitoring ceased abruptly due to the Holiday Farm Fire, which burned from September through October 2020, cutting off personnel access and electrical power to the mesocosm facility. 

This project examined the interactions between stream water and subsurface sediment to quantify how these interactions influenced organic C respiration and dissolved inorganic C (DIC) production in the hyporheic zone of a high-gradient headwater mountain stream draining a forested catchment at the H. J. Andrews Experimental Forest, Oregon, USA. The study used six 2-m long hyporheic mesocosms which were packed with streambed sediment in the spring of 2016. The mesocosms are located at the Watershed 1 (WS1) stream gage and stream water from WS1 has been pumped through the mesocosms continuously since they were first packed through the end of (and beyond) this study in autumn of 2018. The mesocosms were designed around 1-m long 20-cm diameter aluminum pipe segments with sample ports located each meter along the flowpath through each mesocosm – thus sampling at the inlet, at 1 m, and at the outlet which represents the full 2-m long flow path. Sampling was conducted on seven dates between Oct 23 2016 and Aug 27 2018. On two of these dates, only background samples were collected. On the remaining 5 dates, sampling was designed around continuous-injection tracer experiments using both a conservative tracer (salt) and a reactive tracer (various dissolved organic substrates). For background sampling events, samples were generally only collected once. The tracer experiments involved 4 discreet sampling times: 1. pre-injection (under background conditions); 2. early plateau; 3. late plateau, and 4. post-injection (and in one injection experiment, a 5th sample at late-post-injection time). For each round of samples, the mesocosm water temperature, pH, EC, and DO were measured with sensors in a small flow-through cell. Then water samples were collected for laboratory analysis for both DOC and DIC. The median travel time of water through each pipe segment of the 2-m mesocosms was also calculated from the conservative tracer break-through curves. 

Accurate mapping of headwater streams and their flow status has important implications for understanding and managing water resources and land uses. However, accurate information is rare, especially in rugged, forested terrain. We developed a streamflow permanence classification model for forested lands in western Oregon using the latest light detection and ranging‐derived hydrography published in the National Hydrography Dataset. Models were trained using 2,518 flow/no flow field observations collected in late summer 2019–2021 across headwaters of 129 sub‐watersheds. The final model, the Western Oregon WeT DRy model, used Random Forest and 13 environmental covariates for classifying every 5‐m stream sub‐reach across 426 sub‐watersheds. The most important covariates were annual precipitation and drainage area. Model output included probabilities of late summer surface flow presence and were subsequently categorized into three streamflow permanence classes—Wet, Dry, and Ambiguous. Ambiguous denoted model probabilities and associated prediction intervals that extended over the 50% classification threshold between wet and dry. Model accuracy was 0.83 for sub‐watersheds that contained training data and decreased to 0.67 for sub‐watersheds that did not have observations of late summer surface flow. The model identified where predictions extrapolated beyond the domain characterized by the training data. The combination of spatially continuous estimates of late summer streamflow status along with uncertainty and extrapolation estimates provide critical information for strategic project planning and designing additional field data collection. 

Abstract Field studies of hyporheic exchange in mountain systems are often conducted using short study reaches and a limited number of observations. It is common practice to assume these study reaches represent hyporheic exchange at larger scales or different sites and to infer general relationships among potential causal mechanisms from the limited number of observations. However, these assumptions of representativeness are rarely tested. In this study, we develop numerical models from four segments of mountain streams in different geomorphologic settings and extract shorter reaches to test how representative exchange metrics are in shorter reaches compared to their reference segments. We also map the locations of the representative reaches to determine if a pattern exists based on location. Finally, we compare variance of these shorter within‐site reaches to 29 additional reaches across the same basin to understand the impacts of inferring causal mechanisms, for example, the expectation that wide and narrow valley bottoms will yield different hyporheic exchange patterns. Our results show that the location and length strategy of the study reach must be considered before assuming an exchange metric to be representative of anything other than the exact segment studied. Further, it is necessary to quantify within and between site variations before making causal inferences based on observable characteristics, such as valley width or stream morphology. Our findings have implications for future field practices and how those practices are translated into models.