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Headwater streams are control points for carbon dioxide (CO₂) emissions to the atmosphere, with relative contributions to CO₂emission fluxes from lateral groundwater inputs widely assumed to overwhelm those from in‐stream metabolic processes. We analyzed continuous measurements of stream dissolved CO₂and oxygen (O₂) concentrations during spring and early summer in two Mediterranean headwater streams from which we evaluated the contribution of in‐stream net ecosystem production (NEP) to CO₂emission. The two streams exhibited contrasting hydrological regimes: one was non‐perennial with relatively small groundwater inflows, while the other was perennial and received significant lateral groundwater inputs. The non‐perennial stream exhibited strong inverse coupling between instantaneous and daily CO₂and O₂concentrations, and a strong correlation between aerobic ecosystem respiration (ER) and gross primary production (GPP) despite persistent negative NEP. At the perennial stream, the CO₂–O₂relationship varied largely over time, ER and GPP were uncorrelated, and NEP, which was consistently negative, increased with increasing temperature. Mean NEP contribution to CO₂emission was 51% and 57% at the non‐perennial and perennial stream, respectively. Although these proportions varied with assumptions about metabolic stoichiometry and groundwater CO₂concentration, in‐stream CO₂production consistently and substantially contributed to total atmospheric CO₂flux in both streams. We conclude that in‐stream metabolism can be more important for driving C cycling in some headwater streams than previously assumed.

 

The Tracer Additions for Spiraling Curve Characterization (TASCC) model has been rapidly adopted to interpret in‐stream nutrient spiraling metrics over a range of concentrations from breakthrough curves (BTCs) obtained during pulse solute injection experiments. TASCC analyses often identify hysteresis in the relationship between spiraling metrics and concentration as nutrient concentration in BTCs rises and falls. The mechanisms behind these hysteresis patterns have yet to be determined. We hypothesized that differences in the time a solute is exposed to bioactive environments (i.e., biophysical opportunity) between the rising and falling limbs of BTCs causes hysteresis in TASCCs. We tested this hypothesis using nitrate data from Elkhorn Creek (CO, USA) combined with a process‐based particle‐tracking model representing travel times and transformations along each flow path in the water column and hyporheic zone, from which the bioactive zone comprised only a thin superficial layer. In‐stream nitrate uptake was controlled by hyporheic exchange and the cumulative time nitrate spend in the bioactive layer. This bioactive residence time generally increased from the rising to the falling limb of the BTC, systematically generating hysteresis in the TASCC curves. Hysteresis decreased when nutrient uptake primarily occurred in the water column compared to the hyporheic zone, and with increasing the distance between the injection and sampling points. Hysteresis increased with the depth of the hyporheic bioactive layer. Our results emphasize that good characterization of spatial heterogeneity of surface‐subsurface flow paths and bioactive hot spots within streams is essential to understanding the mechanisms of in‐stream nutrient uptake.

 

Abstract. A comprehensive set of measurements and calculated metricsdescribing physical, chemical, and biological conditions in the rivercorridor is presented. These data were collected in a catchment-wide,synoptic campaign in the H. J. Andrews ExperimentalForest (Cascade Mountains, Oregon, USA) in summer 2016 during low-dischargeconditions. Extensive characterization of 62 sites including surface water,hyporheic water, and streambed sediment was conducted spanning 1st- through5th-order reaches in the river network. The objective of the sample designand data acquisition was to generate a novel data set to support scaling ofriver corridor processes across varying flows and morphologic forms presentin a river network. The data are available at https://doi.org/10.4211/hs.f4484e0703f743c696c2e1f209abb842 (Ward, 2019). 

Abstract. Although most field and modeling studies of river corridorexchange have been conducted at scales ranging from tens to hundreds of meters,results of these studies are used to predict their ecological andhydrological influences at the scale of river networks. Further complicatingprediction, exchanges are expected to vary with hydrologic forcing and thelocal geomorphic setting. While we desire predictive power, we lack acomplete spatiotemporal relationship relating discharge to the variation ingeologic setting and hydrologic forcing that is expected across a riverbasin. Indeed, the conceptual model of Wondzell (2011) predicts systematicvariation in river corridor exchange as a function of (1) variation inbaseflow over time at a fixed location, (2) variation in discharge withlocation in the river network, and (3) local geomorphic setting. To testthis conceptual model we conducted more than 60 solute tracer studiesincluding a synoptic campaign in the 5th-order river network of the H. J. Andrews Experimental Forest (Oregon, USA) and replicate-in-time experimentsin four watersheds. We interpret the data using a series of metricsdescribing river corridor exchange and solute transport, testing forconsistent direction and magnitude of relationships relating these metricsto discharge and local geomorphic setting. We confirmed systematic decreasein river corridor exchange space through the river networks, from headwatersto the larger main stem. However, we did not find systematic variation withchanges in discharge through time or with local geomorphic setting. Whileinterpretation of our results is complicated by problems with the analyticalmethods, the results are sufficiently robust for us to conclude that space-for-timeand time-for-space substitutions are not appropriate in our study system.Finally, we suggest two strategies that will improve the interpretability oftracer test results and help the hyporheic community develop robust datasets that will enable comparisons across multiple sites and/or dischargeconditions.