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The Upper Clark Fork River (UCFR) Long Term Research in Environmental Biology (LTREB) umbrella monitoring project generating these data is conducted separately and complementarily to the 200-million-dollar (USD) superfund project for ecological restoration of the UCFR, associated tributaries, and head water streams including Silver Bow and Warm Springs Creeks. Restoration along the UCFR in western Montana includes removal of metal-laden floodplain soils, lowering of the floodplain to its original elevation, and re-vegetation of over 70 km of the river’s floodplain closest to contaminant sources. The UCFR LTREB project includes bi-weekly water quality monitoring across the first 200 km of the river and its major tributaries along a gradient of heavy metal contamination associated with historic mining. Monitoring includes inorganic phosphorus and nitrogen concentrations, biotic standing stocks, and dissolved and whole-water heavy metal concentrations. The monitoring program began in 2017 with funding extended through 2028. The original analytical intent for these data was to assess the response of river dissolved organic carbon to the floodplain restoration. Data are Aurora Total Organic Carbon combustion analyses of the concentration of organic carbon dissolved in filtered samples of well-mixed river thalweg water. Data are from the 2021 water year (1 Oct 2020 to 30 Sep 2021) from samples collected on the Upper Clark Fork River (USGS HUC 17010201) at project sites distributed along the river from the vicinity of Anaconda to Missoula, Montana, USA. 

Abstract Rivers efficiently collect, process, and transport terrestrial‐derived carbon. River ecosystem metabolism is the primary mechanism for processing carbon. Diel cycles of dissolved oxygen (DO) have been used for decades to infer river ecosystem metabolic rates, which are routinely used to predict metabolism of carbon dioxide (CO₂) with uncertainties of the assumed stoichiometry ranging by a factor of 4. Dissolved inorganic carbon (DIC) has been less used to directly infer metabolism because it is more difficult to quantify, involves the complexity of inorganic carbon speciation, and as shown in this study, likely requires a two‐station approach. Here, we developed DIC metabolism models using single‐ and two‐station approaches. We compared metabolism estimates based on simultaneous DO and DIC monitoring in the Upper Clark Fork River (USA), which also allowed us to estimate ecosystem‐level photosynthetic and respiratory quotients (PQ_Eand RQ_E). We observed that metabolism estimates from DIC varied more between single‐ and two‐station approaches than estimates from DO. Due to carbonate buffering, CO₂is slower to equilibrate with the atmosphere compared to DO, likely incorporating a longer distance of upstream heterogeneity. Reach‐averaged PQ_Eranged from 1.5 to 2.0, while RQ_Eranged from 0.8 to 1.5. Gross primary production from DO was larger than that from DIC, as was net ecosystem production by . The river was autotrophic based on DO but heterotrophic based on DIC, complicating our understanding of how metabolism regulated CO₂production. We suggest future studies simultaneously model metabolism from DO and DIC to understand carbon processing in rivers. 

Abstract Total alkalinity (A_T) is an important parameter in the study of aquatic biogeochemical cycles, chemical speciation modeling, and many other important fundamental and anthropogenic (e.g., industrial) processes. We know little about its short‐term variability, however, because studies are based on traditional bottle sampling typically with coarse temporal resolution. In this work, an autonomous A_Tsensor, named the Submersible Autonomous Moored Instrument for Alkalinity (SAMI‐alk), was tested for freshwater applications. A comprehensive evaluation was conducted in the laboratory using freshwater standards. The results demonstrated excellent precision and accuracy (± 0.1%–0.4%) over the A_Trange from 800 to 3000 μmol L⁻¹. The system had no drift over an 8 d test and also demonstrated limited sensitivity to variations in temperature and ionic strength. Three SAMI‐alks were deployed for 23 d in the Clark Fork River, Montana, with a suite of other sensors. Compared to discrete samples, in situ accuracy for the three instruments were within 10–20 μmol L⁻¹(0.3–0.6%), indicating good performance considering the challenges of in situ measurements in a high sediment, high biofouling riverine environment with large and rapid changes in temperature. These data reveal the complex A_Tdynamics that are typically missed by coarse sampling. We observed A_Tdiel cycles as large as 60–80 μmol L⁻¹, as well as a rapid change caused by a runoff event. Significant errors in inorganic carbon system modeling result if these short‐term variations are not considered. This study demonstrates both the feasibility of the technology and importance of high‐resolution A_Tmeasurements.