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  1. The concurrent reduction in acid deposition and increase in precipitation impact stream solute dynamics in complex ways that make predictions of future water quality difficult. To understand how changes in acid deposition and precipitation have influenced dissolved organic carbon (DOC) and nitrogen (N) loading to streams, we investigated trends from 1991 to 2018 in stream concentrations (DOC, ~3,800 measurements), dissolved organic nitrogen (DON, ~1,160 measurements), and dissolved inorganic N (DIN, ~2,130 measurements) in a forested watershed in Vermont, USA. Our analysis included concentration-discharge (C-Q) relationships and Seasonal Mann-Kendall tests on long-term, flow-adjusted concentrations. To understand whether hydrologic flushing and changes in acid deposition influenced long-term patterns by liberating DOC and dissolved N from watershed soils, we measured their concentrations in the leachate of 108 topsoil cores of 5 cm diameter that we flushed with solutions simulating high and low acid deposition during four different seasons. Our results indicate that DOC and DON often co-varied in both the long-term stream dataset and the soil core experiment. Additionally, leachate from winter soil cores produced especially high concentrations of all three solutes. This seasonal signal was consistent with C-Q relation showing that organic materials (e.g., DOC and DON), which accumulate during winter, are flushed into streams during spring snowmelt. Acid deposition had opposite effects on DOC and DON compared to DIN in the soil core experiment. Low acid deposition solutions, which mimic present day precipitation, produced the highest DOC and DON leachate concentrations. Conversely, high acid deposition solutions generally produced the highest DIN leachate concentrations. These results are consistent with the increasing trend in stream DOC concentrations and generally decreasing trend in stream DIN we observed in the long-term data. These results suggest that the impact of acid deposition on the liberation of soil carbon (C) and N differed for DOC and DON vs. DIN, and these impacts were reflected in long-term stream chemistry patterns. As watersheds continue to recover from acid deposition, stream C:N ratios will likely continue to increase, with important consequences for stream metabolism and biogeochemical processes. 
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    Free, publicly-accessible full text available March 13, 2024
  2. Abstract Winters in snow-covered regions have warmed, likely shifting the timing and magnitude of nutrient export, leading to unquantified changes in water quality. Intermittent, seasonal, and permanent snow covers more than half of the global land surface. Warming has reduced the cold conditions that limit winter runoff and nutrient transport, while cold season snowmelt, the amount of winter precipitation falling as rain, and rain-on-snow have increased. We used existing geospatial datasets (rain-on-snow frequency overlain on nitrogen and phosphorous inventories) to identify areas of the contiguous United States (US) where water quality could be threatened by this change. Next, to illustrate the potential export impacts of these events, we examined flow and turbidity data from a large regional rain-on-snow event in the United States’ largest river basin, the Mississippi River Basin. We show that rain-on-snow, a major flood-generating mechanism for large areas of the globe (Berghuijs et al 2019 Water Resour. Res. 55 4582–93; Berghuijs et al 2016 Geophys. Res. Lett. 43 4382–90), affects 53% of the contiguous US and puts 50% of US nitrogen and phosphorus pools (43% of the contiguous US) at risk of export to groundwater and surface water. Further, the 2019 rain-on-snow event in the Mississippi River Basin demonstrates that these events could have large, cascading impacts on winter nutrient transport. We suggest that the assumption of low wintertime discharge and nutrient transport in historically snow-covered regions no longer holds. Critically, however, we lack sufficient data to accurately measure and predict these episodic and potentially large wintertime nutrient export events at regional to continental scales. 
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  3. Abstract

    Oxygen (O2) regulates soil reduction‐oxidation processes and therefore modulates biogeochemical cycles. The difficulties associated with accurately characterizing soil O2variability have prompted the use of soil moisture as a proxy for O2, as O2diffusion into soil water is much slower than in soil air. The use of soil moisture alone as a proxy measurement for O2could result in inaccurate O2estimations. For example, O2may remain high during cool months when soil respiration rates are low. We analyzed high‐frequency sensor data (e.g., soil moisture, CO2, gas‐phase soil pore O2) with a machine learning technique, the Self‐Organizing Map, to pinpoint suites of soil conditions associated with contrasting O2regimes. At two riparian sites in northern Vermont, we found that O2levels varied seasonally, and with soil moisture. For example, 47% of low O2levels were associated with wet and cool soil conditions, whereas 32% were associated with dry and warm conditions. Contrastingly, the majority (62%) of high O2conditions occurred under dry and warm conditions. High soil moisture levels did not always lead to low O2, as 38% of high O2values occurred under wet and cool conditions. Our results highlight challenges with predicting soil O2solely based on water content, as variable combinations of soil and hydrologic conditions can complicate the relationship between water content and O2. This indicates that process‐based ecosystem and denitrification models that rely solely on soil moisture to estimate O2may need to incorporate other site and climate‐specific drivers to accurately predict soil O2.

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  4. null (Ed.)
    Understanding and predicting catchment responses to a regional disturbance is difficult because catchments are spatially heterogeneous systems that exhibit unique moderating characteristics. Changes in precipitation composition in the Northeastern U.S. is one prominent example, where reduction in wet and dry deposition is hypothesized to have caused increased dissolved organic carbon (DOC) export from many northern hemisphere forested catchments; however, findings from different locations contradict each other. Using shifts in acid deposition as a test case, we illustrate an iterative “process and pattern” approach to investigate the role of catchment characteristics in modulating the steam DOC response. We use a novel dataset that integrates regional and catchment-scale atmospheric deposition data, catchment characteristics and co-located stream Q and stream chemistry data. We use these data to investigate opportunities and limitations of a pattern-to-process approach where we explore regional patterns of reduced acid deposition, catchment characteristics and stream DOC response and specific soil processes at select locations. For pattern investigation, we quantify long-term trends of flow-adjusted DOC concentrations in stream water, along with wet deposition trends in sulfate, for USGS headwater catchments using Seasonal Kendall tests and then compare trend results to catchment attributes. Our investigation of climatic, topographic, and hydrologic catchment attributes vs. directionality of DOC trends suggests soil depth and catchment connectivity as possible modulating factors for DOC concentrations. This informed our process-to-pattern investigation, in which we experimentally simulated increased and decreased acid deposition on soil cores from catchments of contrasting long-term DOC response [Sleepers River Research Watershed (SRRW) for long-term increases in DOC and the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO) for long-term decreases in DOC]. SRRW soils generally released more DOC than SSHCZO soils and losses into recovery solutions were higher. Scanning electron microscope imaging indicates a significant DOC contribution from destabilizing soil aggregates mostly from hydrologically disconnected landscape positions. Results from this work illustrate the value of an iterative process and pattern approach to understand catchment-scale response to regional disturbance and suggest opportunities for further investigations. 
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  5. null (Ed.)
    Stream drying and wildfire are projected to increase with climate change in the western United States, and both are likely to impact stream chemistry patterns and processes. To investigate drying and wildfire effects on stream chemistry (carbon, nutrients, anions, cations, and isotopes), we examined seasonal drying in two intermittent streams in southwestern Idaho, one stream that was unburned and one that burned 8 months prior to our study period. During the seasonal recession following snowmelt, we hypothesized that spatiotemporal patterns of stream chemistry would change due to increased evaporation, groundwater dominance, and autochthonous carbon production. With increased nutrients and reduced canopy cover, we expected greater shifts in the burned stream. To capture spatial chemistry patterns, we sampled surface water for a suite of analytes along the length of each stream with a high spatial scope (50-m sampling along ~2,500 m). To capture temporal variation, we sampled each stream in April (higher flow), May, and June (lower flow) in 2016. Seasonal patterns and processes influencing stream chemistry were generally similar in both streams, but some were amplified in the burned stream. Mean dissolved inorganic carbon (DIC) concentrations increased with drying by 22% in the unburned and by 300% in the burned stream. In contrast, mean total nitrogen (TN) concentrations decreased in both streams, with a 16% TN decrease in the unburned stream and a 500% TN decrease (mostly nitrate) in the burned stream. Contrary to expectations, dissolved organic carbon (DOC) concentrations varied more in space than in time. In addition, we found the streams did not become more evaporative relative to the Local Meteoric Water Line (LMWL) and we found weak evidence for evapoconcentration with drying. However, consistent with our expectations, strontium-DIC ratios indicated stream water shifted toward groundwater-dominance, especially in the burned stream. Fluorescence and absorbance measurements showed considerable spatial variation in DOC sourcing each month in both streams, and mean values suggested a temporal shift from allochthonous toward autochthonous carbon sources in the burned stream. Our findings suggest that the effects of fire may magnify some chemistry patterns but not the biophysical controls that we tested with stream drying. 
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  6. Abstract

    Research at long‐term catchment monitoring sites has generated a great volume, variety, and velocity of data for analysis of stream water chemistry dynamics. To harness the potential of these big data and extract patterns that are indicative of underlying functional relationships, machine learning tools have advantages over traditional statistical methods, and are increasingly being applied for dimension reduction, feature extraction, and trend identification. Still, as examples of complex systems, catchments are characterized by multivariate factor interactions and equifinality that are not easily identified by most machine‐learning methods. Using dissolved organic carbon (DOC) dynamics as an illustration, we applied a new evolutionary algorithm (EA) to extract geologic, topographic, meteorologic, hydrologic, and land use attributes that were correlated to mean stream DOC concentration in forested catchments distributed across the continental United States. The EA reduced dimensionality of our attribute dataset to identify the combination of factors, and their specific value ranges, that interacted to drive membership in High or Low mean DOC clusters. High mean DOC concentrations were associated with two distinct geographic locations of variable climatic and vegetative conditions, indicating equifinality. Our findings underscore the importance of critical zone structure in mediating hydrological and biogeochemical processes to govern DOC dynamics at the catchment scale. This multi‐scale, pattern‐to‐process approach is being applied to refine hypotheses for process‐based modeling of DOC dynamics in forested headwater streams at catchment to site scales.

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  7. Abstract

    The shallow and deep hypothesis suggests that stream concentration‐discharge (CQ) relationships are shaped by distinct source waters from different depths. Under this hypothesis, baseflows are typically dominated by groundwater and mostly reflect groundwater chemistry, whereas high flows are typically dominated by shallow soil water and mostly reflect soil water chemistry. Aspects of this hypothesis draw on applications like end member mixing analyses and hydrograph separation, yet direct data support for the hypothesis remains scarce. This work tests the shallow and deep hypothesis using co‐located measurements of soil water, groundwater, and streamwater chemistry at two intensively monitored sites, the W‐9 catchment at Sleepers River (Vermont, United States) and the Hafren catchment at Plynlimon (Wales). At both sites, depth profiles of subsurface water chemistry and stream CQ relationships for the 10 solutes analyzed are broadly consistent with the hypothesis. Solutes that are more abundant at depth (e.g., calcium) exhibit dilution patterns (concentration decreases with increasing discharge). Conversely, solutes enriched in shallow soils (e.g., nitrate) generally exhibit flushing patterns (concentration increases with increasing discharge). The hypothesis may hold broadly true for catchments that share such biogeochemical stratifications in the subsurface. Soil water and groundwater chemistries were estimated from high‐ and low‐flow stream chemistries with average relative errors ranging from 24% to 82%. This indicates that streams mirror subsurface waters: stream chemistry can be used to infer scarcely measured subsurface water chemistry, especially where there are distinct shallow and deep end members.

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