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Freshwater ecosystems reflect the landscapes in which they are embedded. The biogeochemistry of these systems is fundamentally linked to climate and watershed processes that control fluxes of water and the mobilization of energy and nutrients imprinting as variation in stream water chemistry. Disentangling these processes is difficult as they operate at multiple scales varying across space. We examined the relative importance of climate, soil, and watershed characteristics in mediating direct and indirect pathways that influence carbon and nitrogen availability in streams and rivers across spatial scales. Our data set comprised landscape and climatic variables and 37,995 chemistry measurements of carbon and nitrogen across 459 streams and rivers spanning the continental United States. Models explained a small fraction of carbon and nitrogen concentrations at the continental scale (25% and 6%, respectively) but 61% and 40%, respectively, at smaller spatial scales. Hydrometeorological processes were always important in mediating the availability of solutes but the mechanistic implications were variable across spatial scales. The influence of hydrometeorology on concentrations was often not direct, rather it was mediated by soil characteristics for carbon and watershed characteristics for nitrogen. For example, the seasonality of precipitation was often important in determining carbon concentrations through its influence on soil moisture at biogeoclimatic spatial scales, whereas it had a direct influence on concentrations at the continental scale. Our results suggest that hydrometeorological forcing remains the consistent driver of energy and nutrient concentrations but the mechanism influencing patterns varies across broad spatial scales.

 

Key Points We re‐evaluate equations proposed by Francis Hall to assess concentration‐discharge ( C ‐ Q ) relationships using newly available long‐term and high‐frequency data sets Across time steps we find that log‐log and log‐linear models perform equally well to describe C ‐ Q relationships Parametrization of storage‐discharge relationships via recession analyses provides additional insight to C ‐ Q relationships 

Stream water was collected at weekly to monthly intervals at 29 stream sites in New Hampshire (USA). Ten of the stream sites were instrumented with high‐frequency sensors. Twenty-one of the stream sites (including 5 sensor sites) are in the Lamprey River Hydrologic Observatory (LRHO; Wymore et al 2021) and two stream sites were nearby the LRHO. Groundwater was collected from two riparian well fields (JF, 14 wells and WHB, 13 wells). Wells were installed in 2004 and sampled monthly through May 2007, then quarterly until December 2009, after which a subset (JF, 6 and WHB, 5) was generally sampled quarterly. Stream and groundwater samples span a 17-year collection period and were analyzed for sodium, chloride and specific conductance. Methods and findings are described in the associated Limnology and Oceanography Letters manuscript. 

Processes that drive variability in catchment solute sourcing, transformation, and transport can be investigated using concentration–discharge (C–Q) relationships. These relationships reflect catchment and in‐stream processes operating across nested temporal scales, incorporating both short and long‐term patterns. Scientists can therefore leverage catchment‐scale C–Q datasets to identify and distinguish among the underlying meteorological, biological, and geological processes that drive solute export patterns from catchments and influence the shape of their respective C–Q relationships. We have synthesized current knowledge regarding the influence of biological, geological, and meteorological processes on C–Q patterns for various solute types across diel to decadal time scales. We identify cross‐scale linkages and tools researchers can use to explore these interactions across time scales. Finally, we identify knowledge gaps in our understanding of C–Q temporal dynamics as reflections of catchment and in‐stream processes. We also lay the foundation for developing an integrated approach to investigate cross‐scale linkages in the temporal dynamics of C–Q relationships, reflecting catchment biogeochemical processes and the effects of environmental change on water quality.

This article is categorized under:

Science of Water > Hydrological Processes

Science of Water > Water Quality

Science of Water > Water and Environmental Change

 

Elevated salt concentrations in streams draining developed watersheds are well documented, but the effects of hydrologic variability and the role of groundwater in surface water salinization are poorly understood. To characterize these effects, we use long‐term data (12–19 yr) and high‐frequency specific conductance (SPC) data collected from 13 streams across New Hampshire, USA. Concentration–discharge (C–Q) relationships for chloride (Cl⁻) derived from high‐frequency SPC showed distinct seasonal variability. Diluting behavior was common, but flushing behavior occurred in autumn and winter, suggesting that both groundwater and surface runoff contribute salts to streams. Long‐term data show that although extreme flood events initially reduced salt concentrations in groundwater and rural streams, concentrations recovered to preflood conditions in about a decade. Chronic Cl⁻exceedances occurred in urban streams during all seasons. This research suggests that variation in stream flow, extreme events and application of deicing agents play a role in freshwater salinization.

 

Ethical guidelines have provided a cornerstone for morally appropriate research on human or other vertebrate animal subjects since at least 1945. By contrast, although there are environmental impacts associated with all science research activities (including field, laboratory, and computational projects), no comprehensive guiding framework to determine environmentally responsible research practices has been proposed. Drawing from existing models within social, medical, and animal sciences, we propose a framework for explicitly incorporating environmentally focused ethics into scientific research. The Environmental Responsibility 5‐R Framework (ER⁵F) is centered around Recognition, Refinement, Reduction, Replacement, and Restoration. ER⁵F starts with Recognizing that research can have environmental consequences, while each subsequent “R” serves as an opportunity for acknowledging, evaluating, and mitigating the environmental impacts of scientific research. These R's include: Refining research questions, Reducing the resources and energy consumed, Replacing materials with sustainable options and altering methods, and in the case of field research, Restoring an environment to mitigate any harm done. By introducing this novel and approachable framework, we strive to promote enhanced awareness across the entire scientific community by encouraging researchers to recognize their responsibility and identify potential mitigation opportunities for the environmental consequences of their research activities. We affirm that in doing so, scientists can more effectively balance the dual goals of maximizing their novel research outputs while minimizing possible harm to the environment.

 

We examined how climate variability affects the mobilization of material from six watersheds. We analyzed one to seven years of high‐frequency sensor data from a temperate ecosystem and a tropical rainforest. We applied a windowed analysis to correlate concentration‐discharge (C‐Q) behavior with climate anomalies, providing insight into how hydrological and biogeochemical processes change in response to climate variability. Positive precipitation anomalies homogenized the C‐Q responses for dissolved organic matter, nitrate, specific conductance and turbidity, indicating that hydrological processes dominate the C‐Q signal and watersheds act as “conveyor belts” of material. In contrast, drier and warmer conditions led to C‐Q behavior associated with variation in solute concentration, suggesting that biogeochemical processes are a primary control on solute export and their response to flow. Results indicate that climate variability can move watersheds along a continuum from transporter‐to‐transformer of biologically active solutes and responses can potentially vary by biome.

 

High‐frequency in situ sensors have enabled researchers to measure solute concentrations at a time scale that captures the variability in stream discharge. We analyzed discrete samples and high‐frequency time series of solutes to characterize how nitrate (NO₃⁻) and fluorescent dissolved organic matter (fDOM; a proxy for dissolved organic carbon) respond to changes in discharge at annual and intra‐annual timescales across a stream network in New Hampshire, USA. NO₃⁻and fDOM exhibited highly variable concentration‐discharge (c‐Q) behavior at intra‐annual scales. Transport limitation, source limitation, and chemostatic behavior were observed to occur within and among years in all our study watersheds. Annual assessment of c‐Q misclassified streams 31% of the time, as the annual time step missed seasonal and event‐induced shifts in c‐Q dynamics. In some instances, anomalous events lasting less than 5% of the year determine the annual c‐Q behavior for a site. Catchment land use appeared to drive some of the variability among watersheds in c‐Q relationships and their temporal variability. Forested streams had highly variable NO₃⁻c‐Q behavior and streams draining watersheds with more development had greater variability in fDOM c‐Q behavior. Sample frequency impacts how hydrologic systems are characterized and extrapolating c‐Q behavior from discrete samples alone can bias interpretations of c‐Q dynamics and our understanding of solute transport.