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Climate change is rapidly altering hydrological processes and consequently the structure and functioning of Arctic ecosystems. Predicting how these alterations will shape biogeochemical responses in rivers remains a major challenge. We measured [C]arbon and [N]itrogen concentrations continuously from two Arctic watersheds capturing a wide range of flow conditions to assess understudied event‐scale C and N concentration‐discharge (C‐Q) behavior and post‐event recovery of stoichiometric conditions. The watersheds represent low‐gradient, tundra landscapes typical of the eastern Brooks Range on the North Slope of Alaska and are part of the Arctic Long‐Term Ecological Research sites: the Kuparuk River and Oksrukuyik Creek. In both watersheds, we deployed high‐frequency optical sensors to measure dissolved organic carbon (DOC), nitrate (), and total dissolved nitrogen (TDN) for five consecutive thaw seasons (2017–2021). Our analyses revealed a lag in DOC: stoichiometric recovery after a hydrologic perturbation: while DOC was consistently elevated after high flows, diluted during rainfall events and consequently, recovery in post‐event concentration was delayed. Conversely, the co‐enrichment of TDN at high flows, even in watersheds with relatively high N‐demand, represents a potential “leak” of hydrologically available organic N to downstream ecosystems. Our use of high‐frequency, long‐term optical sensors provides an improved method to estimate carbon and nutrient budgets and stoichiometric recovery behavior across event and seasonal timescales, enabling new insights and conceptualizations of a changing Arctic, such as assessing ecosystem disturbance and recovery across multiple timescales.

 

Across watershed science, two key variables emerge–streamflow and solute concentration–which serve as the basis for efforts ranging from basic watershed biogeochemistry research to policy decisions surrounding watershed management. However, we rarely account for how error in discharge (Q) impacts estimates of downstream nutrient loading. Here, we examined the impact of uncertainty in streamflow measurements on estimates of downstream nitrate export using publicly available data from the U.S. Geological Survey (USGS). We characterized how uncertainty in stage-discharge relationships impacts annual flux estimates across 70 USGS gages. Our results indicate the interquartile range of relative error in Q was 33% across these USGS sites. We documented a wide range in mean error in annual nitrate loads; some sites were underestimated (−105%), while predicted loads at other sites vastly overestimated (500%). Overall, any error in estimating Q leads to significant unpredictability of annual nutrient loads, which are often used as critical success benchmarks for governmental nutrient reduction strategies. Moreover, error in annual nitrate loads (as mass, kg) increases with mean Q; thus, as high flows become more unpredictable and intense under future climate change, error in estimates of downstream nutrient loading may also increase. Together, this indicates that error in Q may drastically influence our measures of water quality success and decrease our ability to accurately quantify progress towards algal bloom and ‘dead zone’ reduction.

 

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 

Key Points We compared tools for describing streamflow timeseries, including streamflow metrics, wavelet, and Fourier analysis Each method indicated streamflow data are structured: variability at short timescales is negatively correlated with long timescales Globally, dams were less correlated with streamflow regime than catchment size and climate were 

The interaction of climate change and increasing anthropogenic water withdrawals is anticipated to alter surface water availability and the transport of carbon (C), nitrogen (N), and phosphorus (P) in river networks. But how changes to river flow will alter the balance, or stoichiometry, of these fluxes is unknown. The Lower Flint River Basin (LFRB) is part of an interstate watershed relied upon by several million people for diverse ecosystem services, including seasonal crop irrigation, municipal drinking water access, and public recreation. Recently, increased water demand compounded with intensified droughts have caused historically perennial streams in the LFRB to cease flowing, increasing ecosystem vulnerability. Our objectives were to quantify how riverine dissolved C:N:P varies spatially and seasonally and determine how monthly stoichiometric fluxes varied with overall water availability in a major tributary of LFRB. We used a long‐term record (21–29 years) of solute water chemistry (dissolved organic carbon, nitrate/nitrite, ammonia, and soluble reactive phosphorus) paired with long‐term stream discharge data across six sites within a single LFRB watershed. We found spatial and seasonal differences in soluble nutrient concentrations and stoichiometry attributable to groundwater connections, the presence of a major floodplain wetland, and flow conditions. Further, we showed that water availability, as indicated by the Palmer Drought Severity Index (PDSI), strongly predicted stoichiometry with generally lower C:N and C:P and higher N:P fluxes during periods of low water availability (PDSI < −4). These patterns suggest there may be long‐term and significant changes to stream ecosystem function as water availability is being dramatically altered by human demand with consequential impacts on solute transport, in‐stream processing, and stoichiometric ratios.

 

Abstract Extreme events have increased in frequency globally, with a simultaneous surge in scientific interest about their ecological responses, particularly in sensitive freshwater, coastal, and marine ecosystems. We synthesized observational studies of extreme events in these aquatic ecosystems, finding that many studies do not use consistent definitions of extreme events. Furthermore, many studies do not capture ecological responses across the full spatial scale of the events. In contrast, sampling often extends across longer temporal scales than the event itself, highlighting the usefulness of long-term monitoring. Many ecological studies of extreme events measure biological responses but exclude chemical and physical responses, underscoring the need for integrative and multidisciplinary approaches. To advance extreme event research, we suggest prioritizing pre- and postevent data collection, including leveraging long-term monitoring; making intersite and cross-scale comparisons; adopting novel empirical and statistical approaches; and developing funding streams to support flexible and responsive data collection. 

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

 

While many instructors have reservations against Wikipedia use in academic settings, editing Wikipedia teaches students valuable writing, editing, and critical thinking skills. Wikipedia assignments align with the community of inquiry framework, which focuses on the elements needed for a successful online learning experience. We report on a faculty mentoring network, created by WikiProject Limnology and Oceanography, which helped 14 instructors with little to no prior experience implement a Wikipedia assignment in their classes. We found that Wikipedia assignments increase students’ motivation to produce high quality work and enhance their awareness of reliable scientific sources. Wikipedia assignments can be comparable to other writing assignments in length and complexity, but have a far wider audience than a traditional research paper. Participants in our mentoring network reported challenges with implementing this new type of assignment, and here, we share resources and solutions to those reported barriers.