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Freshwater salinization syndrome (FSS) refers to the suite of interactive effects of salt ions on degradation of physical, biological,and social systems. Best management practices (BMPs), which are methods to effectively reduce runoff and nonpoint source pollution (stormwater, nutrients, sediments), do not typically consider management of salt pollution. We investigate impacts of FSS on mobilization of salts, nutrients, and metals in urban streams and storm water BMPs by analyzing original data on concentrations and fluxes of salts, nutrients, and metals from 7 urban watersheds in the Mid-Atlantic USA and synthesizing literature data. We also explore future critical research needs through a survey of practitioners and scientists. Our original data show 1) sharp pulses in concentrations of salt ions and metals in urban streams directly following both road salt events and stream restoration construction (e.g.,similar to the way concentrations increase during other soil disturbance activities); 2) sharp declines in pH (acidification) in response to road salt applications because of mobilization of H+ from soil exchange sites by Na+; 3) sharp increases inorganic matter from microbial and algal sources (based on fluorescence spectroscopy) in response to road salt applications, likely because of lysing cells and changes insolubility; 4) substantial retention (~30–40%) of Na+more »in stormwater BMP sediments and floodplains in response to salinization; 5) increased ion exchange and mobilization of diverse salt ions (Na+, Ca2+, K+, Mg2+), nutrients(N, P), and trace metals(Cu, Sr) from stormwater BMPs and restored streams in response to FSS; 6) downstream increasing loads ofCl–, SO42–, Br–, F–,andI–along flowpaths through urbanstreams and P release from urban stormwater BMPs in response to salinization; and 7)a substantial annual reduction (>50%) in Na+concentrations in an urban stream when road salt applications were dramatically reduced, which suggests potential for ecosystem recovery. We compare our original results with published metrics of contaminant retention and release across a broad range of stormwater BMPs from North America and Europe.Overall, urban streams and stormwater BMPs consistently retain Na+ and Cl–but mobilize multiple contaminants based on salt types and salinity levels. Finally, we present our top 10 research questions regarding FSS impacts on urban streams and stormwater BMPs. Reducing diverse chemical cocktails of contaminants mobilized by freshwater salinization is a priority for effectively and holistically restoring urban waters.« less

Stream restoration is a popular approach for managing nitrogen (N) in degraded, flashy urban streams. Here, we investigated the long-term effects of stream restoration involving floodplain reconnection on riparian and in-stream N transport and transformation in an urban stream in the Chesapeake Bay watershed. We examined relationships between hydrology, chemistry, and biology using a Before/After-Control/Impact (BACI) study design to determine how hydrologic flashiness, nitrate (NO₃⁻) concentrations (mg/L), and N flux, both NO₃⁻and total N (kg/yr), changed after the restoration and floodplain hydrologic reconnection to its stream channel. We examined two independent surface water and groundwater data sets (EPA and USGS) collected from 2002–2012 at our study sites in the Minebank Run watershed. Restoration was completed during 2004 and 2005. Afterward, the monthly hydrologic flashiness index, based on mean monthly discharge, decreased over time from 2002 and 2008. However, from 2008–2012 hydrologic flashiness returned to pre-restoration levels. Based on the EPA data set, NO₃⁻concentration in groundwater and surface water was significantly less after restoration while the control site showed no change. DOC and NO₃⁻were negatively related before and after restoration suggesting C limitation of N transformations. Long-term trends in surface water NO₃⁻concentrations based on USGS surface water data showed downwardmore »trends after restoration at both the restored and control sites, whereas specific conductance showed no trend. Comparisons of NO₃⁻concentrations with Cl⁻concentrations and specific conductance in both ground and surface waters suggested that NO₃⁻reduction after restoration was not due to dilution or load reductions from the watershed. Modeled NO₃⁻flux decreased post restoration over time but the rate of decrease was reduced likely due to failure of restoration features that facilitated N transformations. Groundwater NO₃⁻concentrations varied among stream features suggesting that some engineered features may be functionally better at creating optimal conditions for N retention. However, some engineered features eroded and failed post restoration thereby reducing efficacy of the stream restoration to reduce flashiness and NO₃⁻flux. N management via stream restoration will be most effective where flashiness can be reduced and DOC made available for denitrifiers. Stream restoration may be an important component of holistic watershed management including stormwater management and nutrient source control if stream restoration and floodplain reconnection can be done in a manner to resist the erosive effects of large storm events that can degrade streams to pre-restoration conditions. Long-term evolution of water quality functions in response to degradation of restored stream channels and floodplains from urban stressors and storms over time warrants further study, however.

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Increasing trends in base cations, pH, and salinity of freshwaters have been documented in US streams over 50 years. These patterns, collectively known as freshwater salinization syndrome (FSS), are driven by multiple processes, including applications of road salt and human-accelerated weathering of impervious surfaces, reductions in acid rain, and other anthropogenic legacies of change. FSS mobilizes chemical cocktails of distinct elemental mixtures via ion exchange, and other biogeochemical processes. We analyzed impacts of FSS on streamwater chemistry across five urban watersheds in the Baltimore-Washington, USA metropolitan region. Through combined grab-sampling and high-frequency monitoring by USGS sensors, regression relationships were developed among specific conductance and major ion and trace metal concentrations. These linear relationships were statistically significant in most of the urban streams (e.g.R²= 0.62 and 0.43 for Mn and Cu, respectively), and showed that specific conductance could be used as a proxy to predict concentrations of major ions and trace metals. Major ions and trace metals analyzed via linear regression and principal component analysis showed co-mobilization (i.e. correlations among combinations of specific conductance (SC), Mn, Cu, Sr²⁺, and all base cations during certain times of year and hydrologic conditions). Co-mobilization of metals and base cations was strongest during peakmore »snow events but could continue over 24 h after SC peaked, suggesting ongoing cation exchange in soils and stream sediments. Mn and Cu concentrations predicted from SC as a proxy indicated acceptable goodness of fit for predictedvs.observed values (Nash–Sutcliffe efficiency > 0.28). Metals concentrations remained elevated for days after SC decreased following snowstorms, suggesting lag times and continued mobilization after road salt use. High-frequency sensor monitoring and proxies associated with FSS may help better predict contaminant pulses and contaminant exceedances in response to salinization and impacts on aquatic life, infrastructure, and drinking water.

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We study the linear subspace fitting problem in the overparameterized setting, where the estimated subspace can perfectly interpolate the training examples. Our scope includes the least-squares solutions to subspace fitting tasks with varying levels of supervision in the training data (i.e., the proportion of input-output examples of the desired low-dimensional mapping) and orthonormality of the vectors defining the learned operator. This flexible family of problems connects standard, unsupervised subspace fitting that enforces strict orthonormality with a corresponding regression task that is fully supervised and does not constrain the linear operator structure. This class of problems is defined over a supervision-orthonormality plane, where each coordinate induces a problem instance with a unique pair of supervision level and softness of orthonormality constraints. We explore this plane and show that the generalization errors of the corresponding subspace fitting problems follow double descent trends as the settings become more supervised and less orthonormally constrained.