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Abstract Rising chloride concentrations pose critical risks to freshwater stream ecosystems in temperate regions like the Delaware River Basin (DRB), USA, where winter deicer applications (i.e., road salt) are common. Increasing chloride concentrations have been documented in the region, but the extent to which chloride exceeds regulatory benchmarks remains unclear because detection of exceedances requires continuous monitoring of chloride (i.e., hourly or daily). A network of 82 non-tidal continuous specific conductance (SC) monitoring sites, spanning varied land use and geological settings, was established across the DRB to address this research need. First, a cluster analysis was conducted to group sites based on their watershed characteristics. Next, regression models for sites and clusters were developed to predict chloride using SC as a proxy. Finally, daily mean and hourly mean chloride concentration predictions were made for a three-year period (2020–2022) at the 82 study sites and analyzed to determine where and when chloride exceeded federal regulatory benchmarks. Chloride exceedance events occurred at 35% of the sites, all of which had 5% impervious cover or greater. Seasonally elevated chloride also was predicted at sites with less than 5% impervious cover. Variability in chloride patterns likely was influenced by deicer material types, winter weather patterns, geological settings, and gaps in data coverage. This study demonstrated the value of SC as a proxy for predicting chloride concentrations and showed how SC-chloride regression relationships vary across settings. More broadly, this study highlighted the value of continuous water quality monitoring to assess effects of freshwater salinization at a regional scale. 

ABSTRACT Impervious cover (IC) is a common metric for assessing the degree of urbanisation in watersheds. However, there are different methods for determining IC, and use of IC correlation with urban watershed response to hydrologic and geochemical inputs can be strongly influenced by the end members (IC below 10% and above 40%). The resolution of the imagery (e.g., 1 m vs. 30 m) used to measure IC can influence the estimate of IC, with differences up to 15% observed between these two resolutions for 21 watersheds along the east coast of the United States. The differences are greatest in the middle range between 10% and 40% IC. When using IC for correlation with urban watershed responses such as discharge flashiness or median solute concentrations, fits with R²between 0.4 and 0.78 were obtained when including end members of IC from 0% to 50%. However, when trying to distinguish behaviour between urban watersheds that fall in the middle ranges of IC, these same parameters do not correlate well with IC. Correlations fail significance tests, can switch direction, and fall below an R²of 0.1 without the end members of very low or very high IC. Because of improved accuracy, the finest resolution is preferred when available, and mixing IC estimation methods should be avoided. Furthermore, using regressions that include end members may not contribute to differentiating how IC in the 10%–40% range impacts hydrologic and geochemical responses in urban watersheds. Understanding this middle range of IC is important for comparing urban and suburban watersheds or planning watershed development to minimise impacts. 

Abstract A typical classroom exercise in hydrogeology is to develop a conceptual model of a contaminated site, identify groundwater flow direction(s), and predict the location and mass of a contaminant plume. This requires knowledge of key hydrogeological concepts and is highly visuospatial in nature. Among multiple discrete spatial thinking skills identified by cognitive science, the combination of visual penetrative ability and working in multiple frames of reference were identified to significantly predict performance on a hydrogeology task and showed that together with hydrogeology knowledge, these spatial thinking skills account for 49% of the variability on task performance. Seventy-two hydrogeology practitioners and students with varying levels of expertise were administered multiple spatial thinking tests and an assessment of hydrogeology knowledge before completing a hydrogeology task that was developed for the study. Using spatial thinking and knowledge test scores as predictor variables, a hierarchical regression analysis was conducted with performance on the hydrogeology task as the outcome variable. The resulting model predicts that at low levels of hydrogeology knowledge, the identified spatial thinking skills account for more than a 25% difference on the hydrogeology task. This study provides empirical evidence that visual penetrative ability and working in multiple frames of reference are important skills in hydrogeology; thus, instructors are encouraged to recognize that underdeveloped spatial thinking skills could present hurdles for students and that targeted spatial thinking training may yield positive results for both weak and strong spatial thinkers. 

Complex networks play a fundamental role in understanding phenomena from the collective behavior of spins, neural networks, and power grids to the spread of diseases. Topological phenomena in such networks have recently been exploited to preserve the response of systems in the presence of disorder. We propose and demonstrate topological structurally disordered systems with a modal structure that enhances nonlinear phenomena in the topological channels by inhibiting the ultrafast leakage of energy from edge modes to bulk modes. We present the construction of the graph and show that its dynamics enhances the topologically protected photon pair generation rate by an order of magnitude. Disordered nonlinear topological graphs will enable advanced quantum interconnects, efficient nonlinear sources, and light-based information processing for artificial intelligence. 

The propagation of spin waves in magnetically ordered systems has emerged as a potential means to shuttle quantum information over large distances. Conventionally, the arrival time of a spin wavepacket at a distance,d, is assumed to be determined by its group velocity,v_g. Here, we report time-resolved optical measurements of wavepacket propagation in the Kagome ferromagnet Fe₃Sn₂that demonstrate the arrival of spin information at times significantly less thand/v_g. We show that this spin wave “precursor” originates from the interaction of light with the unusual spectrum of magnetostatic modes in Fe₃Sn₂. Related effects may have far-reaching consequences toward realizing long-range, ultrafast spin wave transport in both ferromagnetic and antiferromagnetic systems. 

Rubidium atoms in a honeycomb optical lattice are driven through band structure singularities.