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High degrees of spatial heterogeneity in hydrologic systems pose a major barrier for their protection and remediation. Dissolved and particulate contaminants are mixed and retained over timescales ranging from seconds to years due to their interactions with these structural heterogeneities. Over the last two decades, a new class of models has demonstrated its capacity to describe observed ‘anomalous transport’ behavior that is ubiquitous to nearly all flowing waters. The promise of these models lies in their potential for predicting transport using minimal parameters, while remaining faithful to the underlying complexity of the system. In this review, we highlight recent experimental studies that have improved our understanding of the structural controls of anomalous transport, as well as modeling studies that use these new insights to better predict contaminant fate. 

With the increased use of nanoparticles (NPs) in consumer, food, and pharmaceutical products, their eventual release into streams is inevitable. Critical factors affecting the transport of NPs in streams are the hyporheic exchange between the water column and porous streambed substrate and the interaction with biofilms. In this study, the transport behavior of two titanium dioxide NPs – catalytic- (P90) and food-grade (E171) – was evaluated in four field streams lined with different streambed substrate sizes for varying seasonal biofilm conditions. When biofilm growth was minimal, NP retention in the streams increased with increasing substrate size due to increased hyporheic exchange and subsequent physical and chemical interactions between the NPs and substrate. For all streams, the average mass recovery at the 40 m sampling point for E171 and P90 was 44 ± 8.7% and 16 ± 8.0%, respectively. The greater mobility of E171 was due to the inherent presence of negatively charged surface phosphates that reduced aggregation and decreased its interaction with the substrate. When biofilms were thriving in the streams the average mass recovery at 40 m for both NPs decreased significantly (E171 = 5.8 ± 7.3%, P = 0.0017; P90 = 2.4 ± 0.7%, P = 0.041), and the mass recovery difference between the two NPs became insignificant ( P = 0.38). 

A growing empirical literature associates climate anomalies with increased risk of violent conflict. This association has been portrayed as a bellwether of future societal instability as the frequency and intensity of extreme weather events are predicted to increase. This paper investigates the theoretical foundation of this claim. A seminal microeconomic model of opportunity costs—a mechanism often thought to drive climate–conflict relationships—is extended by considering realistic changes in the distribution of climate-dependent agricultural income. Results advise caution in using empirical associations between short-run climate anomalies and conflicts to predict the effect of sustained shifts in climate regimes: Although war occurs in bad years, conflict may decrease if agents expect more frequent bad years. Theory suggests a nonmonotonic relation between climate variability and conflict that emerges as agents adapt and adjust their behavior to the new income distribution. We identify 3 measurable statistics of the income distribution that are each unambiguously associated with conflict likelihood. Jointly, these statistics offer a unique signature to distinguish opportunity costs from competing mechanisms that may relate climate anomalies to conflict.

 

In this paper, we develop and validate a rigorous modeling framework, based on Duhamel's Theorem, for the unsteady one‐dimensional vertical transport of a solute across a flat sediment‐water interface (SWI) and through the benthic biolayer of a turbulent stream. The modeling framework is novel in capturing the two‐way coupling between evolving solute concentrations above and below the SWI and in allowing for a depth‐varying diffusivity. Three diffusivity profiles within the sediment (constant, exponentially decaying, and a hybrid model) are evaluated against an extensive set of previously published laboratory measurements of turbulent mass transfer across the SWI. The exponential diffusivity profile best represents experimental observations and its reference diffusivity scales with the permeability Reynolds number, a dimensionless measure of turbulence at the SWI. The depth over which turbulence‐enhanced diffusivity decays is of the order of centimeters and comparable to the thickness of the benthic biolayer. Thus, turbulent mixing across the SWI may serve as a universal transport mechanism, supplying the nutrient and energy fluxes needed to sustain microbial growth, and nutrient processing, in the benthic biolayer of stream and coastal sediments.

 

Assessments of riverine ecosystem health and water quality require knowledge of how headwater streams transport and transform nutrients. Estimates of nutrient demand at the watershed scale are commonly inferred from reach‐scale solute injections, which are typically reported as uptake velocities (v_f). Multiple interacting processes controlv_f, making it challenging to predict howv_fresponds to physical changes in the stream. In this study, we linkv_fto a continuous time random walk model to quantify howv_fis controlled by in‐stream (velocity, dispersion, and benthic reaction) and hyporheic processes (exchange rate, residence times, and hyporheic reaction). We fit the model to conservative (NaCl) and nitrate (NO₃⁻‐N) pulse tracer injections in unshaded replicate streams at the Notre Dame Linked Experimental Ecosystem Facility, which differed only in substrate size and distribution. Experiments were conducted over the first 25 days of biofilm colonization to examine how the interaction between substrate type and biofilm growth influenced modeled processes andv_f. Model fits of benthic reaction rates were ∼8× greater than hyporheic reaction rates for all experiments and did not vary with substrate type or over time. High benthic reactivity was associated with filamentous green algae coverage on the streambed, which dominated total algal biomass. Finally,v_fwas most sensitive to benthic reaction rate and stream velocity, and sensitivity varied with stream conditions due to its nonlinear dependence on all modeled processes. Together, these results demonstrate how reach‐scale nutrient demand reflects the relative contributions of biotic and abiotic processes in the benthic layer and the hyporheic zone.

 

Abstract. A comprehensive set of measurements and calculated metricsdescribing physical, chemical, and biological conditions in the rivercorridor is presented. These data were collected in a catchment-wide,synoptic campaign in the H. J. Andrews ExperimentalForest (Cascade Mountains, Oregon, USA) in summer 2016 during low-dischargeconditions. Extensive characterization of 62 sites including surface water,hyporheic water, and streambed sediment was conducted spanning 1st- through5th-order reaches in the river network. The objective of the sample designand data acquisition was to generate a novel data set to support scaling ofriver corridor processes across varying flows and morphologic forms presentin a river network. The data are available at https://doi.org/10.4211/hs.f4484e0703f743c696c2e1f209abb842 (Ward, 2019). 

Abstract. Although most field and modeling studies of river corridorexchange have been conducted at scales ranging from tens to hundreds of meters,results of these studies are used to predict their ecological andhydrological influences at the scale of river networks. Further complicatingprediction, exchanges are expected to vary with hydrologic forcing and thelocal geomorphic setting. While we desire predictive power, we lack acomplete spatiotemporal relationship relating discharge to the variation ingeologic setting and hydrologic forcing that is expected across a riverbasin. Indeed, the conceptual model of Wondzell (2011) predicts systematicvariation in river corridor exchange as a function of (1) variation inbaseflow over time at a fixed location, (2) variation in discharge withlocation in the river network, and (3) local geomorphic setting. To testthis conceptual model we conducted more than 60 solute tracer studiesincluding a synoptic campaign in the 5th-order river network of the H. J. Andrews Experimental Forest (Oregon, USA) and replicate-in-time experimentsin four watersheds. We interpret the data using a series of metricsdescribing river corridor exchange and solute transport, testing forconsistent direction and magnitude of relationships relating these metricsto discharge and local geomorphic setting. We confirmed systematic decreasein river corridor exchange space through the river networks, from headwatersto the larger main stem. However, we did not find systematic variation withchanges in discharge through time or with local geomorphic setting. Whileinterpretation of our results is complicated by problems with the analyticalmethods, the results are sufficiently robust for us to conclude that space-for-timeand time-for-space substitutions are not appropriate in our study system.Finally, we suggest two strategies that will improve the interpretability oftracer test results and help the hyporheic community develop robust datasets that will enable comparisons across multiple sites and/or dischargeconditions. 

In low‐gradient, macrophyte‐rich rivers, we expect that the significant change in macrophyte biomass among seasons will strongly influence both biological activity and hydraulic conditions resulting in significant effects on nutrient dynamics. Understanding seasonal variation will improve modelling of nutrient transport in river networks, including annual estimations of export, which could optimise decision‐making and management outcomes.

We explored the relationships among seasonal differences in reach‐scale nutrient uptake, macrophyte abundance, solute transport and transient storage in the River Gudenå (Denmark), a large macrophyte‐rich river. We used the minimal pulse addition technique to measure uptake of ammonium, nitrate, soluble reactive phosphorus, as well as reach‐scale metabolism, and surface transient storage in spring, summer, and autumn.

We found that riverine uptake changed among seasons and was linked to macrophyte biomass via both biological activity, reflected in reach‐scale metabolism, and through physical processes, as solute transport was influenced by longitudinal dispersion. In this macrophyte‐rich river, seasonal changes in macrophyte biomass affected contact time between the water and biota, which influenced ammonium and soluble reactive phosphorus uptake. Using stoichiometric scaling of reach‐scale metabolism, we found that seasonal variation also influenced the relative contributions of autotrophic and heterotrophic biota in assimilatory uptake.

In summary, riverine nutrient uptake was not static, highlighting the importance of seasonality, with significant implications for modelling of nutrient export in river networks. Moreover, current management strategies that remove macrophyte biomass (i.e. weed cutting and dredging) will short‐circuit the positive effects of enhanced nutrient uptake resulting from abundant macrophytes in rivers.