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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.

 

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.

 

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.