Characterization of hyporheic exchange drivers and patterns within a low-gradient, first-order, river confluence during low and high flow

Confluences are nodes in riverine networks characterized by complex three-dimensional changes in flow hydrodynamics and riverbed morphology, and are valued for important ecological functions. This physical complexity is often investigated within the water column or riverbed, while few studies have focused on hyporheic fluxes, which is the mixing of surface water and groundwater across the riverbed. This study aims to understand how hyporheic flux across the riverbed is organized by confluence physical drivers. Field investigations were carried out at a low gradient, headwater confluence between Baltimore Brook and Cold Brook in Marcellus, New York, USA. The study measured channel bathymetry, hydraulic permeability, and vertical temperature profiles, as indicators of the hyporheic exchange due to temperature gradients. Confluence geometry, hydrodynamics, and morphodynamics were found to significantly affect hyporheic exchange rate and patterns. Local scale bed morphology, such as the confluence scour hole and minor topographic irregularities, influenced the distribution of bed pressure head and the related patterns of downwelling/upwelling. Furthermore, classical back-to-back bend planform and the related secondary circulation probably affected hyporheic exchange patterns around the confluence shear layer. Finally, even variations in the hydrological conditions played a role on hyporheic fluxes modifying confluence planform, and, in turn, flow circulation patterns

Quantifying the environmental impact of pollutant plumes from coastal rivers with remote sensing and river basin modelling

Coastal regions contaminated by polluted river water leaving inland river basins can be difficult to monitor due to their size and remoteness, but it is important to quantify the impact of such pollution to manage for coastal sustainability. In this research, we demonstrate how river plumes can be monitored and analysed by a combination of remote sensing and river basin modelling to estimate their spatial, temporal, and water quality characteristics. Our results show that multispectral remote sensing is able to differentiate the water quality characteristics and two-dimensional spatial characteristics between plumes from four discharge locations along the coast of Campania, Italy. Our results also show that river basin modelling, when informed by land cover, land use and wastewater treatment plant (WWTP) data, is able to estimate the plume volume, and pollutant load, attributed to rainfall-runoff and wastewater-discharge for each of the discharges. This research documents a new method for combining remote sensing and watershed modelling to quantify the environmental impact of pollution from coastal rivers

Remote sensing for environmental forensics: Thermal infrared images capture different surface temperatures in pollutant pools and dosed soils due to volatilization

The challenges of in-situ monitoring of contaminated landscapes include the rapid assessment of large areas for potential pollutants and their potential health risk due to volatilization. This research tested in a laboratory setting if thermal infrared remote sensing can discriminate between areas with volatilizing chemicals. Five pollutants of metal salts were prepared by mixing antimony with a solvent of hydrochloric acid, and cobalt, lead, nickel, and zinc with a solvent of nitric acid. Four pollutants of hydrocarbons, at two different concentrations, were prepared by mixing diesel, gasoline, motor oil, and olive oil with a solvent of acetone. The pollutants and solvents were in liquid pools and dosed on soils in petri dishes, each pollutant in a separate container, along with controls of a deionized water pool and un-dosed soil. The petri dishes were arranged in arrays, spaced to create intermediate areas without volatilization, and placed adjacent to a fume hood that created an updraft to remove volatilization products. The cooling of the pollutant surface due to volatilization was confirmed using thermocouple-based monitoring of in-situ kinetic temperature, and the thermal infrared radiometric temperature had a strong correlation with kinetic temperature. Based on two-tailed unpaired t tests of temperatures from 256 pixels for each petri dish, with a 0.05 alpha, 97% of the 66 polluted pool pairs had statistically different temperatures, and 85% of the 66 dosed soil pairs had statistically different temperatures. This study validated that thermography can differentiate between pollutant types and concentrations based on volatilization affecting temperature and thereby extend the remote sensing toolbox for environmental forensics. Further work is required to scale up this thermography technique from the relatively simple laboratory setting to more complex field applications

Time-Variable Transit Time Distributions in the Hyporheic Zone of a Headwater Mountain Stream

Exchange of water between streams and their hyporheic zones is known to be dynamic in response to hydrologic forcing, variable in space, and to exist in a framework with nested flow cells. The expected result of heterogeneous geomorphic setting, hydrologic forcing, and between‐feature interaction is hyporheic transit times that are highly variable in both space and time. Transit time distributions (TTDs) are important as they reflect the potential for hyporheic processes to impact biogeochemical transformations and ecosystems. In this study we simulate time‐variable transit time distributions based on dynamic vertical exchange in a headwater mountain stream with observed, heterogeneous step‐pool morphology. Our simulations include hyporheic exchange over a 600 m river corridor reach driven by continuously observed, time‐variable hydrologic conditions for more than 1 year. We found that spatial variability at an instance in time is typically larger than temporal variation for the reach. Furthermore, we found reach‐scale TTDs were marginally variable under all but the most extreme hydrologic conditions, indicating that TTDs are highly transferable in time. Finally, we found that aggregation of annual variation in space and time into a “master TTD” reasonably represents most of the hydrologic dynamics simulated, suggesting that this aggregation approach may provide a relevant basis for scaling from features or short reaches to entire networks