Remote sensing (RS) is often employed to estimate suspended sediment concentration (SSC) in rivers, and the availability of hyperspectral imagery enhances the effectiveness of RS-based water quality monitoring due to its high spectral resolution. Yet, the necessity of hyperspectral imagery for SSC estimation in rivers has not been fully validated. This study thus compares the performance of hyperspectral RS with that of multispectral RS by conducting field-scale experiments in shallow rivers. In the field experiments, we measured radiance from a water body mixed with suspended sediments using a drone-mounted hyperspectral sensor, with the sediment and riverbed types considered as controlling factors. We retrieved the SSC from UAV imagery using an optimal band ratio analysis, which successfully estimated SSC distributions in the sand bed conditions with both multispectral and hyperspectral data. In the vegetated bed conditions, meanwhile, the prediction accuracy decreased significantly due to the temporally varying bottom reflectance associated with the random movement of vegetation caused by near-bed turbulence. This is because temporally inhomogeneous bottom reflectance distorts the relationship between the SSC and total reflectance. Nevertheless, the hyperspectral imaging exhibited better prediction accuracy than the multispectral imaging, effectively extracting optimal spectral bands sensitive to back-scattered reflectance from sediments while constraining the bottom reflectance caused by the vegetation-covered bed.

Contaminant trapping by recirculation zones occurring at the apex of natural meandering channels induces a long tail in the contaminant cloud, thereby complicating the prediction of mixing behaviors. Thus, the understanding of the interaction between solute trapping and recirculating flow is important for responding to and mitigating water pollution accidents. In this research, the EFDC model was employed to reproduce three-dimensional flow structures of recirculating flow at the channel apex and investigate the influence on contaminant mixing. To investigate the contaminant transport characteristics from the storage zone in meandering channels, simulations were conducted using various discharge values to assess the impact of storage zone development on the concentration–time curves. The analysis of the relationship between the storage zone size and mixing behaviors indicates that an increase in discharge could result in a shorter tail and larger longitudinal dispersion even with the larger storage zone size. On the other hand, the enlarged recirculation zone size contributes to reducing transverse dispersion, evidenced by flatter dosage curves under lower flow rate conditions. These findings suggest that the increase in longitudinal dispersion with a larger flow rate is primarily caused by the reduction in transverse dispersion resulting from the formation of the recirculation zone.

The dispersion coefficients are crucial in understanding the spreading of pollutant clouds in river flows, particularly in the context of the depth-averaged two-dimensional (2D) advection–dispersion equation (ADE). Traditionally, the 2D stream-tube routing procedure (2D STRP) has been the predominant method for determining both the longitudinal and transverse dispersion coefficients of the 2D ADE under transient concentration conditions. This study aims to quantitatively analyze and address the limitations of the 2D STRP using hypothetically generated data. The findings of these evaluations revealed that the existing 2D STRP failed to accurately reproduce reliable results when the tracer clouds reached wall boundaries. This limitation prompted the development of the 2D STRP-i, which effectively resolves this drawback. The newly developed routing-based observation method, 2D STRP-i, enables the reliable estimation of dispersion coefficients, considering the effect of the wall boundary. The results indicated that the existing 2D STRP yielded 2D dispersion coefficients with relative errors ranging from 40% to 200%, while 2D STRP-i consistently yielded relative errors of 3% to 5% on average. When applied to tracer test data obtained through remote sensing, the 2D STRP-i demonstrated its ability to accurately observe temporal concentration distributions, even when wall boundaries have a significant impact on contaminant transport.

As the demand for recreational activities in rivers has increased, the assessment of the existing safety measures of these activities has become crucial to prevent accidents. Current safety measures have mainly focused on water quality factors, while the safety of in-water activities is also influenced by river hydraulic conditions. Hence, we proposed a spatial river recreational index (SRRI) that considers hydraulic parameters to evaluate the safety of recreational activities in rivers. Using a 3D hydrodynamic model, we reproduced the spatial distribution of hydraulic parameters under various discharge conditions to estimate the SRRI based on fuzzy logic. The application of the SRRI at the confluence of the Nakdong-Guemho River in South Korea revealed that each hydraulic parameter contributed differently to the safety according to discharge and morphological conditions. For instance, flow direction decreased safety in the near-field of the river confluence, while water depth played a significant role in the meandering reach of the Nakdong River. Flow velocity was the most critical factor for nonpowered activities, such as sailing and paddling/wading, under high-flow conditions. Sailing was found to be unsafe in the main flow zone and near-field of the river confluence due to its sensitivity to discharge change. In contrast, paddling/wading and leisure boats were less sensitive to discharge changes and could be partly allowed under high-flow conditions, except in the deep-water zone in the meandering reach. Therefore, SRRI is expected to help many users with safe recreational activities in rivers by providing spatial safety information based on various hydraulic conditions.

Understanding the dynamics of hyporheic flow is important for managing water resources, since this interfacial flow exchange affects the fate and transport of contaminants in rivers. This study numerically quantifies the effect of hyporheic exchange on solute residence times in surface water systems by simulating solute transport in unified turbulent open-channel and hyporheic zone systems. Interfacial hyporheic fluxes (q_int) increase with increased Reynolds number (Re) that produces an enhanced bottom pressure gradient over the ripple bed. Heavy-tailed breakthrough curves emerge when hyporheic flow is considered in transport simulation. This reveals that hyporheic flow is a dominant driver of non-Fickian transport in surface water as this interfacial flow exchange delays solute transport with slow porewater flows. Furthermore, the increase in Re extends the longitudinal spreading of solute tracers because a higher surface flow velocity intensifies the magnitude of hyporheic flow and associated storage effects. This can be confirmed by the ratio of the maximum residence time to the peak arrival time that increases with the increase in Re, following a power-law relationship with both Re and q_int.

Research on the effects of microplastics on water environments is being widely conducted because the discharge of microplastics into the ocean and freshwater systems is rapidly increasing. For the numerical simulation of the transport and diffusion of microplastics introduced into water systems and evaluation of the ecological impacts, the settling velocities of microplastics must be investigated first. The settling behavior of microplastics has been commonly assumed to be similar to that of sediment particles, but this has not been sufficiently verified for various types of microplastic. In this study, a laboratory experiment was performed to measure the settling velocities of spherical microplastic particles in freshwater using a particle tracking technique, and a new calibration coefficient of the settling velocity was proposed based on the experimental data. The experimental results showed a clear linear relationship between the settling velocity and dimensionless particle diameter in the laminar flow region, as suggested by Stokes' law. However, the settling velocities in the transition region had a nonlinear relationship, which was also clearly demonstrated in the relationship between the drag coefficient and the particle Reynolds number. The evaluation of the existing equations for settling velocity showed that previous empirical equations based on experiments on sediment particles produced relative errors of 20% or more. However, the proposed calibration coefficient provided a more accurate prediction of the settling velocities of microplastic particles than the existing empirical equations based on sediment studies.