Search Results (25)

Ice-jam formation during winter low-flow conditions represents a persistent hydrotechnical hazard in small and medium-sized rivers of Central Europe. Despite extensive monitoring efforts, preventive structural measures remain insufficiently developed and rarely evaluated under real geomorphological constraints. This study proposes and hydraulically verifies a low-profile riverbed sill designed to suppress the initiation and stabilization of frazil and anchor ice during critical winter discharges. The analysis integrates 20 years of hydrological and water-temperature data (2004–2024), 26 detailed cross-sectional surveys, a high-resolution longitudinal profile derived from DMR 3.0, and a newly formulated Ice-Jam Risk Index (Iice) combining flow velocity, depth-to-width ratio and thermal deficit. Application to the Torysa River (rkm 42.8–43.6) revealed a clearly defined high-risk zone (rkm 43.20–43.38), where hydraulic conditions frequently fall below the critical thresholds for ice accumulation (U < 0.35 m·s⁻¹; h/B < (h/B)_crit; ΔT > 0.5 °C), indicating shallow and laterally widened channel sections prone to anchor-ice stabilization. Model simulations demonstrated that the proposed sill increases mean velocity by 22–35% during Q₆₅–Q₈₅ conditions, reducing the local I(ice) by 61%, while preserving the conveyance capacity for discharges above Q₅₀ and avoiding measurable backwater impacts upstream. Field-based morphology, risk index interpolation and hydraulic modeling all confirm that the structure effectively disrupts the formation of stable anchor-ice nuclei, which have historically triggered severe ice-jam floods in this reach (2011/12, 2016/17, 2021/22). The results show that a properly dimensioned low-profile sill provides a passive, low-cost, and transferable engineering solution for winter flood risk mitigation, outperforming reactive ice-management techniques while maintaining ecological and hydraulic compatibility with small natural rivers. The methodology is replicable for other rivers where supercooling, low-flow hydraulics and channel morphology jointly control ice-jam initiation. Full article

A previous analysis of Antarctic acoustic data relevant to quantifying frazil contributions to sea ice accretion is reconsidered to address inconsistencies with river frazil results acquired with similar instrumentation but augmented to suppress instrument icing. It was found that sound attenuation by consequent icing limited credible Antarctic acoustic frazil measurements to afternoon and early evening periods, which are shown to encompass daily minimums in frazil production. This reality was masked by use of an unvalidated liquid oblate spheroidal frazil characterization model, which greatly overestimated frazil concentrations. Much lower frazil contents were derived for these periods using a robust 2-frequency characterization algorithm, which incorporated a validated, alternative theory of scattering by elastic solid spheres. Physical arguments based on these results and instrument depth data were strongly suggestive of maximal but, currently, unquantified frazil presences during unanalyzed heavily iced late evening and morning time periods. Full article

The study focuses on the detection of breaking wave crests in the highly dynamic waters of an Antarctic coastal polynya using high-resolution panchromatic satellite imagery. Accurate assessment of whitecap coverage is crucial for improving our understanding of the interactions between wave generation, air–sea heat exchange, and sea ice formation in these complex environments. As open-ocean whitecap detection methods are inadequate in coastal polynyas partially covered with frazil ice, we discuss an approach that exploits specific lighting conditions: the alignment of sunlight with the dominant wind direction and low solar elevation. Under such conditions, steep breaking waves cast pronounced shadows, which are used as the primary indicator of wave crests, particularly in frazil streak zones. The algorithm is optimized to exploit these conditions and minimize false positives along frazil streak boundaries. We applied the algorithm to a WorldView-2 image covering different parts of Terra Nova Bay Polynya (Ross Sea), a dynamic polar coastal zone. This case study demonstrates that the spatial distribution of detected breaking waves is consistent with ice conditions and wind forcing patterns, while also revealing deviations that point to complex wind–wave–ice interactions. Although quantitative validation of satellite-derived whitecaps coverage was not possible due to the lack of in situ data, the method performs reliably under a range of conditions. Limitations of the proposed approach are pointed out and discussed. Finally, the study highlights the risk of misinterpretation of lower-resolution reflectance data in areas where whitecaps and sea ice coexist at subpixel scales. Full article

Sediment transport in alluvial channels has a long history of intensive research. River ice could affect sediment transport and channel morphology through the impact of various dynamic and thermal ice processes. However, studies on sediment transport under the influence of ice have been minimal until recent years. This phenomenon was partially due to the complicated interactions between ice, flow, and sediment dynamics, which require a good understanding of the river ice process, in addition to the difficult field data collection conditions. This paper reviews the progress and needs of river ice-related research on sediment transport and channel morphology, including the influence of ice cover and surface ice runs on sediment transport, the effects of frazil ice, anchor ice, and bank stability with freeze-thaw effects. Full article

The detection of thin-ice thickness using satellite microwave radiometers is a strong tool for estimating sea-ice production in coastal polynyas, which leads to dense water formation driving ocean thermohaline circulation. Thin-ice areas are classified into two ice types: active frazil, comprising frazil ice and open water, and thin solid ice, areas of relatively uniform thin ice. A thin-ice algorithm for AMSR-E has been developed to classify these two ice types and estimate ice thickness of <20 cm. In this study, we validate the applicability of the algorithm to the successor, AMSR2, using validation data of ice types identified from Sentinel-1 and ice thickness derived from MODIS. The validation results show an ice-type misclassification rate of ~3% and mean absolute errors in ice thickness of 2.0 cm and 5.0 cm for active frazil and thin solid ice, respectively. These values are similar to those for AMSR-E, indicating that the thin-ice algorithm can be applied to AMSR2. Further validations with the moored ADCP backscattering data capturing underwater frazil ice signals demonstrate that the algorithm can accurately distinguish between two ice types and effectively detect deep-penetrating frazil ice. The AMSR2 thin-ice thickness data has been released as a JAXA research product. Full article

Frazil ice is the foundation for all other ice phenomena, and its spatiotemporal evolution is critical for regulating ice conditions in rivers and channels, as well as for preventing and controlling ice damage. This paper investigates the dynamic transport pattern of frazil ice during the early stages of winter freezing in water conveyance channels based on a CFD-DEM coupled numerical model, and derives predictive formulae for the spatiotemporal evolution of frazil ice and floating ice. First, static repose angle simulations and slope sliding simulations were used to calibrate the contact parameters between frazil ice particles and between frazil ice and the channel bed, ensuring the accurate calculation of contact forces in the model. On this basis, the processes of frazil ice transport, aggregation, and upward movement in water transfer channels were simulated, and the influence of contact parameters on simulation results was analyzed, showing a significant effect when the ice concentration was high. Numerical results indicate that the amount of suspended frazil ice is positively correlated with the frazil ice generation rate and water depth, with minimal influence from the flow velocity; the amount of floating ice increases linearly along the channel, with growth positively correlated with the frazil ice generation rate and water depth, and negatively correlated with the flow velocity. Predictive formulae correlating frazil ice and floating ice amounts with the flow velocity, water depth, and other factors were proposed based on numerical results. There is good agreement between the predictive and numerical results: the maximum APE between the predicted and simulated values of suspended frazil ice is 13.24%, and the MAPE is 6.32%; the maximum APE between the predicted and simulated values of floating ice increment is 7.80%, and the MAPE is 2.89%. The proposed prediction formulae can provide a theoretical basis for accurately predicting ice conditions during the early stages of winter freezing in rivers and channels. Full article

This study is based on the research results of frazil ice evolution in recent years and proposes an improved frazil ice evolution mathematical model. Based on the NSGA-II genetic algorithm, seven key parameters were used as optimization design variables, the minimum average difference between the number of frazil ice, the mean and the standard deviation of particle diameter of the simulation results, and the observed data were used as the optimization objective, the Pareto optimal solution set was optimized, and the importance of each objective function was analyzed and discussed. The results show that compared to previous models, the improved model has better agreement between simulation results and experimental results. The optimal parameters obtained by the optimization model reduces the difference rate of water temperature process by 5.75%, the difference rate of quantity process by 39.13%, the difference rate of mean particle size process by 47.64%, and the difference rate of standard deviation process by 56.84% during the period of intense evolution corresponding to the initial parameter group. The results prove the validity of the optimization model of frazil ice evolution parameters. Full article

The constant inherent optical properties (IOPs) for sea ice currently applied in sea ice models do not realistically represent the dividing of shortwave radiative fluxes in sea ice and the ocean below it. Here we implement a parameterization of variable IOPs based on ice microstructures in the Los Alamos sea ice model, version 6.0 (CICE6) and investigate its effects on the simulation of the dividing of shortwave radiation and sea ice in the Arctic. Our sensitivity experiments indicate that variable IOP parameterization results in strong seasonal variation for the IOP parameters, typically reaching the seasonal maximum in the boreal summer. With such large differences, variable IOP parameterization leads to increased absorbed solar radiation at the surface and in the interior of Arctic sea ice relative to constant IOPs, up to ~3 W/m², but decreased solar radiation penetrating into the ocean, up to ~5–6 W/m². The changes in the dividing of shortwave fluxes in sea ice and the ocean below it induced by the variable IOPs have significant influence on Arctic sea ice thickness by modulating surface and bottom melting and frazil ice formation (increasing surface melting by ~16% and reducing bottom melting by ~11% in summer). Full article

Hanging dams are thick accumulations of frazil ice beneath an existing ice cover that are formed during the freeze-up period at locations where a fast-flowing river section enters a section with relatively low velocity. Hanging dams can have a substantial impact on the hydraulics of an ice-covered river. This paper presents an experimental study on hanging dam formation and evolution conducted using a laboratory physical model of a river issuing water into a relatively large reservoir using simulated frazil ice and a simulated ice cover. The incoming ice supply rate and the approach Froude number of the river are the two parameters that have an impact on the hanging dam formation with respect to several physical characteristics of the hanging dam. Hanging dam erosion was observed by increasing the approach Froude number of the river after a hanging dam had already formed. Both the formation and erosion of the hanging dam were qualitatively compared with field observations of hanging dam occurrences using satellite imagery and hydrometric data to support the applicability of the experimental results to a field scenario. The results presented in this paper comprise the first published qualitative laboratory data on hanging dam formation, helping to improve our understanding of the fundamental mechanisms of hanging dam formation and evolution. Full article

The application of UAV to acquire data on the morphometry of frazil ice floe in motion is demonstrated in the measurements conducted in the area of the Wrocław Water Junction at the Opatowice weir on the Odra River (Poland). Image processing was performed using open-source software dedicated to image analysis. The methodology presented in the publication offers a cost-effective and low-overhead technique for describing ice phenomena in lowland rivers. The focus of the methodology was on measuring the area, average size, perimeter, and circularity of frazil ice floe. The measurements were carried out for individual frames captured by a UAV, and the results were analyzed using statistical techniques. In prior research, the team effectively assessed ice velocity on an identical test sample. Deriving the average velocity, surface area, and fundamental morphological traits of frazil ice facilitates the automated segmentation, classification, and prediction of potential risks related to ice blockages on water routes. These risks encompass potential waterway obstructions, as well as infrastructure impairments, and may pose a danger to human safety. Full article

Frazil ice comprises millimeter-sized ice crystal particles or flocculations in water, and its generation and evolution primarily occur during the initial stage of the river ice process. Meanwhile, ice damage caused by frazil ice is common, so it is crucial to determine its generation and evolution mechanisms to develop a full understanding of the river ice processes, the prediction of ice development, and ice damage prevention. The recent developments in frazil ice research and modeling are summarized in this article. From the perspectives of field measurements and laboratory experiments, the techniques and methods for observing frazil ice are reviewed, including the flow generation, temperature control, and observation techniques necessary for laboratory observations of frazil ice, as well as the challenging observation techniques used for field measurements. Frazil ice’s evolution mechanisms (nucleation, thermal growth, secondary nucleation, collisional fragmentation, and flocculation) are affected by water temperature processes. Work on the movement and distribution of frazil ice is also presented. A review of the current numerical models used to assess frazil ice evolution is conducted. Moreover, the open issues and potential future research topics are suggested. Full article

Ground penetrating radar (GPR) has proven to be a very effective method for examining ice thickness. However, two preconditions must be met for this approach to be useful; the round-trip travel time of electromagnetic (EM) waves and radar transmission speed in the ice must be known. These issues are problematic because many factors affect radar transmission speed in ice, including impurities, physical properties such as porosity and density, and temperature. Results show that if these factors are not taken into account and a signal velocity of 0.17 m/ns in pure ice is used to estimate thickness, overestimates will result. We carried out a series of GPR surveys using dual channel host 200 MHz shielded antennas at the Toudaoguai Hydrological Station on the Yellow River, China, and collected samples to analyze ice impurities and physical properties. The results show that the ice crystal types include frazil, granular, and column at the Toudaoguai Hydrologic Station section. Our analysis of ice gas bubble and sediment content showed that the gas bubble volume content is between 11.95 and 13.0% in the frazil ice and between 7.9% and 8.6% in granular and columnar ice. At the same time, the ice sediment content ranged between 0.11‰ and 0.57‰, and the average was 0.24‰ in granular and columnar ice, which was about one-tenth that of the suspended sediment concentration in water. Additionally, a combination of GPR data as well as ice impurities, porosity, density, and temperature enabled us to provide insights on the variability of radar transmission speed and the equivalent dielectric permittivity in river ice. Our extensive observations reveal that radar transmission speed falls between 0.141 m/ns and 0.164 m/ns and that the equivalent dielectric permittivity of river ice increases in concert with ice temperature. Full article

Unfrozen free and non-free water between ice crystals in flat and hummock ice in the Yellow River exists as water films with varying contents based on ice temperature. These contents can affect the radar wave velocity of the ice despite its theoretical dependence on the crystal structure and ice body components. The unfrozen water content in ice depends on the ice temperature, which is controlled by the air temperature, solar radiation, and ice thickness. Winter air temperature and radar-detected ice thickness data observed at the Shisifenzi bend in the Yellow River from 2020 to 2021 were analyzed. The unfrozen water content in the ice was the primary factor influencing the accuracy of flat ice thickness detection. The heat flux at the ice–water interface in the Yellow River was determined. The evolution of ice thickness and temperature were simulated using a one-dimensional (1D) ice thermodynamic model forced by the local weather station data (i.e., air temperature, solar radiation, wind speed, and cloud cover). On this basis, the measured ice thickness data of 13 drill holes were combined to calculate 1251 thermodynamically simulated ice thicknesses consistent with the ice thickness detection time of the radar; therefore, statistical relationships regarding the influence of air temperature and the combined action of air temperature and ice thickness on the radar wave velocity in granular and columnar ice during air temperature increases and decreases were determined. Finally, the statistical relationship between the combined influence of air temperature and ice thickness on radar wave velocity was selected as a parameterization scheme to dynamically correct the radar wave velocity of flat ice. To enhance the radar detection accuracy for flat ice thickness, the radar wave velocity of ice was parameterized as a function. Given the presence of unfrozen frazil ice and accumulated broken ice blocks in the Yellow River, radar is suggested to detect the thickness of different types of ice in future research. Full article

River ice segmentation, used for surface ice concentration estimation, is important for validating river processes and ice-formation models, predicting ice jam and flooding risks, and managing water supply and hydroelectric power generation. Furthermore, discriminating between anchor ice and frazil ice is an important factor in understanding sediment transport and release events. Modern deep learning techniques have proved to deliver promising results; however, they can show poor generalization ability and can be inefficient when hardware and computing power is limited. As river ice images are often collected in remote locations by unmanned aerial vehicles with limited computation power, we explore the performance-latency trade-offs for river ice segmentation. We propose a novel convolution block inspired by both depthwise separable convolutions and local binary convolutions giving additional efficiency and parameter savings. Our novel convolution block is used in a shallow architecture which has 99.9% fewer trainable parameters, 99% fewer multiply–add operations, and 69.8% less memory usage than a UNet, while achieving virtually the same segmentation performance. We find that the this network trains fast and is able to achieve high segmentation performance early in training due to an emphasis on both pixel intensity and texture. When compared to very efficient segmentation networks such as LR-ASPP with a MobileNetV3 backbone, we achieve good performance (mIoU of 64) 91% faster during training on a CPU and an overall mIoU that is 7.7% higher. We also find that our network is able to generalize better to new domains such as snowy environments. Full article

Climate change leads to more variable meteorological conditions. In many Northern Hemisphere temperate regions, cold seasons have become more variable and unpredictable, necessitating frequent river ice observations over long sections of rivers. Satellite SAR (Synthetic Aperture Radar)-based river ice detection models have been successfully applied and tested, but different hydrological, morphological and climatological conditions can affect their skill. In this study, we developed and tested Sentinel-1 SAR-based ice detection models in 525 km sections of the Nemunas and Neris Rivers. We analyzed three binary classification models based on VV, VH backscatter and logistic regression. The model sensitivity and specificity were used to determine the optimal threshold between ice and water classes. We used in situ observations and Sentinel-2 Sen2Cor ice mask to validate models in different ice conditions. In most cases, SAR-based ice detection models outperformed Sen2Cor classification because Sen2Cor misclassified pixels as ice in areas with translucent clouds, undetected by the scene classification algorithm, and misclassified pixels as water in cloud or river valley shadow. SAR models were less accurate in river sections where river flow and ice formation conditions were affected by large valley-dammed reservoirs. Sen2Cor and SAR models accurately detected border and consolidated ice but were less accurate in moving ice conditions. The skill of models depended on how dense the moving ice was. With a lowered classification threshold and increased model sensitivity, SAR models detected sparse frazil ice. In most cases, the VV polarization-based model was more accurate than the VH polarization-based model. The results of logistic and VV models were highly correlated, and the use of VV was more constructive due to its simpler algorithm. Full article