Search Results (66)

In Peru, overweight and obesity affect 20–38% of adults, increasing the risk of NCDs (type 2 diabetes, heart diseases, and others) that emphasize the need for healthy foods. Chia (Salvia hispanica L.) seeds contain high amounts of polyunsaturated fatty acid essentials (omega-3) (17–23%), antioxidants, proteins, and minerals that prevent NCDs. Chia grows in the regions of Arequipa and Puno–Peru, with 4098 tn of production in 2023. Chia mucilage is a soluble fiber with a high water-holding capacity that possesses the techno-functional properties that would improve the properties of gelification and emulsification of foods: jams, ice cream, yogurt, and others. Peru holds the N°1 position in the ranking of blueberry (Vaccinium corymbosum) exporters. This berry contains antioxidants and flavonoids. Cushuro (Nostoc sphaericum) is a gelatinous spherical blue-green alga; it grows over 3000 masl on the Peruvian highland, and it contains good protein and polysaccharide contents. The work aimed to develop a hydrogel-type jam with chia mucilage (0.05–1.00%), blueberries (36–40%), and fresh cushuro (54–60%), compared with a control sample containing pectin and sugar. The characterization of the hydrogel-type jam was moisture (79.53 ± 1.51%), ash (0.20 ± 0.01%), protein (1.02 ± 0.28%), total carbohydrates (19.05 ± 1.76%), fat (0.21 ± 0.03%), antioxidants (318.56 ± 61.5 µm Trolox/g), and phenolic content (2.43 ± 0.93 mg GAE/g). Then, after 30 days of storage, the °Brix (9.9 ± 0.3), viscosity (3921.62 ± 1373.19), pH (3.18 ± 0.02), and water activity (0.82 ± 0.5) values of the hydrogel type-jam complied with the Peruvian applicable legislation (NTP 203.047) and health law (No. 30021). The hydrogel’s functional properties could help reduce the percentage of NCD, promoting the food industry with healthy products. Full article

Ice jamming is the primary mechanism that can generate overland flooding and recharge the isolated basins of the Peace–Athabasca Delta (PAD), a valuable ecosystem of international importance and the ancient homeland of the Indigenous Peoples of the region. Focusing on the regulated Peace River and the Peace Sector of the delta, which has been experiencing a drying trend in between rare ice-jam floods over the last ~50 years, this study describes recent notable breakup events, associated observational data, and numerical applications to determine river discharge during the breakup events. Synthesis and interpretation of this material provide a new physical understanding that can inform the ongoing development of a protocol for strategic flow releases toward enhancing basin recharge in years when major ice jams are likely to form near the PAD. Additionally, several recommendations are made for future monitoring activities and improvements in proposed antecedent criteria for early identification of “promising” breakup events. Full article

The stability of bridge foundations is affected by local scour, and the formation of ice jams exacerbates local scour around bridge piers. These processes, particularly the evolution of ice jams and local scour around piers, are more complex in curved sections than in straight sections. This study, based on experiments in an S-shaped channel, investigates how various factors—the flow Froude number, ice–water discharge rate, median particle diameter, pier spacing, and pier diameter—affect the maximum local scour depth around double piers in tandem and the distribution of ice jam thickness. The results indicate that under ice-jammed flow conditions, the maximum local scour depth around double piers in tandem is positively correlated with the ice–water discharge rate, pier spacing, and pier diameter and negatively correlated with median particle diameter. The maximum local scour depth is positively correlated with the flow Froude number when it ranges from 0.1 to 0.114, peaking at 0.114. Above this value, the correlation becomes negative. In curved channels, the arrangement of double piers in tandem substantially influences ice jam thickness distribution, with increases in pier diameter and spacing directly correlating with greater ice jam thickness at each cross-section. Furthermore, ice jam thickness is responsive to flow conditions, escalating with higher ice–water discharge rates and decreasing flow Froude numbers. Full article

This article provides a comprehensive overview of ice-jam flood forecasting methodologies applicable to rivers during freezing. It emphasizes the importance of understanding river ice processes and fluvial geomorphology for developing a freeze-up ice-jam flood forecasting system. The article showcases a stochastic modelling approach, which involves simulating a deterministic river ice model multiple times with varying parameters and boundary conditions. This approach has been applied to the Exploits River at Badger in Newfoundland, Canada, a river that has experienced several freeze-up ice-jam floods. The forecasting involves two approaches: predicting the extent of the ice cover during river freezing and using an ensemble method to determine backwater flood level elevations. Other examples of current ice-jam flood forecasting systems for the Kokemäenjoki River (Pori, Finland), Saint John River (Edmundston, NB, Canada), and Churchill River (Mud Lake, NL, Canada) that are operational are also presented. The text provides a detailed explanation of the processes involved in river freeze-up and ice-jam formation, as well as the methodologies used for freeze-up ice-jam flood forecasting. Ice-jam flood forecasting systems used for freeze-up were compared to those employed for spring breakup. Spring breakup and freeze-up ice-jam flood forecasting systems differ in their driving factors and methodologies. Spring breakup, driven by snowmelt runoff, typically relies on deterministic and probabilistic approaches to predict peak flows. Freeze-up, driven by cold temperatures, focuses on the complex interactions between atmospheric conditions, river flow, and ice dynamics. Both systems require air temperature forecasts, but snowpack data are more crucial for spring breakup forecasting. To account for uncertainty, both approaches may employ ensemble forecasting techniques, generating multiple forecasts using slightly different initial conditions or model parameters. The objective of this review is to provide an overview of the current state-of-the-art in ice-jam flood forecasting systems and to identify gaps and areas for improvement in existing ice-jam flood forecasting approaches, with a focus on enhancing their accuracy, reliability, and decision-making potential. In conclusion, an effective freeze-up ice-jam flood forecasting system requires real-time data collection and analysis, historical data analysis, ice jam modeling, user interface design, alert systems, and integration with other relevant systems. This combination allows operators to better understand ice jam behavior and make informed decisions about potential risks or mitigation measures to protect people and property along rivers. The key findings of this review are as follows: (i) Ice-jam flood forecasting systems are often based on simple, empirical models that rely heavily on historical data and limited real-time monitoring information. (ii) There is a need for more sophisticated modeling techniques that can better capture the complex interactions between ice cover, water levels, and channel geometry. (iii) Combining data from multiple sources such as satellite imagery, ground-based sensors, numerical models, and machine learning algorithms can significantly improve the accuracy and reliability of ice-jam flood forecasts. (iv) Effective decision-support tools are crucial for integrating ice-jam flood forecasts into emergency response and mitigation strategies. Full article

The interaction of water flow, ice, and structures is common in fluvial ice processes, particularly around Ice Control Structures (ICSs) that are used to manage and prevent ice jam floods. To evaluate the effectiveness of ICSs, it is essential to understand the complex interaction between water flow, ice and the structure. Numerical modeling is a valuable tool that can facilitate such understanding. Until now, classical Eulerian mesh-based methods have not been evaluated for the simulation of ice interaction with ICS. In this paper we evaluate the capability, accuracy, and efficiency of a coupled Computational Fluid Dynamic (CFD) and multi-body motion numerical model, based on the mesh-based FLOW-3D V.2023 R1 software for simulation of ice-structure interactions in several benchmark cases. The model’s performance was compared with results from meshless-based models (performed by others) for the same laboratory test cases that were used as a reference for the comparison. To this end, simulation results from a range of dam break laboratory experiments were analyzed, encompassing varying numbers of floating objects with distinct characteristics, both in the presence and absence of ICS, and under different downstream water levels. The results show that the overall accuracy of the FLOW-3D model under various experimental conditions resulted in a RMSE of 0.0534 as opposed to an overall RMSE of 0.0599 for the meshless methods. Instabilities were observed in the FLOW-3D model for more complex phenomena that involve open boundaries and a larger number of blocks. Although the FLOW-3D model exhibited a similar computational time to the GPU-accelerated meshless-based models, constraints on the processors speed and the number of cores available for use by the processors could limit the computational time. Full article

Accurate river ice mapping is crucial for predicting and managing floods caused by ice jams and for the safe operation of hydropower and water resource facilities. Although satellite multispectral images are widely used for river ice mapping, atmospheric contamination limits their effectiveness. This study developed river ice mapping models for the Han River in South Korea using atmospherically uncorrected Landsat-8 Operational Land Imager (OLI) multispectral reflectance data, addressing atmospheric influences with a Random Forest (RF) classification approach. The RF-based river ice mapping models were developed by implementing various combinations of input variables, incorporating the Landsat-8 multispectral top-of-atmosphere (TOA) reflectance, normalized difference indices for snow, water, and bare ice, and atmospheric factors such as aerosol optical depth, water vapor content, and ozone concentration from the Moderate Resolution Imaging Spectroradiometer observations, as well as surface elevation from the GLO-30 digital elevation model. The RF model developed using all variables achieved excellent performance in the classification of snow-covered ice, snow-free ice, and water, with an overall accuracy and kappa coefficient exceeding 98.4% and 0.98 for test samples, and higher than 83.7% and 0.75 when compared against reference river ice maps generated by manually interpreting the Landsat-8 images under various atmospheric conditions. The RF-based river ice mapping model for the atmospherically corrected Landsat-8 multispectral surface reflectance was also developed, but it showed very low performance under atmospheric conditions heavily contaminated by aerosol and water vapor. Aerosol optical depth and water vapor content were identified as the most important variables. This study demonstrates that multispectral reflectance data, despite atmospheric contamination, can be effectively used for river ice monitoring by applying machine learning with atmospheric auxiliary data to mitigate atmospheric effects. Full article

During the ice flood period of the Yellow River, the fracture and destruction of river ice can easily lead to the formation of ice jams and ice dams in the curved and narrow reaches. However, the occurrence and development mechanism of river ice fracture remain incompletely understood in the Yellow River. Therefore, based on the three-point bending physical test of the Yellow River ice, a three-point bending fracture numerical model of the Yellow River ice was constructed. The fracture failure process of the Yellow River ice under three-point bending was simulated, and the effects of the crack-to-height ratio and ice grain size on the fracture properties of the river ice were analyzed. By comparing the results with those of physical tests on river ice, it is evident that the fracture model can effectively simulate the cracking process of river ice. Within the confines of the simulated sample size spectrum, as the crack-to-height ratio varies from 0.2 to 0.8, the fracture toughness value of the Yellow River ice spans a range from 115.01 to 143.37 KPa·m^1/2. Correspondingly, within the simulated calculation values ranging from 5.38 mm to 24.07 mm for ice crystal size, the fracture toughness value of the Yellow River ice exhibits a range from 116.89 to 143.37 KPa·m^1/2. The findings reveal that an increase in the crack-to-depth ratio leads to a decrement in the fracture toughness of river ice. Within the scale range encompassed by the model calculations, as the average size of the ice crystal grains augments, the fracture toughness of the river ice exhibits a gradual ascending trend. The research results provide a parameter basis for studying the fracture performance of the Yellow River ice using a numerical simulation method and lays a foundation for investigating the cracking process of river ice from macro and micro multi-scales. Full article

Jabuticaba fruit (Plinia cauliflora) is widely consumed in various forms such as juice, jam, wine, and liquors; however, its potential therapeutic effects on diabetic complications remain inadequately explored. We aimed to investigate the potential antiglycation activity of Jabuticaba, identify the active compounds through bioassay-guided fractionation, and assess its effects on cataract formation in a Streptozotocin-induced diabetic type 1 rat model. Through bioassay-guided fractionation, we identified gallic acid (IC₅₀: 24.7 µg/mL), protocatechuic acid (IC₅₀: 1.22 µg/mL), and an ellagitannin, Repandinin B (IC₅₀: 0.55 µg/mL), as active compounds contributing to antiglycation effects. In the animal study, the addition of Jabuticaba juice extract to the drinking water at a concentration of 0.5% (w/v) for 12 weeks demonstrated an amelioration in cataract progression. These results suggest that Jabuticaba has high antiglycation effects leading to the delaying of cataract formation in type 1 diabetes. Full article

Spring-breakup ice-jam floods are a major hazard for many rivers in cold regions. They can cause severe damage to infrastructure, property, and ecosystems along riverbanks. To reduce the risk and impact of these events, it is essential to develop reliable and timely forecasting systems that can provide early warning and guidance for mitigation actions. In this paper, we highlight the elements and processes required for the successful development of a spring-breakup ice-jam flood forecasting system, using the lower Churchill River in Labrador, Canada as a case study. We review the existing forecasting methodologies and systems for spring-breakup ice-jam floods and discuss their strengths and limitations. We then describe the case study of the lower Churchill River, where a large ice-jam flood occurred in May 2017, triggering an independent review and a series of recommendations for improving the flood preparedness and response. We present the main components and features of the forecasting system that was developed for the lower Churchill River, based on the recommendations from the independent review. We also discuss the improvements that were made to the forecasting system, such as parallelization, adaptation, and determination of ice-jam prone areas. Finally, we provide some conclusions and recommendations for future research and development of spring-breakup ice-jam flood forecasting systems, focusing on the requirements for a technical framework that incorporates community engagement and special considerations for regulated rivers. Full article

Many communities along rivers in the Northwest Territories do not have water-level gauges, making flood hazard analyses difficult at these sites. These include the communities of Jean Marie River, Tulita and Fort Good Hope on the Mackenzie River, Nahanni Butte on the Liard River and Fort McPherson on the Peel River. However, gauges do exist at other sites upstream and downstream of these communities, from which flood hazard assessments can be extrapolated to the ungauged communities. Reach-based extrapolation becomes particularly challenging when analysing ice-jam flood hazards since data sparsity is an additional challenge at these locations. A simple empirical approach using non-dimensional stage and discharge was implemented, which allowed only a minimum of the required data from all sites to be extracted. From the gauged sites, water-surface elevations and slopes from digital elevation models, channel widths, thalweg elevations and ice thicknesses from under-ice flow measurement surveys and recorded water levels were obtained. As a test case, results from the gauged reach of Fort Simpson were extrapolated to the ungauged reach of Jean Marie River and are presented in this technical note. Full article

The fruit of Choerospondias axillaris (Anacardiaceae), known as south wild jujube in China, has been consumed widely in several regions of the world to produce fruit pastille and leathers, juice, jam, and candy. A comprehensive chemical study on the fresh fruits led to the isolation and identification of 18 compounds, including 7 new (1–7) and 11 known (8–18) comprised of 5 alkenyl (cyclohexenols and cyclohexenones) derivatives (1–5), 3 benzofuran derivatives (6–8), 6 flavonoids (9–14) and 4 lignans (15–18). Their structures were elucidated by extensive spectroscopic analysis. The known lignans 15–18 were isolated from the genus Choerospondias for the first time. Most of the isolates exhibited significant inhibitory activity on α-glucosidase with IC₅₀ values from 2.26 ± 0.06 to 43.9 ± 0.96 μM. Molecular docking experiments strongly supported the potent α-glucosidase inhibitory activity. The results indicated that C. axillaris fruits could be an excellent source of functional foods that acquire potential hypoglycemic bioactive components. Full article

The Oder River, situated along the border between Poland and Germany, is regularly affected by ice-jam events and their associated hazards, such as a sudden rise in water level and the endangerment to flood-protection infrastructure. The existing databases on past ice-jam events lack substantial information considering ice formation, blockage origins or the spatiotemporal evolution of the ice cover needed for a comprehensive understanding of relevant ice processes. Within this study, the evaluation of satellite and Uncrewed Aerial Vehicle (UAV) data was carried out in order to analyze the capabilities of enhancing river ice information in the study area. Satellite imagery was proven to be a valuable source of investigating ice-jam phenomena on all scales, leading to the identification of initial ice-jam locations, surveying spatiotemporal ice cover evolution or monitoring the maximum ice-cover extent. A simplified approach for river ice classification of satellite radar data using the K-Means Cluster Analysis is introduced, enabling the differentiation between river ice formations. Based on UAV data taken in this study, workflows were presented, allowing for measurements of ice floe velocities and the localization of flooded and ice-covered flow control structures. Full article

This study introduces a new automated system that blends multi-satellite information and citizen science data for reliable and timely observations of lake and river ice in under-observed northern regions. The system leverages the Google Earth Engine resources to facilitate the analysis and visualization of ice conditions. The adopted approach utilizes a combination of moderate and high-resolution optical data, along with radar observations. The results demonstrate the system’s capability to accurately detect and monitor river ice, particularly during key periods, such as the freeze-up and the breakup. The integration citizen science data showed added values in the validation of remote sensing products, as well as filling gaps whenever satellite observations cannot be collected due to cloud obstruction. Moreover, it was shown that citizen science data can be converted to valuable quantitative information, such as the case of ice thickness, which is very useful when combined with ice extent derived from remote sensing. In this study, citizen science data were employed for the quantitative assessment of the remote sensing product. Obtained results showed a good agreement between the product and observed river status, with a Critical Success Index of 0.82. Notably, the system has shown effectiveness in capturing the spatial and temporal evolution of snow and ice conditions, as evidenced by its application in analyzing specific ice jam events in 2023. The study concludes that the developed system marks a significant advancement in river ice monitoring, combining technological innovation with community engagement. Full article

Timely release of flow from upstream hydropower generation facilities on the Peace River can enhance potential ice-jam flooding near the drying Peace–Athabasca Delta (PAD), a Ramsar wetland of international importance and homeland to Indigenous Peoples. An important consideration in deciding whether and when to commence a release is the celerity of the breakup front as it advances along the Peace River. Relevant historical data for a key stretch of the river are analyzed to determine average celerities, which can vary by an order of magnitude from year to year. Seven breakup events are identified that might have been candidates for a release, and the predictability of associated celerities is explored in terms of antecedent hydroclimatic variables, including cumulative winter snowfall, snow water equivalent on 1 April, ice cover thickness, coldness of the winter, and freezeup level. It is shown that celerity can be predicted to within a factor of two or less, with the freezeup level giving the best results. Three of the seven “promising” events culminated in PAD floods and were associated with the three highest celerities. The empirical findings are shown to generally align with physical understanding of breakup driving and resisting factors. Full article

Large-scale two-dimensional hydrodynamic modeling at high resolution is still rarely performed because of its high computational cost and the lack of topographical data for some areas. Despite this, such modeling has been performed for the Odra River, the second largest river in Poland. This river has a high potential for flooding, which has been severely experienced many times in history, most recently in 1997 and 2010, when floods caused large losses. Since then, many different types of activities have been executed in order to reduce the risk of flooding. The paper presents a 2D modeling concept created during these activities. Given that the river valley is up to several kilometers wide, and consists of many complex topographical features and hydrotechnical facilities, a cascade of 25 2D models in MIKE21 software was developed. It covers a 600 km long section of the Odra River and an area of 5700 km² in total. A regular grid resolution of 4–6 m was used in the modeling. The models were applied for numerous purposes, first for the elaboration of flood hazard and flood risk maps for larger cities, and then for the verification of historic flood data and stage–discharge relations at gauge stations, as well as the verification of design discharges via flood routing. Other important uses were the evaluation of the effectiveness of flood mitigating works, including the feasibility study for the Racibórz reservoir, and the assessment of flood hazard due to embankment failure or ice jamming. Selected applications, as well as practical aspects of the model’s preparation and use, are presented. Full article