Ice and Snow Properties and Their Applications

1. Introduction

Ice and snow are essential components of the Earth’s cryosphere, contributing significantly to the global climate system and human civilization [1]. While seawater constitutes 96.5% of the Earth’s hydrosphere, freshwater accounts for just 3.5%, with the majority of this freshwater stored as ice or snow in polar regions, predominantly in glaciers, ice caps, and snow cover. Throughout history, ice and snow have shaped human development, influencing migration, agriculture, transportation, and even the rise and fall of civilizations [2]. The melting of glaciers and the retreat of polar ice caps are becoming increasingly prominent, which highlights the ongoing importance of understanding the properties and behaviors of ice and snow, particularly in light of the challenges posed by global warming.

The transformation of ice and snow due to climate change is having a profound impact on water resources, ecosystems, and infrastructure [3]. Rising temperatures are causing glaciers to diminish, sea ice to shrink, and snow cover to recede. These shifts are not only altering landscapes but also influencing critical functions such as water storage, hydrological cycles, and the stability of ecosystems. In the polar regions, for instance, the dynamics of ice and snow play a crucial role in freshwater storage and ecosystem health [4]. The retreat of glaciers and the shrinking of ice sheets are contributing to rising sea levels, while changes in sea ice affect marine life and species migration [5]. Furthermore, the reduction in snow cover alters seasonal freshwater flow, impacting hydrology in affected areas. These changes present challenges in managing water resources, preserving ecosystems, and maintaining infrastructure in cold regions, making the study of ice and snow properties ever more important.

In addition to their environmental significance, ice and snow play a vital role in engineering, especially in regions where human activities are becoming more widespread. The physical, mechanical properties of ice are key to designing structures such as roads, buildings, and power lines in ice-prone areas [6]. For example, in Arctic and Antarctic regions, the design of infrastructure such as ice roads, ports, and even airports require an in-depth understanding of ice behavior under different temperatures and mechanical stress. As climate change affects ice stability, engineering solutions must adapt to the changing conditions. Ice-related challenges, such as the increasing risk of ice-jam flooding, require innovative strategies in water management and flood prevention. Moreover, engineers are exploring new opportunities for renewable energy, such as offshore wind and solar power in ice-covered areas, further underscoring the importance of understanding ice dynamics in engineering applications.

Ecologically, the melting of ice and snow is reshaping ecosystems, particularly in polar and subpolar regions [7]. Ice serves as a platform for marine life, from algae growth to fish breeding, while also regulating species migration. The loss of ice cover threatens these ecosystems by disrupting the food chain and altering habitats. As sea ice declines, ecosystems are becoming increasingly vulnerable, affecting biodiversity and food security. Snowmelt also influences freshwater ecosystems, as it determines the timing and volume of water flow into rivers and lakes [8]. The ecological consequences of these changes extend beyond the immediate loss of habitat; they also affect migration patterns, breeding cycles, and overall ecosystem health. The research presented in this Special Issue delves into how changes in snow and ice properties are affecting ecosystems and explores ways to mitigate these impacts through the better understanding and management of frozen landscapes.

This Special Issue, “Ice and Snow Properties and Their Applications”, aims to advance knowledge in the areas of hydrology, ecology, and engineering by focusing on the changing physical, thermal, and mechanical properties of ice and snow. With climate change rapidly altering the cryosphere, it is crucial to employ interdisciplinary approaches to study these changes. The research collated in this Special Issue utilizes a range of methods, including remote sensing, numerical modeling, and experimental studies, to improve our understanding of ice and snow behavior. These studies will help provide the data necessary for developing strategies to mitigate the risks associated with ice dynamics, such as flooding and ice-related disasters, and to support the sustainable development of infrastructure and ecosystems in cold regions. By bringing together research from diverse fields, this Special Issue fosters collaboration that will help inform future scientific advancements and practical solutions in the face of a rapidly changing cryosphere.

2. List and Summaries of the Contributions

This Special Issue received 14 manuscript submissions, all of which were subject to the rigorous review process of Water. In total, 12 papers were finally accepted for publication and included in this Special Issue. The contributions are listed in the List of Contributions section.

As shown in

Table 1. Analysis of the contributions published in this Special Issue.

Number of Contribution	Research Area	Focus	Research Methods	Potential Applications
1	Ecology	Impact of freeze–thaw processes on spring algal blooms	Literature survey	Algal bloom prevention and lake management
2	Environmental science	Meteorological changes and water resources	Data analysis and modeling	Water resource management and climate change research
3	Ice engineering	Ship resistance in rafted ice regions	Numerical modeling	Ice resistance prediction for ship design
4	Environmental science	Sea surface temperature prediction	Data analysis and modeling	Improved SST forecasting and resource efficiency
5	Environmental science	Lake ice formation and breakup prediction	Remote sensing and statistical modeling	Lake ice prediction and climate impact assessment
6	Ice engineering	Ice formation and mechanical properties of columnar ice	Experiment	Ice property research and polar engineering
7	Ice engineering	Accurate segmentation of ice multiphase components	Experiment	Ice engineering and disaster prevention
8	Ice engineering	Flexural strength and fracture toughness of snow ice	Experiment	Ice engineering
9	Environmental science	Solar radiation transfer through ice and lake water temperature changes	Experiment	Climate modeling, environmental monitoring
10	Environmental science	Thickness of lake ice	Data analysis and modeling	Temporary ice runway
11	Environmental science	Snow and ice surface albedo scheme for lake	Data analysis and modeling	Climate impact assessment, environmental monitoring
12	Ice engineering	Simulation of an ice-class propeller in ice blockage	Numerical modeling	Anti-cavitation design and excitation force suppression of propellers

, the published papers cover broad topics such as ecology in cold regions, environmental science concerning meteorology and hydrology, ice engineering (including multiphase components), grain structure, mechanical property, and resistance to ships.

3. An Overview of Published Articles

As reviewed above, the published articles are mostly derived from the field of environmental science and ice engineering. An overview of these articles is provided here.

Lakes, as critical freshwater resources, are influenced by both natural processes and anthropogenic factors. At mid-to-high latitudes, the freeze-–thaw cycles of lakes play a unique role in nutrient migration, water temperature changes, and algal physiology, which differ significantly from processes in low-latitude lakes [9]. The phenomenon of spring algal blooms has become more frequent and intense in these regions, demanding an understanding of its driving factors for effective prevention and management strategies [10]. Zhao et al. (Contribution 1) conducted a literature survey of publications from 2007 to 2023, identifying research trends and hotspots in the study of freeze–thaw processes and their impact on algal blooms. They identified nutrient dynamics, water temperature changes, and algal physiology during freeze–thaw periods as key factors influencing bloom formation. The study highlights phosphorus transformation during frozen periods as a critical driver and emphasizes the dual pressure of climate change and human activity in increasing bloom frequency and intensity. An integrated framework for understanding and managing algal blooms was introduced, combining principle analysis, modeling, and basin-scale management strategies. This research provides valuable insights for mitigating the ecological and water security challenges posed by algal blooms in sensitive lake regions.

The study of surface temperature changes, particularly in natural environments such as lakes, rivers, and coastal regions, is crucial for understanding climate dynamics and their impacts on ecosystems and water resources [11,12]. Traditional modeling approaches, such as physical or statistical models, often simplify real-world conditions to idealized representations, which can lead to inaccuracies when applied to complex, heterogeneous environments. However, with the rapid advancement of imaging technologies and remote sensing techniques, it is now possible to capture more detailed and accurate surface temperature variations under natural conditions. AI and ML techniques allow researchers to process vast amounts of data from various sensors and sources, uncovering intricate relationships between surface temperature and the multiple environmental factors that influence it, such as atmospheric conditions, solar radiation, and water interactions. Three papers were published on the topic of measuring sea/lake surface temperature changes using machine learning and experimental methods. Yue et al. (Contribution 2) examined the impact of climate change on water resources in the Heilongjiang (Amur) River Basin, which spans four countries and serves as an important international boundary river. Using daily temperature and precipitation data from 282 meteorological stations over a period from 1980 to 2022, their study analyzes spatial and temporal trends in temperature and precipitation changes. The results show a significant increasing trend in both temperature and precipitation within the basin. Spatially, the annual warming rate increases from the southeastern coastal regions to the northwestern plateau, while precipitation increases more significantly in the central and southern plains. Temperature and precipitation change points were identified in 2001 and 2012, respectively. The study further employs the long short-term memory (LSTM) model to predict precipitation, showing high accuracy with improved performance compared to traditional models. Jiao et al. (Contribution 4) addressed the challenge of large errors in SST predictions along the coast, focusing on improving forecast accuracy using deep learning techniques. Specifically, the study develops an optimal SST prediction model based on LSTM, using Xiaomaidao Station as a case study, and then extends it to 14 coastal stations along the Bohai Sea and Yellow Sea. The results demonstrate that the LSTM-based SST model significantly reduces forecast errors, with a 78% reduction in the mean absolute error for 1–3 day forecasts at Xiaomaidao Station and a 61% average reduction for other stations. The model not only improves forecast accuracy but also enhances computational efficiency, saving resources while increasing the reliability of short-term SST predictions. Niu et al. (Contribution 9) investigated the warming mechanisms of lake water under the ice during the frozen period in the Tibetan Plateau (TP), focusing on Qinghai Lake, the largest lake in China. This study conducted a field experiment to examine thermal conditions and radiation transfer across air–ice–water interfaces. Using high-resolution remote sensing technologies, the study identifies three stages of lake surface conditions: snow stage, sand stage, and bare ice stage. During the snow and sand stages, reduced solar radiation penetration leads to lower water temperatures. However, during the bare ice stage, increased solar radiation penetration significantly warms the water beneath the ice. The study also highlights how surface coverings (snow, sand, and ice) influence ice and water temperatures, with the bare ice stage exhibiting the greatest diurnal temperature variations. The findings enhance understanding of solar radiation transfer and temperature changes in ice-covered lakes and provide key parameters for improving models of lake dynamics in high-altitude regions. Wang et al. (Contribution 11) investigated the feasibility and safety of ice runway construction on Huhenuoer Lake, located in Chen Barag Banner, northeastern China. The study focused on the ice formation period from 2023 to 2024, utilizing field measurements and modeling approaches. Ice thickness data, collected through drilling, revealed that thickness exceeded 100 cm by 29 February 2024, with a record high of 139 cm recorded at site #2 on 14 March 2024. The Stefan equation was employed to model ice growth processes, yielding a fitted Stefan coefficient of 2.202, while a safety-adjusted coefficient of 1.870 was recommended for runway construction. Spatial analysis indicated that the northern part of the lake is most suitable for runway construction. By integrating the Stefan model with fitting techniques, the study established relationships between ice thickness, cumulative snowfall, and negative accumulated temperature. Using the P-III method, the 50-year return period values for maximum negative accumulated temperature and cumulative snowfall were determined as 2092.46 °C·d and 58.4 mm, respectively. These values were applied to predict ice thickness patterns for varying return periods. The study concludes with practical recommendations for ice runway construction on Huhenuoer Lake, introducing ice field research and growth modeling to support operational planning and safety. This work provides technical insights for the development of ice runways in similar environments. Cao et al. (Contribution 12) conducted surface albedo measurements of snow and ice on Lake Ulansu in the Central Asian arid climate zone during the winter of 2016–2017. The study categorized observations into three stages based on ice growth and surface conditions: bare ice, snow cover, and melting. During the bare ice stage, the mean surface albedo was 0.35, with a decreasing trend attributed to wind-blown sediment accumulation (range: 0.99–1.87 g/m²). Snowfall events during the snow cover stage significantly increased albedo to 0.91, while the melting stage saw albedo decrease at a decay rate of 0.20–0.30 per day. Four existing albedo schemes were evaluated but deemed unsuitable for Lake Ulansu. A new surface albedo scheme was proposed by integrating existing models with measured data, incorporating the effect of sediment content on bare ice albedo for the first time. This scheme demonstrated a modeling efficiency of 0.933 over the three-month period, with validation against observations from other winters achieving an efficiency of 0.940. The closer the value is to 1, the higher the model’s predictive accuracy and reliability. The proposed scheme shows potential applicability to other lakes in the Central Asian arid climate zone, characterized by low precipitation, frequent sandstorms, and intense solar radiation. This work provides a robust framework for improving albedo modeling in similar environments.

The seasonal dynamics of lake ice in cold-region ecosystems plays a crucial role in regulating ecosystem functions [13,14]. It affects various physical, chemical, and biological processes within lakes by altering temperature and light conditions, dissolved gas levels, and biological productivity. These changes, in turn, influence both the health of aquatic ecosystems and the livelihoods of human communities dependent on these water bodies. Kirchner et al. (Contribution 5) introduced a novel approach for predicting lake ice formation and breakup in Southwest Alaska, a region vital for both biodiversity and local communities. Due to the limited availability of consistent data for large lakes in this sparsely populated area, the study utilized optical remote sensing data from MODIS (2002–2016) to establish a phenology record for key lakes. Additionally, the researchers developed a survival model using temperature and solar radiation-based predictors to model ice formation and breakup from 1982 to 2022, including years when lakes did not freeze. The model was validated using observational data from two lakes and temperature profiles from three others. The results indicate that cumulative freeze-degree days and thaw-degree days were the strongest predictors of ice formation and breakup. The study also found that lake volume influenced ice phenology, with smaller lakes exhibiting longer and more consistent ice-cover durations. The research provides valuable insights into the future behavior of lake ice in the Boreal region, highlighting the potential for shorter ice seasons in smaller lakes and increased variability in larger ones. This study presents an innovative methodology for lake ice prediction in data-scarce regions and contributes to understanding the future of lake ice dynamics under climate change.

Ice plays a critical role in the design and construction of infrastructure in cold regions, such as ice roads, buildings, and artificial ice rinks [15,16]. Understanding the physical characteristics and mechanical properties of ice, including its formation, structure, and response to stress, is essential for improving engineering applications and mitigating ice-related hazards. Recent advancements in experimental methods and technologies, such as wind tunnels, X-ray computed tomography (CT), and three-point bending tests, have facilitated more accurate and detailed analyses of ice properties, contributing to a deeper understanding of its behavior under various environmental conditions [17]. Three papers were published on the topic of ice formation and mechanical properties using experimental ways. Zhang et al. (Contribution 6) presented the design and use of a small open-circuit wind tunnel to simulate and analyze the formation of columnar ice in laboratory conditions. The study focuses on the effects of environmental temperature and wind speed on the ice formation process. It was found that increasing wind speed led to a decrease in grain size of the columnar ice. Key findings include the validation of wind tunnel contraction sections, real-time temperature monitoring during ice formation, and a positive correlation between wind speed and grain size. The method provides a controlled environment to study the mechanical properties of polar columnar ice and offers a foundation for future research on ice behavior under windy polar conditions. This technique also facilitates the study of ice’s mechanical properties in polar environments, offering valuable insights for ice engineering and structural designs in cold climates. Hu et al. (Contribution 7) explored the use of X-ray computed tomography (CT) to analyze the multiphase components of natural ice, which include gas, ice, unfrozen water, sediment, and brine. The study applies a watershed algorithm for the multi-threshold segmentation of CT images to improve the accuracy of the segmentation process and create high-precision three-dimensional models of ice. By analyzing Yellow River ice, Wuliangsuhai lake ice, and Arctic sea ice, the study demonstrates that the combined use of CT and the watershed algorithm can efficiently and non-destructively segment ice into its multiphase components. The results provide a detailed microscopic understanding of the ice’s composition, with implications for ice engineering, ice remote sensing, and disaster prevention in ice-related infrastructure. The study contributes to the field by offering an advanced methodology for analyzing ice structure and composition at a microscopic level, enhancing the accuracy of ice models for scientific and engineering applications. Han et al. (Contribution 8) investigates the mechanical properties of granular snow ice, focusing on its flexural strength and fracture toughness under varying strain rates and temperatures. Through a series of three-point bending tests, the study finds that flexural strength increases at low strain rates but decreases at higher strain rates. The study also observes that temperature significantly influences the flexural strength and brittleness of granular snow ice. At colder temperatures, the ice becomes more brittle, and the strain rate at which maximum strength occurs decreases. Additionally, the study explores fracture toughness, noting that it decreases as strain rate increases and that fracture patterns remain consistent across various temperatures and strain rates, with cracks predominantly developing along prefabricated lines. These findings provide crucial insights into the mechanical behavior of granular snow ice, which is important for designing and maintaining structures in cold regions, such as ice rinks and cold-climate construction projects. The results contribute to the understanding of the tough–brittle transition in ice and its mechanical response to environmental conditions.

In ship–ice interaction studies, most existing research has primarily focused on the resistance faced by ships navigating through level ice conditions [18,19,20], with less attention given to the more complex conditions, such as rafted ice. Rafted ice is common in polar regions or areas with high ice concentrations, where vessels may encounter higher resistance than under typical level ice conditions. Accurately predicting ship resistance in these challenging conditions is essential for optimizing ship design, operational strategies, and ensuring the safety and efficiency of maritime activities in icy waters. Huang et al. (Contribution 3) developed a numerical model designed to predict ship resistance in areas with rafted ice, addressing a significant gap in previous research. The study used preset grid cells to simulate rafted ice conditions and validates the model’s accuracy and reliability through comparisons with test results. How factors such as ice thickness, ship speed, and the bending and crushing strengths of ice affect the ice resistance encountered by ships under both level and rafted ice conditions was investigated. The results show that while ship resistance is generally higher in rafted ice than in level ice, the patterns of resistance differ between the two conditions. Specifically, ships navigating through rafted ice face more concentrated ice resistance compared to the more distributed resistance experienced under level ice conditions. Huang et al. (Contribution 10) investigated the hydrodynamics and cavitation behavior of ice-class propellers operating in ice-covered environments. The study focused on the non-uniform inflow conditions caused by ice blocks sliding along the ship hull in front of the propeller blades, which lead to increased excitation forces and significant cavitation. Using a hybrid Reynolds-averaged Navier–Stokes/large eddy simulation (RANS/LES) method combined with the Schnerr–Sauer cavitation model, the researchers analyzed hydrodynamic performance, excitation forces, cavitation evolution, and flow field characteristics under ice blockage conditions. The numerical method demonstrated a high accuracy, with hydrodynamic errors controlled within 3.0%. The results revealed that at low cavitation numbers, cavitation remains severe even with reduced blockage distance, and hydrodynamic coefficients do not increase significantly. When the blockage distance is 0.15 times the propeller diameter, the cavitation area covers 20% of the propeller blades. As the advance coefficient increases, the total cavitation area decreases, but the cavitation area behind the ice blockage persists, leading to a rise in excitation force. Ice blockage also induces backflow in the wake, with the most significant backflow occurring at the tip of the blade behind the ice. Higher advance coefficients amplify the high-pressure area on the pressure side and increase pressure differences, causing a sharp rise in excitation forces. This study provides a theoretical foundation for the anti-cavitation design and excitation force suppression of propellers operating in ice-covered regions, offering valuable insights for improving propeller performance and durability in such environments.