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Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering

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A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 20650

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Prof. Dr. Zhijun Li

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State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China
Interests: ice physical and mechanical properties; ice engineering; polar sciences and technology; ecosystem under ice; physical modeling
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Dr. Fang Li

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Guest Editor

School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: ice mechanics; ice-structure interaction; ice loads; ice navigation; ship performance in ice
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Dr. Sasan Tavakoli

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Guest Editor

Department of Mechanical Engineering, Aalto University, Espoo, Finland
Interests: fluid–structure interaction in the ocean; hydrodynamic of high-speed boats; wave–ice interactions; water waves; ocean renewable energy; polar seas
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Dr. Xuemei Liu

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Guest Editor

Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 4888 Shengbei Street, Changchun 130102, China
Interests: lake ecohydrology; hydrodynamic - water quality - water ecology simulation; water resource management; algae bloom
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Dr. Changlei Dai

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Guest Editor

School of Hydraulic and Electric-Power, Heilongjiang University, Harbin 150080, China
Interests: cold region hydrology; river ice measurement and forecast; ice cream disaster; ice and snow landscape
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The ice/snow in the cold region play an important rule for Earth Science, Engineering Science and Social Science. At present, global warming causes delayed formation of ice, thinner ice and shorter duration of seasonal ice covers, the geographical ice margin to move further away from the equator, the perennial ice to become thinner and decrease in extent, and as a result the fraction of first-year ice becomes higher. The ice/snow research advances for the cold regions at the middle latitude, where the ice temperature is near freezing point may support the ice sciences and engineering at polar regions. Therefore, understanding the properties of ice/snow behaviour on ground or underground, and their actions and applications in hydrology, ecology and engineering are useful for Earth Sciences, Engineering Sciences and Social Sciences in cold regions.

This special issue will cover the physical, thermal, mechanical, optical, and electrical properties of any kind of crystal ice/snow and the melting water from ice/snow, as well as permafrost. The scope will also include the theoretical studies and practice applications in remote sensing, investigation, experiments and numerical modellings in cold regions snow/ice forming and melting processes in water bodies and permafrost, contributions in ecosystem, behaviours in engineering and entertainment. The other topics closely related to this issue are also welcome.

The special issue is prepared to address the ice/snow behaviours and their applications. The issue can guide future ice science and engineering in polar and sub-polar regions under climate changes.

Prof. Dr. Zhijun Li
Dr. Fang Li
Dr. Sasan Tavakoli
Dr. Xuemei Liu
Dr. Changlei Dai
Guest Editors

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Keywords

glacier ice
lake ice
river ice
sea ice
ice/snow properties
engineering
ice-structure interaction
ice-wave interaction
ecosystem
remote sensing
observations and investigations
numerical modeling
ice-period water environment
physical modeling

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Published Papers (13 papers)

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Editorial

Jump to: Research

8 pages, 190 KiB

Open AccessEditorial

Cold Region Ice/Snow Actions in Hydrology, Ecology and Engineering

by Zhijun Li, Fang Li, Sasan Tavakoli, Xuemei Liu and Changlei Dai

Water 2024, 16(5), 689; https://doi.org/10.3390/w16050689 - 27 Feb 2024

Viewed by 1257

Abstract

In the Earth’s hydrosphere, 96 [...] Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

Research

Jump to: Editorial

14 pages, 9375 KiB

Open AccessArticle

Investigation of the Recent Ice Characteristics in the Bohai Sea in the Winters of 2005–2022 Using Multi-Source Data

by Ge Li, Yan Jiao, Xue Chen, Yiding Zhao, Rui Li, Donglin Guo, Lei Ge, Qiaokun Hou and Qingkai Wang

Water 2024, 16(2), 290; https://doi.org/10.3390/w16020290 - 15 Jan 2024

Cited by 2 | Viewed by 1283

Abstract

The safety of winter activities in the Bohai Sea requires more detailed information on ice characteristics and a more refined ice zone division. In the present study, 1/12°-resolution sea ice characteristic data were obtained based on the NEMO-LIM2 ice–ocean coupling model that assimilated MODIS satellite sea ice observations from the years of 2005 to 2022 to acquire new sea ice hindcasting data. On this basis, the ice period, ice thickness, ice concentration, ice temperature, ice salinity, and design ice thickness for different return periods in the 1/4°-resolution refined zoning were analyzed, which were then compared with the sea ice characteristics in the previous 21-ice-zone standard. The distribution of ice temperature and ice salinity was closely related to the distribution of ice thickness. The results of ice period, ice thickness, and ice concentration, as well as design ice thickness for different return periods, and the comparison with the previous 21-ice-zone standards, showed that the ice condition on the west coast of the Bohai Sea has significantly reduced. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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21 pages, 15842 KiB

Open AccessArticle

River Ice Regime Recognition Based on Deep Learning: Ice Concentration, Area, and Velocity

by Zhiyong Yang, Jun Zong, Yuelong Zhu, Xiuheng Liu, Ran Tao and Yufeng Yu

Water 2024, 16(1), 58; https://doi.org/10.3390/w16010058 - 22 Dec 2023

Cited by 2 | Viewed by 1252

Abstract

The real-time derivation of the concentration, area, and velocity of river surface ice based on camera imagery is essential for predicting the potential risks related to ice blockages in water routes. The key lies in the continuous tracking and velocity measuring of river ice, and reliable ice motion detection is a prerequisite for the dynamic perception of tracking targets. Previous studies did not utilize motion tracking for measuring ice velocity, and particle image velocimetry and feature point matching were used. This study aimed to use deep learning methods to address the challenging problems of deriving the ice concentration, area, and velocity based on camera imagery, and the focus was on measuring the ice velocity and drawing trajectories using the particle video tracking algorithm. We built a dataset named IPC_RI_IDS and collected information during the ice cover break-up process in the Nenjiang River (China). Our suggested approach was divided into four steps: (1) image preprocessing, where the camera image was calibrated to real-world coordinates; (2) determining the ice and water pixels in the camera image using the lightweight semantic segmentation network and then calculating the ice concentration and area; (3) enhancing and optimizing motion detection using the semantic segmentation results; and (4) adapting the particle video tracking algorithm to measure ice velocity using the proposed tracking points generation strategy. Finally, we analyzed the surface ice data in the study area and attempted to predict the stage of the ice break-up process to provide support for the real-time short-term forecasts of ice floods. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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18 pages, 4389 KiB

Open AccessArticle

Research on the Evolution of Snow Crystal Necks and the Effect on Hardness during Snowpack Metamorphism

by Jie Wei, Peng Lu, Shengbo Hu, Qiuming Zhao, Shunqi Yuan, Puzhen Huo and Qingkai Wang

Water 2024, 16(1), 48; https://doi.org/10.3390/w16010048 - 22 Dec 2023

Viewed by 1367

Abstract

To study the snow microstructure at various metamorphism times and extract the snow neck area, a constant density (200 kg/m³) snow metamorphism experiment was conducted. The findings show that the neck region is mostly influenced by temperature, sun radiation, snow density and specific humidity, with wind speed having little effect. Additionally, we developed a multiple linear regression equation for the neck area under atmospheric forcing: “S = 288T + 2E + 189ρ + 12,194V − 20,443RH − 42,729”. This equation accounts for solar radiation (E), temperature (T), snow density (ρ), specific humidity (RH) and wind speed (V). Notably, the above five factors can account for 84% of the factors affecting the neck area, making it a crucial factor. The relationship between snow hardness and neck area is correlated at 71%, and in later stages of metamorphism, the correlation may increase to 91%. Based on the neck area, the following hardness value prediction is made: “H = 0.002764S + 67.922837”. This study documents the growth variations in the neck region of the metamorphic snow cover and elucidates the process by which outside factors impact the microstructure and macroscopic physical characteristics of the snow cover. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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24 pages, 6098 KiB

Open AccessArticle

Reconstruction of Snow Cover in Kaidu River Basin via Snow Grain Size Gap-Filling Based on Machine Learning

by Linglong Zhu, Guangyi Ma, Yonghong Zhang, Jiangeng Wang and Xi Kan

Water 2023, 15(21), 3726; https://doi.org/10.3390/w15213726 - 25 Oct 2023

Viewed by 1560

Abstract

Fine spatiotemporal resolution snow monitoring at the watershed scale is crucial for the management of snow water resources. This research proposes a cloud removal algorithm via snow grain size (SGS) gap-filling based on a space–time extra tree, which aims to address the issue of cloud occlusion that limits the coverage and time resolution of long-time series snow products. To fully characterize the geomorphic characteristics and snow duration time of the Kaidu River Basin (KRB), we designed dimensional data that incorporate spatiotemporal information. Combining other geographic and snow phenological information as input for estimating SGS. A spatiotemporal extreme tree model was constructed and trained to simulate the nonlinear mapping relationship between multidimensional inputs and SGS. The estimation results of SGS can characterize the snow cover under clouds. This study found that when the cloud cover is less than 70%, the model’s estimation of SGS meets expectations, and snow cover reconstruction achieves good results. In specific cloud removal cases, compared to traditional spatiotemporal filtering and multi-sensor fusion, the proposed method has better detail characterization ability and exhibits better performance in snow cover reconstruction and cloud removal in complex mountainous environments. Overall, from 2000 to 2020, 66.75% of snow products successfully removed cloud coverage. This resulted in a decrease in the annual average cloud coverage rate from 52.46% to 34.41% when compared with the MOD10A1 snow product. Additionally, there was an increase in snow coverage rate from 21.52% to 33.84%. This improvement in cloud removal greatly enhanced the time resolution of snow cover data without compromising the accuracy of snow identification. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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17 pages, 14033 KiB

Open AccessArticle

Multi-Scale Polar Object Detection Based on Computer Vision

by Shifeng Ding, Dinghan Zeng, Li Zhou, Sen Han, Fang Li and Qingkai Wang

Water 2023, 15(19), 3431; https://doi.org/10.3390/w15193431 - 29 Sep 2023

Cited by 2 | Viewed by 1333

Abstract

When ships navigate in polar regions, they may collide with ice masses, which may cause structural damage and endanger the safety of their occupants. Therefore, it is essential to promptly detect sea ice, icebergs, and passing ships. However, individual data sources have limits and should be combined and integrated to obtain more thorough information. A polar multi-target local-scale dataset with five categories was constructed. Sea ice, icebergs, ice melt ponds, icebreakers, and inter-ice channels were identified by a single-shot detector (SSD), with a final mAP value of 70.19%. A remote sensing sea ice dataset with 15,948 labels was constructed. The You Only Look Once (YOLOv5) model was improved with Squeeze-and-Excitation Networks (SE), Funnel Activation (FReLU), Fast Spatial Pyramid Pooling, and Cross Stage Partial Network (SPPCSPC-F). In the detection stage, a slicing operation was performed on remote sensing images to detect small targets. Simulated sea ice data were included to verify the model’s generalization ability. Then, the improved model was trained and evaluated in an ablation experiment. The mAP, recall (R), and precision (P) values of the improved YOLOv5 were 75.3%, 70.3, and 75.4%, with value increases of 3.5%, 3.4%, and 1.9%, respectively, compared to the original model. The improved YOLOv5 was also compared with other models such as YOLOv3, Faster-RCNN, and YOLOv4-tiny. The results indicated that the performance of the proposed model surpassed those of the other conventional models. This study achieved the detection of multiple targets on different scales in a polar region and realized data fusion, avoiding the limitations of using a single data source, and provides a method to support polar ship path planning. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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18 pages, 10601 KiB

Open AccessArticle

Investigations on Flexural Strength of a Columnar Saline Model Ice under Circular Plate Central Loading

by Yukui Tian, Weihang Zhao, Chaoge Yu, Xuhao Gang, Peng Lu and Qianjin Yue

Water 2023, 15(19), 3371; https://doi.org/10.3390/w15193371 - 26 Sep 2023

Cited by 1 | Viewed by 942

Abstract

The properties of ice strength have a significant impact on the design and safety of structures in ice-infested waters. To analyze the flexural strength of columnar saline model ice, we conducted circular plate center loading tests at the Small Ice Model Basin of the China Ship Scientific Research Center (CSSRC SIMB) in China. The tests involved varying the loading rate and ice temperature, and a numerical model was developed using FEM and LS-DYNA for validation and comparison. The results of the tests revealed the crack propagation process, stress distribution, load response, and failure mode of the model ice. The model ice displayed typical brittle failure, and the flexural strength was linearly related to ice temperature but not significantly correlated with loading rate. The porosity of the model ice affected the load response and time of failure but not the failure mode. The model ice with 7% porosity had a 7.8% reduction in load response compared to the nonporous model ice. This study provides a reliable method for measuring and analyzing the flexural strength of model ice. It also serves as a foundation for further research on the interaction between structures and ice sheets. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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14 pages, 4927 KiB

Open AccessArticle

Study on the Constitutive Equation and Mechanical Properties of Natural Snow under Step Loading

by Hongwei Han, Meiying Yang, Xingchao Liu, Yu Li, Gongwen Gao and Enliang Wang

Water 2023, 15(18), 3271; https://doi.org/10.3390/w15183271 - 15 Sep 2023

Cited by 3 | Viewed by 1561

Abstract

Snow, as an important component of the cryosphere, holds a crucial role in the construction of polar infrastructure. However, the current research on the mechanical properties of snow is not comprehensive. To contribute to our understanding of the mechanical behaviors of snow in cold regions, uniaxial compression tests under step loading were performed on the snow. With the Maxwell model as the basis, different temperatures, densities, and loading rates were set to establish constitutive equations of snow. The changes in the elastic modulus and viscosity coefficient of snow with respect to three variables were investigated. The results show that the loading rate has no obvious effect on the elastic modulus and viscosity coefficient of snow. Both the elastic modulus and viscosity coefficient of snow follow an exponential function with respect to density, with an increase in density, resulting in a higher value. As temperature decreases, the elastic modulus and viscosity coefficient initially decrease and then increase, whereas no specific functional relationship between them was observed. Additionally, a new constitutive equation considering snow density is derived based on the Maxwell model. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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17 pages, 3770 KiB

Open AccessArticle

Risk Evaluation of Ice Flood Disaster in the Upper Heilongjiang River Based on Catastrophe Theory

by Yu Li, Hongwei Han, Yonghe Sun, Xingtao Xiao, Houchu Liao, Xingchao Liu and Enliang Wang

Water 2023, 15(15), 2724; https://doi.org/10.3390/w15152724 - 28 Jul 2023

Cited by 2 | Viewed by 1443

Abstract

The ice flood phenomenon frequently occurs in frigid locations of high latitude and high altitude, which triggers ice dam or ice jam flooding thus endangering personal and property safety. Hence, a scientific risk evaluation with enough consideration of each factor is a basic and necessary requirement for preventing ice flood disaster risks. This study establishes a risk evaluation system for ice flood disasters based on the catastrophe theory and utilizes the Pearson correlation coefficient to screen underlying indicators to evaluate the risk of ice flood in the upper Heilongjiang River region. Considering the correlation between different indicators, a hierarchical cluster analysis is invoked to simplify the indicator set and to select typical years. The results of the evaluation system indicate that the catastrophe membership values in the Mohe, Tahe, and Huma regions from 2000 to 2020 ranged from 0.86 to 0.93. Based on the membership values and the actual disaster situations, a four-level classification of risk ratings is conducted. The comparison between the results obtained from the catastrophe theory evaluation method and the fuzzy comprehensive evaluation method reveals similar risk levels, which verifies the effectiveness and practicality of the catastrophe theory applied to the ice flood risk evaluation and presents a novel method for the study of ice floods. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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21 pages, 7915 KiB

Open AccessArticle

Observations of Snow–Slush–Snow Ice Transformation and Properties of Brash Ice in Ship Channels

by Vasiola Zhaka, Robert Bridges, Kaj Riska, Jonny Nilimaa and Andrzej Cwirzen

Water 2023, 15(13), 2360; https://doi.org/10.3390/w15132360 - 26 Jun 2023

Cited by 3 | Viewed by 1592

Abstract

The thickness and properties of brash ice are usually compared with the properties of the surrounding level ice. The differences between these ice types are important to understand since the consolidated brash ice layer is typically assumed to have the same properties as level ice. Therefore, significant effort in the measurement campaign during the winters of 2020–2021, 2021–2022, and 2023 was made to develop a better understanding of the full-scale brash ice channel development. The channels were located near the shore in the Bay of Bothnia, Luleå, Sweden. The main parameters investigated were the snow, slush, and total ice thicknesses, including ice formed from freezing water and from freezing slush as well as the ice microstructure and strength. To our knowledge, this is the first paper to report the influence of snow in brash ice channels. It was observed that a significant amount of snow covered the brash ice channels between the ship passages. After each ship passage, the snow was submerged and formed slush-filled voids, which thereafter transformed into snow ice (SI) clusters frozen together with columnar ice. The SI content in the brash ice and side ridges was estimated from image analyses. The analyses showed that the snow ice content was 73% in level ice in the vicinity of the ship channel, 58% in the side ridges of the channel, and 21% in the middle of the test channel, whereas in the main channel, the SI contents were 54%, 43%, and 41% in each location, respectively. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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19 pages, 7689 KiB

Open AccessArticle

Recent Advances and Challenges in the Inverse Identification of Thermal Diffusivity of Natural Ice in China

by Zhijun Li, Xiang Fu, Liqiong Shi, Wenfeng Huang and Chunjiang Li

Water 2023, 15(6), 1041; https://doi.org/10.3390/w15061041 - 9 Mar 2023

Viewed by 1827

Abstract

The ice thermal parameters are the key to reasonably simulating ice phenology, distribution, and thickness, but they have always been a “vulnerable group” in ice research. Technically, it may seem simple to obtain accurate ice thermal property parameters, but in reality, there are numerous impact factors, requiring a rigorous research process. In the 1980s, the thermal conductivity of ice was explored in the field and laboratory, after which there has been no significant progress in China. In this century, mathematics is introduced, after which the inversion identification and analysis with the time-series data of the vertical temperature profiles of ice layers by in situ testing are carried out. The in situ thermal diffusivities of different natural ices were obtained and cross-validated with the inversion identification results. Both natural freshwater ice and sea ice exhibited differences in the thermal diffusivity of the pure ice chosen for the current simulations due to impurities within the unfrozen water among the ice crystals, but the trends are consistent with the results of a small number of laboratory tests on different types of saltwater frozen ice. In this paper, the inversion identification results of the thermal diffusivity of typical ice were selected, and the factors constraining the thermal diffusivities were analyzed. The importance of parameterizing the thermal diffusivity in the phase transition zone of ice under the trend of global warming was illustrated. Future research ideas on the physical mechanism, application value, and parameterization scheme of the thermal diffusivity of natural ice were envisaged. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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17 pages, 4640 KiB

Open AccessArticle

Ice Mass Balance in Liaodong Bay: Modeling and Observations

by Yuxian Ma, Dewen Ding, Ning Xu, Shuai Yuan and Wenqi Shi

Water 2023, 15(5), 943; https://doi.org/10.3390/w15050943 - 1 Mar 2023

Viewed by 1883

Abstract

During the winters of 2009/2010 and 2020/2021, observations were carried out at an eastern port of Liaodong Bay to examine the variations in sea ice thickness and atmospheric conditions. The daily ice thickness (DIT) and the cumulative ice thickness (CIT) are the two main observation items related to the thickness of sea ice. For DIT, the sea ice thickness gradually decreases as the temperature increases, and the freezing rate a is 1.48 cm/(°C·d)^1/2. For CIT, when the temperature is −12 °C, the maximum growth rate of ice thickness decreases from 3.5 cm/d to 1.5 cm/d as the ice thickness increases from 0 to 20 cm. The residual method was applied to calculate the oceanic heat flux, which is an important parameter of ice modeling, and both the analytic model (Stefan’s law) and numerical model (high-resolution thermodynamic snow-and-ice model) were utilized in this work. It was found that the accuracy of the simulation results was high when the growth coefficient of the analytic mode was 2.3 cm/(°C·d)^1/2. With an oceanic heat flux of 2 W·m⁻², the maximum error of the numerical model approached 60% in 2010 and 3.7% in 2021. However, using the oceanic heat flux calculated in this work, the maximum error can be significantly reduced to 4.2% in the winter of 2009/2010 and 1.5% in 2020/2021. Additionally, the oceanic heat flux in Liaodong Bay showed a decreasing trend with the increase in ice thickness and air temperature. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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11 pages, 5201 KiB

Open AccessArticle

Simulation and Key Physical Drivers of Primary Productivity in a Temperate Lake during the Ice-Covered Period: Based on the VGPM Model

by Jie Zhang, Fei Xie, Haoming Song, Jingya Meng and Yiwen Zhang

Water 2023, 15(5), 918; https://doi.org/10.3390/w15050918 - 27 Feb 2023

Cited by 1 | Viewed by 2035

Abstract

The primary productivity of seasonal ice-covered water bodies is an important variable for understanding how temperate lake ecosystems are changing due to global warming. But there have been few studies on the complete change process of primary productivity during the ice-covered period, and the connection between ice physical and associated biological production has not been fully understood. In this study, a Vertically Generalized Production Model (VGPM) suitable for the ice-covered period was used to calculate the primary productivity of a temperate lake, and the key physical controlling factor was analyzed in the process of primary productivity change in the ice-covered period. The results showed that there was a high level of primary productivity, (189.1 ± 112.6) mg C·m⁻²·d⁻¹, under the ice in the study site, Hanzhang Lake. The phytoplankton production under the ice was not as severely restricted by light as commonly thought. The water temperature played a more crucial role in the changes of primary productivity than the light beneath the ice. The study highlighted the variability in primary productivity covering the whole ice-covered age, and provided a better understanding of how the aquatic environment of lakes in seasonal ice-covered areas was affected by warmer temperatures. Full article

(This article belongs to the Special Issue Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering)

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