River Ice Can Shape Watershed Ecology

The objectives of the study were to describe the existing ice conditions in the Peace River and to predict changes as a result of the proposed Site C Clean Energy Project (the Project). The analyses of changes due to the Project were conducted using the CRISSP and PRTIGM models. Sixteen winters were simulated to provide a representative range of meteorological conditions on which to base the conclusions of the study. Potential changes are described in terms of the following ice characteristics: maximum upstream extent of ice cover; timing of ice cover formation and break-up; freeze-up and break-up water levels at the Town of Peace River; ice thickness; changes in ice conditions relevant for river ice crossings. The analyses also included predicting changes in these ice characteristics due to the combined influence of the Project and the proposed Dunvegan Hydro Project in Alberta. Two future climate scenarios were also considered.

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A conceptual model of river ice breakup

Canadian Journal of Civil Engineering ◽

10.1139/l84-071 ◽

1984 ◽

Vol 11 (3) ◽

pp. 516-529 ◽

Cited By ~ 9

Author(s):

S. Beltaos

Keyword(s):

Conceptual Model ◽

Water Surface ◽

Flow Characteristics ◽

Ice Cover ◽

River Ice ◽

Meandering Channel ◽

Transverse Cracking ◽

Ice Breakup ◽

Pertinent Data ◽

Short Term Forecasting

A conceptual model of ice breakup is formulated and used to analyze and compare data from four river gauge sites. Emphasis is on the development of generalized short-term forecasting methods, which to date have been site specific. The features to be forecast are the onset and flooding potential of breakup. These are related to the water surface width available for passage of the large sheets of ice that form by transverse cracking of the ice cover. Thus it is possible to study the effects of parameters such as ice cover dimensions and channel geometry. Owing to a lack of pertinent data, other parameters such as ice mechanical properties and flow characteristics are only considered indirectly. The mechanism of transverse cracking is examined in the light of recent field observations. Bending on planes parallel to the water surface, caused by stream curvature, could account for the observed crack spacing but more data are needed for positive conclusions. The present model does not apply in cases of “overmature” breakup, proximity of stage controls, and river planforms different from the single meandering channel type. Key words: breakup, cracks, field data, forecasting, gauge records, ice, ice clearing, ice sheets, model, onset, river ice, rivers.

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River ice cover influence on sediment transportation at present and under projected hydroclimatic conditions

Hydrological Processes ◽

10.1002/hyp.10522 ◽

2015 ◽

Vol 29 (22) ◽

pp. 4738-4755 ◽

Cited By ~ 12

Author(s):

Maria Kämäri ◽

Petteri Alho ◽

Noora Veijalainen ◽

Juha Aaltonen ◽

Mikko Huokuna ◽

...

Keyword(s):

Ice Cover ◽

River Ice ◽

Sediment Transportation

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Drone Surveying of Volumetric Ice Growth in a Steep River

Frontiers in Remote Sensing ◽

10.3389/frsen.2021.767073 ◽

2021 ◽

Vol 2 ◽

Author(s):

Einar Rødtang ◽

Knut Alfredsen ◽

Ana Juárez

Keyword(s):

Structure From Motion ◽

Complex Geometry ◽

Low Cost ◽

Single Point ◽

Ice Cover ◽

River Ice ◽

Ice Thickness ◽

Surface Geometry ◽

Ice Volume ◽

Anchor Ice

Representative ice thickness data is essential for accurate hydraulic modelling, assessing the potential for ice induced floods, understanding environmental conditions during winter and estimation of ice-run forces. Steep rivers exhibit complex freeze-up behaviour combining formation of columnar ice with successions of anchor ice dams to build a complete ice cover, resulting in an ice cover with complex geometry. For such ice covers traditional single point measurements are unrepresentative. Gathering sufficiently distributed measurements for representativeness is labour intensive and at times impossible with hard to access ice. Structure from Motion (SfM) software and low-cost drones have enabled river ice mapping without the need to directly access the ice, thereby reducing both the workload and the potential danger in accessing the ice. In this paper we show how drone-based photography can be used to efficiently survey river ice and how these photographic surveys can be processed into digital elevation models (DEMs) using Structure from Motion. We also show how DEMs of the riverbed, riverbanks and ice conditions can be used to deduce ice volume and ice thickness distributions. A QGIS plugin has been implemented to automate these tasks. These techniques are demonstrated with a survey of a stretch of the river Sokna in Trøndelag, Norway. The survey was carried out during the winter 2020–2021 at various stages of freeze-up using a simple quadcopter with camera. The 500 m stretch of river studied was estimated to have an ice volume of up to 8.6 × 103 m3 (This corresponds to an average ice thickness of ∼67 cm) during the full ice cover condition of which up to 7.2 × 103 m3 (This corresponds to an average ice thickness of ∼57 cm) could be anchor ice. Ground Control Points were measured with an RTK-GPS and used to determine that the accuracy of these ice surface geometry measurements lie between 0.03 and 0.09 m. The ice thicknesses estimated through the SfM methods are on average 18 cm thicker than the manual measurements. Primarily due to the SfM methods inability to detect suspended ice covers. This paper highlights the need to develop better ways of estimating the volume of air beneath suspended ice covers.

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Longitudinal floating structures – new concepts in river ice control

Canadian Journal of Civil Engineering ◽

10.1139/l91-115 ◽

1991 ◽

Vol 18 (6) ◽

pp. 933-939 ◽

Cited By ~ 2

Author(s):

Darryl J. Calkins

Keyword(s):

Patent Application ◽

Ice Cover ◽

River Ice ◽

Army Corps ◽

Army Corps Of Engineers ◽

Ice Jams ◽

Control Structures ◽

Ice Jam ◽

New Concepts ◽

Ice Control

Ice control structures placed in the streamwise direction of a river were analyzed to determine the effectiveness in reducing ice jam thicknesses. The theory describing the thickness for “wide” river ice jams was modified to analyze these longitudinal types, providing the computational verification that ice jam thicknesses could be reduced where the mode of ice cover thickening is internal collapse. These longitudinal structures appear to provide a new tool for modifying the river ice regime at freeze-up and possibly at breakup. By decreasing the ice jam thicknesses, which leads to lower stages, the structures have the potential for decreasing ice jam flood levels. The structures' ability to function is independent of the flow velocity and these structures should perform in rivers with velocities greater than the usual limitation of roughly 1 m/s associated with conventional cross-channel ice booms. Other possible applications include controlling ice movement at outlets from lakes, enhancing river ice cover progression, or even restraining the ice cover at breakup. A U.S. patent application has been filed jointly by the author and the U.S. Army Corps of Engineers. Key words: river ice, ice jams, ice control, hydraulic structures, ice booms.

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ICENET: A Semantic Segmentation Deep Network for River Ice by Fusing Positional and Channel-Wise Attentive Features

Remote Sensing ◽

10.3390/rs12020221 ◽

2020 ◽

Vol 12 (2) ◽

pp. 221 ◽

Cited By ~ 2

Author(s):

Xiuwei Zhang ◽

Jiaojiao Jin ◽

Zeze Lan ◽

Chunjiang Li ◽

Minhao Fan ◽

...

Keyword(s):

State Of The Art ◽

Yellow River ◽

Semantic Segmentation ◽

Ice Cover ◽

River Ice ◽

Superior Result ◽

Aerial Vehicle ◽

Deep Convolution Neural Network ◽

Uav Image ◽

Cover Density

River ice monitoring is of great significance for river management, ship navigation and ice hazard forecasting in cold-regions. Accurate ice segmentation is one most important pieces of technology in ice monitoring research. It can provide the prerequisite information for the calculation of ice cover density, drift ice speed, ice cover distribution, change detection and so on. Unmanned aerial vehicle (UAV) aerial photography has the advantages of higher spatial and temporal resolution. As UAV technology has become more popular and cheaper, it has been widely used in ice monitoring. So, we focused on river ice segmentation based on UAV remote sensing images. In this study, the NWPU_YRCC dataset was built for river ice segmentation, in which all images were captured by different UAVs in the region of the Yellow River, the most difficult river to manage in the world. To the best of our knowledge, this is the first public UAV image dataset for river ice segmentation. Meanwhile, a semantic segmentation deep convolution neural network by fusing positional and channel-wise attentive features is proposed for river ice semantic segmentation, named ICENET. Experiments demonstrated that the proposed ICENET outperforms the state-of-the-art methods, achieving a superior result on the NWPU_YRCC dataset.

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