Athabasca River ice jam formation and release events in 2006 and 2007

2009 ◽  
Vol 55 (2) ◽  
pp. 249-261 ◽  
Author(s):  
Yuntong She ◽  
Robyn Andrishak ◽  
Faye Hicks ◽  
Brian Morse ◽  
Edward Stander ◽  
...  
Keyword(s):  
River Ice ◽  
Athabasca River ◽  
Ice Jam

Observations of ice jam release waves on the Athabasca River near Fort McMurray, Alberta

2007 ◽  
Vol 34 (4) ◽  
pp. 473-484 ◽  
Author(s):  
T Kowalczyk Hutchison ◽  
F E Hicks
Keyword(s):  
Wave Propagation ◽  
Wave Speed ◽  
Flood Forecasting ◽  
River Ice ◽  
Historical Records ◽  
Athabasca River ◽  
Fort Mcmurray ◽  
Release Wave ◽  
Ice Jam ◽  
High Release

This paper presents an investigation of all documented ice jam release events for the Athabasca River at Fort McMurray, Alberta. A review of the historical records indicates that release waves in excess of 3 m and propagation speeds of 4–5 m/s are not uncommon. Numerous occurrences of increases in wave speed and magnitude suggest that temporary stalling of ice runs may be a significant factor in release event propagation. Detailed measurements of ice jam release events in 2001–2003, including most notably a 4.3 m high release wave measured in 2002, provide unprecedented data describing ice jam release wave propagation and suggest that continued propagation of a portion of the release wave downstream of a reformed jam could be a significant factor in immediate re-release.Key words: ice jam, floods, flood forecasting, river ice, ice jam release.

Ice jam mitigation

1990 ◽  
Vol 17 (5) ◽  
pp. 675-685 ◽  
Author(s):  
Harold S. Belore ◽  
Brian C. Burrell ◽  
Spyros Beltaos
Keyword(s):  
Key Words ◽  
Carrying Capacity ◽  
Flood Control ◽  
Human Life ◽  
Water Levels ◽  
Economic Losses ◽  
River Ice ◽  
Ice Jams ◽  
Ice Jam ◽  
Ice Breakup

In Canada, flooding due to the rise in water levels upstream of an ice jam, or the temporary exceedance of the flow and ice-carrying capacity of a channel upon release of an ice jam, has resulted in the loss of human life and extensive economic losses. Ice jam mitigation is a component of river ice management which includes all activities carried out to prevent or remove ice jams, or to reduce the damages that may result from an ice jam event. This paper presents a brief overview of measures to mitigate the damaging effects of ice jams and contains a discussion on their application to Canadian rivers. Key words: controlled ice breakup, flood control, ice jams, ice management, river ice.

Shokotsu River ice jam formation

2003 ◽  
Vol 37 (1) ◽  
pp. 35-49 ◽  
Author(s):  
Hung Tao Shen ◽  
Lianwu Liu
Keyword(s):  
River Ice ◽  
Ice Jam

Transferability of a neuro-fuzzy river ice jam flood forecasting model

2007 ◽  
Vol 48 (3) ◽  
pp. 188-201 ◽  
Author(s):  
C. Mahabir ◽  
F.E. Hicks ◽  
A. Robinson Fayek
Keyword(s):  
Flood Forecasting ◽  
River Ice ◽  
Forecasting Model ◽  
Ice Jam ◽  
Neuro Fuzzy

scholarly journals A Stochastic Modelling Approach to Forecast Real-time Ice Jam Flood Severity Along the Transborder (New Brunswick/Maine) Saint John River of North America

2021 ◽  
Author(s):  
Apurba Das ◽  
Sujata Budhathoki ◽  
Karl-Erich Lindenschmidt
Keyword(s):  
Land Surface ◽  
Human Life ◽  
Stochastic Modelling ◽  
Stochastic Approach ◽  
Monte Carlo Analysis ◽  
Flood Forecasting ◽  
River Ice ◽  
Ice Jam ◽  
Saint John ◽  
Modelling Approach

Abstract Ice jam floods (IJF) are a major concern for many riverine communities, government and non-government authorities and companies in the higher latitudes of the northern hemisphere. Ice jam related flooding can result in millions of dollars of property damages, loss of human life and adverse impacts on ecology. Ice jam flood forecasting is challenging as its formation mechanism is chaotic and depends on numerous unpredictable hydraulic and river ice factors. In this study, Modélisation environnementale communautaire – surface hydrology (MESH), a semi-distributed physically-based land-surface hydrological modelling system was used to acquire a 10-day flow forecast, an important boundary condition for any modelling of river ice-jam flood forecasting. A stochastic modelling approach was then applied to simulate hundreds of possible ice-jam scenarios using the hydrodynamic river ice model RIVICE within a Monte-Carlo Analysis (MOCA) framework for the Saint John River from Fort Kent to Grand Falls. First, a 10-day outlook was simulated to provide insight on the severity of ice jam flooding during spring breakup. Then, 3-day forecasts were modelled to provide longitudinal profiles of exceedance probabilities of ice jam flood staging along the river during the ice-cover breakup. Overall, results show that the stochastic approach performed well to estimate maximum probable ice-jam backwater level elevations for the spring 2021 breakup season.

Response to Commentary by Beltaos and Peters on: “Past variation in Lower Peace River ice-jam flood frequency” by Wolfe et al. (2020)

2020 ◽  
Vol 28 (4) ◽  
pp. 567-568
Author(s):  
Brent B. Wolfe ◽  
Roland I. Hall ◽  
Johan A. Wiklund ◽  
Mitchell L. Kay
Keyword(s):  
Flood Frequency ◽  
River Ice ◽  
Ice Jam ◽  
Peace River

scholarly journals Modeling River Ice Breakup Dates by k-Nearest Neighbor Ensemble

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 220
Author(s):  
Wei Sun ◽  
Ying Lv ◽  
Gongchen Li ◽  
Yumin Chen
Keyword(s):  
Nearest Neighbor ◽  
Distance Functions ◽  
River Ice ◽  
K Nearest Neighbor ◽  
Athabasca River ◽  
Ice Breakup ◽  
Promising Tool ◽  
Improved Performance ◽  
Chebychev Distance ◽  
Leave One Out

Forecasting of river ice breakup timing is directly related to the local ice-caused flooding management. However, river ice forecasting using k-nearest neighbor (kNN) algorithms is limited. Thus, a kNN stacking ensemble learning (KSEL) method was developed and applied to forecasting breakup dates (BDs) for the Athabasca River at Fort McMurray in Canada. The kNN base models with diverse inputs and distance functions were developed and their outputs were further combined. The performance of these models was examined using the leave-one-out cross validation method based on the historical BDs and corresponding climate and river conditions in 1980–2015. The results indicated that the kNN with the Chebychev distance functions generally outperformed other kNN base models. Through the simple average methods, the ensemble kNN models using multiple-type (Mahalanobis and Chebychev) distance functions had the overall optimal performance among all models. The improved performance indicates that the kNN ensemble is a promising tool for river ice forecasting. The structure of optimal models also implies that the breakup timing is mainly linked with temperature and water flow conditions before breakup as well as during and just after freeze up.

Modelling climatic impacts on ice-jam floods: a review of current models, modelling capabilities, challenges, and future prospects.

2021 ◽  
Author(s):  
Apurba Das ◽  
Karl-Erich Lindenschmidt
Keyword(s):  
Climate Change ◽  
Current Knowledge ◽  
Climate Change Impacts ◽  
Climatic Conditions ◽  
River Ice ◽  
Ice Jams ◽  
Ice Jam ◽  
Northern Latitudes ◽  
Climatic Impacts ◽  
Current Modelling

River ice is an important hydraulic and hydrological component of many rivers in the high northern latitudes of the world. It controls the hydraulic characteristics of streamflow, affects the geomorphology of channels, and can cause flooding due to ice-jam formation during ice-cover freeze-up and breakup periods. In recent decades, climate change has considerably altered ice regimes, affecting the severity of ice-jam flooding. Although many approaches have been developed to model river ice regimes and the severity of ice jam flooding, appropriate methods that account for impacts of the future climate on ice-jam flooding have not been well established. Therefore, the main goals of this study are to review the current knowledge of climate change impacts on river ice processes and to assess the current modelling capabilities to determine the severity of ice jams under future climatic conditions. Finally, a conceptual river ice-jam modelling approach is presented for incorporating climate change impacts on ice jams.

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