Comparative testing of numerical models of river ice jams

Abstract

Ice processes in general, and ice jams in particular, play a dominant role in the hydrologic regime of Canadian rivers, often causing extreme floods and affecting the life cycle of many aquatic, terrestrial, and avian species. Various numerical models have been developed to help simulate the formation and consequences of these very dynamic and often destructive jam events. To test and compare the performance of existing models, a series of three tests have been devised and coordinated by a task force appointed by the Committee on River Ice Processes and the Environment (CRIPE). The results indicate that the overall performance of the models is good when calibration data are available, but considerably more varied when the models are applied in uncalibrated or “blind” mode. However, the diversity of results in the blind mode may be attributed more to the variations in perceptions of the physical processes by the users, as compared to the mechanics of the numerical computations.

Ice jam modelling and field data collection for flood forecasting in the Saint John River, Canada

“…This can be a user‐specified value, applicable to the entire length of the jam, or a model‐generated function of jam thickness (Nezhikhovskiy, ). The latter option is used exclusively herein, on the basis of early runs that indicated improved model performance (Tang and Beltaos, ) as well as on extensive empirical evidence (Beltaos, ; Carson et al ). Thickness of sheet‐ice cover ( h i ). Porosity ( p ) of the rubble comprising the jam, invariably taken as 0.40. Internal friction angle ( φ ) of the rubble comprising the jam, default value = 45°. Ratio of lateral‐to‐longitudinal stresses within the rubble mass ( K 1 ), default value = 0.33. The user's manual offers no other guidance on how to select K 1 ; consequently, the default value has been used in all runs described herein.…”

“…This can be a user-specified value, applicable to the entire length of the jam, or a model-generated function of jam thickness (Nezhikhovskiy, 1964). The latter option is used exclusively herein, on the basis of early runs that indicated improved model performance (Tang and Beltaos, 2008) as well as on extensive empirical evidence (Beltaos, 2001;Carson et al 2011). 8.…”

“…Several public domain models of ice jams are available (e.g. ICEJAM, RIVJAM, Hydrologic Engineering Centre's River Analysis System (HEC‐RAS); Carson et al , ). They are based on similar differential equations (steady‐state one‐dimensional flow; stability of ice rubble, which is considered a granular medium); however, they utilize different solution methods and assumptions concerning the key conditions at the toe (downstream end of the jam).…”

Probability prediction of peak break‐up water level through vine copulas

“…The basic principles of ice jam stability, as formulated by Pariset, Hausser, and Gagnon () and Uzuner and Kennedy (), are common model features for these hydraulic models, whereas the hydraulic roughness of the underside of the ice jam, ice jam grounding, numerical solution algorithms, and other supplementary aspects are handled differently in each hydraulic model. Carson et al () indicated that the overall performances of these hydraulic models are good when calibration data are available, but a lack of detailed measurements may lead to discrepancies among model predictions for the water level downstream of the jam. Moreover, the predictive capability of a hydraulic model is hampered by the brevity of the event and the ever changing flow and ice conditions (Beltaos, Rowsell, & Tang, ; Blackburn & Hicks, ).…”

Ice-Cover and Jamming Effects on Inline Structures and Upstream Water Levels

“…There are several ways an ice jam can create complexities with the normal river flow causing serious economic and ecological effects (Prowse et al, 1994;Beltaos et al, 2001). Most scientific literatures (e.g., Bolsenga, 1968;Henoch, 1973;Smith 1980;Beltaos, 1983;Lu et al, 1999;She et al, 2006;Kalra and Ahmad, 2012;Paz et al, 2013;Carson et al, 2011) have depicted the ice jam-induced flooding and other effects on ecosystem. Growth of ice cover may initiate swift increase in river water level instigating inundation and destruction to property and infrastructures such as bridges, roads, and buildings.…”