For ice-jam flood forecasting it is important to differentiate between intact ice covers and ice runs. Ice runs consist of long accumulations of rubble ice that stem from broken up ice covers or ice-jams that have released. A water wave generally travels ahead of the ice run at a faster celerity, arriving at the potentially high flood–risk area much sooner than the ice accumulation. Hence, a rapid detection of the ice run is necessary to lengthen response times for flood mitigation. Intact ice covers are stationary and hence are not an immediate threat to a downstream flood situation, allowing more time for flood preparedness. However, once ice accumulations are moving and potentially pose imminent impacts to flooding, flood response may have to switch from a mitigation to an evacuation mode of the flood management plan. Ice runs are generally observed, often by chance, through ground observations or airborne surveys. In this technical note, we introduce a novel method of differentiating ice runs from intact ice covers using imagery acquired from space-borne radar backscatter signals. The signals are decomposed into different scatter components—surface scattering, volume scattering and double-bounce—the ratios of one to another allow differentiation between intact and running ice. The method is demonstrated for the breakup season of spring 2018 along the Athabasca River, when an ice run shoved into an intact ice cover which led to some flooding in Fort McMurray, Alberta, Canada.

Abstract Forecasting ice jams and their consequential flooding is more challenging than predicting open water flood conditions. This is due to the chaotic nature of ice jam formation since slight changes in water and ice flows, location of the ice jam toe along the river and initial water levels at the time of jam formation can lead to marked differences in the outcome of backwater level elevations and flood severity. In this paper, we introduce a novel, operational real-time flood forecasting system that captures this stochastic nature of ice-jam floods and places the forecasts in a probabilistic context in the form of flood hazard maps (probability of flood extents and depths). This novel system was tested successfully for the ice-cover breakup period in the spring of 2018 along the Athabasca River at the Town of Fort McMurray, Canada.

Abstract Ice phenology, defined as the timing of freeze-up and ice-cover breakup, plays a key role in streamflow regimes in cold-region river catchments. River freeze-up and ice-cover breakup events are controlled by meteorological and hydrological variables. In this study, we present a modelling framework consisting of a physically-based semi-distributed hydrological model and the integration of a 1D stream temperature model that can predict the ice duration in cold region rivers. The hydrological model provides streamflow and hydraulic parameters for the stream temperature model to obtain instream water temperature. The model was successfully applied in the Athabasca River basin in western Canada. Calibration was carried out using the water temperature recorded in the stations at the towns of Hinton, Athabasca and Fort McMurray. Model results show consistent correspondence between simulated freeze-up and breakup dates and the hydrometric station data. In the main tributaries of the basin, freeze-up timing spans from the last week of September to the second week of November and ice-cover breakup occurs from the second week of March to the last week of May. The model presents an application of water temperature and ice phenology simulation which can be incorporated in ice-jam flood forecasting and future climate change studies.

Monitoring spatiotemporal variations of river ice covers is critical for selecting safe ice transportation routes. The coherence of synthetic aperture radar (SAR) interferometry (InSAR) conveys imp...

The monitoring of river ice development is a crucial guidance indicator to establish safe crossings along river ice covers. This is the first study, based on our knowledge, to understand the interactions between river ice cover structures and radar signals and to further monitor ice development using C-band synthetic aperture radar images. The study was applied to the Slave River, Canada, using the Freeman–Durden decomposition of quad-pol C-band Radarsat-2 FQ14W images and ice core crystallography analysis. Results demonstrate that the combination of volume and surface scattering can be used to monitor ice cover development that cannot be interpreted from single polarization images, such as Radarsat-2 spotlight images used in this study. These results indicate that the decomposed quad-pol Radarsat-2 images can provide a more effective guide than the single-pol Radarsat-2 SLA images to select safe ice transportation routes. This decomposition approach can be extended to other snow and ice covered rivers.