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

Publication: Environmental Reviews
23 April 2021


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 the impacts of future climate on ice-jam flooding have not been well established. Therefore, the main goals of this study are to review current knowledge regarding climate change impacts on river ice processes and to assess 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.


La glace de rivière est une composante hydraulique et hydrologique importante de nombreuses rivières dans les hautes latitudes nordiques dans le monde. Elle contrôle les caractéristiques hydrauliques du débit des cours d’eau, affecte la géomorphologie des canaux et peut provoquer des inondations en raison de la formation d’embâcles pendant les périodes de gel et de débâcle de la couverture de glace. Au cours des dernières décennies, les changements climatiques ont considérablement modifié le régime des glaces, affectant la gravité des inondations dues aux embâcles. Bien que de nombreuses approches aient été développées pour modéliser les régimes de glace de rivière et la gravité des inondations par embâcle, les méthodes appropriées qui tiennent compte des impacts du climat futur sur les inondations par embâcle n’ont pas été bien établies. Par conséquent, les principaux objectifs de cette étude sont de passer en revue les connaissances actuelles concernant les impacts des changements climatiques sur les processus de glace de rivière et d’évaluer les capacités actuelles de modélisation pour déterminer la gravité des embâcles dans des conditions climatiques futures. Enfin, une approche conceptuelle de modélisation des embâcles de rivière est présentée pour intégrer les impacts des changements climatiques sur les embâcles. [Traduit par la Rédaction]

1. Introduction

River ice is one of the major components of the hydrologic regime in the world’s high northern latitudes where the majority of rivers are seasonally affected by river ice (Prowse et al. 2007; Yang et al. 2020). Whether it is stationary on the riverbank, anchored to the river bottom, suspended in the water column, or moving with the river flow, river ice affects the hydrologic and hydraulic conditions of rivers, resulting in a range of positive and negative impacts on riverside communities, economies, and ecosystems (Beltaos 1996; Prowse 1994, 2001).
River ice has a significant influence on the hydraulic conditions of a river. Figure 1 shows stage–discharge relationships for different hydrological and ice processes along the Athabasca River at Fort McMurray. The hydrometric gauge data indicated in Fig. 1 are maintained by the Water Survey of Canada (WSC), Environment and Climate Change Canada (ECCC). The streamflow data are not estimated directly, but rather through a stage–discharge model that has been established from the direct measurements of discharge and water level under open-water conditions at the station; however, they are estimated under ice-covered conditions in the river, which is indicated by B-flags in the gauge recordings. The B-flags designate the ice-on and ice-off dates along the river at the hydrometric gauging station. During a season, the first B-flag indicates the beginning of ice effects on river flows at freeze-up at or near the gauge station. Similarly, the last B-flag indicates the last day of ice effects on the streamflow. The first B-flag records commencement of the ice-cover formation at or near the gauge station and the last B-flag marks when the ice has cleared from the gauging site.
Fig. 1.
Fig. 1. Stage–discharge relationships at Water Survey of Canada’s gauge station along the Athabasca River below Fort McMurray.
The observed relationship illustrates that under open-water conditions, there is a deterministic relationship between water-level elevation and stream discharge, in contrast to the relatively scattered distributions depicting the relationship between water-level elevation and stream discharge during freeze-up and spring ice-cover breakup. The water-level elevations, however, are relatively consistent and characterized by low flow conditions when the ice cover is intact. The data presented in Fig. 1 are field-survey data collected during conditions of intact ice cover at the gauge station. The ice-affected instantaneous maximum water-level elevations are highly inconsistent with their corresponding discharges, as instantaneous maximum water-level elevations could be occurring due to extreme ice-jam formation and upstream ice-jam release.
The presence of river ice disrupts the unique open-water stage–discharge relationship because ice changes the conveying capacity and hydraulic characteristics of rivers. The presence of ice increases a river’s wetted perimeter and overall channel resistance, which alters the velocity profile (low streamflow velocity) and forces water levels to rise (Beltaos 2014). If the geomorphology of the channel remains unchanged, the open-water stage–discharge relationship is usually curvilinear and very simple to observe, as it mostly depends on channel discharge. Ice-jam water-level conditions, however, are challenging and difficult to monitor because they are controlled by many additional parameters, not only stream discharge. These parameters include various river ice parameters (e.g., ice strength, porosity, volume, ice-cover type), river width, and ice-jam toe location and length. These parameters are often difficult to measure during ice-jam conditions, and their impacts on river hydraulics are often unpredictable; therefore, for a given discharge, a range of water levels is possible for both freeze-up and breakup jams.
The changes in water level or backwater height due to the ice cover can be estimated from the difference between ice-covered and open-water depths, as described in a study by Beltaos (1982). This equation may work well under a static or steady ice-covered condition; however, dynamic ice conditions such as those during ice jams may require the consideration of additional parameters. Under an equivalent discharge, large ice-cover thickness and roughness can raise water levels to twice or three times the open-water depth. This effect is usually higher during freeze-up and breakup. At freeze-up, ice floes start to accumulate to form an initial ice cover that can protrude downward quite far into the flow, hence significantly increasing flow resistance and constricting the flow. As winter progresses, thermal smoothing reduces the roughness of the ice-cover underside; however, frazil-ice deposition can occasionally result in a hanging dam formation, which may lead to significant backwater effects. The largest river ice effect occurs during the spring ice-cover breakup when the flow of broken rubble ice is arrested, causing ice jams to form in the river channel, as breakup ice jams tend to be thicker and rougher compared with freeze-up jams. Moreover, mid-winter breakup and associated ice-jam effects can be as significant as spring ice-jam events, as they can create high water levels and freeze in place to persist throughout the winter.
Freeze-up usually occurs during low flow conditions, when precipitation stops contributing to runoff, as it starts to accumulate in the form of snowfall (Beltaos 2014). The low river flow conditions are usually consistent throughout winter due to the reduction in flow contributions from runoff, upstream storage, and groundwater fluxes. The amount of flow can be modified due to ice-cover formation in three ways: reduction of the groundwater supply due to freezing in small and shallow rivers; loss of a portion of flow volume due to ice-cover formation and thickening (although this storage effect is usually active for a short period after freeze-up and stores small magnitudes of overall flow except for very small streams, as the rate of freezing decreases with ice-cover thickening); and hydraulic storage or flow abstraction due to ice-cover progression in the upstream direction, which abstracts the largest magnitude of flow (Prowse and Beltaos 2002). Hydraulic abstraction remains effective as long as the ice cover progresses in the upstream direction due to the accumulation of ice floes from upstream stretches; eventually, the flow is no longer stored but “returned to its unperturbed value” (Beltaos 2014). The stored water eventually melts during spring breakup to contribute to the total streamflow.
Ice jamming and subsequent flooding during the ice-cover breakup period can damage property and infrastructure, interfere with ship and boat traffic, and hinder hydropower generation and hydrometric gauging (Beltaos 2008a, 2008b). Extreme ice jams are one of the major sources of physical disturbances that are detrimental to many instream aquatic species and their habitats (e.g., severe fish mortality and loss of spawning grounds). Adjusting for inflation on previous estimations of damage, French (2018) reported that the annual cost of river ice jams in North America is about 300 million USD; however, ice-jam flood (IJF) events have also been found to be beneficial to floodplains and perched basins and ponds in some deltaic environments where high water staging attained by ice jamming both replenishes floodplains and perched basins with essential moisture and sediments and maintains water balances that are favourable to these ecosystems (Peters et al. 2006). The ice-jam formation is also affected by sediment transportation as sediment deposits and accumulates during winter due to low flow and bed shear stresses, altering the river geomorphology through bank erosion and disrupting aquatic habitat (White et al. 2006; Knack and Shen 2018).
It is now firmly established that the world’s climate system has warmed significantly over the last several decades, impacting many hydrological and meteorological processes (IPCC Core Writing Team et al. 2014). Implications have been significantly greater in the Northern Hemisphere compared with the Southern Hemisphere (Feulner et al. 2013) due to interhemispheric temperature asymmetry. Several studies have demonstrated shifts in the timing and magnitude of total precipitation and river discharge, a decreasing trend in snow cover, melting of sea-ice glaciers, thawing of permafrost, earlier river ice-cover breakup, and changes in many biological and geomorphological processes (Bush et al. 2014; Callaghan et al. 2011; DeBeer et al. 2016; Derksen and Brown 2012; Hinzman et al. 2005; Prowse et al. 2009; Serreze et al. 2000; White et al. 2007). In Canada, studies suggest that these climate-related changes could contribute to many extreme events such as widespread forest fires, prolonged drought and dry conditions, and severe flood events (Bush et al. 2014). In 2011, property damage due to extreme events cost Canadian insurance companies $1.7 billion in insured losses. Although there are many uncertainties in climate change related research findings, scientists predict that climate change will increase the frequency and (or) intensity of extreme events in northern regions (Warren and Lemmen 2014).
As many Canadian communities are located along the banks of major rivers that are affected by severe ice-jam conditions almost every year, changes in ice regimes may result in wide-ranging consequences from severe damage to human fatalities. The 2020 ice-jam flood event along the Athabasca River at Fort McMurray is a recent example of the severity of ice-jam flooding. This event may or may not have been directly connected to climate change impacts; however, it resulted in one human fatality and millions of dollars in property and business losses for the community. Therefore, with the current implications and projected future changes, it is necessary to assess the future frequency and severity of ice-jam floods. Although some research has investigated the duration of the ice-cover period (de Rham 2019; Lemmen et al. 2008; Magnuson et al. 2000a, 2000b; Prowse et al. 2011) and frequency analysis (Das et al. 2020), appropriate modelling approaches to assess climate change impacts on ice-jam flooding have not been well established. Therefore, given the broad economic and environmental significance of ice-jam floods and their sensitivity to a changing climate, a clear understanding of current modelling capabilities for simulating climate change impacts is required. Thus, the main objective of this review is to investigate the current modelling capabilities for quantifying the impacts of climate change on ice-jam flooding. The specific objectives are to (i) assess the current status of research related to climate change impacts on river ice regimes and associated extreme events, (ii) evaluate current modelling capabilities for simulating future climate impacts on river ice processes, and (iii) provide recommendations for future research.

2. Climatic control of river ice processes

2.1. Brief overview of climate change in the Northern Hemisphere

The global climate system is changing, with changes to climatic behavior (mean and variability) projected beyond the 21st century (IPCC Core Writing Team et al. 2014). Compared with the Southern Hemisphere, the average annual surface air temperature in the Northern Hemisphere is 1 to 2 °C higher due to increased ocean heat transport and reduced snow and ice albedos (Feulner et al. 2013; Romero-Lankao et al. 2014). The interhemispheric temperature asymmetry (i.e., the temperature difference between the Northern Hemisphere and Southern Hemisphere) has grown with a significant positive trend, especially since 1980 (Friedman et al. 2013). This asymmetry, which is considered to be an emerging indicator of global climate change, has also been attributed to the decline in sea ice and snow cover in the Northern Hemisphere (Stouffer et al. 1989).
In Canada, a statistically significant increase in air temperature has been observed. Recent analyses have shown a statistically significant 1.5 °C rise in annual air temperature across Canada between 1950 and 2010 (Vincent et al. 2012). Even after removing the effects of climatic variability, Vincent et al. (2015) found a statistically significant increasing trend in air temperature. Annual precipitation trends have also changed over the years (Warren and Egginton 2008; Nordstrom 2009; Turcotte et al. 2019). In winter, an increasing trend has been observed in the northern part of the country, while a decreasing trend has been revealed in the southwestern part of the country (ECCC 2016). In spring, overall precipitation has increased across Canada (Bush and Lemmen 2019).
In a warming climate, precipitation is less likely to occur as snowfall than as rainfall events. A study by Kapnick and Hall (2012) showed that the recent snowpack changes in western North America have been caused by regional-scale warming. This finding is contrary to the prediction that a shift from a snow-dominated to a rain-dominated regime does not significantly affect the mean streamflow. Berghuijs et al. (2014), in their study of the contiguous United States, found that a shift in precipitation from snow to rain decreases mean streamflow. In Canada, overall snow cover and accumulation of seasonal flow has also been decreasing over the years (ECCC 2016). On a global scale, the largest changes in the hydrological cycle due to warming are predicted for the snow-dominated basins of mid to higher latitudes, because adding or removing snow cover fundamentally changes the capacity of the snowpack to act as a reservoir for water storage (Nijssen et al. 2001).
An assessment of future scenarios using multimodel ensembles from phase 3 (B1 and A2 scenarios) and phase 5 (RCP 4.5 and 8.5) of the Coupled Model Intercomparison Project (CMIP) revealed that interhemispheric temperature asymmetry is likely to increase in all future scenarios (Friedman et al. 2013). Another assessment of 20 global climate models from the CMIP5 under the RCP 8.5 scenario projects strong warming (>8 °C) in high-latitude regions (north of 60 °N) with moderate warming (5 to 7 °C) in the mid-latitudes (40 to 60 °N) of the Northern Hemisphere (Feng et al. 2014). Other studies (e.g., Barnes and Polvani 2015; Miao et al. 2014; Peacock 2012) have also pointed out that warming will accelerate with increasing latitude, and as a result, the Northern Hemisphere is likely to warm disproportionately. The resultant change in environmental conditions will pose risks not only to northern natural systems, but also to local communities that have been historically dependent on these natural systems for their livelihood, cultural integrity, and traditional way of life (Wesche and Armitage 2014).

2.2. Current climate-induced impacts on river ice

Many factors related to the river ice regime could be affected by climate-induced changes such as the duration of the ice season, the thickness of the ice cover, and severity of ice jams (Beltaos and Prowse 2009). The following section summarizes key findings related to climate-induced impacts on river ice.
Air temperature is a strong driving factor governing the ice-cover duration along rivers. Under a changing climate, higher air temperatures can delay ice-cover formation and expedite breakup during spring, resulting in shorter ice-cover durations along many rivers in cold regions (Beltaos and Prowse 2009). In contrast, if air temperatures trend towards colder conditions, the duration of ice cover increases. Long-term data analyses related to river ice freeze-up and breakup dates in many studies reveal a decreasing trend in the overall duration of the ice-cover season along many rivers in northern regions (Beltaos and Prowse 2009; Ginzburg 1992; Soldatova 1992). Although there is large spatial variability in freeze-up dates, earlier breakup dates have been observed in many locations. Strong trends of later freeze-up and earlier breakup along many rivers in European Russia, western Siberia, and the Danube have shortened ice-cover duration by about 20 days per century (Beltaos and Prowse 2001; Zhang et al. 2001; Borshch et al. 2001); however, an opposite pattern of longer ice-cover duration has been reported in eastern Siberia and Atlantic Canada (Turcotte et al. 2019; Beltaos and Prowse 2001; Zhang et al. 2001). Smith (2000) examined the long-term river ice data of nine Russian Arctic rivers and found no significant trends in eight data categories, except for the timing of ice-cover melt. Breakup dates 1 to 3 weeks earlier (shorter ice-cover duration) were observed along the Pechora, Ob, Olenek, Indigirka, and Kolyma rivers, while earlier freeze-up dates resulted in longer ice-cover periods along the Onega, Varzuga, and Yenisei rivers but not along the Mezen River. Several similar ice phenological studies have also been carried out for the rivers of northwestern European Russia, Lithuania, and Mongolia (Batima et al. 2004; Stonevicius et al. 2008; Vuglinsky 2006). The results of these studies found significant trends of later freeze-up and earlier breakup dates. Zachrisson (1989) recorded an earlier breakup date along the Tornealven River in northern Scandinavia.
Many studies related to ice-cover breakup dates have also been conducted in Canada (Beltaos 2002, 2004; Chen and She 2020; Doyle and Ball 2008; Janowicz 2017; Rannie 1983; Williams 1970) and the United States (US) (Hodgkins et al. 2005; White et al. 2007), all of which found trends of earlier ice-cover breakup dates and shorter ice-cover durations for many rivers. Chen and She (2020) recently completed a large-scale study on spatial and temporal variations in spring ice-cover breakup in five river basins in Canada that identified earlier breakup trends, mainly resulting from warmer air temperatures. Another comprehensive study of trends in river ice in Canada by Lacroix et al. (2005) demonstrated a clear pattern towards earlier breakup in most of the country. However, due to complex spatial variability in freeze-up regimes, it is difficult to discern any clear temporal trends. While all the studied rivers in Alaska and Maine found earlier breakup trends, only two of them showed later freeze-up trends (White et al. 2007). Trends toward shorter freshwater-ice durations over much of the Circumpolar North closely correspond to the increasing air temperature trends observed over most of this region, and these trends are most pronounced at the end of the last century (Magnuson et al. 2000b; Prowse et al. 2011).
As the thickness of river ice cover is difficult and often dangerous to measure, very few studies have been carried out to analyze historical trends and climate change impacts on river ice thickness. A long-term ice thickness data analysis along the Piscataquis River in central Maine (US) detected a total decrease of 23 cm from 1912 to 2001 (Huntington et al. 2003). Vuglinsky (2006) reported that river ice-cover thickness had decreased by 2–14 cm along most Russian rivers, including rivers of European Russia. Significant decreases of 20–80 cm in river ice-cover thicknesses were observed in Mongolian rivers from the 1960s to 2000 (Batima et al. 2004). Although climate change impact studies on river ice-cover thicknesses in Canada are sparse, Beltaos (2004) applied an indirect approach to determine maximum ice thicknesses along two Canadian Atlantic rivers, finding no significant trends.
While a larger pool of literature is available on river ice freeze-up and breakup trends and a few studies report on ice thickness trends, very limited work has examined the impact of climate change on the severity of extreme ice-jam events. Researchers have reported that the frequency of mid-winter breakup and associated ice-jam flooding has also increased in Canada and the US (Beltaos and Prowse 2001; Prowse et al. 2002; Beltaos et al. 2007a, 2007b; White et al. 2007; Carr and Vuyovich 2014; Newton et al. 2017) as a result of mild weather conditions (temperature above 0 °C) and winter precipitation (rain-on-snow events). Beltaos (2002) examined long-term hydrodynamic data along the Saint John River in eastern Canada from the 1920s to the 1990s and found a dramatic increase in peak winter flows, as mild days increased during the winter. Mid-winter breakups were also reported along the St. Lawrence River, Quebec, Canada (Turcotte et al. 2020), the Picataquis River in Maine, US (Huntington et al. 2003), the Salmon River near Salmon, US (White et al. 2006), the Fox and Grande rivers in the midwestern US (Carr and Vuyovich 2014), and the Klondike River, Yukon, Canada (Janowicz 2010). Reported mid-winter breakups and ice-jam formation along these rivers coincided well with the increased trends of mild winter days and rain-on-snow events (Newton et al. 2017). Turcotte et al. (2019) report that a rise in air temperature and drop in winter precipitation reduces the chances of ice-jam floods, while a rise in winter precipitation (rainfall) exacerbates winter breakups and associated ice jams. However, if thinner ice covers form due to warm weather conditions during freeze-up and winter, the chances of ice-jam formation and flooding will further reduce, as ice simply washes out of the channel. A mid-winter breakup can create several persistent open-water stretches throughout winter that can generate more frazil ice and lead to relatively greater ice-cover thickness. In the Saint John River, Canada, detailed field data measurements after mid-winter breakup events suggest that the ice-cover thickness was significantly higher in locations where jams occurred than the normal ice-cover thickness of the reach (Beltaos et al. 2003). Therefore, winter ice-jam formation can be responsible for aggravating the spring ice-cover breakup by providing more ice in the channel before the spring breakup (Turcotte et al. 2019; Beltaos 2002).
On the other hand, a rise in spring precipitation has a greater probability of more frequent ice-jam formation during spring breakup if the other river ice parameters and conditions remain favourable (Beltaos and Burrell 2003). Both increased and decreased spring flow trends have been observed along rivers in northern regions, and these trends influence and shift ice-jam regimes in many rivers (Zhang et al. 2001). Studies show that there was an increasing trend in spring flows in southwestern Canada (Zhang et al. 2001) and a decreasing trend in the northwestern US (Lins and Michaels 1994). A recent study by Rokaya et al. (2018) reported that there were distinct shifts in both the timing and magnitude of ice-jam floods from 1903 to 2015 in Canada. While an earlier ice-jam flood tendency was observed along rivers in southeastern Canada and some western parts of Canada, a delayed ice-jam flood tendency was observed in central and Atlantic Canada. Analyses of trends on the magnitude of ice-jam flooding in rivers show that the severity of flooding has increased along rivers in the northwestern and some southcentral regions of Canada, while severity has decreased in Alberta, Atlantic Canada, southern Ontario, and northern regions of Saskatchewan and Manitoba.
A reduction in the frequency of ice-jam floods in many deltas in Canada such as the Peace–Athabasca Delta (PAD) and Slave River Delta (SRD) has also been reported, suggesting a decreasing trend of ice-jam severity since the 1960s (Das 2015). This decreased severity has an adverse impact on delta ecology such as the drying of perched basins and ponds that provide habitat for many aquatic species in the deltas. As the rivers are regulated, only part of the changing signal is a result of regulation; other parts are also related to climate change (Beltaos et al. 2006; Beltaos 2014; Wolfe et al. 2020; Beltaos and Peters 2020). Many studies indicate that the significant reduction in the frequency of spring ice jams in the PAD is a result of the combined impacts of flow regulation at the W.A.C. Bennett Dam and extensive climate variation within the Peace River basin (Prowse and Conly 1998; Beltaos et al. 2006; Beltaos 2014). In recent years, there has been a lot of discussion regarding the causes of the drying trend in the Canadian delta, i.e., whether the trend is a result of regulation or climate change (Beltaos 2018; Timoney et al. 2019; Beltaos and Peters 2020; Wolfe et al. 2020). Based on historical data analyses, Beltaos (2018) claimed that river regulation was a key factor in the significant drying trend observed in the PAD since 1967. Timoney et al. (2019) disagreed with this finding and argued that regulation may not be the major cause of drying in the delta and it is rather due to “multi-decadal net desiccation and climate-driven declines in water levels”.

2.3. Expected climate change impacts on river ice regimes

Although there are a limited number of studies involving long-term observation of complex ice-cover factors such as ice thickness and the severity of ice breakup and jams, many studies on the long-term changes in freeze-up and breakup timing and duration of river ice cover have investigated the impacts of climate change on ice regimes. Over the years, many studies have examined and identified some foreseeable changes in river ice regimes.
Under a warming climate scenario in the future, it is expected that ice-cover duration in rivers will be shorter due to higher water and air temperature during freeze-up and spring breakup. A recent study on the future of global river ice by Yang et al. (2020) estimates that global mean river ice duration will likely decrease by 16.7 days under RCP 8.5 and 7.3 days under RCP 4.5 scenarios in the future (2080–2100) compared with the period of 2009–2029. Borshch et al. (2001) estimated expected changes in river ice duration from a uniform 2 °C increase in air temperature across various locations in the former Soviet Union. The results from this study showed that freeze-up and spring breakup dates would be delayed by 4–12 days and advanced by 4–10 days, respectively. Several studies have also reported that an expected increase in air temperature of 3–7 °C would result in a substantially higher number of breakup days (15–35) in northern Canada (Magnuson et al. 2000a, 2000b; Prowse et al. 2002). A comprehensive analysis of monthly temperature projections for the period 2040–2069 revealed that the ice-cover duration in many places in Canada would be shortened by approximately 20 days compared with the baseline period of 1961–1990 (Prowse et al. 2007). Modelling work carried out by Andrishak and Hicks (2008) predicted a reduction of 28 days in ice-cover duration along the Peace River, Alberta, Canada, by the mid-21st century. However, these findings regarding the relationship between ice dates and air temperature may not be reliable under future climatic conditions, as other governing parameters that influence ice regimes such as river discharge could also change under altered climatic conditions. For example, while increased river flows could delay freeze-up and advance spring breakup, low-flow conditions could advance freeze-up and delay breakup. Andres and Van der Vinne (1998) reported that reduced flow conditions often accelerate earlier ice-cover formation along the Peace River, which is contrary to the expected trend with warmer climatic conditions.
With changes in the timing and duration of ice-cover formation, warmer climatic conditions can change overall ice regimes along a river. An extremely cold climate would promote frazil-ice generation and accelerate complete ice-cover formation, while a warmer climate would impede both ice-cover formation and frazil-ice generation (Prowse and Beltaos 2002). An increase in flow would enhance turbulence and frazil-ice generation and lead to more shoving and thickening of the initial ice-cover formation. The effect of warmer conditions may have a similar effect to an increased flow environment, as warmer air temperatures would reduce the internal strength of an ice accumulation, leading to more telescoping of the ice cover as well. Thus, the combination of higher flows and air temperature could increase the severity of freeze-up jamming (Beltaos and Prowse 2009).
It is expected that changes in winter air temperatures could have a significant impact on the total thickness of the ice cover. Warmer air temperatures may produce thinner ice cover in temperate regions, while extreme cold temperatures may produce a thicker ice cover in Arctic areas. Studies suggest that there will be many rivers that will be fully or partially ice free under the pronounced warmer climatic trends in the future (Beltaos and Prowse 2009). Overall, it is predicted that under warming climatic conditions, ice cover will be relatively thin and weak and winter discharge will increase, which could enhance freeze-up consolidation and mid-winter breakup events along many rivers; hence, the severity of mid-winter ice-jam flooding will likely increase. Lamichhane et al. (2020) estimated winter ice-cover thickness along the Grand River, Ohio (US), under various RCP scenarios (2.6, 4.5, and 8.5) using Stefan’s equation and predicted that thicknesses would decrease considerably in the period 2015–2098.
While warmer climatic conditions would alter the overall ice regimes, they could also affect the severity of ice-cover breakup and jamming. The severity of ice-cover breakup and associated flooding are dictated by the type of ice-cover breakup, i.e., thermal or mechanical. Thermal breakup occurs when mild weather and low-flow conditions of the river cause the ice cover to deteriorate gradually. The ice cover breaks and disintegrates in place and is flushed away by the moderate flow. In this type of breakup, the possibility of ice-jam formation is minimal and backwater levels remain low. Mechanical breakup, on the other hand, is triggered by rapid and high run-off conditions, which lead to premature ice-cover breakup before significant thermal ice-cover deterioration occurs. This type of breakup may lead to severe ice-jam formation and has great potential to produce large-scale flooding (Beltaos 2003). The resulting ice jams from a mechanical breakup can be more persistent than those from a thermal breakup due to the strong mechanical resistance of the ice cover, requiring a significant driving force to dislodge the jams. A premature breakup event, which occurs due to the combination of thermal effects and mechanical fracture, can often create extreme flooding.
Changing climatic conditions can modify natural processes of both the driving and resisting forces that govern breakup regimes (Beltaos and Prowse 2009). The driving forces are usually characterized by drag forces exerted by the moving water on the underside of the ice cover, the thrust of moving water on the ice cover, and the component of the weight in the sloping direction acting on the ice cover or ice jam. These forces usually depend on upstream ice conditions and flow discharge, which is mainly affected by the amount of total precipitation (e.g., rainfall and snowmelt) (Turcotte et al. 2019). The resisting forces are usually characterized by ice competence, which depends on ice thickness and flexural strength. The first two factors (ice thickness and strength) directly influence the severity of the breakup and are strongly controlled by the intensity of atmospheric heat fluxes. For example, a relatively long pre-breakup melt period leads to a greater probability of thermal breakup and reduced probability of mechanical breakup. The pre-breakup melting from atmospheric fluxes also depends on the type of ice cover that forms during freeze-up and the amount of snow on the ice cover at breakup. A greater depth of snow could create strong insulation that reduces the rate of ice-cover thinning; the snow must melt before the underlying ice cover starts to melt. Also, the snow layer reduces solar radiation impinging on the ice cover to weaken it. Changes in the internal strength of ice are usually controlled by the intensity of solar radiation absorption by the ice sheet (Ashton 1989; Beltaos 1995, 2008a, 2008b); therefore, a general increase in cloudiness could increase the ice competency due to less shortwave radiation, thus increasing the breakup resistance and probability of severe ice-jam flooding. Rapid snowmelt events and ablation of ice sheets due to a higher magnitude and intensity of atmospheric fluxes can increase river discharge and the probability of a mechanical ice-cover breakup. Hence, freeze-up levels of a season will play a vital role in controlling the frequency of ice-jam occurrences. Higher freeze-up stages mean that higher runoff is required to dislodge the ice cover from the banks and other boundary supports at breakup. Therefore, when other factors are favourable, high freeze-up levels will reduce the probability of major ice-jam occurrences during breakup in the future.
Because warmer climatic conditions and changing precipitation patterns are pronounced in flow regimes in Canada, the severity of ice-jam floods will be highly influenced by these factors. A warmer winter under a future climate scenario would directly reduce ice-cover thickness and thus the severity of ice jams. While a reduction in winter and spring precipitation will tend to cause fewer mid-winter breakups and less severe ice-jam floods, greater winter and spring precipitation may lead to frequent winter breakups, ice jams, and dynamic spring breakups, hence increasing the severity of ice-jam floods (Turcotte et al. 2019). Rokaya et al. (2019) show that relatively low flow conditions at breakup would reduce the probability of ice-jam flooding along the Athabasca River at Fort McMurray in the period from 2041 to 2070. Another similar study at the same site by Das et al. (2020) also shows that the frequency of ice-jam flooding is likely to be reduced in the future. However, both studies concluded that extreme ice-jam floods are still probable under certain climatic conditions.
Apart from these direct climate change impacts on river ice regimes, ice properties, and streamflow discharge, there are some indirect factors that could also impact ice regimes and the severity of ice-jam floods under future climatic conditions (Turcotte et al. 2019). A higher amount of fall precipitation in the future would increase flows at freeze-up, resulting in higher freeze-up levels. These higher levels may, in turn, increase discharge thresholds, which could initiate breakup, thus decreasing the probability of ice jams, especially for low-gradient rivers (Beltaos et al. 2006; Turcotte et al. 2019). The geomorphology of a river can change more rapidly if there is increased open-water runoff. More dynamic ice regimes alter sediment transportation processes, which could change the location of ice jams and modify overall ice-cover and ice-jam processes (Kolerski and Shen 2015; Turcotte et al. 2019). Warmer groundwater influx will promote prolonged open-water sections in winter or reduce ice-cover strength along small streams, which could impact downstream ice-jam processes, as small streams usually flow into large rivers, e.g., the Clearwater River, which flows into the Athabasca River at Fort McMurray. Moreover, changes in hydrological regimes, permafrost thaw, sea-level rise, land use, and infrastructure development will have some level of impact on ice parameters and the severity of ice-jam floods (Turcotte et al. 2019).

3. Existing methodologies for determining climate change impacts on river ice regimes

In recent years, many attempts have been carried out to assess climate change impacts on river ice regimes, including statistical and empirical analyses and hydrological and hydraulic river ice-jam modelling (Rokaya et al. 2019; Timalsina et al. 2013; Turcotte et al. 2019, 2020; Yang et al. 2020). Statistical and empirical approaches are mainly used to analyze historical data to determine variability in long-term river ice processes and the correlation between different climatic parameters (including air temperature, snowfall, and rainfall) and variables of river ice regimes (such as ice duration, ice thicknesses, and ice-jam flood frequency). Historical data (discharge, water level, and ice-in and ice-out dates) are recorded at various hydrometric stations and documented through photographs, satellite imagery, and reports. However, river ice processes are often so dynamic and extreme that they can destroy the gauge station and interfere with the collection of ice and water-level information. An empirical approach such as degree-days or Stefan’s equation could be applied to estimate ice-in and ice-out dates or ice thickness, but these estimations are only approximate and are unable to accurately capture the dynamic processes of ice regimes. One of the main downsides of this approach is the large dataset required for both temporally and spatially distributed data along the rivers to fully understand climate change impact trends. More importantly, projecting a statistically significant historical trend into future climate scenarios may not be all that accurate or reliable. Many studies suggest that climate change impacts on dynamic river ice phenomena are not linear, and analyses require incorporation of evolving meteorological and hydrological variables. Although fairly high correlations (r2 = 0.6 to 0.7) between mean air temperature and ice-cover duration have been found (Ginzburg 1992; Soldatova 1992), river ice processes cannot be fully captured using only heat index parameters, as other climate-dependent parameters such as snow depth, solar radiation, and river discharge exert a large influence on river ice processes. Borshch et al. (2001) reported that incorporating river discharge with air temperature can significantly improve the prediction of changes to ice-cover breakup. However, studies (e.g., Bonsal et al. 2006; Schmidt et al. 2019) have also noted the influence of large-scale atmospheric and oceanic oscillations on ice duration, in addition to long-term climate change.
Different hydrological models (e.g., MESH, variable infiltration capacity (VIC)) are used to simulate snowmelt and river discharge conditions for both past and future scenarios using a variety of meteorological forcing data from global and regional climate models (Eum et al. 2017; Rokaya et al. 2020). Because runoff is an important variable controlling river freeze-up and breakup regimes, hydrographs simulated from a hydrological model can be used to indicate both freeze-up and breakup timing for comparison between historical and future freshets. Moreover, some hydrological models can simulate the amount of melting water from water that is stored in the channel (hydraulic and groundwater storage) in winter; the amount of melting water has a large impact on various breakup mechanisms in rivers (Beltaos 2017; Jasek et al. 2005). Although these hydrological models are able to simulate an important river ice governing variable (i.e., stream discharge), they are still unable to simulate river ice processes, ice-jam formation, and release events. Beltaos et al. (2006) applied the hydrological model WATFLOOD coupled with the ONE-D hydrodynamic model results to assess daily flow hydrographs for the historical period along the Peace River in western Canada. Although the hydrological model overestimated spring discharge, it was able to estimate the timing of spring runoff quite accurately. More recently, Rokaya et al. (2019) and Das et al. (2020) coupled hydrological modelling results (e.g., streamflow) with a river ice hydraulic model to examine the severity of ice-jam flooding along the Athabasca River at Fort McMurray under future climatic conditions. Such coupled modelling approaches have been shown to have great potential for assessing scenarios under future climatic conditions. Moreover, many river ice models exist that could capture river ice and ice-jam processes very well if adequate calibration data are available. River ice hydraulic models range from one-dimensional (1D) steady-state to 1D unsteady-state to two-dimensional (2D) models. The basic theory of many of the models has mostly been formulated based on studies by Pariset et al. (1966) and Uzuner and Kennedy (1976). Almost all the models have some common parameter and boundary condition inputs. Some parameters are user defined, and some are estimated based on empirical equations. Moreover, some river ice aspects such as the hydraulic roughness of the ice-cover underside during ice-jam formation, ice-jam grounding, ice-jam toe locations, and the volume of ice contributing to a jam are handled separately in each model. For example, while the RIVJAM steady-state model considers seepage through the voids of the jam during simulation, this phenomenon is ignored in the ICEJAM steady-state model (Healy and Hicks 1999). An important ice-jam parameter, the toe geometry, is inputted by the user in RIVJAM and calculated using a maximum erosive velocity principle. For detailed descriptions and differences of these two-steady state models, readers are referred to the study by Healy and Hicks (1999). ICEPRO and ICESIM are two similar models that solve the St. Venant equations of motion for both open-water and ice-covered stretches (Carson et al. 2011). However, a minor improvement in the ice shoving mechanism has been carried out in the ICEPRO model. River1D is a hydraulic flood routing model capable of modelling streamflow under both open-water and ice-covered conditions. The model uses the characteristic dissipative Galerkin finite-element scheme to solve the ice-jam stability equation with St. Venant equations (Hicks and Steffler 1992). HEC-RAS simulates ice-covered channels with a user-defined intact ice-cover thickness and wide-river ice-jam approach (Daly et al. 1998). In the ice-covered simulation, users are allowed to specify ice-cover thickness and roughness at each cross section, and in a wide-river ice-jam simulation, ice thickness is estimated by an ice-jam force balance. The hydraulic roughness is user defined or is estimated using empirical data. MIKE-11 is a commercially available model able to simulate various thermal ice processes. The model uses the finite-difference discretization approach to solve the 1D St. Venant equation. All of these models have the limitation of not being able to be applied to dynamic ice conditions.
RIVICE is a 1D fully dynamic river ice model that simulates various river ice processes. It solves time-varying flows using the St. Venant equations through the finite-difference solution (Environment Canada (EC) 2013). In this model, various river ice parameters such as hydraulic roughness, ice volumes, and ice thicknesses are user defined or solved by empirical equations. The main limitation of this model is its inability to simulate thermal ice covers along rivers.
RICE, RICEN, and CRISSP are 1D hydrodynamic river ice models that have been continually updated over the years. The updated version of CRISSP1D is more robust and applicable to complex river geometry and has various improvements in river ice phenomena such as under ice-cover ice transport, dynamic ice-cover stability, and secondary consolidation and breakup. In these models, a Lagrangian–Eulerian solution to the transport of thermal energy and ice equations is applied to estimate a thermal parameter, water temperature, and ice concentration. Ice-cover accumulation underneath the ice cover is calculated based on a critical velocity criterion, and a finite-difference formula is applied to estimate the ice-cover growth and decay (Chen et al. 2006); however, these models cannot handle complex flow patterns and river networks.
The DynaRICE model is a 2D hydrodynamic river ice model able to model ice jams and surface ice transport. The CRISSP2D model is an extension to the DynaRICE model to include thermal ice processes. The CRISSP2D can simulate complex flow conditions, the supercooling phenomenon, and dynamic ice transport and ice jams. The model solves 2D depth-averaged Navier–Stokes equations in a finite-element scheme by applying the streamline upwind Petrov–Galerkin method to estimate channel hydraulics. Ice dynamics and surface ice transport are estimated using a Lagrangian discrete parcel approach (Liu et al. 2006). One of the limitations of this model is its inability to consider vertical variations (three dimensions).
Because each model can be applied in a variety of hydraulic conditions and applications (e.g., freeze-up, ice-cover progression, and ice simulations) and performs based on its numerical solution algorithm to run each model, a good understanding of river ice processes, local climatic conditions, and channel morphology is required. A summary of available river ice models is given in Table 1.
Table 1.
Table 1. Summary of available river ice models.
Although applications of the above-listed models for the assessment of climate change impacts on river ice and ice-jam floods are sparse, some numerical models have been used to predict changes in ice regimes in rivers due to climate change. For example, Andrishak and Hicks (2008) applied the River1D thermal river ice process model to predict the duration and extent of ice cover along a Canadian river for a future climate analogue in the mid-21st century. The Canadian second-generation general climate model (CGCM2) provided the air temperature input for the model. Although this study shows good potential for using a numerical model to predict ice duration under future climatic conditions, a constant hydraulic boundary condition was assumed, which is very unlikely with continuous changing climatic conditions. In terms of thermal ice-cover simulations, River1D may have great potential to be incorporated into climate change studies to estimate some important modelling parameters such as ice-cover thicknesses, inflowing ice volumes, and timing of freeze-up and spring breakup. However, to apply it to a more comprehensive climate change study, improvements are still necessary for this model to incorporate dynamic ice-cover stability, hydraulic thickening, and snow-cover impact (Andrishak and Hicks 2008). Although there are several comprehensive models, e.g., CRISSP1D and CRISSP2D, that have been developed to simulate entire ice regimes from freeze-up to breakup, their applications in modelling climate change impacts on river ice are sparse. Therefore, the potentiality of these models being incorporated into climate change studies still needs to be investigated.
Timalsina et al. (2013, 2015) applied a gridded HBV tool for rainfall runoff and the Mike-Ice model for river ice to determine climate change impacts on river ice regimes. In this study, two GCMs, HadAm3H SRES (A2 and B2) and ECHAM4 SRES (B2), were downscaled to the study reach using an atmospheric regional climate model (RCM) to drive a hydrological model for simulating the future flow regime along a Norwegian river. Das et al. (2020) and Rokaya et al. (2019) applied the RIVICE hydrodynamic river ice model to assess the severity of ice-jam flooding. Input files for the hydrodynamic model were derived using available global circulation models (GCMs), the Community Climate System Model (CCSM), and the Third Generation Coupled Climate Model (CGCM3). These models were used to drive the Canadian Regional Climate Model (CRCM) to produce regional projections for the future. Both studies used stochastic modelling to simulate hundreds of ice-jam scenarios under future climatic conditions.
River ice hydraulic models can also be combined with empirical river ice models (Turcotte and Morse 2015) to examine future climate change impacts on river ice regimes. While empirical models can derive some of the important model parameters (e.g., the location of ice jams and the magnitude of streamflow), river ice models are required to simulate ice-jam water levels.
Although some geospatial modelling studies have been carried out over the years to understand the current impacts of river geomorphology on ice-cover and ice-jam locations (De Munck et al. 2017; Lindenschmidt and Chun 2014; Lindenschmidt and Das 2015), their application in climate change studies is sparse. Because they consider various geomorphological parameters to understand river ice processes, they can be applied to quantify future changes in river ice regimes or ice-jam processes (e.g., ice-jam location) if any geomorphological change occurs.

4. A conceptual modelling approach to determine future climate change impacts on river ice

The modelling of future climate change impacts on river ice regimes requires reliable estimates of input parameters under future climatic conditions. Common river ice and hydraulic parameters of ice-jam models are bathymetry, stream discharge, roughness coefficients of the riverbed and ice cover, ice-cover porosity, thickness of sheet ice cover, strength parameters, river ice erosion and deposition velocity thresholds, the volume of ice cover, and ice-jam toe locations. As a single model or approach is unable to determine these input parameters, a combination of different models and approaches can be applied to assess the severity of the ice-jam scenarios.
Moreover, ice-cover processes can be very vulnerable to destructive conditions such as ice-jam formation during spring ice-cover breakup. Therefore, studies are mostly carried out to determine ice-jam severity during breakup. However, as the above discussions reveal, river ice cover and hydraulic characteristics have a great influence on the severity of breakup and ice-jam flooding along rivers. Therefore, the modelling of climate change impacts on the severity of ice-jam flooding should simultaneously simulate river ice and hydrological processes of the entire winter and spring breakup. This approach could also improve current river ice-jam modelling capacity and management strategies.
Efforts should be concentrated on developing a comprehensive river ice (CRI) model that can simultaneously simulate entire river ice and hydrological processes from freeze-up to breakup, incorporate all the historical trends and geomorphological changes, and deal with climatic, hydrological, and cryologic parameter uncertainties to quantify probable climate change impacts on ice-jam flooding under future climatic conditions. It would be both unrealistic and enormously challenging for a single research group to develop this type of model; thus, multiple model combinations and couplings, as well as collaboration with different experts and research groups, may be necessary. Figure 2 illustrates a conceptual CRI model flow chart to quantify the severity of ice-jam flooding under a future climate scenario. GCM output can serve as input for hydrological processes, thermal river ice processes, and empirical models, as researchers currently rely extensively on these emission scenarios to develop future climate scenarios. As discussed in preceding sections, it is clear that the available hydrological models can simulate future flow conditions based on future air temperature and precipitation trends from GCM outputs and that a thermal river ice processes model could simulate the probable freeze-up levels, ice-cover formation, ice volumes, and other necessary river ice information from freeze-up to breakup.
Fig. 2.
Fig. 2. A conceptual comprehensive river ice model to assess climate change impacts on the severity of ice jams.
Although GCMs are downscaled to a regional scale, these models have often failed to simulate the actual climatic conditions. Even with sophisticated downscaling, there are often significant differences between modelled climatic variables (e.g., air temperature) and historically observed variables (Das et al. 2017). The standard approach is to consider the model-indicated changes or biases between baseline and future values of climatic variables and then apply these changes to observed baseline values to come up with projected future values. This can be carried out using a simple empirical model. The absolute differences for temperatures and relative changes for streamflow are often applied to baseline values (Andrishak and Hicks 2008; Eum et al. 2017). An empirical model can be applied to understand the basic trends such as degree days of freezing and melting, physical ice processes, and morphological changes of the study site. This model can then be coupled with a geospatial model to identify future ice-jam locations and necessary changes in model cross sections for both thermal river ice and ice-jam models. The empirical model can also estimate the river ice parameter thresholds based on historical observations for the study site. All this information can be transferred to an ice-jam hydrodynamic model to simulate probable ice-jam scenarios.
Because multiple model combinations of CRI models require input from various sources, there can be considerable uncertainty in model inputs and outputs. One of the possible solutions is to analyze past climate conditions and associated impacts on river ice using the same model combination to quantify the model bias to historical events (Turcotte et al. 2019). This bias can be incorporated into the entire modelling process when future climate change needs to be derived. Another solution is to explore uncertainty in the model by simulating hundreds of scenarios to identify the most probable distributions (Fu et al. 2014). Recently, a stochastic modelling approach was introduced by Lindenschmidt et al. (2016) and used in several ice-jam flood studies (Lindenschmidt 2020; Das et al. 2020; Rokaya et al. 2019), where hundreds of ice-jam scenarios were generated in a Monte Carlo framework using the RIVICE hydrodynamic model. This stochastic approach can also be applied to the proposed CRI model to create a confidence band or probability distribution of probable ice-jam severity under a future climate scenario.

5. Limitations and recommendations

A major limitation in current river ice modelling systems is their inability to incorporate entire river ice processes from freeze-up to breakup. Moreover, there are limitations in simulating dynamic ice processes, predicting mechanical breakup, and characterizing hydrodynamic impacts on river ice thicknesses. Although many models simulate unsteady hydrodynamic ice conditions, most of them are capable of modelling only equilibrium ice-jam conditions, which may limit the applicability of these models to simulating climate scenarios. Although attempts have been made to model the breakup and jamming processes in several studies (Knack and Shen 2018; She et al. 2009; Shen et al. 2008), a comprehensive understanding and modelling approach for the mechanical breakup is still lacking. The rates of hydraulic thickening and deterioration of river ice covers are important parameters for estimating total winter ice thicknesses and identifying ice duration and breakup timing; however, the number of models available that can quantify these hydraulic processes are very sparse. For example, the CRISSP1D and CRISSP2D hydrodynamic models that simulate rates of hydraulic decay and deterioration are not freely accessible; therefore, applicability and understanding the capabilities of these software packages is difficult.
Although regular monitoring and long-term historical data related to spring ice-cover breakup and ice jamming may become available in many locations, winter ice-cover data such as spatial and temporal variations of ice thickness and ice-cover types and strengths have been unevenly and sparsely collected. All these parameters are necessary to improve modelling capacity and advance knowledge of climate change impact modelling and analyses. Two further challenges include identifying uncertainty in ice-jam modelling and assessing future climate change impacts on the severity of ice-jam flooding.
To address the above challenges, different research groups must collaborate to improve current modelling, monitoring, and research capabilities. Education and knowledge dissemination among scientists, engineers, and decision-makers would be an important step forward in dealing with this complex natural phenomenon. Increased monitoring is also highly recommended, using all available sources and tools such as satellite imagery, aerial surveys, photography, and knowledge from local residents. To assist in understanding past and future trends, traditional knowledge can be incorporated into the empirical modelling and ice-jam database.

6. Conclusion

Climate change is modifying river ice regimes and affecting the severity of ice-jam flooding in cold regions. While it remains unknown whether climate change impacts will lead to more severe or less extreme events, it is perhaps time for more collaboration to quantify the overall climate change impacts on river ice under future climatic conditions.
In this study, both the historical and future climatic impacts on river ice have been summarized. Current modelling capabilities, a conceptual model, and existing challenges and limitations have also been discussed. A conceptual CRI model to assess climate change impacts on river ice-jam events for the future could be an effective means of assessing future climate change impacts; however, developing this model would be very challenging and difficult. It can, therefore, only be done if scientists, engineers, and decision-makers work together and incorporate all possible resources and options for modelling, monitoring, and collaborating as experts.


The authors thank the University of Saskatchewan’s Global Water Future program at the Global Institute for Water Security for their funding support of this research.


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Published In

cover image Environmental Reviews
Environmental Reviews
Volume 29Number 3September 2021
Pages: 378 - 390


Received: 21 October 2020
Accepted: 22 April 2021
Accepted manuscript online: 23 April 2021
Version of record online: 23 April 2021


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Key Words

  1. ice jam
  2. climate change
  3. northern river
  4. modelling


  1. embâcle
  2. changements climatiques
  3. rivière du nord
  4. modélisation



Global Institute for Water Security, University of Saskatchewan, 11 Innovation Blvd., Saskatoon, SK S7N 3H5, Canada.
Karl-Erich Lindenschmidt
School of Environment and Sustainability, University of Saskatchewan, 117 Science Place, Saskatoon, SK S7N 5C8, Canada.


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