A global river ice classification model

Turcotte, Benoit; Morse, Brian

doi:10.1016/j.jhydrol.2013.10.032

Cited by 41 publications

(31 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Anchor ice is usually initiated by the accumulation of tiny ice particles that have adhesive features in supercooled water and therefore attach to in-stream vegetation, coarse material and large wood (Stickler and Alfredsen 2009;Lind and others 2014a). Suspended ice is created when anchor ice dams collapse or when water recedes during winter, thereby leaving ice elevated above the water surface (Prowse 1995;Turcotte and Morse 2013). Ice formations were drawn on maps and photographed during field visits between six to nine times through November to April during the winters 2011-2012 and 2012-2013.…”

Section: Ice Studiesmentioning

confidence: 99%

How Do Biota Respond to Additional Physical Restoration of Restored Streams?

et al. 2016

View full text Add to dashboard Cite

Restoration of channelized streams by returning coarse sediment from stream edges to the wetted channel has become a common practice in Sweden. Yet, restoration activities do not always result in the return of desired biota. This study evaluated a restoration project in the Vindel River in northern Sweden in which practitioners further increased channel complexity of previously restored stream reaches by placing very large boulders (>1 m), trees (>8 m), and salmonid spawning gravel from adjacent upland areas into the channels. One reach restored with basic methods and another with enhanced methods were selected in each of ten different tributaries to the main channel. Geomorphic and hydraulic complexity was enhanced but the chemical composition of riparian soils and the communities of riparian plants and fish did not exhibit any clear responses to the enhanced restoration measures during the first 5 years compared to reaches restored with basic restoration methods. The variation in the collected data was among streams instead of between types of restored reaches. We conclude that restoration is a disturbance in itself, that immigration potential varies across landscapes, and that biotic recovery processes in boreal river systems are slow. We suggest that enhanced restoration has to apply a catchment-scale approach accounting for connectivity and availability of source populations, and that low-intensity monitoring has to be performed over several decades to evaluate restoration outcomes.

show abstract

Section: Ice Studiesmentioning

confidence: 99%

How Do Biota Respond to Additional Physical Restoration of Restored Streams?

et al. 2016

View full text Add to dashboard Cite

show abstract

“…This could lead to a method that provides some modelling capability at the same time as it preserves the desired simplicity of the hydrological index method. A similar strategy could be to explore the possibility of linking the hydrological ice indexes to the conceptual ice model developed by Turcotte and Morse [42]. This method links ice cover formation with ice formation processes using simple parameters like channel type, channel size, and winter intensity that can easily be found for any river.…”

Section: Discussionmentioning

confidence: 99%

An Assessment of Ice Effects on Indices for Hydrological Alteration in Flow Regimes

Alfredsen

2017

Water

View full text Add to dashboard Cite

Preserving hydrological variability is important when developing environmental flow regimes, and a number of tools have been developed to support this process. A commonly applied method is the index of hydrological alteration (IHA), which describes a set of indices that can be used to assess changes in flow regimes. In cold climate regions, river ice can have large effects on flow regimes through frazil and anchor ice formation, ice cover formation, and ice break-up, and the impact of this is usually not included in the commonly used indexes. However, to understand the effect of ice formation and the break-up on the flow regime, the ice effects on the hydrology should be considered when assessing winter alteration indexes. This paper looks at the effects of river ice on winter flow conditions using data from Norwegian rivers, and discusses these effects in relation to hydrological variability. This paper also shows how indexes can be used to classify ice-induced variability, how this should be used to avoid ice-induced effects in the current analysis, and how this can be combined with the current indices to improve the winter flow regime classification. The findings from this paper show that frazil-and anchor-induced raises of the water level have a large impact on the perceived flow in winter, producing higher flow and deeper water than what the open water conditions discharge could do. Corresponding to this, winter lows connected to ice-induced high flows at other locations are also common. Finally, issues related to the assessment of the temporal and spatial effects of ice formation are discussed.

show abstract

“…In many northern communities, river flooding risks in spring are caused by ice‐related events (Chang, Meng, Wang, Wang, & Huang, ; Chokmani, Ouarda, Hamilton, Ghedira, & Gingras, ; Turcotte & Morse, ). Rising temperatures in spring result in ice cover breakup, and then the broken ice may further cause ice jams against intact ice further downstream (Fu, Popescu, Wang, Mynett, & Zhang, ; Lesack, Marsh, Hicks, & Forbes, , ).…”

Section: Introductionmentioning

confidence: 99%

Multiple model combination methods for annual maximum water level prediction during river ice breakup

Sun

Trevor

2018

Hydrological Processes

View full text Add to dashboard Cite

The Athabasca River is the largest unregulated river in Alberta, Canada, with ice jams frequently occurring in the vicinity of Fort McMurray. Modelling tools are desired to forecast ice‐related flood events. Multiple model combination methods can often obtain better predictive performances than any member models due to possible variance reduction of forecast errors or correction of biases. However, few applications of this method to river ice forecasting are reported. Thus, a framework of multiple model combination methods for maximum breakup water level (MBWL) Prediction during river ice breakup is proposed. Within the framework, the member models describe the relations between the MBWL (predicted variable) and their corresponding indicators (predictor variables); the combining models link the relations between the predicted MBWL by each member model and the observed MBWL. Especially, adaptive neuro‐fuzzy inference systems, artificial neural networks, and multiple linear regression are not only employed as member models but also as combining models. Simple average methods (SAM) are selected as the basic combining model due to simple calculations. In the SAM, an equal weight (1/n) is assigned to n member models. The historical breakup data of the Athabasca River at Fort McMurray for the past 36 years (1980 to 2015) are collected to facilitate the comparison of models. These models are examined using the leave‐one‐out cross validation and the holdout validation methods. A SAM, which is the average output from three optimal member models, is selected as the best model as it has the optimal validation performance (lowest average squared errors). In terms of lowest average squared errors, the SAM improves upon the optimal artificial neural networks, adaptive neuro‐fuzzy inference systems, and multiple linear regression member models by 21.95%, 30.97%, and 24.03%, respectively. This result sheds light on the effectiveness of combining different forecasting models when a scarce river ice data set is investigated. The indicators included in the SAM may indicate that the MBWL is affected by water flow conditions just after freeze‐up, overall freezing conditions during winter, and snowpack conditions before breakup.

show abstract

A global river ice classification model

Cited by 41 publications

References 41 publications

How Do Biota Respond to Additional Physical Restoration of Restored Streams?

How Do Biota Respond to Additional Physical Restoration of Restored Streams?

An Assessment of Ice Effects on Indices for Hydrological Alteration in Flow Regimes

Multiple model combination methods for annual maximum water level prediction during river ice breakup

Contact Info

Product

Resources

About