RIVICE—A Non-Proprietary, Open-Source, One-Dimensional River-Ice Model

Lindenschmidt, Karl–Erich

doi:10.3390/w9050314

Cited by 69 publications

(36 citation statements)

References 25 publications

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“…In addition, it can also simulate ice phenomena in separate subroutines, which greatly reduces the computational requirements and allows for simulations that are more efficient. RIVICE has been widely applied in many cold region rivers (e.g., Lindenschmidt, ; Rokaya, Wheater, & Lindenschmidt, ; Zhang, Mosaffa, Chu, & Lindenschmidt, ).…”

Section: Methodsmentioning

confidence: 99%

Modelling the effects of climate and flow regulation on ice‐affected backwater staging in a large northern river

Rokaya

Peters

Bonsal

et al. 2019

River Research & Apps

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In cold region environments, ice-jam floods (IJFs) pose a severe risk to local communities, economies, and ecosystems. Previous studies have shown that both climate and regulation affect IJF probabilities, but their relative impacts are poorly understood. This study presents a probabilistic modelling framework that couples hydrologic and hydraulic models to assess the relative role of regulated and naturalized flows on ice-affected backwater staging. The framework is evaluated at an IJFprone town on the Peace River in western Canada, which has been regulated since 1972. Naturalized flows were generated for the comparison, and ice-affected backwater profiles were calculated along jams of varying length and location and for different combinations of model parameters and boundary conditions. Results show significant differences in backwater staging (~2 m for a return period of T = 1:10 year) between two study time periods (1973-1992 vs 1993-2012) as compared with two different hydraulic flow conditions (regulated vs naturalized), suggesting a larger role of climate than regulation in backwater staging. However, regulation was found to offset flood risk during the 1973-1992 period and exacerbate flood risk during the 1993-2012 period.

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Section: Methodsmentioning

confidence: 99%

Modelling the effects of climate and flow regulation on ice‐affected backwater staging in a large northern river

Rokaya

Peters

Bonsal

et al. 2019

River Research & Apps

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“…Many were detailed in CRIPE 2019 proceedings (de Rham et al, 2019) and are reiterated/updated here: application of site-specific break-up forecast methodologies (e.g., Beltaos, 1997;Beltaos et al, 2003); flood studies (Buttle et al, 2016); evaluation of locations using the global river ice classification model (Turcotte and Morse 2013); cold-regions ecological assessments (e.g. Peters et al, 2014;2016); baseline information for under-ice sediment transportation studies (as reviewed by Turcotte et al, 2011) and riverine habitats stressors (as reviewed by Prowse and Culp 2008); calibration and validation of river ice hydrology (Morales-Marin et al, 2019) and hydraulics (Lindenschmidt, 2017) modelling efforts; and ground truth observations for remote sensing applications (Pavelsky and Smith 2004;Yang et al, 2020).…”

Section: Utility Of the Database And Research Needsmentioning

confidence: 99%

A Canadian River Ice Database from National Hydrometric Program Archives

Rham¹,

Dibike²,

Beltaos³

et al. 2020

Preprint

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Abstract. River ice is a common occurrence in cold climate hydrological systems. The annual cycle of river ice formation, growth, decay and clearance can include low flows and ice jams, as well as mid-winter and spring break-up events. Reports and associated data on river ice occurrence are often limited to site and season-specific studies. Within Canada, the National Hydrometric Program (NHP) operates a network of gauging stations with water level as the primary measured variable to derive discharge. In the late 1990s, the Water Science and Technology Directorate of Environment and Climate Change Canada initiated a long-term effort to compile, archive and extract river ice related information from NHP hydrometric records. This data article describes the original research data set produced by this near 20-year effort: the Canadian River Ice Database (CRID). The CRID holds almost 73,000 variables from a network of 196 NHP stations throughout Canada that were in operation within the period 1894 to 2015. Over 100,000 paper and digital files were reviewed representing 10,378 station-years of active operation. The task of compiling this database involved manual extraction and input of more than 460,000 data entries on water level, discharge, date, time and data quality rating. Guidelines on the data extraction, rating procedure and challenges are provided. At each location, a time series of up to 15 variables specific to the occurrence of freeze-up and winter-low events, mid-winter break-up, ice thickness, spring break-up and maximum open-water level were compiled. This database follows up on several earlier efforts to compile information on river ice, which are summarized herein, and expands the scope and detail for use in Canadian river ice research and applications. Following the Government of Canada Open Data initiative, this original river ice data set is available at: https://doi.org/10.18164/c21e1852-ba8e-44af-bc13-48eeedfcf2f4 (de Rham et al., 2020).

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“…RIVICE is a hydraulic river ice model that mimics important ice processes both during river freeze-up and ice-cover breakup (ECCC, 2013;Lindenschmidt, 2017a). RIVICE is a one-dimensional model (variations in the longitudinal direction), hydrodynamic model that dynamically simulates the progression of ice-cover and ice-jam formation and collapse.…”

Section: Rivice Modelmentioning

confidence: 99%

“…Instantaneous maxima of the water level elevations were made available for each ice-jam event by Water Survey of Canada. The model was previously calibrated for a number of severe ice-jam flood events, particularly 1977, 1978, 1979 and 1997 and the reader is referred to Lindenschmidt (2017aLindenschmidt ( , 2017b for the calibration and validation of the model. Figure 10 (top panel) shows an ensemble of longitudinal water level profiles from the Monte-Carlo analysis as conceptualized in Figure 6, in which the volume of ice remained zero but an ice cover downstream of the gauge was still possible.…”

Section: Gauge Datamentioning

confidence: 99%

A Stochastic Hydraulic Modelling Approach to Determining the Probable Maximum Staging of Ice-Jam Floods

Lindenschmidt¹,

Rokaya²

2019

J ENVIRON INFORM

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There is a need to determine the maximum backwater staging possible from ice jam flooding along high flood risk prone sections of northern rivers. Similar to the probable maximum flood PMF, which is primarily estimated for the most extreme open-water floods, probable maximum floods from ice jamming PMFice can provide upper thresholds of water level elevations so essential for infrastructure designed in and along cold-region rivers. However, the processes for maximum ice-jam flooding are quite different from those of extreme open-water floods which requires river ice processes to be incorporated into the calculation approach. This paper presents a novel method for estimating the probable maximum staging from ice-jam floods. The method is based on the implementation of a deterministic hydraulic model that mimics ice jam processes and is nested in a stochastic framework to carry out Monte-Carlo simulations to randomise parameter and boundary condition value inputs for many hundreds of simulations. This stochastic approach provides the frequency distributions of many of the boundary conditions used to force the river ice hydraulic model. The stochastic modelling framework yields ensembles of backwater levels from which the maximum level provides an indication of the probable maximum staging possible, the PMFice.

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RIVICE—A Non-Proprietary, Open-Source, One-Dimensional River-Ice Model

Cited by 69 publications

References 25 publications

Modelling the effects of climate and flow regulation on ice‐affected backwater staging in a large northern river

Modelling the effects of climate and flow regulation on ice‐affected backwater staging in a large northern river

A Canadian River Ice Database from National Hydrometric Program Archives

A Stochastic Hydraulic Modelling Approach to Determining the Probable Maximum Staging of Ice-Jam Floods

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