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River ice-jam modelling in MESH
Karl-Erich LindenschmidtPrabin Rokaya, Luis Morales-Marín, Howard Wheater
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Lindenschmidt et al. (2015) Ice jam flood hazard assessment and mapping of the Peace River at the Town of Peace River. CRIPE 18th Workshop on the Hydraulics of Ice Covered Rivers, Quebec City, August 18-20, 2015. http://cripe.civil.ualberta.ca/Downloads/18th_Workshop/23_Lindenschmidt_et_al_2015.pdf
Outlook:MESH/RIVICE coupling for Peace River
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Description of RIVICE General
a) one-dimensional hydrodynamicsb) implicit finite-difference simulationc) includes optional water temperature simulationd) considers major ice phenomena and processes
Ice processesa) ice cover formation and ablationb) frazil ice formationc) border ice advancementd) anchor icee) ice transportf) hanging damsg) ice jams
source: Lindenschmidt (submitted) Modelling river ice processes. Water.
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1979 ice-jam along Athabasca River
0 20000 40000 60000220
230
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250
260
270
chainage (m)
elev
atio
n (m
a.s.
l.)
220
1979
icejamtoe↓
source: Lindenschmidt (submitted) Modelling river ice processes. Water.
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Near real-time Ice-Related Flood Hazard Assessment (RIFHA) funder:
a) Canadian Space Agency
partners:a) C-Core (remote sensing)b) GIWS (remote sensing & river ice modelling)c) Alberta Environment and Parks (Athabasca River)d) NFLD Environment and Conservation (Exploits River)e) Joint Task Force Atlantic (emergency response)
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External parameters influencing ice jams
Q
V ice
W
toe location
Lindenschmidt, K.-E., Das, A., Rokaya, P. and Chu, T. (2016) Ice jam flood risk assessment and mapping. Hydrological Processes 30: 3754–3769
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Main parameters to calibrate against stage-frequency curve
Q
W d
/s
toe
loca
tion
probability
V ic
e
W fl
ood
?
source: Lindenschmidt (in prep.) Stage-frequency distributions as objective functions for calibration and global sensitivity analyses. Environmental Modelling & Software.
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Monte Carlo simulation method40
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0.25discharge d/s water level cross-section inflowing ice
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Simulated and observed ice jam stagefrequency distributions for the Fort McMurray gauge
source: Rokaya, Morales-Marín, Wheater & Lindenschmidt (submitted) Hydro-climatic variability and implications for ice-jam flooding in the Athabasca River Basin. Cold Regions Science & Technology.
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Peak daily historical and future flowsfrom mid-April to mid-May (breakup period)
source: Rokaya, Morales-Marín, Wheater & Lindenschmidt (submitted) Hydro-climatic variability and implications for ice-jam flooding in the Athabasca River Basin. Cold Regions Science & Technology.
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Main parameters to calibrate against stage-frequency curve
Q
W d
/s
toe
loca
tion
probability
V ic
e
W fl
ood
?
source: Lindenschmidt (in prep.) Stage-frequency distributions as objective functions for calibration and global sensitivity analyses. Environmental Modelling & Software.
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mdpi.com/si/6509
Deadline for manuscript submission: 16 December 2016
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Near real-time Ice-Related Flood Hazard Assessment (RIFHA) improve decision making for disaster management and
emergency response within the context of river ice-related flooding.
combine a) satellite-based river ice monitoring, b) in-situ observations and c) hydro-dynamic river ice modelling
to build novel capacity for generation and delivery of near real-time ice-related flood risk assessment info.
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Monte Carlo simulation method40
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Chainage (m)
Elev
atio
n (m
a.s.l
.)
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Ensemble of ice-jam backwater levels along the Athabasca River
source: Rokaya, Morales-Marín, Wheater & Lindenschmidt (submitted) Hydro-climatic variability and implications for ice-jam flooding in the Athabasca River Basin. Cold Regions Science & Technology.
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Average historical and future monthlyflows in November (freeze-up period)
source: Rokaya, Morales-Marín, Wheater & Lindenschmidt (submitted) Hydro-climatic variability and implications for ice-jam flooding in the Athabasca River Basin. Cold Regions Science & Technology.