River ice-jam modelling in MESH. Karl-Erich Lindenschmidt Prabin Rokaya, Luis Morales-Marín, Howard Wheater
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1 River ice-jam modelling in MESH Karl-Erich Lindenschmidt Prabin Rokaya, Luis Morales-Marín, Howard Wheater
2 Outlook: MESH/RIVICE coupling for Peace River Lindenschmidt et al. (215) 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 18-2,
3 Description of RIVICE General a) one-dimensional hydrodynamics b) implicit finite-difference simulation c) includes optional water temperature simulation d) considers major ice phenomena and processes Ice processes a) ice cover formation and ablation b) frazil ice formation c) border ice advancement d) anchor ice e) ice transport f) hanging dams g) ice jams source: Lindenschmidt (submitted) Modelling river ice processes. Water.
4 1979 ice-jam along Athabasca River elevation (m a.s.l.) ice jam toe chainage (m) source: Lindenschmidt (submitted) Modelling river ice processes. Water.
5 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)
6 External parameters influencing ice jams V ice Q W toe location Lindenschmidt, K.-E., Das, A., Rokaya, P. and Chu, T. (216) Ice jam flood risk assessment and mapping. Hydrological Processes 3:
7 Main parameters to calibrate against stage-frequency curve Q W d/s toe location V ice? W flood probability source: Lindenschmidt (in prep.) Stage-frequency distributions as objective functions for calibration and global sensitivity analyses. Environmental Modelling & Software.
8 Monte Carlo simulation method.2 discharge d/s water level cross-section inflowing ice
9 Simulated and observed ice jam stage frequency 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.
10 Peak daily historical and future flows from 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.
11 Main parameters to calibrate against stage-frequency curve Q W d/s toe location V ice W flood? probability source: Lindenschmidt (in prep.) Stage-frequency distributions as objective functions for calibration and global sensitivity analyses. Environmental Modelling & Software.
12 mdpi.com/si/659 Deadline for manuscript submission: 16 December 216
13 Near real-time Ice-Related Flood Hazard Assessment (RIFHA) improve decision making for disaster management and emergency response within the context of river icerelated 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.
14 Chainage (m) cross-section d/s water level discharge Elevation (m a.s.l.) Monte Carlo simulation method inflowing ice
15 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.
16 Average historical and future monthly flows 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.
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