river ice-jam modelling in mesh - changing cold … ice-jam modelling in mesh karl-erich...

River ice-jam modelling in MESH

Karl-Erich LindenschmidtPrabin Rokaya, Luis Morales-Marín, Howard Wheater

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

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.

1979 ice-jam along Athabasca River

0 20000 40000 60000220

230

240

250

260

270

chainage (m)

elev

atio

n (m

a.s.

l.)

220

1979

icejamtoe↓

source: Lindenschmidt (submitted) Modelling river ice processes. Water.

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)

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

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.

Monte Carlo simulation method40

080

012

0016

0020

0024

0028

0032

0036

0040

0044

0048

0052

0056

00

0

0.04

0.08

0.12

0.16

0.2

307.

630

8.0

308.

430

8.8

309.

230

9.6

310.

031

0.4

310.

831

1.2

311.

631

2.0

0

0.05

0.1

0.15

0.2

0.25

680

700

720

740

760

780

800

820

840

860

880

900

920

940

960

0

0.04

0.08

0.12

0.16

010

020

030

040

050

060

070

080

090

010

0011

00

0

0.05

0.1

0.15

0.2

0.25discharge d/s water level cross-section inflowing ice

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.

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.

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.

mdpi.com/si/6509

Deadline for manuscript submission: 16 December 2016

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.

Monte Carlo simulation method40

080

012

0016

0020

0024

0028

0032

0036

0040

0044

0048

0052

0056

00

0

0.04

0.08

0.12

0.16

0.2

307.

630

8.0

308.

430

8.8

309.

230

9.6

310.

031

0.4

310.

831

1.2

311.

631

2.0

0

0.05

0.1

0.15

0.2

0.25

680

700

720

740

760

780

800

820

840

860

880

900

920

940

960

0

0.04

0.08

0.12

0.16

010

020

030

040

050

060

070

080

090

010

0011

00

0

0.05

0.1

0.15

0.2

0.25discharge d/s water level cross-section inflowing ice

0 20000 40000 60000230

240

250

260

270

Chainage (m)

Elev

atio

n (m

a.s.l

.)

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.

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.