Model couplings to include - river water temperature, - overland and instream water-quality and - river ice processes in the MESH modelling system

Karl-Erich LindenschmidtSujata Budhathoki, Apurba Das, Hinata Kadowaki, Zhaoqin Li, Luis Morales, Prabin Rokaya

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MESH-RBM: In-stream water temperature model

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RBM model source

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A grid-based semi-Lagrangian water temperature model for MESH: Structure

Water temperature model RBM

Boundary and initial conditions: Theadw = f(Tair)

Hydraulic characteristicsStream depth (H) a width (W): H, W = f(Adrainage), V = Q/(H*W)

Hydrological model MESH

Connectivity of

river network

Cell channel

flow

Met. forcing data for each cell:- Precipitation- Min and max air temperature- Wind speed- Down. short- and long-wave rad.- Vapor pressure

Cell channel water temp.RBM output

RBM input from MESH

RBM input

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Hinton:RMSE = 1.78 °CPBIAS = 5.20%NSE = 0.82

Athabasca:RMSE = 2.25 °C PBIAS = 2.20%NSE = 0.87

Fort McMurray:RMSE = 2.37 °C PBIAS = -1.80%NSE = 0.89

Water temperatures at three different stations

Maps of multi-annual averages of simulated water temperature

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Landsat heat map

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MESH-SED: Sediment & nutrient transport

modelling

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SHESED model source

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MESH-SED conceptualization and software flow diagram

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Requires seasonally varying vegetation cover to refine simulations

Preliminary results:observed vs. simulated sediment

loads at Fort McMurray

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MESH-RIVICE: Ice-jam flood modelling

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MESH

Streamflow

RIVICE

Water level profiles

Model parameters

Incoming ice volume

Downstream Water Level

Location of toe of the ice jam R

IVIC

E bo

unda

ry

cond

ition

s

Hydrological Processes

River ice Processes

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River ice processes

incoming ice blocks

heat transfer

frazil ice formation

in transit

deposition erosion

juxta-position retraction

slush pan formation

lead

ing

edge

downstream water level from under-ice rating curve:W = f(Q_MESH)

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(1) Remote sensing:provides info on- ice types- ice thicknesses- upstream ice extent

(2) Stochastic, real-time, river ice flood modelling:

(3) Dynamic flood hazard assessment & mapping:

(4) Flood advisories & warnings:provides info for- decision support- preparedness measures- disaster management

flow

ice volume

jam

toe

→lo

catio

n

flood water level

free

ze-u

p w

ater

leve

l

RIFHA – Real near-time flood hazard assessmentFunding and Radarsat-2 data from CSA’s EOADP

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Flow forecasts from MESHMESH inputs from theCanadian Global Deterministic Prediction System (GDPS)

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10-day forecasted meteorological data

MESH simulation resulting in min/max flows of 10-dayforecasted flows

Water level elevation at gauge

corresponding water level elevation at downstream boundary

water level profile

ensemble

thalweg

conf

luen

ce

Monte-Carlo simulations

f

Q

f

Vice

f

W

↔range

min max min range

Ice-jam flood forecasting operational framework

18Lindenschmidt, K.-E. et al. (in prep.) A novel stochastic modelling approach to operationally forecast ice-jam flooding.

Flood hazard maps for Forecasts 4 to 6

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Thank you