Flood forecast technological platforms: an adaptive

response to extreme events

José M P Vieira

Summary

• Floods. Threats and challenges

• Hydrological data collection and forecast

• Mathematical Modelling

• FEWS-AVE platform

• Conclusion

Summary

• Floods. Threats and challenges

• Hydrological data collection and forecast

• Mathematical Modelling

• FEWS-AVE platform

• Conclusion

4

Flooding in Bangkok (photo by Adri Verwey, Deltares)

5

Flooding in Bangkok (photo by Adri Verwey, Deltares)

6

Flooding in Bangkok (photo by Adri Verwey, Deltares)

7

8JLS Pinho

River Douro

9JLS Pinho

River Mondego

10JLS Pinho

Brazilian basins

Minas Gerais

Floods. Threats and challenges

• New developments / tools for forecasting and

warning systems

• Real-time meteorological information

– Satellite based weather radar

– Meteorological radar

• Atmospheric models forecasting for different time

horizons

• Hydro-meteorological monitoring11

Summary

• Floods. Threats and challenges

• Hydrological data collection and forecast

• Mathematical Modelling

• FEWS-AVE platform

• Conclusion

Hydrological data collection and forecast

Forecast Systems

• Australia • USA • Europe

Hydrological data collection and forecast

14

Available data in

real time

Hydrological data collection and forecast

15

Forecasts

CFS GFS

WRF GEFSWeather Research Forecasting

MeteoGaliciaGlobal Ensemble Forecast System

Global Forecast SystemClimate Forecast System

Summary

• Floods. Threats and challenges

• Hydrological data collection and forecast

• Mathematical Modelling

• FEWS-AVE platform

• Conclusion

Mathematical modelling

• Models base

17

Model Country Model Country

APICONT USA PCRASTER Netherlands

ARMA UK PDM UK

BASEFLOW USA PREVAH Switzerland

CHANLOSS USA PRTF UK

CONSUSE USA RESSNGL USA

Continuum Italy REW Netherlands

D-Flow FM Netherlands RIBASIM Netherlands

DELFT3D Netherlands RSNELEV USA

DELFT-3D Netherlands RTC Tools Netherlands

DODO UK SAC-SMA USA

DPWE Bank retreat model Taiwan Sacramento Netherlands

DPWE Landslide model Taiwan SACSMA-HT USA

EFDC Netherlands SARROUTE USA

Flux Austria SelfeWWMII USA, France

GLACIER USA Snow17 USA

Grid2Grid UK SOBEK Netherlands

HBV Sweden SOBEK-2d Netherlands

HEC-HMS USA Source Australia

HEC-RAS USA SSARRESV USA

HEC-ResSim USA StarWars Netherlands

Het Wageningen  Netherlands STF UK

HSPF Netherlands SWAN Netherlands

ISIS UK SWMM USA

JFlow UK SynHP Germany

KW UK TATUM USA

LAG/K USA TCM UK

LAYCOEF USA Telemac Belgium

LAYCOEF USA TETIS Spain

LISFLOOD-FP UK TOPKAPI Italy

MCRM UK TOPKAPI-X Italy

Mike11 Denmark TRITON UK

Modflow96/VKD Netherlands/UK TWAM UK

MUSKROUT USA Unit-HG USA

NAM Denmark URBS Australia

OpenDA Netherlands WALRUS Netherlands

OpenStreams Netherlands WASIM-ETH Switzerland

PACK UK WW3 Netherlands

PCOverslag Netherlands XBeach Netherlands

HMS

Sacramento

Sobek

HEC-RASRMA2

DELFT3D

RTC

Mathematical modelling

• Hydrologic model (Sobek-Sacramento)

18

Mathematical modelling

• 1D Hydrodynamics models (continuity and

momentum equations)

19

lat

fq

x

Q

t

A=

+

02

2

=−+

+

+

w

wif

f

f

f

WRAC

QgQ

x

hgA

A

Q

xt

Q

( ) ( )ff

fSA

x

CDA

xx

QC

t

CA+

+

−=

Mathematical modelling

• 2D Hydrodynamics models (continuity and

momentum equations)

20

( ) ( ) 0

ηηη=

++

++

y

Vh

x

Uh

t

( )

+

+

+

+−

++

+

−

−+=

+

+

2

2

2

2

2

222

ρ

ε

ηη

cosρ

2

ηρ

ρ

η

y

U

x

U

Ch

VUgU

h

kWh

X

g

xgfV

y

UV

x

UU

t

U va

( )

+

+

+

+−

++

+

−

−−=

+

+

2

2

2

2

2

222

ρ

ε

ηη

ρ

2

ηρ

ρ

η

y

V

x

V

Ch

VUgV

h

senkWh

y

g

ygfU

y

VV

x

VU

t

V va

( ) ( ) 0)()( =+

−

−

+

+

Ck

y

CE

yx

CE

xVC

yUC

xt

CCyx

Mathematical modelling

• Mesh discretization

21

Mathematical modelling

• Hydraulics structures

22

( ),C,A,hhfQ sjm= Bridges

Weirs

Orifices

Gates

Syphons

Turbines/Pumps

Mathematical modelling

• RTC (real time control of hydraulic structures)

23

Summary

• Floods. Threats and challenges

• Hydrological data collection and forecast

• Mathematical Modelling

• FEWS-AVE platform

• Conclusion

Fews-AVE platform

• Delft-FEWS (Flood and Early Warning Systems)

25

Fews-AVE platform

• U.Minho former experiences with Delft-FEWS

26

Alqueva CEMIG

Lima Ave

Fews-AVE platform

• River Ave Case Study. Basin description

27

Fews-AVE platform

• River Ave Case Study. GFS forecast precipitation

28

Forecasts

CFS GFS

WRF GEFS

Fews-AVE platform

• River Ave Case Study. WRF forecast precipitation

29

Forecasts

CFS GFS

WRF GEFS

Fews-AVE platform

• River Ave case study. Models calibration

30

Sub-basin NSE BIAS RMSE MAE R2 Average

sim.

Average

obs.

(-) (-) (m3/s) (m3/s) (m3/s) (-) (m3/s) (m3/s)

Este 0.68 1.9 3.6 2.6 0.78 6.9 8.8

Selho 0.77 0.2 1.1 0.6 0.78 1.6 1.8

Fews-AVE platform

• River Ave case study. Flows forecasts for river Este

31

Fews-AVE platform

• River Ave case study. Flows forecasts for river Selho

32

Fews-AVE platform

• Uncertainty analysis of precipitation forecasts (WRF,GFS,

GEFS)

33

Pre

cip

ita

tion

(m

m/d

ay)

Pre

cip

ita

tion

(m

m/d

ay)

Pre

cip

ita

tion

(m

m/d

ay)

Pre

cip

ita

tion

(m

m/d

ay)

Stations Forecasts Stations Forecasts Stations Forecasts Stations Forecasts

1 Day 2 Days 3 Days 4 Days

Fews-AVE platform

• Results of PID controller against manual operation

34

Water Sci Technol. 2019;80(1):173-183. doi:10.2166/wst.2019.264

Summary

• Floods. Threats and challenges

• Hydrological data collection and forecast

• Mathematical Modelling

• FEWS-AVE platform

• Conclusion

Conclusion

• Traditional approach

36

APC R A

F

Intermédia Ribª Mortágua

Rios Ceira e Dueça Rio Alva

Rio Mondego

PSC

Nalerta

Almaça Coimbra Côja Fajão

Góis Lousã Penacova Penela

Ponte Cabouco

- Estação hidrométrica (niveis e caudais)

- Estação udométrica (precipitações)

APC R A

F

Intermédia Ribª Mortágua

Rios Ceira e Dueça Rio Alva

Rio Mondego

PSC

Nalerta

Ponte Cabouco

- Estação hidrométrica

▪ New approach

Conclusion

• The flood forecast platform developed at the University of Minho is

based on the Delft-FEWS platform, and use:

– Hydrological data from: real time meteorological information;

forecasting from atmospheric models; and hydro-meteorological

monitoring

– Hydrological and hydrodynamics models

• Good results from hydrological and hydrodynamics model calibration

allows the prediction of reliable river flows forecasting (key-issue for

flooding early warning)

• The flood forecast accuracy greatly depends on the quality of

precipitation data and on the knowledge of river hydrodynamics.

That is why precipitation gauge stations were recently installed in

river Ave basin, and installation of pressure sensors at flood prone

river stretches are planned.

37

Thank you for your attention

José M. P. Vieira

jvieira@civil.uminho.pt