Application of the SWAT model to Mediterranean flash floods ...number of measures 2009-2011: Catl: 14977; Marq: 18765; Perp: 25909 Catllar: 90 km² Marquixanes: 810 km² Perpignan:

Application of the SWAT model to Mediterranean flash floods

Does the use of fine climate stations grid and sub-basins delineation improve the modelling of river discharge and

sediments fluxes at hourly time-step?

1

L. BOITHIAS, D. d’A. BRESSIANI, S. SAUVAGE, K.C. ABBASPOUR, R. SRINIVASAN, W. LUDWIG, E. RICHARD, J.-M. SANCHEZ-PEREZ

2015 SWAT Conference, Pula, June 24-26

Application of the SWAT model to Mediterranean flash floods

Does the use of fine climate stations grid and sub-basins delineation improve the modelling of river discharge and

sediments fluxes at hourly time-step?

2

L. BOITHIAS, D. d’A. BRESSIANI, S. SAUVAGE, K.C. ABBASPOUR, R. SRINIVASAN, W. LUDWIG, E. RICHARD, J.-M. SANCHEZ-PEREZ

2015 SWAT Conference, Pula, June 24-26

Context

• Global change is expected to increase the frequency of intense rainfall events and consequent flash floods across the Mediterranean coastal basins in the next decades.

• Some complex physically-based distributed models are able to simulate hydrological processes at the flood time-scale but they do not capture below-ground processes.

• The SWAT model has recently been upgraded to sub-daily time-step calculations. However, its sub-daily module has only been tested in small catchments (~1 km²).

3

Objectives

• The objectives of this study were :

(1) to assess the ability of the SWAT model to simulate discharge at hourly time-step in a ~1400 km² river basin

(2) to assess the possible gain of model’s performance when using fine grids of climate stations and sub-basins representation.

4

Green&Ampt infiltration equation

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SOL_K CN2

SOL_CLAY SOL_SAND SOLB_BD

SOL_AWC SOLB_BD

Data for model set up

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DEM: SRTM 90m

Land use: Corine Land Cover -> mostly range land and forests

Soil: FAO + associated INRA soil properties

-> Mostly shallow (1.4m) sandy soils

Pula

Toulouse


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Daily discharge out of 2 dams - Vinça (irrigation): 24 hm3, data from 2000 to 2013 - Bouillouses (hydropower): 17 hm3, waiting for the data from EDF

Dams


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60

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100

120

1 2 3 4 5 6 7 8 9 10 11 12

Ave

rage

mo

nth

ly r

ain

fall

(mm

)

Months

OBS

SAF

Climate data - Daily temperature, humidity, wind, radiation (PET): SAFRAN - Hourly rainfall: measured (OBS ) / SAFRAN (SAF )

8 km

2 sub-basin delineations

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Minimal drainage area: 1500 ha 66 subbasins, 549 HRU

Minimal drainage area: 100 ha 691 subbasins, 2342 HRU

Calibration/validation periods for discharge simulation: - warm-up 2005-2009 - calibration 2009-2011 - validation 2012-2015

Calibration/validation measured data

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Subdaily discharge in 3 gauging stations (Banque Hydro) -> focus on 3 embeded catchments number of measures 2009-2011: Catl: 14977; Marq: 18765; Perp: 25909

Catllar: 90 km²

Marquixanes: 810 km²

Perpignan: 1400 km²

Dams Outlets

Parameters for SWAT-CUP set up

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Parameter Min Max CN2 .mgt R -0.1 0.1 ALPHA_BF .gw V 0.01 1

GW_DELAY .gw V 0 500 GW_REVAP .gw V 0.02 0.2

GWQMN .gw V 0 5000 RCHRG_DP .gw V 0.01 0.99 REVAPMN .gw V 0 500

CH_K2 .rte V 0.01 10 CH_N2 .rte V 0.025 0.15

CH_K1 .sub V 0.01 10 CH_N1 .sub V 0.025 0.15 ESCO .hru V 0.7 0.9

EPCO .hru V 0.7 1 LAT_TTIME .hru V 0 180

CANMX .hru V 0 100

OV_N .hru V 0.01 0.6

SOL_K .sol R 0 9 SOL_AWC .sol R -0.1 0.1 SOL_BD .sol R -0.1 0.1

SOL_CBN .sol R -0.1 0.1 SURLAG .bsn V 0.05 24

21 parameters

-> daily and hourly autocalibration

Experimental design

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24 combinations -> 24 calibrations (2009-2011)

3 outlets

2 rainfall data sets

2 sub-basin delineations

2 time-steps

Hourly

Daily

1500 ha

100 ha

Rain gauges

SAFRAN

90 km²

810 km²

1400 km²

Daily discharge in Catllar (90 km²)

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1/17/2009 8/5/2009 2/21/2010 9/9/2010 3/28/2011 10/14/2011

Dai

ly d

isch

arge

(m

3/s

) Simulated 100ha SAFSimulated 100ha OBSSimulated 1500ha SAFSimulated 1500ha OBSObserved

Daily discharge in Catllar (90 km²)

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1/17/2009 8/5/2009 2/21/2010 9/9/2010 3/28/2011 10/14/2011

Dai

ly d

isch

arge

(m

3/s

) Simulated 100ha SAFSimulated 100ha OBSSimulated 1500ha SAFSimulated 1500ha OBSObserved

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Dai

ly d

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NASH OBS SAF

100 ha 0.65 0.59

1500 ha 0.65 0.64

NASH OBS SAF

100 ha 0.56 0.22

1500 ha 0.64 0.40

NASH OBS SAF

100 ha 0.48 0.28

1500 ha 0.50 0.55

Hourly discharge in Catllar (90 km²)

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Ho

url

y d

isch

. (m

3/s

)

Simulated 100ha SAFSimulated 100ha OBSSimulated 1500ha SAFSimulated 1500ha OBSObserved

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Ho

ruly

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char

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m3

/s)

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NASH OBS SAF

100 ha -0.97 -0.02

1500 ha -0.13 -0.41

NASH OBS SAF

100 ha -0.11 -0.14

1500 ha 0.36 0.23

NASH OBS SAF

100 ha 0.06 0.18

1500 ha 0.28 0.40

Summary of the performances

Outlet Meteo data Min. drain. area Daily NS Hourly NS

90 km² SAF 1500 ha 0.50 0.38

100 ha 0.45 0.29

OBS 1500 ha 0.55 0.40

100 ha 0.52 0.14

810 km² SAF 1500 ha -0.86 -1.00

100 ha 0.46 0.18

OBS 1500 ha -0.55 -1.12

100 ha -0.75 -0.93

1400 km² SAF 1500 ha 0.35 0.24

100 ha 0.78 0.68

OBS 1500 ha 0.56 0.38

100 ha 0.62 0.52

16

2009-2011



90 km² SAF 1500 ha 0.50 0.38

100 ha 0.45 0.29

OBS 1500 ha 0.55 0.40

100 ha 0.52 0.14

810 km² SAF 1500 ha -0.86 -1.00

100 ha 0.46 0.18

OBS 1500 ha -0.55 -1.12

100 ha -0.75 -0.93

1400 km² SAF 1500 ha 0.35 0.24

100 ha 0.78 0.68

OBS 1500 ha 0.56 0.38

100 ha 0.62 0.52

17

2009-2011



90 km² SAF 1500 ha 0.50 0.38

100 ha 0.45 0.29

OBS 1500 ha 0.55 0.40

100 ha 0.52 0.14

810 km² SAF 1500 ha -0.86 -1.00

100 ha 0.46 0.18

OBS 1500 ha -0.55 -1.12

100 ha -0.75 -0.93

1400 km² SAF 1500 ha 0.35 0.24

100 ha 0.78 0.68

OBS 1500 ha 0.56 0.38

100 ha 0.62 0.52

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2009-2011

Missing upstream dam data?



90 km² SAF 1500 ha 0.50 0.38

100 ha 0.45 0.29

OBS 1500 ha 0.55 0.40

100 ha 0.52 0.14

810 km² SAF 1500 ha -0.86 -1.00

100 ha 0.46 0.18

OBS 1500 ha -0.55 -1.12

100 ha -0.75 -0.93

1400 km² SAF 1500 ha 0.35 0.24

100 ha 0.78 0.68

OBS 1500 ha 0.56 0.38

100 ha 0.62 0.52

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2009-2011

Daily discharge out of dam controls

the discharge d/h

Most sensitive parameters

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Outlet Meteo data Min. drain. area Daily Hourly

90 km² SAF 1500 ha LATTIME (116)

CN2 (0.06)

GWQMN (475)

CN2 (0.06)

SOL_K (0.31)

LATTIME (116)

100 ha LATTIME (6)

CN2 (0.06)

GWQMN (3875)

CN2 (0.08)

LATTIME (2.7)

SOL_K (3)

OBS 1500 ha SOL_K (8)

LATTIME (6)

SOL_AWC (0.04)

SOL_K (6)

CH_N2 (0.13)

SURLAG (16)

100 ha SOL_K (8)

LATTIME (6)

GWQMN (3875)

SOL_K (6)

CN2 (-0.04)

SURLAG (16)

810 km² SAF 1500 ha SOL_K (5)

CN2 (-0.05)

SOL_AWC (0.06)

SOL_K (5)

CH_N2 (0.14)

CN2 (-0.05)

100 ha SOL_K (5)

GWQMN (625)

ALPHA_BF (0.69)

SOL_K (6)

SURLAG (9)

ALPHA_BF (0.72)


CN2 (-0.05)

CH_N2 (0.14)

SOL_K (5)

CH_N2 (0.14)

CN2 (-0.05)

100 ha SOL_K (6)

CN2 (0.01)

SOL_BD (0.04)

SOL_K (6)

CN2 (0.01)

SOL_BD (0.04)

1400 km² SAF 1500 ha SOL_K (5)

RCHRG_DP (0.50)

GWQMN (625)

CH_N2 (0.13)

RCHRG_DP (0.28)

GWQMN (4775)

100 ha SOL_K (3)

CH_N2 (0.05)

RCHRG_DP (0.04)

CH_N2 (0.15)

RCHRG_DP (0.09)

CN2 (-0.02)

OBS 1500 ha CH_N2 (0.05)

SOL_K (0.05)

GWQMN (2375)

CH_N2 (0.11)

RCHRG_DP (0.64)

GWQMN (4275)

100 ha CH_N2 (0.15)

LATTIME (26)

SOL_BD (0.04)

CH_N2 (0.11)

LATTIME (33)

SOL_K (8)

9 parameters out of 21


21



CN2 (0.06)

GWQMN (475)

CN2 (0.06)

SOL_K (0.31)

LATTIME (116)

100 ha LATTIME (6)

CN2 (0.06)

GWQMN (3875)

CN2 (0.08)

LATTIME (2.7)

SOL_K (3)


LATTIME (6)

SOL_AWC (0.04)

SOL_K (6)

CH_N2 (0.13)

SURLAG (16)

100 ha SOL_K (8)

LATTIME (6)

GWQMN (3875)

SOL_K (6)

CN2 (-0.04)

SURLAG (16)

810 km² SAF 1500 ha SOL_K (5)

CN2 (-0.05)

SOL_AWC (0.06)

SOL_K (5)

CH_N2 (0.14)

CN2 (-0.05)

100 ha SOL_K (5)

GWQMN (625)

ALPHA_BF (0.69)

SOL_K (6)

SURLAG (9)

ALPHA_BF (0.72)


CN2 (-0.05)

CH_N2 (0.14)

SOL_K (5)

CH_N2 (0.14)

CN2 (-0.05)

100 ha SOL_K (6)

CN2 (0.01)

SOL_BD (0.04)

SOL_K (6)

CN2 (0.01)

SOL_BD (0.04)

1400 km² SAF 1500 ha SOL_K (5)

RCHRG_DP (0.50)

GWQMN (625)

CH_N2 (0.13)

RCHRG_DP (0.28)

GWQMN (4775)

100 ha SOL_K (3)

CH_N2 (0.05)

RCHRG_DP (0.04)

CH_N2 (0.15)

RCHRG_DP (0.09)

CN2 (-0.02)

OBS 1500 ha CH_N2 (0.05)

SOL_K (0.05)

GWQMN (2375)

CH_N2 (0.11)

RCHRG_DP (0.64)

GWQMN (4275)

100 ha CH_N2 (0.15)

LATTIME (26)

SOL_BD (0.04)

CH_N2 (0.11)

LATTIME (33)

SOL_K (8)

SOL_K > CN2 > CH_N2


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CN2 (0.06)

GWQMN (475)

CN2 (0.06)

SOL_K (0.31)

LATTIME (116)

100 ha LATTIME (6)

CN2 (0.06)

GWQMN (3875)

CN2 (0.08)

LATTIME (2.7)

SOL_K (3)


LATTIME (6)

SOL_AWC (0.04)

SOL_K (6)

CH_N2 (0.13)

SURLAG (16)

100 ha SOL_K (8)

LATTIME (6)

GWQMN (3875)

SOL_K (6)

CN2 (-0.04)

SURLAG (16)

810 km² SAF 1500 ha SOL_K (5)

CN2 (-0.05)

SOL_AWC (0.06)

SOL_K (5)

CH_N2 (0.14)

CN2 (-0.05)

100 ha SOL_K (5)

GWQMN (625)

ALPHA_BF (0.69)

SOL_K (6)

SURLAG (9)

ALPHA_BF (0.72)


CN2 (-0.05)

CH_N2 (0.14)

SOL_K (5)

CH_N2 (0.14)

CN2 (-0.05)

100 ha SOL_K (6)

CN2 (0.01)

SOL_BD (0.04)

SOL_K (6)

CN2 (0.01)

SOL_BD (0.04)

1400 km² SAF 1500 ha SOL_K (5)

RCHRG_DP (0.50)

GWQMN (625)

CH_N2 (0.13)

RCHRG_DP (0.28)

GWQMN (4775)

100 ha SOL_K (3)

CH_N2 (0.05)

RCHRG_DP (0.04)

CH_N2 (0.15)

RCHRG_DP (0.09)

CN2 (-0.02)

OBS 1500 ha CH_N2 (0.05)

SOL_K (0.05)

GWQMN (2375)

CH_N2 (0.11)

RCHRG_DP (0.64)

GWQMN (4275)

100 ha CH_N2 (0.15)

LATTIME (26)

SOL_BD (0.04)

CH_N2 (0.11)

LATTIME (33)

SOL_K (8)

SOL_K > LAT_TTIME > CN2

SOL_K > LAT_TTIME

CH_N2 > RCHRG_DP

Conclusions

• For a 90 km2 basin without dam: – Hourly simulations catch sub-daily peaks but Nash are

lower than daily Nash

– Rainfall distribution and sub-basin delineation are sensitive model inputs • Simulations with PCP from rain gauges seems more reliable than

modelled PCP grids

• It seems there is no need to discretize the basin at 100 ha

– SOL_K appears to be the most sensitive parameter and needs to be accurately estimated

• For bigger basins with dams: – The quality of the hourly simulation depends on the

quality of the daily out-of-dam discharge data (*.day file)

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Perspectives

• Simulation of suspended sediments

• Coupling with the process oriented MARINE model – Comparison of the hourly simulated discharge. If ok:

– Soil water content to initialize the MARINE model

– Later also suspended sediments in runoff

• Application to the other coastal flash-flood prone basins of the Lion Gulf

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Lion Gulf

Come and see the posters this afternoon !

Thank you for your attention !

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[email protected]

Effect of the daily discharge out of the Vinça dam…

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Dé

bit

(m

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débit sortant Vinça(m3/s)

Q observed Perpi

The calibration on Perpignan does not make much sense !

… on the discharge in Perpignan

Documents

Application of the SWAT model to Mediterranean flash floods ...number of measures 2009-2011: Catl: 14977; Marq: 18765; Perp: 25909 Catllar: 90 km² Marquixanes: 810 km² Perpignan: