Application of the SWAT model to Mediterranean flash floods ...number of measures 2009-2011: Catl:...
Transcript of Application of the SWAT model to Mediterranean flash floods ...number of measures 2009-2011: Catl:...
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?
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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?
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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).
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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.
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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
Data for model set up
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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
Data for model set up
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20
40
60
80
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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0
5
10
15
20
25
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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10
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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
0
5
10
15
20
25
9/29 10/19 11/8
Dai
ly d
isch
arge
(m
3/s
)
0
5
10
15
20
2/26 3/18 4/7
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4
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10
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10/24 11/13 12/3 12/23
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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70
1/17 8/5 2/21 9/9 3/28 10/14
Ho
url
y d
isch
. (m
3/s
)
Simulated 100ha SAFSimulated 100ha OBSSimulated 1500ha SAFSimulated 1500ha OBSObserved
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10
20
30
40
50
60
70
10/9 10/14 10/19
Ho
ruly
dis
char
ge (
m3
/s)
0
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30
40
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3/13 3/18 3/23
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5
10
15
11/3 11/13 11/23 12/3
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
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2009-2011
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
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2009-2011
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
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2009-2011
Missing upstream dam data?
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
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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)
OBS 1500 ha SOL_K (5)
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
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)
OBS 1500 ha SOL_K (5)
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
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)
OBS 1500 ha SOL_K (5)
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 !
Effect of the daily discharge out of the Vinça dam…
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Dé
bit
(m
3/s
)
débit sortant Vinça(m3/s)
Q observed Perpi
The calibration on Perpignan does not make much sense !
… on the discharge in Perpignan