26
PROJECT OVERVIEW & APPLICATIONS HYDROSYS EPFL‐EFLUM Dec. 10th 2009
| Date post: | 05-Dec-2014 |
| Category: |
Technology |
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PROJECTOVERVIEW&APPLICATIONS
HYDROSYS
EPFL‐EFLUMDec.10th2009
ProjectGoals
Enablingon‐sitedatacollec0on,visualiza0onandtransfertosupportnewwaysofobservingenvironmentalprocesses.
Providingasysteminfrastructuretosupportteamsofusersintheon‐sitemonitoringofeventsandanalysisofnaturalresources.Itintroducestheinnova0veconceptofevent‐drivencampaignsusinghandhelddevices,poten0allysupportedbyanunmannedaerialvehicle(UAV).
Improvingmonitoringandmanagementforenvironmentalscien0sts,ins0tu0ons,serviceproviders,engineeringcompaniesandmunicipali0esthroughitsstrongintegra0onofhandhelds,sensornetworksandmodeling.
www.hydrosysonline.eu
ProjectGoals
La Fouly: GEOtop application to an instrumented watershed in the Valais
Silvia Simoni
Environmental Fluid Mechanics Department - EPFL
2. GEOtop overviewfor details: www.geotop.org
Outline
3. Rainfall-run off modeling using La Fouly data
1. Rationale for using a 3D-physically based modelData spatial variability
4. Snow melt: how to deal with it in absence of measured snow depth
Lausanne Dec. 10th 2009 - Silvia Simoni
catchment area=20 km2
z min=1785 m z max=3238 m
Location: La Fouly - Val Ferret, Orsiere VS.
La Fouly deployment
main stream: Dranse de Ferret
water level measuring point
Available data
Meteorological data (precipitation, wind speed and velocity, air temperature and humidity, radiation)0
100
300
water level @ the outlet − hourly mean
wate
r lev
el [m
m]
18/06 25/06 02/07 09/07 16/07 23/07 30/07 05/08 12/08 19/08 26/08 02/09 09/09 16/09 23/09 30/09 07/10
010
030
00
24
68
hourly cumulated rain @ ST1033
prec
ipita
tion
[mm
]
18/06 25/06 02/07 09/07 16/07 23/07 30/07 05/08 12/08 19/08 26/08 02/09 09/09 16/09 23/09 30/09 07/10
02
46
8−5
05
1020
hourly averaged air Temperature @ ST1033
Air T
empe
ratu
re [C
]
18/06 25/06 02/07 09/07 16/07 23/07 30/07 05/08 12/08 19/08 26/08 02/09 09/09 16/09 23/09 30/09 07/10
−50
510
200
400
800
1200
Incoming short wave radiation @ ST1033
ISW
radi
atio
n [W
/m2]
18/06 25/06 02/07 09/07 16/07 23/07 30/07 05/08 12/08 19/08 26/08 02/09 09/09 16/09 23/09 30/09 07/10
040
080
012
00
Soil data (soil moisture, suction and temperature)
Water level data Discharge from rating curve
PeriodJune - October 2009
10 Sensorscope stations
Lausanne Dec. 10th 2009 - Silvia Simoni
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Discharge rating curve
Lausanne Dec. 10th 2009 - Silvia Simoni
0
1000
2000
3000
4000
5000
6000
7000
8000
0 10 20 30 40 50
Q [l/s]
h [cm]
MeasumentsDischarge rating curve Q=1.594 (h+15.56)
2.03
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Spatial variability of rainfall
Swiss-South Africa Joint Scientific Conference, Nov 5th 20098
Italy
NItaly
GPRS base station
G. S
. Ber
nard
01
23
45
Hourly Cumulated Rainfall measured @ SS1032
time (day/month)
cum
ula
ted r
ain
[m
m]
18/06 21/06 25/06 28/06 01/07 04/07 08/07 11/07 14/07 17/07 21/07 24/07 27/07 30/07 03/08 06/08 09/08
0
SG1038SG1044
ST1037
SS1032 ST1035ST1036
ST1034
SS1033ST1043
ST1042ST1041
ST1040
02
46
8
Hourly Cumulated Rainfall @ ST1042
time (day/month)
cum
ula
ted r
ain
[m
m]
18/06 21/06 25/06 28/06 01/07 04/07 08/07 11/07 14/07 17/07 21/07 24/07 27/07 30/07 03/08 06/08 09/08
0
Lacs de Fenetre
100
200
300
400
500
water level @ La Fouly 2009 data − hourly mean
time (day/month)
wate
r lev
el [m
m]
20/05 26/05 01/06 07/06 12/06 18/06 24/06 30/06 06/07 11/07 17/07 23/07 29/07 04/08 09/08 15/08 21/08 27/08
500
GPS base station
Spatial variability effect on Precipitation
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0 2 4 6 8
02
46
810
ST1033 mm
ST10
40 m
m
Station Scattergram for the stations
x=182 m
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0 2 4 6 8
02
46
810
ST1033 mm
ST10
36 m
m
x=1243 m
Lausanne Dec. 10th 2009 - Silvia Simoni
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Spatial variability effect on Precipitation
●
●●●
●
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●
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0 500 1000 1500 2000
0.0
0.2
0.4
0.6
0.8
1.0
Influence of spatial distance on the spatial correlation between stations (based on rainfall data)
real distance between stations [m]
corre
latio
n co
effic
ient
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0.0
0.2
0.4
0.6
0.8
1.0
Influence of Aspect on the spatial correlation between stations (based on rainfall data)
aspect difference between stations [deg]
corre
latio
n co
effic
ient
0 30 60 90 120 150 180
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Lausanne Dec. 10th 2009 - Silvia Simoni
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Spatial variability effect on cumulated Precipitation
Lausanne Dec. 10th 2009 - Silvia Simoni
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
●
●
●
●
●
●
●
●
100
200
300
400
Spatial variability impact on totally cumulated rainfall
elevation [m a.s.l.]
tota
l cum
rain
fall [
mm
]
1700 1800 1900 2000 2100 2200 2300 2400 2500
1032
1033
10341036
1037
1040
10421043
ST1037
SS1032 ST1035
ST1036ST1034
SS1033ST1043
ST1042ST1041ST1040
Spatial variability effect on wind speed and directions
Lausanne Dec. 10th 2009 - Silvia Simoni
Meteorological station: 1034
N
NE
E
SE
S
SW
W
NW
Wind velocity [m/s]v >= 5.0
3.0 <= v < 5.02.0 <= v < 3.01.0 <= v < 2.00.5 <= v < 1.0calm (v < 0.5)
0.0% 7.5% 15.0% 22.5% 30.0%
Meteorological station: 1033
N
NE
E
SE
S
SW
W
NW
Wind velocity [m/s]v >= 5.0
3.0 <= v < 5.02.0 <= v < 3.01.0 <= v < 2.00.5 <= v < 1.0calm (v < 0.5)
0.0% 6.5% 13.0% 19.5% 26.0%
Meteorological station: 1035
N
NE
E
SE
S
SW
W
NW
Wind velocity [m/s]v >= 5.0
3.0 <= v < 5.02.0 <= v < 3.01.0 <= v < 2.00.5 <= v < 1.0calm (v < 0.5)
0.0% 5.0% 10.0% 15.0% 20.0%
Meteorological station: 1037
N
NE
E
SE
S
SW
W
NW
Wind velocity [m/s]v >= 5.0
3.0 <= v < 5.02.0 <= v < 3.01.0 <= v < 2.00.5 <= v < 1.0calm (v < 0.5)
0.0% 6.0% 12.0% 18.0% 24.0%
Meteorological station: 1040
N
NE
E
SE
S
SW
W
NW
Wind velocity [m/s]v >= 5.0
3.0 <= v < 5.02.0 <= v < 3.01.0 <= v < 2.00.5 <= v < 1.0calm (v < 0.5)
0.0% 5.0% 10.0% 15.0% 20.0%
Meteorological station: 1042
N
NE
E
SE
S
SW
W
NW
Wind velocity [m/s]v >= 5.0
3.0 <= v < 5.02.0 <= v < 3.01.0 <= v < 2.00.5 <= v < 1.0calm (v < 0.5)
0.0% 6.5% 13.0% 19.5% 26.0%
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
July 9th 2009
N
Spatial interpolation of Precipitation
July 2th 2009
Lausanne Dec. 10th 2009 - Silvia Simoni
02
46
810
Hourly Cumulated Rainfall @ ST1043
time (day/month)
cum
ula
ted r
ain
[m
m]
18/06 25/06 02/07 09/07 15/07 22/07 29/07 05/08 12/08 19/08 25/08 01/09 08/09 15/09 22/09 29/09 05/10 12/10
0
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
snow, ice, permafrostwater cycle
natural hazards
GEOtop model
14
evapo-transpiration, energy fluxesBertoldi et al., 2006
Endrizzi 2007
Simoni 2007
Rigon et al., 2006
Open source LGPL3
The GEOtop model1. 3D topography
3. Energy balance- radiation- boundary-layer interaction- snow and glacier melt- freezing soil
2. Water balance
- effective rainfall- surface flow- subsurface flow- snow/ice melt
- distributed model- DEM preprosessing: drainage directions => channel network
slopes and aspect => radiationcurvatures => shadowingsky view factor => radiation
Lausanne Dec. 10th 2009 - Silvia Simoni
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Rainfall-run off - infiltration mechanism
Infiltration: Richards 3D or Richards 1D + lateral darcian flow
Effective rainfall: vegetation accounted for
Drainage along slopes: kinematic scheme
Channel routing: Saint-Venant equation
!"
!t
d#
d"=
!
!x
!KL(")
"!"
!x! sin$
#$+
!
!y
!KL(")
"!"
!y
#$+
!
!z
!Kz(")
"!"
!x! cos$
#$
Lausanne Dec. 10th 2009 - Silvia Simoni
W water inflow from hillslopes into the channel network at a distance s from the outlet at time !
W (x, t) = !c(x, t)
Q(x, t) = AT
! t
0
! L
0
sW (!, s)"4"D(t! !)3
exp
#! (s! uc(t! !))2
4D(t! !)
$dsd!
c(x, t) = Cmh(x, t)! [!z(x)]0.5
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Rainfall-run off contribute
Determining a stage-discharge relationship
020
0040
00Discharge @ La Fouly 2009 data from ST1043
time (day/month)
run
off [
l/s]
27/06 03/07 10/07 16/07 22/07 29/07 04/08 10/08 17/08 23/08 29/08 05/09 11/09 17/09 24/09 30/09 06/10 13/10
020
0040
00 GEOtop no snow
Q measured
05
1015
time
Disc
harg
e [m
3/s]
Modeled discharge at La Fouly: sensitivity analysis on D and C_m
18/06 25/06 01/07 08/07 14/07 21/07 27/07 03/08 09/08 16/08 22/08 29/08 04/09 11/09 17/09 24/09 30/09 07/10
05
1015 D=100 m2/s C_m=0.5 m^1/3/s, n_Dt_w=10
D=50 m2/s C_m=0.25 m^1/3/s, n_Dt_w=2
D=50 m2/s, C_m=0.25 m^1/3/s, n_Dt_w=10
Lausanne Dec. 10th 2009 - Silvia Simoni
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Soil moisture
Lausanne Dec. 10th 2009 - Silvia Simoni
2530
3540
4550
Soil Moisture − 20cm @ SS1043
time (day/month)
Soil m
oist
ure
[−]
18/06 25/06 02/07 09/07 15/07 22/07 29/07 05/08 12/08 19/08 25/08 01/09 08/09 15/09 22/09 29/09 05/10 12/10
2530
3540
4550
Soil Moist. (V)
Precip
02
46
810
Hou
rly c
umul
ated
rain
[mm
]
1043
Measured soil moisture
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Soil moisture
Lausanne Dec. 10th 2009 - Silvia Simoni
2530
3540
4550
Soil Moisture − 20cm @ SS1043
time (day/month)
Soil m
oist
ure
[−]
18/06 25/06 02/07 09/07 15/07 22/07 29/07 05/08 12/08 19/08 25/08 01/09 08/09 15/09 22/09 29/09 05/10 12/10
2530
3540
4550
Soil Moist. (V)
Precip
02
46
810
Hou
rly c
umul
ated
rain
[mm
]
1043
Measured soil moisture
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Soil moisture
Lausanne Dec. 10th 2009 - Silvia Simoni
2530
3540
4550
Soil Moisture − 20cm @ SS1043
time (day/month)
Soil m
oist
ure
[−]
18/06 25/06 02/07 09/07 15/07 22/07 29/07 05/08 12/08 19/08 25/08 01/09 08/09 15/09 22/09 29/09 05/10 12/10
2530
3540
4550
Soil Moist. (V)
Precip
02
46
810
Hou
rly c
umul
ated
rain
[mm
]
1043
Measured soil moisture
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Soil moisture
Lausanne Dec. 10th 2009 - Silvia Simoni
2530
3540
4550
Soil Moisture − 20cm @ SS1043
time (day/month)
Soil m
oist
ure
[−]
18/06 25/06 02/07 09/07 15/07 22/07 29/07 05/08 12/08 19/08 25/08 01/09 08/09 15/09 22/09 29/09 05/10 12/10
2530
3540
4550
Soil Moist. (V)
Precip
02
46
810
Hou
rly c
umul
ated
rain
[mm
]
1043
Measured soil moisture
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Modeled soil moisture
0.20
0.30
0.40
0.50
Soil Moisture @ ST1043
soil m
oist
ure
[−]
24/06 24/06 25/06 26/06 27/06 28/06 29/06 30/06 01/07 02/07 03/07 04/07 05/07 05/07 06/07 07/07 08/07
0.20
0.30
0.40
0.50
0.125 m0.3 m
0.3 m measured
Adding snow melt
Challange: setting initial condition on snow depthhow to???
020
0040
00
Discharge @ La Fouly 2009 data from ST1043
time (day/month)
run
off [
l/s]
27/06 03/07 10/07 16/07 22/07 29/07 04/08 10/08 17/08 23/08 29/08 05/09 11/09 17/09 24/09 30/09 06/10 13/10
020
0040
00 GEOtop no snow
Q measured
Lausanne Dec. 10th 2009 - Silvia Simoni
MODIS data June 27th 2009
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
Adding snow melt
Lausanne Dec. 10th 2009 - Silvia Simoni
1. Data 2. Spatial variability 3. GEOtop 4. Rainfall-run off 5.Snow melt 6.Soil moisture
020
0040
00Discharge @ La Fouly 2009 data from all stations
time (day/month)
run
off [
l/s]
27/06 03/07 10/07 16/07 22/07 29/07 04/08 10/08 17/08 23/08 29/08 05/09 11/09 17/09 24/09 30/09 06/10 13/10
020
0040
00 GEOtop no snow
Q measured
First attempts
Snow depth distribution according to topography, slope and aspect
2. Characterizing the soil more in detail to improve soil moisture modeling
Further work
4. Investigating subsurface flows and their link with potential hazards such as debris-flows and shallow landslide.
1. Introducing snow melt
.....
3. Comparing fluxes computed from flux tower with the ones computed by the model.
Lausanne Dec. 10th 2009 - Silvia Simoni
Enjoy GEOtop!
snow, ice, permafrostwater cycle
natural hazards
evapo-transpiration, energy fluxes
