The rational behind GEOtop: through its historical development and applications R. Rigon Dipartimento di Ingegneria Civile ed Ambientale - CUDAM Università di Trento
Dec 07, 2014
The rational behind GEOtop:through its historical
development and applicationsR. Rigon
Dipartimento di Ingegneria Civile ed Ambientale - CUDAM
Università di Trento
Four or Five problems we wanted toinvestigate
Rainfall–Runoff spatial patterns
Problem : We cannot currently predict the spatial pattern of watershed response to precipitation and cannot quantitatively describe the surface and subsurface
contributions to streamflow with enough accuracy and consistency to be operationally useful.
Critical issues: Watershed runoff and streamflow are affected by heterogeneity in soil hydraulic properties, landscape structural properties, soil moisture profile,
surface–subsurface interaction, interception by plants, snowpack, and storm properties.
(Committee of hydrological Sciences NRC, 2003)
Snow mantle evolution and ablation
Problem: We would like to predict the spatial pattern of snow cover, its volumes and its effects on runoff with enough accuracy and consistency to be operationally
useful.
Critical Issue: Also in this case we know enough of the snow physics “in a point” but we do not have many tools
to understand the snow cover effects on larger, catchment scales.
Related problem: snow avalanches
Soil freezing and permafrost
Problem: We would like to predict the spatial pattern of soil temperatures even in complex terrain and in presence
of phase transitions
Critical Issue: Soil freezing introduces high non linearities at low temperatures.
Related problem: snow avalanches
Landslide and debris flow initiationProblem: We cannot currently predict, the triggering of
shallow landslides which eventually turns into a debris or a mudflow.
Critical Issue: Initial and boundary conditions. Landslide initiation is affected by heterogeneity in soil hydraulic and
geotechnical properties, landscape structural and geological properties, soil moisture profile, surface–
subsurface interactions.
We did not forget Ecohydrology ...but we will not discuss it here
Problem: We wouldlike to better understand the interactions between soils, hydrology and plants.
Critical Issues: the biological system are highly non linear. The basic physiological laws are not really known (or
hydrologist ignore many of them)
Committee of hydrological Sciences NRC, 2003:
“Although our understanding of individual processes is improving, the integration of that body of knowledge in
spatially distributed predictive models has not been approached systematically”.
This talk is not about new equations or new paradigms: is mostly abot consistency of the modeling approach. It
show a tool we use to lear about the hydrological processes at the small scales.
A small tribute to Stephan Gruber
We present here the evolution of the GEOTOP models and discuss their limitation
The GEOtop Project
GEOtop 0.5 was the ancestor (1997)
Paolo Verardo and Marco Pegoretti coded it
GEOtop 0.5 was the ancestor (1997)
GIUH +Kinematic wave+
Bucket model
Paolo Verardo and Marco Pegoretti coded it
GEOtop 0.5 was the ancestor (1997)
GIUH +Kinematic wave+
Bucket model
Penm
an-M
onte
ith
+Ra
diat
ion
Phys
ics
Paolo Verardo and Marco Pegoretti coded it
GEOtop 0.5 (1997)P
Qsup
Qsub
I∂Qsup
∂t+ c(x)
∂Qsup
∂s= c(x) qLc ∝ y(x)m
Qsub = T∇z b
Qc(t) =Z t
0dτ
Z L
odx
x W (x,τ)!4πDL(t! τ)
exp"!x!u(t! τ)
2
4DL(t! τ)
#
Eagleson, 1971; Beven and Kirkby, 1979; Rodriguez-Iturbe and Valdes, 1979; Rinaldo et al., 1991
GEOtop 0.5 (1997)
Brutsaert, 1975; Iqbal, 1983; Garrat, 1992, Enthekabi, 1997 and many others
ET =Δ/λ(Rn!G) +ρ/ra δqa
1+Δ/γ+ rg/ra
Rn = [sh R "SW P + V R "SW D] (1!V α)+VεsR "LW !VεsσT 4s
ET Rn
G
GEOtop 0.5 (1997)
Brutsaert, 1975; Iqbal, 1983; Garrat, 1992, Enthekabi, 1997 and many others
ET =Δ/λ(Rn!G) +ρ/ra δqa
1+Δ/γ+ rg/ra
Rn = [sh R "SW P + V R "SW D] (1!V α)+VεsR "LW !VεsσT 4s
ET Rn
G
Calculating ET in highly complex terrain needs a proper treatment of radiation physics (including the effect of the vie angle and the shadowing). Below you see how much
this is a limit for radiation to arrive to the surface.
GEOtop 0.5 (1997)
ET Rn
G
ET =Δ/λ(Rn!G) +ρ/ra δqa
1+Δ/γ+ rg/ra
Rn = [sh R "SW P + V R "SW D] (1!V α)+VεsR "LW !VεsσT 4s
Albedo is a key factor too. It can be easily detected from Earth Observation (EO) products and simple modelling of the canopy evolution during the seasons (actually still not
included in GEOTOP)
GEOtop 0.5 Real ET
After Feddes et al, 1988
Real ET is obtained cutting the potential ET in dependence of water availability. In complex terrain water tend to
accumulate in lowland concave - convergent sites.
Many large scale hydrological models pretends to give ET estimation by neglecting this fact ;-)
GEOtop 0.5 worked well for flood predictions and weekly ET (after a proper parameter calibration). It also showed
some dynamics on the soil moisture storage (dS/dt = 0 in some models!) and redistribution at catchment scale,
HOWEVER ....
It could not describe properly the vertical distribution of soil moisture in soils (essential to landslide forecasting and
emissivity estimations). Moreover, using air T for soil T (Ts) was a huge limitation.
GEOtop 0.75 (2000)
GIUH +Kinematic wave+
Bucket model
Radi
atio
n Ph
ysic
s
Ener
gy b
udge
t in
tegr
atio
n
Code integrations by Giacomo Bertoldi
GEOtop 0.75 is conceived to integrate the full energy balance. As a consequence Ts becomes a variable of the model (this obviuosly complicates GEOtop) but increases at the same the possibility to check its behavior (Ts or its radiative effect is a measurable quantity): we add complexity but at the same time we add observables. Ts is strongly affected by water content.
GEOtop 0.75 Energy Balance (2000)
dEdt
=CpdTsdt
= Rn!H!ET +Qp!G!Qm
H = ρ cpCH u(Ts!Ta)
ET = λρCe u(q"(Ta)!q"(Ta)Ua)
G
HRn ET Qp
Qm
dE/dt
CH, CE ↑
CH, CE ↓
Aerodynamic roughness length
Ts>Ta
Ts<Ta
Similarity theory by Louis (1979)
GEOtop 0.75 (2000): Turbulent fluxes appear!
Pointwise calibration of fluxes Little Washita (OK) SGP 97 data set
Key parameters: roughness length, initial soil moisture
We did also simulation of the soil moisture content in the Washita basin. However the soil moisture content given by the model has no vertical distribution and any comparison with the SGP97 dataset CANNOT be very reliable. Below you see results of the model for other cases studies that show the opportunities that a model like GEOtop offers.
0 12 24 36 48 60 72 84 96 108 120 W/m2
Winter
Summer
Spring
Fall
Mean seasonal ET at Serraia (TN)
Grafico bilancio del bacino del Lago della Serraia (1998 - 2000)
-0.200-0.1000.0000.1000.2000.3000.4000.5000.6000.7000.8000.9001.0001.1001.200
gen-98
feb-98
mar-98
apr-9
8
mag
-98
giu-98
lug-98
ago-98
set-9
8
ott-9
8
nov-98
dic-98
gen-99
feb-99
mar-99
apr-9
9
mag
-99
giu-99
lug-99
ago-99
set-9
9
ott-9
9
nov-99
dic-99
gen-00
feb-00
mar-00
apr-0
0
mag
-00
giu-00
lug-00
ago-00
set-0
0
ott-0
0
nov-00
dic-00
Tempo (mese-anno)
Po
rta
ta m
ed
ia m
en
sil
e (
mc
/s)
-60.6-30.30.030.360.690.9121.1151.4181.7212.0242.3272.6302.9333.1363.4
Inte
ns
ita
(m
m/m
es
e)
P - precipitazione ET - evapotraspirazioneInv - volume invasato (accumulo) R - rilascio
Hydrological Balance 1998-2000Serraia (TN)
One interesting thing to check would be the sensitivity of the hydrological balance partition to the parameter
set.
Serraia
There is a strong spatial variability of vertical surface fluxes: do they induce feedback effects ?Are those processes negligible at larger scales ?
A more accurate ABL model would be necessary to try an answer.
We cannot compare our model result with ESTAR because we do not have vertical distribution of soil moisture.
What happens when no topographic gradient is present ?
GEOtop 0.875 (2003)
GIUH +Kinematic wave+
Richards +Soil freezing &
Snow Cover
Radi
atio
n Ph
ysic
s
Ener
gy b
udge
t in
tegr
atio
n
Code integrations by Davide Tamanini
Dunne Saturation Overland Flow
Unsaturated Layer
Surface Layer
Saturated Layer:
Horton Overland Flow
Modified from Abbot et al., 1986
Richards’ equation is solved
σ(ψ)∂ψ∂t
= ∇ · (K(ψ)∇(ψ+ηz))+qs
ψ=1α
!"θr!θsθs!θr
#1/m
!1$1/n
K(θ) = KS"θr!θsθs!θr
#ν!1!
!1!
"θr!θsθs!θr
#1/m$m$2
Richards, 1931; van Genuchten, 1980; Mualem, 1976; Veerecken, 1990; Sposito, 1997, Putti et al, 2004
We acknowledge the SHE model however GEOtop REALLY integrate the energy balance. Still GEOtop is 1D for energy fluxes but it is a complete 3D system for mass fluxes. As one can notice we used van Genuchten and Mualem parametrizations of Richards equation. Under this hypothesis Sposito 1997 shows that the equation is almost scale invariant (at the price to introduce a suitable factor in block effective hydraulic conductivities). Parameters are obtained by the Veerecken pedotransfer function.
Snow cover is modeled(single layer)
Tarboton and Luce, 1996; Zanotti et al, 2004
Snow cover and soil freezing cannot be neglected in mountain areas and if we want to model the hydrological cycle during the whole year. Because water viscosity strongly depends on temperature we added it to the model as a first step to have a consistent thermodynamic system. As you find below, parametrization of subgrid variability is still needed also at these scales. Finally we could realistically compare GEOtop and ESTAR.
- Rilling is parametrized
- Conductivity is made dependent on Ts
ESTAR vs GEOtop soil moisture evolution
Jackson T.J., http://hydrolab.arsusda.gov/sgp97; Jackson et al, 1995
Rigon et al., JHM, 2006
Rigon et al., JHM, 2006
Some other case studies
Saturation overland flow in a headwater catchment:
application to Solstice Basin (CA)
in collaboration with Bill Dietrich and Norman Miller (Berkeley University)
The Solstice Basin (CA)
Headwater catchment located in Marin County, CA, area 16’000 m2;
Colluvial soil: maximum thickness from 2 to 5.5 meters in the hollows, from 0.2 to 0.7 m on sideslopes
Monitored during years 1986-’87 (C. Wilson, W.E. Dietrich)
120 piezometers on sideslopes and hollows
Saturated source area measurement.
Basin and bedrock topography
Experimental evidence:February 1986 storm
• measured rainfall each 6 h• measured stream flow each 6 h
0
10
20
30
40
50
60
70
8011-Feb
12-Feb
13-Feb
14-Feb
15-Feb
16-Feb
17-Feb
18-Feb
19-Feb
20-Feb
21-Feb
22-Feb
23-Feb
24-Feb
Rai
nfal
l mm
/6h
0
10
20
30
40
50
60
70
80
Stre
amflo
w l/
s
Solstice raingage mm/6h Pan Toll Raingage mm/6h
Measured Streamflow l/s
• Total storm 400 mm in 10 days• measured saturated area: “squishy soil”
Experimental evidence: hypothesis on the hydrologic behavior (Wilson and Dietrich, 1988)
a) Cross - hollow direction - Deep water table in the sideslopes - Infiltration gradients in the sideslopes - Exfiltration gradients in the hollows
Experimental evidence: hypothesis on the hydrologic behavior (Wilson and Dietrich, 1988)
a) Cross - hollow direction - Deep water table in the sideslopes - Infiltration gradients in the sideslopes - Exfiltration gradients in the hollows
b) Long - hollow direction - Saturation overland flow - Shallow water table - Effects of local conductivity changes
Experimental evidence: hypothesis on the hydrologic behavior (Wilson and Dietrich, 1988)
a) Cross - hollow direction - Deep water table in the sideslopes - Infiltration gradients in the sideslopes - Exfiltration gradients in the hollows
b) Long - hollow direction - Saturation overland flow - Shallow water table - Effects of local conductivity changes
c) Expansion of saturation saturated area - Expansion beginning from the nose of the hollows
Experimental evidence: hypothesis on the hydrologic behavior (Wilson and Dietrich, 1988)
Conductivities against depht: model with 8 layers
0
200
400
600
800
1000
1200
1400
1.00E-071.00E-061.00E-051.00E-041.00E-031.00E-021.00E-01Kv cm/s
dep
ht
cm
Solstice1 Solstice2 Sideslope Model
Soil parameters settings:• 8 soil layers with 20 m thickness• Impermeable boundary condition• Spin-up of 3 years
Bedrock shape variation:• With uniform soil profile• With measured bedrock shape • Bedrock with different permeability
Soil and bedrock properties:
Sideslopes: shallow conductive bedrock
K decreasing with depth
Hollows: loamy-sand thick colluvium, deep impermeable bedrock, some conductive points (Lehre et al. , 1986)
GEOtop model settings
• Surface conductivity 0.01 m/s• Subsurface conductivity in first layer 0.001 m/s
Either slow turbulent surface flow or quick shallow subsurface strom flow: equifinallity or preferential flow evidence?
GEOtop model results
GEOtop model results Saturated area - water content first layer 5 cm
Hollows partially saturated at the beginning of the storm
0
10
20
30
40
50
60
70
8011-Feb
12-Feb
13-Feb
14-Feb
15-Feb
16-Feb
17-Feb
18-Feb
19-Feb
20-Feb
21-Feb
22-Feb
23-Feb
24-Feb
Rai
nfal
l mm
/6h
0
10
20
30
40
50
60
70
80
Stre
amflo
w l/
s
Solstice raingage mm/6h Pan Toll Raingage mm/6h
Measured Streamflow l/s
GEOtop model results Saturated area - water content first layer 5 cm
0
10
20
30
40
50
60
70
8011-Feb
12-Feb
13-Feb
14-Feb
15-Feb
16-Feb
17-Feb
18-Feb
19-Feb
20-Feb
21-Feb
22-Feb
23-Feb
24-Feb
Rai
nfal
l mm
/6h
0
10
20
30
40
50
60
70
80
Stre
amflo
w l/
s
Solstice raingage mm/6h Pan Toll Raingage mm/6h
Measured Streamflow l/s
Different behavior of the hollows and the side slopes at the peak
Measured discontinuous patterns at the end of the event
0
10
20
30
40
50
60
70
8011-Feb
12-Feb
13-Feb
14-Feb
15-Feb
16-Feb
17-Feb
18-Feb
19-Feb
20-Feb
21-Feb
22-Feb
23-Feb
24-Feb
Rai
nfal
l mm
/6h
0
10
20
30
40
50
60
70
80
Stre
amflo
w l/
s
Solstice raingage mm/6h Pan Toll Raingage mm/6h
Measured Streamflow l/s
GEOtop model results Saturated area - water content first layer 5 cm
GEOtop model results total head gradient- first layer 5 cm
Mostly topographically driven
Not only topography drives down-slope water flow but also suction potential drives the up-slope expansion of the saturated area. Delay in basins response, increase of saturated area
GEOtop model results total head gradient- first layer 5 cm
Mass movementsat Sauris (UD)
basin
Mostly worked out by S. Simoni and F. Zanotti
GEOtop 0.875
•DTM•Meteo data•Rain data
•Soil characterization (geotechnical parameters)
3D Mass and Energy budgets at catchment
scale
GEOtop-FS
•dynamic probability of landslide triggering •sediment availability
Run-out module
•liquid and solid discharge•detailed topography•closure relations (concentration & shear stress)•sediment and transport
•run-out distance•erosion-deposit height•flow velocity•hazard mapstr
en
t-2
d
1
Geotop and trent-2d
Geo
top p
ro
ject
•Soil characterization (hydraulic parameters)•land use•vegetation
Sim
oni e
t al
., H
ydro
l. Pr
oc.,
2008
•Soil characterization (hydraulic parameters)•land use•vegetation
GEOtop 0.875
Geo
top p
ro
ject
•DTM•Meteo data•Rain data
•Soil characterization (geotechnical parameters)
3D Mass and Energy budgets at catchment
scale
GEOtop-FS
•dynamic probability of landslide triggering •sediment availability
Run-out module •liquid and solid discharge•detailed topography•closure relations (concentration & shear stress)•sediment and transport
•run-out distance•erosion-deposit height•flow velocity•hazard mapstr
en
t-2
d
Geomorphologicalanalysis
Geological info
Geophysics
stratigraphyquaternary covers
Soil DepthWater content
traditional photointerpretation
rock presenceerosion signatureshuman activities
soil Covertype and weight of soil
cover
model structure data exploited
Climate and Weathermodels
Rainfall, wind...
Earth Observations
A conceptual experiment
Effects of topography on hydrological balance
Elevations 25% Elevations 50%Elevations 40%
Elevations 60% Elevations 125%Elevations 100%
Serraia Basin, 15 km2, 1 year simulationSecurity Exit
Effects of topography on hydrological balance
Bertoldi et al.,JHM, 2006
Security Exit
Effects of topography on hydrological balance
Bertoldi et al.,JHM, 2006
An application to the Valsugana valleyM
ostl
y wo
rked
out
by
S. E
ndri
zzi
xBorgo Valsugana
● Caldonazzo
● Pergine
● Levico
An application to the Valsugana valleyM
ostl
y wo
rked
out
by
S. E
ndri
zzi
GCMs
Step1: Dynamical downscaling
RCMs
Step2: Bias-correction and data disaggregation
From daily to hourly data
Step3: Rainfall-runoff model calibrated
Impacts of climate change
An application to the Valsugana valleyM
ostl
y wo
rked
out
by
L. F
orlin
Monthly mean discharge (m3/s) from HAD_P model, for historic (1961-1988) and simulated control and future scenario.
Results indicate how the approximation is excellent from May to July, with overestimation during autumn and underestimation in winter.The flow is predicted substantially to increase from October to April and decrease during summer months.
An application to the Valsugana valley
Results indicate a future seasonal variability with drier summers and wettest winters.
Monthly mean fluxes (mm/month) from HAD_P model, for control and future scenario.
Mos
tly
work
ed o
ut b
y L
. For
lin
An application to the Valsugana valleyM
ostl
y wo
rked
out
by
L. F
orlin
Monthly mean snow cover (mm/month) and surface temperature (°C) from HAD_P model, for control and future scenario.
Results indicate a substantial decrease in snow cover and increase in surface temperature.
GEOtop 0.9375 (2006-2008)
GIUH +Kinematic wave+
Richards +Soil freezing &
Snow Cover
Radi
atio
n Ph
ysic
s En
ergy
bud
get
Mostly worked out by S. Endrizzi, E. Cordano, s, Simoni e M. Dall’Amico
GEOtop 0.9375 (2006-2008)
Radiation Physics improved by
accepting several parameterizations
Mos
tly
work
ed o
ut b
y S.
End
rizz
i
GEOtop 0.9375 (2006-2008)
Multilayer parameterizationFor each layer a system of 5 equations is solved
€
θw =1ρw
∂W∂t
+∂Qw
∂z
€
θ i =1ρi
∂W∂t
+∂Qi
∂z
€
C∂T∂t
+ Lf∂W∂T
=∂∂z
k∂T∂z
+∂ QwUw( )
∂z
€
k∂T∂z
= −Rn +H + L
€
θw +θ i +θ v = 1
€
W ≠ 0 if T = 273.15K ; W = 0 if T ≠ 273.15K
Liquid and solid water budget equations
Energy budget
equation
Continuity equation
Link phase change - temperature
Mos
tly
work
ed o
ut b
y S.
End
rizz
i
GEOtop 0.9375 (2006-2008)
Mos
tly
work
ed o
ut b
y S.
End
rizz
i
GEOtop model mm SWEMODIS
24 OTTOBRE 2003
GEOtop 0.9375 (2006-2008)
Mos
tly
work
ed o
ut b
y S.
End
rizz
i
GEOtop model mm SWEMODIS
17 January 2004
Application of GEOtop to the Adamello-Mandrone Glacier
(Trentino, Italy)
Mos
tly
work
ed o
ut b
y S.
End
rizz
i
73
Distributed results
Mass balance 1 Oct 2004 - 30 Sep 2005
mm w.eq.
Mos
tly
work
ed o
ut b
y S.
End
rizz
i
74
Comparison model - measurements
• Problems in estimating the snow disapperance date (underestimation of snow precipitation measured with the classical rain gauge)
• Good agreement, in particular for stakes 2 and 7
Ice melting after snow disappearance
The Stubaital case
by G. Bertoldi, P. Rastner, C. Notarnicola, and U. TappeinerData from G. Wolfhart, Institute of echology, Innsbruck
The Stubaital case
by G. Bertoldi, P. Rastner, C. Notarnicola, and U. TappeinerData from G. Wolfhart, Institute of Echology, Innsbruck
• Can we perform a process based calibration ?• Can we avoid parameter equi-finality ?
Yes if are considered …• overall consistency (different components of the water and energy balance)• different time and spatial scales.
Model Obs Model-ObsH [W/m2] 26 20 6LE [W/m2] 88 85 3G [W/m2] 4 4 0H [W/m2] 80 76 4
Ts [K] 11 12 -1SWC [ ] 0.48 0.37 0.11
Model - Observations comparisonSnow - free season 2005
Initial assumption: time constant vegetation density
The Stubaital case
by G. Bertoldi, P. Rastner, C. Notarnicola, and U. TappeinerData from G. Wolfhart, Institute of Echology, Innsbruck
• The illuminations alone (sun incidence angle, shadows) explains 71% of the variability.• Best agreement for valley meadows and alpine pasture.• Major differences for high elevations regions (glaciers and south facing slopes) and for forests.
LANDSAT LST GEOTOP LSTΔT=LSTGeoTop-LSTLandsat
What are the dominant processes ?What is the optimal model complexity level ?
Preliminary simulation with UNIFORM LAND COVER; meadow valley model calibration.
The Stubaital case
by G. Bertoldi, P. Rastner, C. Notarnicola, and U. TappeinerData from G. Wolfhart, Institute of Echology, Innsbruck
Some of the next steps
GEOtop Development
Automatic Calibration
Data Assimilation
GEOTOP-SF0.75
GEOTOP-SF0.875
GEOTOP-SF0.9375
0.5
0.75
0.875
0.9375
0.9375- EO
GEOFRAME
GEOtop will be splitted in components and the components
managed by JGrass. The components will be based on the
OpenMI standard.
=
JGrass (www.jgrass.org) is a full featured GIS system based on udig(www.refractions.net ). It allows communication to databases,
internet and provides an interfaces to components’ Input-Outputs
=
Tools di analisi(UNITN/R)
Database (PostgresSQL/PostGIS/CUAHSI)
Modelli(UNITN/OpenMI)
Interfacce(Java/JGRASS)
users webexternal database
GEOFRAME
WEBservices
WMSWFS-TWPS
PostGISPostgres
JGrass
GIS engine
UIBuilder
HSQLDB
GRASS GIS
Eclipse RCPuDig
JGrassJ-Console engine
OpenMI
Hor
ton
Mac
hine
Hyd
rolo
g. m
odel
Sta
tistic
al a
nal.
GEOFRAME: JGrass 3.0 structure
udig itself lives upon the Rich Client Platform given by Eclipse
(www.eclipse.or). JGrass uses also HSQL as internal database, and a custom interfaces builder to give a
GUI to any command.
=
88
Serially linked models by file transfer. Feedback loops not represented.
Interface
Model
Data
Interface
Model
Data
Interface
Model
Data
Interface
Model
Data
FileFile
File
GEOFRAME: OpenMI
88
Serially linked models by file transfer. Feedback loops not represented.
Interface
Model
Data
Interface
Model
Data
Interface
Model
Data
Interface
Model
Data
FileFile
File
from HarmonIT Roger Moore’s, CEH, Wallingford, UK presentation
GEOFRAME: OpenMI
88
Serially linked models by file transfer. Feedback loops not represented.
Interface
Model
Data
Interface
Model
Data
Interface
Model
Data
Interface
Model
Data
FileFile
File
GEOFRAME: OpenMI
OpenMI gives a set of standard interfaces to make model
components to communicate, even having feedbacks between components, and can link
components programmed in C, FORTRAN or PASCAL
=
9018
3-D3-D
3-DSea
2-DEstuary
1-DRiver
Graph tool
Connection toolGEOFRAME: OpenMI
9018
3-D3-D
3-DSea
2-DEstuary
1-DRiver
Graph tool
Connection tool
from HarmonIT Roger Moore’s, CEH, Wallingford, UK presentation
GEOFRAME: OpenMI
9018
3-D3-D
3-DSea
2-DEstuary
1-DRiver
Graph tool
Connection toolGEOFRAME: OpenMI
OpenMI provides methods to change at run-time the model
configuration. Different components doing the same job can be used in
alternative seamlessly.
=
9218
WeatherGenerator
Monitoreddata
WeatherForecast
SurfacesInterception
SurfacesRunoff
Subsurface Flow
Evapotranspiration
http://www.openmi.org, http://www.openmi-life.org/, http://public.wldelft.nl/display/OPENMI/Home
GEOFRAME: OpenMI
9318
SurfacesRunoff
Subsurface Flow
Evapotranspiration
Channel RoutingII
Channel Routing III
Channel Routing 1
http://www.openmi.org, http://www.openmi-life.org/, http://public.wldelft.nl/display/OPENMI/Home
GEOFRAME: OpenMI
GEOFRAME : J-Hydro
JGrass provides also the database to store and retrieve simulations
=
after Dietrich et al., 2001
Still, as the painting by Rosseau, shows GEOtop is a mosaic of “realistic pieces” inside an improbable
ecosystem (not to speak of other model). Things are however getting better ;-)
HYDROLOGIS: andrea antonello, silvia franceschi, www.hydrologis.com
DICA Dipartimento di Ingegneria Civile ed AmbientaleCUDAM Centro Universitario per la Difesa dell’Ambiente Montano riccardo rigon
GEOtop Developers Team (GDT)stefano endrizzi, emanuele cordano, christian tiso, giacomo bertoldi
Mountain-eering: matteo dall’amico, silvia simoni, fabrizio zanotti.
Core contributors
Analytics
Dan
ce, H
enry
Mat
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, Hot
el B
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Numerics
Physics
Geography
Hydrology
Thank you for your attention
Comprehensive GEOtop Bibliography
•Simoni, S., F. Zanotti, G. Bertoldi and R. Rigon, Modelling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop-FS, accepted for Hydrol. Proc., published on-line, Dec 2007
•Rigon R., Bertoldi G e T. M. Over, GEOtop: A distributed hydrological model with coupled water and energy budgets, Jour. of Hydromet., Vol. 7, No. 3, pages 371- 388., Vol. 7, No. 3, pages 371-388.
•Bertoldi, G., R. Rigon & T. M. Over, Impact of watershed geomorphic characteristics on the energy and water budgets, Jour. of Hydromet., Vol. 7, No. 3, p. 371- 388. Vol. 7, No. 3, pages 389 - 394, 2006.
B -
•Simoni S., Zanotti F., Rigon R., Squarzoni C., Approccio probabilistico alla determinazione dell'innesco di frane superficiali con in modello accoppiato idro-geotecnico: GEOTOP-SF, Atti del convegno "idra2006 : XXX Convegno di Idraulica e Costruzioni Idrauliche", Roma, 10-15 Settembre, 2006.
•Bertoldi G., Dietrich W.E., Miller N. L., Rigon R.. Bedrock and soil contribution to the formation of sub-surface runoff by saturation in headwater catchments: observations and simulation using a distributed hydrological model, Atti del XXIX Convegno di Idraulica e Costruzioni Idrauliche, Trento, Settembre 2004.
• Zanotti F, Endrizzi S, Bertoldi G, Rigon R. 2004. The GEOTOP snow module. Hydrological Processes 18: 3667–3679. DOI:10/1002/hyp.5794.
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•Zanotti, F., Endrizzi S., Rigon R. Il modulo di accumulo e scioglimento della neve in Geotop. Atti del XXIX Convegno di Idraulica e Costruzioni Idrauliche, Trento, Settembre 2004.
•Tiso, C., Bertoldi G. and R. Rigon. Il modello Geotop-SF per la determinazione dell'innesco di fenomeni di franamento e di colata. Atti del Convegno Interpraevent 2004, Riva del Garda, 24-28 Maggio 2004.
•Bertoldi G., Rigon R. and Over T.M., Un'indagine sugli effetti della topografia sul ciclo idrologico con il modello GEOTOP, Atti del XXVIII Convegno di Idraulica e Costruzioni Idrauliche, Potenza, Italy, 2002.
A few relevant presentations
GEOTOP:a distributed modeling of the
hydrological cycle in the remote sensing era
R. Rigon , G. Bertoldi, T.M. Over., D. Tamanini,
Dipartimento di Ingegneria Civile ed Ambientale - CUDAM Università di Trento
Geography Dept. Eastern Illinois University
CAHM
DA I
I -
Prince
ton,
Oct
ober
25-
27, 20
04
San Francisco AGU Fall meeting - Dec 15 2006
The triggering of shallow landslides and channelized debris flows
analyzed with the distributed model GEOtop - FS
R. Rigon, S. Simoni, F. Zanotti & M. Dall’AmicoDICA & CUDAM Università di Trento - ITALY
Beyond and side by side with Numerics
A reflection on making applicable hydrology todayRiccardo Rigon - Group of Hydrology - Trento University
Dan
ce, H
enry
Mat
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, Hot
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909
The snow and glacier description in the GEOtop
model
Stefano Endrizzi
Department of Civil and Environmental EngineeringUniversity of Trento, Italy
Zürich, 18th March 2008
Application of a physically-based hydrological model to the
Adamello-Mandrone Glacier
Stefano Endrizzi, Riccardo RigonDepartment of Civil and Environmental Engineering
Università di TrentoItaly
Obergurgl (Austria), 28 August 2007
The water and energy balance in mountain catchments:
a distributed modelling approach
G.BertoldiS. Endrizzi, F. Zanotti, T.M. Over, S. Simoni, R.Rigon, U. Tappeiner
Institute for Alpine EnvironmentEURAC, Bozen, Italy
Innsbruck, 31th March 2008