GEOtop 2.0

Gino Severini, Dancer+Sailing+Sea,= Bouquet, 1950

GEOtop 2.0: simulating the combined energy
and water balance

S. Endrizzi, S. Gruber, M. Dall’Amico and R. Rigon
Dec. 10 2013 - AGU Fall Meeting S. Francisco

It is difficult to avoid the impression that a miracle
confronts us here, quite comparable in its striking
nature to the miracle that the human mind can string a
thousand arguments together without getting itself into
contradictions, or to the two miracles of laws of nature
and of the human mind's capacity to divine them.

The inconceivable effectiveness
of mathematics in natural sciences.
E. Wigner

http://en.wikipedia.org/wiki/The_Unreasonable_Effectiveness_of_Mathematics_in_the_Natural_Sciences

The basics

A theory that describes whole hydrology ?

The miracle is hard to see in Hydrology where heterogeneity mixes with
complexity, and phenomena across several scales.

!3

Catchment hydrology
At the catchment scale: ancestors
Freeze and Harlan, Jour. of Hydrology, 1969
SHE, Abbot et al. 1986

Horton Overland Flow

Dunne Saturation
Overland Flow

Surface Layer

Unsaturated Layer

Saturated Layer:!

Modiﬁed from Abbot et al., 1986

!4
Endrizzi et al.

Endrizzi et al.
tRIBS, Ivanov et al, 2004

Catflow, Zehe et al., 2001

Hydrogeosphere, Therrien and Sudicki, 1996

InHM, VanderKwaak, and Loague, 2001

Parflow, Asby an Falgout, 1996

DHSVM, Wigmosta et al., 1994

Cathy, Paniconi and Putti, 1994

Rigon et al, 2006; Bertoldi et al., 2006

Water mass budget
In What GEOtop is different ?

!5

Endrizzi et al.
CLM, Dai et al., 2003

SEWAB, Megelkamp et al., 1999

LSM, Bonan, 1996

Noah LSM, Chen et al., 1996,

BATS, Dickinson et al., 1986,

Rigon et al, 2006

Energy budget

!6

Snow and freezing soil: see also me on Thursday talk

Snow height, density, temperature)

Zanotti et al, 2004; Dall’Amico et al., 2011

Endrizzi et al.

Alpine3D, Lenhing et al., 2006

Freezing Soil - Permafrost

CROCUS, Brun et al., 1992


!7

To study the interactions all is modelled together

Many models do the water budget
Many models do the energy budget
Many model do the snow budget

How many models do the whole stuff together ?
Obviously is also matter of the degree of
physical simplification (i.e. the
equations) used.
!8
Endrizzi et al.

Endrizzi et al.

see also http://abouthydrology.blogspot.com/search/label/GEOtop
Endrizzi et al.

!9

Equations

(Monin - Obukov)
Snow metamorphism

(with some assumptions)

Energy budget

Radiation

Flux-gradient relationship

Double layer vegetation
Diffusive approximation to shallow
water equation
Richards equation +
van Genuchten parameterization +
Mualem derived conductivity
!10

Endrizzi et al.

Equations

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Endrizzi et al.




Se = [1 + (
C(⇥) :=

⇤

w ()

Se :=

⇤⇥
~
~
Jv = K(✓w )r h
⇧ ⇤
K( w ) = Ks Se 1

⇥) )]
m

w

r

⇥s

n

r

(1

Se )

1/m

⇥ m ⌅2
!11

Guidelines

The “ What Else ?” Principle

I said: “Why to use Richards’ equation … do they work at hillslope scale ?”
M.P. said: “What else do you want to use (Topmodel) ? ”
I went home, and after comparing the alternatives, I decided to use Richards
equations ?*

The same story applies more or less to the other processes.

* See also Cordano and Rigon, 2008, to see that alternatives are indeed often simplifications of RE.
See also http://abouthydrology.blogspot.it/2013/06/ezio-todini-70th-symposium-my-talk.html

Endrizzi et al.

!12

Guidelines

The Occam’s Rasor ?
“Lex parsimoniae"
It states that among competing hypotheses, the hypothesis with the fewest
assumptions should be selected

We all either try to formulate laws at one scale by
guessing them, using the available knowledge, or try to
deduce them by a mix of algebraic treatment of the
basic laws of mass, energy and momentum
conservation, and educated simplifications.

!13
Endrizzi et al.

Is there ! It is Open source

Is it feasible ?
Is it usable ?
Does it works ?
We did it !

https://code.google.com/p/geotop/
!14
Endrizzi et al.

Better wrong than “not even wrong”

It is useful ?
e.g Beven, 2000, 2001 (for instance … but also many of my closest
friends) criticized this approach of making models

Yes, it is!

!15
R. Rigon

A mountain catchment

of

applications

<latexit sha1_base64="tYHCApFiY8slQcKMwQxwGacE74A=">AAAA+3icSyrIySwuMTC4ycjEzMLKxs7BycXNw8XFy8cvEFacX1qUnBqanJ+TXxSRlFicmpOZlxpaklmSkxpRUJSamJuUkxqelO0Mkg8vSy0qzszPCympLEiNzU1Mz8tMy0xOLA

High Resolution Joint Water and Energy Balance Modeling and
Observation in a Prealpine Environment
by Hingerl, L., Kunstmann, H., Mauder, M., Wagner, S. and Rigon
R., submitted to Journal of Hydrometeorology 2013

!16
Endrizzi et al.


Closing the hydrological budget

Hingerl et al., 2013

after (Mauder et al., 2006)

Root river in Germany - TERENO experiment

Figure 2: The catchment of the Rott with the position of the discharge gauge in Raisting,
the TERENO-observatory “Fendt” and the climate stations used for the meteorologic
Zacharias et al., 2011 - http://teodoor.icg.kfa-juelich.de/

Endrizzi et al.

forcing in the model.

!17


15
10
0

5

Discharge [m³/s]

20

30

measured
simulated

40

Precipitation [mm]


25

20

10

0

30

“Traditional approach” by calibrating discharges

11.2009

01.2010

03.2010

05.2010

07.2010

09.2010

11.2010

Figure 5: Simulated and measured discharge at the gauge in Raisting for the hydrologic

25

20

Endrizzi et al.

10

0

30

year 2010.

measured

!18


Energy ﬂuxes - NO calibration

!19
Endrizzi et al.

0

10

20

simulated 6cm
measured 6cm

−10

Soil temperature [C°]

Temperature is among the prognostic variables

03.2011

05.2011

07.2011

09.2011

11.2011

03.2011

05.2011

07.2011

09.2011

11.2011

03.2011

05.2011

07.2011

09.2011

11.2011

20
10
0
−10


01.2011

simulated 21cm
measured 25cm

11.2010

01.2011

0

10

20

simulated 51cm
measured 50cm

−10



11.2010

11.2010

01.2011

Fig. 9. Simulated soil temperatures for di↵erent depths compared to measurements from
the TERENO prealpine observatory Fendt.

!20
Endrizzi et al.

We close the budget

a)


Netto shortwave radiation
Netto longwave radiation
Sensible heat flux
Latent heat flux
Soil heat flux

c)

This is the land-use types coniferous forest (a), and settlements
Energy balance forconiferous forest. But there is also pasture pasture (b) and set- !21
c) showingal.
Endrizzi et absolute monthly means of simulated energy ﬂuxes and the longwave

Small mountain catchment ecohydrology

of

applications

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Modeling the variability of snow, evapotranspiration and soil
moisture along inner alpine elevation gradient

Della Chiesa, S., Bertoldi, G., Niedrist, Obojes, .G., Albertson, J. D., Wohlfahrt,G.,
Tappeiner U. X - 40
DELLA CHIESA ET AL.: ELEVATION GRADIENT GRASSLAND DRY ALPINE VALLEY

Figure 1.

Endrizzi et al.

Study area is a side slope in the upper Vinschgau watershed in South Tyrol, Italy

!22


Well, it is not my merit
but the guys here added (off-line) a GRADIENT GRASSLAND DRY ALPINE VALLEY
DELLA CHIESA ET AL.: ELEVATION dynamic vegetation model and study alpine
X - 43

There are effects of temperature and precipitation quantity and phase
varying with height, of variable snow cover, climate interannual variability
… There is irrigation.

ET at 1500 m
Endrizzi et al.

450
400
ET cumulative [mm]

Della Chiesa et al., 2013

grassland along a transect at varying elevation from 1000 m to 2000 m

ET obs
ET mod

350
300
250
200
150
100
50
0
Apr/11

May

Jun

Jul

Aug

Sep

Oct

!23


Snow Water Equivalent at different elevations


DELLA CHIESA ET AL.: ELEVATION GRADIENT GRASSLAND DRY ALPINE VALLEY

X - 45

What can we observe ?

o di↵erent years and elevation gradient on SWE a), cumulative ET

ibution ✓ 5cm depth c). The black dashed line represents to water
SWC results refer to the snow free period only.

!24

Endrizzi et6. E↵ects of the two di↵erent years and elevation gradient on SWE a), cumulative ET
Figure al.



This reflects in different soil moisture distributions

Figure 6. E↵ects of the two di↵erent years and elevation gradient on SWE a), cumulative ET

differentfrequency distribution ✓ 5cm depth c). The black dashed line represents to water
at different elevations and different years
b) and SWC
limitation point. Notice that SWC results refer to the snow free period only.

This has influences on the ecosystems.
Details in the paper
!25
Endrizzi et al.

So far

Could have been used another model instead of GEOtop

<latexit sha1_base64="tYHCApFiY8slQcKMwQxwGacE74A=">AAAA+3icSyrIySwuMTC4ycjEzMLKxs7BycXNw8XFy8

Certainly we needed a model with all the hydrological components
simulated. A model where lateral subsurface and surface redistribution is
accurately described. A model were snow is modelled. A model were
temperature is an explicit prognostic variable… SO …

!26
Endrizzi et al.

Going to a conclusion: are the equations right ?

(Monin - Obukov)
Snow metamorphism

(with some assumptions)

Energy budget

Radiation

Flux-gradient relationship

Double layer vegetation
Diffusive approximation to shallow
water
Richards equation +
van Genuchten parameterization +
Mualem derived conductivity
!27

Endrizzi et al.

Going to a conclusion: what happens at the interfaces

Snow-ABL interactions

Vegetation-ABL

Surface Water-Groundwater

!28
Endrizzi et al.

To sum up our position

Some misconceptions about distributed modelling
“Distributed model are overparameterised”
“Model parameters cannot be identified”
“These models require too high computational time”
“They cannot be used for ungauged basins”
“Reality is simpler than that (and we learn just from simple models)”
not completely wrong but not completely true.

eat the apple before talking!
see also http://www.nature.com/nature/journal/v469/n7328/abs/469038a.html

Endrizzi et al.

!29

Looking at larger sites

!30
Dall’Amico et al.

And operationally

Snow height by Mountain-eering

More details on the cryospheric processes
in session C44B 02 - On thursday
Dall’Amico et al.

!31

Going ahead

Several options for going ahead

Making of GEOtop a library
Embedding in Object Modeling system vs. 3
Parallelizing it
Making easier its use
Develop the R and Java (uDig) interfaces
Data assimilation and real time
!32
Endrizzi et al.

Going ahead

Process-wise
Re-think the processes schemes
Change them, without loosing the old work
Test, Test, Test

Create a community
Actually it includes 4 core research groups: Quebec (was Zurich),
Trento (CUDAM and Mountain-eering), Bozen, KIT (Garmisch) and
some group
!33
Endrizzi et al.

Splitting GEOtop

of

applications


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So can we go on ?

Formetta et al. to be submitted to EM&S, 2013

!34
Endrizzi et al.

and embedding it in OMS

Formetta et al., 2013

Towards GEOtop 3.0

OMS v3 - David et al., 2013

Endrizzi et al.

!35



Drake river soil moisture

Formetta et al. to be submitted to EM&S, 2013

Endrizzi et al.

!36


Endrizzi et al.

!37

presentation available at about http://hydrology.blogspot.com

Ulrici, 2000 ?

Thank you

For giving information about hydrology and receiving news about positions,
conferences, session, subscribe to abouthydrology@googlegroups.com
Riccardo Rigon

!38

Soil Moisture, Water Setention Curves, (Landslides,) and all that

Another Application
A lab case

!39
Rigon et al.

GEOtop in the lab

Thanks to Neaples Group: the IWL3 experiment
R. Greco1, L. Comegna1, E. Damiano1, A. Guida1,2, L. Olivares1, and L. Picarelli1
1Dipartimento di Ingegneria Civile Design Edilizia e Ambiente, Seconda Università di Napoli, via Roma 29, 81031
Aversa (CE), Italy 
2Centro Euro-Mediterraneo sui Cambiamenti Climatici, via Maiorise, Capua (CE) 81043, Italy

!40
Rigon et al.

t

GEOtop in the lab

Soil
Thickness
(cm)

Slope
Length
(cm)

Initial
porosity n0

Rainfall
intensity
(mm/h)

Initial mean
s uction
(kPa)

Duration
of test
(min)

10.0

100

0.75

55

17.5

36

10.0
120
0.76
56
41.0
30
The inclination of the slope is 40°.
!
The test are carried out with constant and spatially homogeneous
rainfall intensity.
Several devices (tensiometer, pore pressure transducer, TDR and laser
!41
Rigon et al.

Analysis of the data

Suctions and pressures
failure
first displacement
first displacement

.

-5 cm

!
!
factor of safety here is 1.2

-10 cm

!42
Rigon et al.


Water Content

!43
Rigon et al.


Water Content talks

Hydraulic conductivity was measured in the lab. The value given was
around one order of magnitude less than the artificial rainfall
So we expect an Hortonian flux: saturation at the top and
movement downward.
Which we do not have!

!44
Rigon et al.

So we expect an Hortonian flux: saturation at the top and
movement downward.

red line is more ore less what we expect just after the beginning
of irrigation in a Hortonian interpretation of infiltration
Rigon et al.

!45

Questions
What about the Darcy scale here ?

!46
Rigon et al.


Water Content talks

Is irrigation really stationary ? What happens after the 28th minute ? Lateral flow
triggers ?
!47
Rigon et al.

Let’s go !

Two hydraulic conductivities
One hypothesis we did is that, despite the homogeneity of the
preparation of the experiment, hydraulic conductivity (at
saturation) at the bottom is different from hydraulic conductivity at
the top of the mock-up.
Due to packing of particles ? Due to some unavoidable imperfection
in preparation ? Due to avoidable imperfection of the preparation ?

What else ?

!48
Rigon et al.

Which parameters ?

Suction talks
Both suction and water content data were used to calibrate van Genuchten
parameters. Also the hydraulic conductivity is among

Se = [1 + (
Se :=

n

⇥) )]
m

w

r

⇥s

r

Also hydraulic conductivity at saturation is a calibration parameter

K(

w)

= Ks

⇧

Se

⇤

1

(1

Se )

1/m

⇥ m ⌅2

!49
Rigon et al.

Which parameters ?

Calibrated Parameters

alfa
0.052

n
m
1.805 0.445983

Ksat_layer superficiale (0-5cm) = 0.178 mm/s
Ksat_layer di fondo (5-10cm) = 0.117 mm/s

!50
Endrizzi et al.

Water content

Averaging does not get the right result

even if water contents are reproduced fairly well until the 21th minute

Rigon et al.

!52

Who says that we do not learn from comps models ?

Lesson Learned
The relation assumed between Soil Water Retention Curves and
hydraulic conductivity could not be correct :

!
•

does van Genuchten parameterisation needs to be substituted ?

•

does Mualem theory really works ?

•

Well, in some some the model does not work. However, in the
science perspective, certainly it does !

!53
Rigon et al.

The Bibliography
Journal Papers
Bertoldi, G., Notarnicola, C., Leitinger, G., Endrizzi, S., Della Chiesa, S.,
Zebisch, M., & Tappeiner, U. (2010). Topographical and
ecohydrological controls on land surface temperature in an Alpine
catchment. Ecohydrology, 3(doi:10.1002/eco.129), 189–204.
!
Bertoldi, G., Rigon, R., & Over, T. M. (2006). Impact of Watershed
Geomorphic Characteristics on the Energy and Water Budgets. Journal
of Hydrometeorology,, 7, 389–403.
!
Bertoldi G.; Della Chiesa, S; Notarnicola, C.; Pasolli, L.; Niedrist, G;
Tappeiner, U. (2013), Estimation of soil moisture patterns in mountain
grasslands by means of SAR RADARSAT 2 images and hydrological
modeling, submitted to Journal of Hydrology
Dall’Amico, M.; Endrizzi, S., Gruber, S; and Rigon, R. (2011), An energyconserving model of freezing variably-saturated soil, The Cryosphere.
Della Chiesa, S.; Bertoldi, G.; Niedrist, Obojes, N.G.; Albertson, J. D.;
Wohlfahrt,G.; Tappeiner (2013), Modeling the variability of snow,
evapotranspiration and soil moisture along inner alpine elevation
gradient , submitted to Ecohydrology.

!
Rigon! et al.

!54

The Bibliography
Journal Papers
Endrizzi S. and Marsh P. Observations and modeling of turbulent fluxes
during melt at the shrub-tundra transition zone 1: point scale
variations, (2010) Hydrology Research
Endrizzi S., Gruber S., Investigating the effects of lateral water flow on
spatial patterns of ground temperature, depth of thaw and ice content,
Peer reviewed proceedings of the 10th International Conference on
Permafrost, 25–29 June 2012, Salekhard, Russia, 91–96, 2012
Endrizzi S., Gruber S., Dall’Amico M., Rigon R., GEOtop 2.0.: Simulating
the combined energy and water balance at and below the land surface
accounting for soil freezing, snow cover and terrain effects, Geosci.
Model Dev., 2013 (submitted)
Fiddes J., Endrizzi S., Gruber S., Large area land surface simulations in
heterogeneous terrain driven by global datasets: a permafrost test case,
(2013), The Cryosphere (submitted)
Formetta, G., Rigon R., David, O., Green, T. R., Capparelli, G. (2013),
Integration of a spatial hydrological model (GEOtop) into the Object
Modeling System (OMS), To be submitted to EM&S
!
!
Rigon et al.

!55

The Bibliography
Journal Papers
Gubler S., Endrizzi S., Gruber S., Purves R. S., Sensitivity and uncertainty
of modeled ground temperatures and related variables in mountain
environments, Geosci. Model Dev., 6, 1319–1336, 2013.

!
Gebremichael, M., Rigon, R., Bertoldi, G., & Over, T. M. (2009). On the
scaling characteristics of observed and simulated spatial soil moisture
fields, Nonlin. Processes Geophys., 16, 141–150.

!
Hingerl L., Kunstmann H., Mauder M., Wagner S., Rigon R. (2013), High
Resolution Joint Water and Energy Balance Modeling and Observation
in a Prealpine Environment, 2013, submitted to Journal of
Hydrometeorology.

!
Rigon, R., Bertoldi, G., & Over, T. M. (2006). GEOtop: A Distributed
Hydrological Model with Coupled Water and Energy Budgets. Journal
of Hydrometeorology, 7, 371–388.
!
!
Rigon et al.

!56

The Bibliography
Journal Papers

Simoni, S., Zanotti, F., Bertoldi, G., & Rigon, R. (2007). Modelling the
probability of occurrence of shallow landslides and channelized debris
flows using GEOtop-FS. Hydrological Processes, doi: 10.10.

!
Zanotti, F., Endrizzi, S., Bertoldi, G., & Rigon, R. (2004). The GEOtop snow
module. Hydrol. Proc., 18, 3667–3679. DOI:10.1002/hyp.5794.
!
!
!
!

!57
Rigon et al.

Epilogue

A fool with a tool is still a
fool

!58
Rigon et al.

GEOtop 2.0

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