Padua cathy meeting

GEOtop and Beyond
CATHY’s days 2011

Jackson Pollok, Free Form, 1949, Moma

R. Rigon, M. Dall’Amico, G. Formetta

Tuesday, January 18, 2011

The structure of GEOtop

1. Radiation
- distributed model
- sky view factor, self and cast
shadowing, slope, aspect, drainage

2. Water balance 6. vegetation
interaction
- effective rainfall
- surface flow (runoff and channel - multi-layer vegetation
routing) scheme
- evapotranspiration

3. Snow-glaciers
- multilayer snow
scheme 5. soil energy balance

- soil
4. surface energy balance temperature
- freezing soil
- radiation
- boundary-layer interaction
2

Rigon et al., CATHY’s days, Padova 2011


Why this complexity ?

snow, ice, permafrost

water cycle in
complex terrain Endrizzi 2007
Dall’Amico 2010
Rigon et al., 2006 Endrizzi et al,
2010a,b in
preparation

evapo-transpiration,
landsliding
energy fluxes

Bertoldi et al., 2006 Simoni et al 2008
Bertoldi et al 2010 Lanni et al, 2010

3



For each time step

Flows

Meteo

Rainfall/Snow Radiation Atm. Turbulence

Snow/Energy budget

4



GEOtop

Richards ++

Surface flows

Channel flow

Next time step
5



Richards ++
First, I would say, it means that it would be better to call it, for
instance: Richards-Mualem-vanGenuchten equation, since it is:

∂ψ
C(ψ)
= ∇ · K(θw ) ∇ (z + ψ)
∂t
m 2
K(θw ) = Ks Se 1 − (1 − Se ) 1/m

−n
Se = [1 + (−αψ) )] m

∂θw () θw − θr
C(ψ) := Se :=
∂ψ φs − θr
6



Richards ++

∂ψ
C(ψ)
= ∇ · K(θw ) ∇ (z + ψ) Water balance
∂t
m 2
K(θw ) = Ks Se 1 − (1 − Se ) 1/m

−n
Se = [1 + (−αψ) )] m

C(ψ) := Se :=
∂ψ φs − θr
6



Richards ++

∂ψ
C(ψ)
∂t
m 2
Parametric
K(θw ) = Ks Se 1 − (1 − Se ) 1/m
Mualem

−n
Se = [1 + (−αψ) )] m

C(ψ) := Se :=
∂ψ φs − θr
6



Richards ++

∂ψ
C(ψ)
∂t
m 2
Parametric
K(θw ) = Ks Se 1 − (1 − Se ) 1/m
Mualem

−n Parametric
Se = [1 + (−αψ) )] m
van Genuchten

C(ψ) := Se :=
∂ψ φs − θr
6


Richards ++

Extending the soil-water relation curve

Extending Richards to treat the transition saturated to unsaturated zone.
Which means:

7


Richards ++

Freezing Soils in unsaturated Conditions

Extending Richards to treat the phase transition. Which means essentially to
extend the soil water retention curves to become dependent on temperature.

Freezing
Unsaturated starts
unfrozen

Unsaturated Freezing
Frozen procedes

8


Richards ++

Soil water retention curve
+

thermodynamic equilibrium (Clausius Clapeyron)
+
Freezing = drying hypothesis

pw
pressure head: ψw =
ρw g

Unfrozen water content

θw (T ) = θw [ψw (T )]

9


Richards ++


Total water Θ = θr + (θs − θr ) · {1 + [−α · ψw0 ]n }−m
content:
n −m
liquid water θw = θr + (θs − θr ) · 1 + −αψw0 − α
Lf
(T − T ∗ ) · H(T − T ∗ )
content: g T0

ρw
ice content: θi = Θ − θw
ρi

depressed g T0
T ∗ := T0 + ψ w0
melting Lf
point

M. Dall’Amico, S. Gruber and R. Rigon, 2010 in preparation
10


Richards ++

Freezing = Drying

unfrozen starts

Frozen procedes

11


Richards ++

Freezing = Drying

12


Richards ++

Freezing = Drying

13


Richards ++

Freezing = Drying
M. Dall’Amico, et al, http://www.the-cryosphere-discuss.net/4/1243/2010/tcd-4-1243-2010.html

Tot Water profile: comparison with Hansson et al
0

after 50 hours
!

Sim
!20

!

!
! Meas
!40

!

!
!60

!

!
!80

!
soil depth [mm]

!

!

!
!120

!

!

!

!
!160

!

!

!

!
!200

!

0.25 0.30 0.35 0.40 0.45 0.50 0.55

water content [!] 14


Applications

Obviously this makes it possible to simulate
a lot of new phenomenologies
Stefano Endrizzi, William Quinton, Philip Marsh, 2011 submitted to TC

Sisik, river in the artic tundra 15


Runoff on Frozen Soil

thaw depth: T(z,t)=0 water table depth: ψm(z,t)=0

44
Stefano Endrizzi, William Quinton, Philip Marsh, 2011 submitted to TC
16


Runoff on Frozen Soil: main result

Runoff on frozen soil

The model allows to show that the runoff
properties of a basin dramatically change when
soil freeze.

Stefano Endrizzi, William Quinton, Philip Marsh, Matteo Dall’Amico, 2010 in preparation
17


Snow generated runoff

Frozen soil can be combine with the snow module

Arabba

Pordoi

Ornella

Saviner
Caprile Pescul

Malga Ciapela

18



Frozen soil can be combine with the snow module

19



We have to work more here!
Discharge at Saviner year 2006−2007

14
GEOtop measured

12
10
Discharge [m3/s]

8
6
4
2
0

01/10 01/12 01/02 01/04 01/06 01/08 01/10

Date (dd/mm)

20


Conclusions

Is Richards’ True ?

21


Conclusions

Well: as representing the water budget it must be true.

21


Conclusions

Well: as representing the water budget it must be true.

However:
• The soil water retention curves need probably to be further extended or
changes beyond v.Genucthen schemes
• Hydraulic conductivity should also be, probably, re-parametrized
•Saturation-Unsaturation must be better characterized
•The theory of freezing soil revisited (I know where it is approximate)
•Therefore, also the scheme that keep the soil rigid has to be revisited.
•Clays where adsorption plays a fundamental role represents a challenge.
•.........

21


Going Beyond

Is this complexity manageable ?

22


Going Beyond


23


Managing Models’ complexity


Certainly this overwhelms the capability of any single
researcher, even the most gifted and dedicated:

•too many processes to deal with at the state-of-art of:
•physics
•numerics
•informatics
•too many datasets to exploit to have reasonable validation/
falsification
•too many ancillary programs neeeded to initialize, bound,
and force the models
24



The Big Science Model

This requires many gifted people to interact. One models of
development:

•The CERN/Fundamental physics way
• The Meteorological field
•.....

There could be another model ? (Which should be however as
well successful in getting finance support, and maybe more
successful in discoveries ;-)

25



The Open Science Model

It is possible that many people interact on a different basis,
with a more “bottom-up” approach, and still doing science at
the higher level (with more democracy and responsability) ?

The Open Source World style:

•GNU/Linux
•Eclipse
•GRASS
•GEOtools (OGC)
•.....
26



Tools
We need tools that helps collaboration

You can find more at:

http://www.slideshare.net/GEOFRAMEcafe/geoframe-a-
system-for-doing-hydrology-by-computer

27


CUAHSI BIANNUAL MEETING - BOULDER (CO) - JULY 14-16 2008

NEW (well relatively) MODELING PARADIGMS
Object-oriented softwa re development. O-O
programming is nothing new, but it has proven to be a successful
key to the design and implementation of modelling frameworks.

Modiﬁed from Rizzoli et al., 2005
Models and data can be seen as objects and therefore they can
exploit properties such as encapsulation, polymorphism, data
abstraction and inheritance.
Component-oriented software development. Objects
(models and data) should be packaged in components, exposing for
re-use only their most important functions. Libraries of
components can then be re-used and efﬁciently integrated across
modelling frameworks.Yet, a certain degree of dependency of the
model component from the framework can actually hinder reuse.

MODELLING BY COMPONENTS

JGrass 3 - OMS3 in the next future

Modeling by components

JGrass 3/ OMS 3

After David et al., 2009
29

Rigon, Antonello, Franceschi



BENEFITS
Discrete units of software which are re-usable
even outside the framework, both for model components
and for tools components.
Seamless and transparent access to data, which
are made independent of the database layer.

A number of tools (simulation, calibration, etc.) that the
modeller will be free to use (including a visual modelling
environment).

A model repository to store your model (and
simulations) and to share it with others.



BENEFITS FOR SCIENTISTS

Tools for studying feedbacks among different processes.

Encapsulation of single processes or submodels

New educational tools and a “storage” of hydrological
knowledge using appropriate onthologies

MUCH MORE in the ﬁeld of possibilities



There exist such a modelling infrastructures ?

YES, there exist many

As a matter of fact just a few have those
characteristics that I believe are important for the
success of the whole ideas:

32



PREREQUISITES
OPEN SOURCE

Programming LANGUAGE NEUTRAL: Fortran, C/C++, Java ....

PLATFORM NEUTRAL: Windows, Linus and Mac

BUSINNES NEUTRAL: GPL would be ﬁne, LGPL better

TARGETED AT PERSONAL PRODUCTIVITY OF
DIFFERENT USERS
People come before program efﬁciency.

DEPLOYEMENT


PREREQUISITES
BUILT BY OPEN SOURCE TOOLS

DEPLOYABLE THROUGH THE WEB
ALLOWS WRAPPING OF EXISTING CODES BUT
PROMOTES BETTER PROGRAMMING STRATEGIES

DATA BASE PROVIDED

CUAHSI SPECIFICATIONS AWARE
OGC COMPLIANT

CAN BE ENDOWED WITH ONTOLOGIES
DEPLOYEMENT

What is next ?

We chose recently OMS3
The Object Modeling System OMS is a modular modeling framework that uses an open
source software approach to enable all members of the scientific community to address
collaboratively the many complex issues associated with the design, development, and
application of distributed hydrological and environmental models.

Products

Development
Tools
OMS

Knowledge
Base

Resources

OMS3 can be found at: http://www.javaforge.com/project/omslib
35


ydroloGIS nvironmental ngineering

JGrass and OMS: what will happen to OpenMI?

A big effort has been done in the last years to bring all the models contained to
OpenMI compliancy. There are several main issues that pushed the decision
to migrate towards OMS:
 OpenMI forces modelers to use a quite restrictive API
 OpenMI is currently proposing its version 2, which from 1.4 introduces several
changes. Migrate to that would require an enormous effort

HydroloGIS s.r.l. - Via Siemens, 19 – 39100 Bolzano www.hydrologis.com



JGrass and OMS: what will happen to OpenMI?

 OMS already contains a set of components that are free and open sourced,
and also already well tested at the USDA, which would come as a present to
JGrass. OpenMI still doesn't have any open source components and seems to
be focused on few proprietary applications
 OMS is an annotation based modern modeling framework that really focuses
on adding few overhead to the modeler
 the OMS team is working on a wrapper to generate OpenMI code from OMS
models




OMS: an annotations based framework
OMS minimizes the burden on a component/model developer to build
code into the framework by not imposing an API. (I know everyone claims
it, but believe me, this time it is true)

package helloworld;
import oms3.annotations.*;

public class Component {
@Role(Role.PARAMETER)
@In
public String message;

@Execute
public void run() {
System.out.println(message);
}
}




OMS: other advantages
With OMS a bunch of important features come into JGrass's modeling
system:

 Components always execute multi-threaded. If the data flow alows it,
the models are executed in parallel.

 Integration with JNA (same as JGrass) for native code access. Java
Native Access (JNA) integration that now supports all versions of
FORTRAN, C, and C++ on all major architectures in 32 and 64 bit.
FORTRAN and C/C++ programmers can continue to use their respective
tools to create components




OMS: other advantages

With OMS a bunch of important features come into JGrass's modeling
system:

 Runtime flexibility for simulation execution. Models can be executed in
different environments that scale from a notebook to a computing cluster
or even a cloud such as Amazon’s Elastic Computing Cloud (EC2).
 The OMS modeler environment bases on Groovy scripting language,
exactly as JGrass's console does



GEOFRAME

GEOFRAME 2011 blueprint

Out R JGrass-udig- OMS3 NWW

GEOtop NewAge Boussinesq PeakFlow
Models

SHALSTAB GEOtop-FS The Horton Machine

In JGrass-udig- OMS3
METEO
/IO
Environmental Data Center
Data (Postgres/Postgis/Ramadda/H2)
41



EPILOGUE

OUR AIM IS NOT TO MODEL EVERYTHING*OR
DO A MODEL OF EVERYTHING BUT GIVE A
S PA C E W E R E D I F F E R E N T, E V E N
CONTRADICTORY, IDEAS, AND DATA CAN BE
EXPLOITED IN A WAY WHICH PROPELS
COLLABORATIVE EFFORTS BY SCIENTISTS
AND USERS.
*“Correctly interpreted, you know, pi contains the entire history of the human race.”
-Dr. Irving Joshua Matrix, from M. Gardner, “The magic numbers of dr. Matrix”


Find this presentation at
http://www.slideshare.net/GEOFRAMEcafe/rr-reflections

Ulrici, 2000 ?

Other material at
http://www.slideshare.net/posterVienna 43


Thank you for your attention
From the work the thousand rivers” (i mille fiumi) by Arrigo Boetti and Anna-marie Sauzeau-Boetti

classification by order of magnitude is the most common method for classifying information relative to a certain category, in the case of rivers, size can be
understood to the power of one, two, or three, that is, it can be expressed in km, km2, or km3 (length, catchment area, or discharge), the length criterion is
the most arbitrary and naive but still the most widespread, and yet it is impossible to measure the length of a river for the thousand and more perplexities
that its fluid nature brings up (because of its meanders and its passage through lakes, because of its ramifications around islands or its movements in the
delta areas, because of manʼs intervention along its course, because of the elusive boundaries between fresh water and salt water...) many rivers have
never been measured because their banks and waters are inaccessible, even the water spirits sympathize at times with the flora and the fauna in order to
keep men away, as a consequence some rivers flow without name, unnamed because of their untouched nature, or unnamable because of human
aversion (some months ago a pilot flying low over the brazilian forest discovered a “new” tributary of the amazon river). other rivers cannot be measured,
instead, because they have a name, a casual name given to them by men (a single name along its entire course when the river, navigable, becomes
means of human communication; different names when the river, formidable, visits isolated human groups); now the entity of a river can be established
either with reference to its name (trail of the human adventure), or with reference to its hydrographic integrity (the adventure of the water from the remotest
source point to the sea, independently of the names assigned to the various stretches), the problem is that the two adventures rarely coincide, usually the
adventure of the explorer is against the current, starting from the sea; the adventure of the water, on the other hand, finishes there, the explorer going
upstream must play heads or tails at every fork, because upstream of every confluence everything rarefies: the water, sometimes the air, but always oneʼs
certainty, while the river that descends towards the sea gradually condenses its waters and the certainty of its inevitable path, who can say whether it is
better to follow man or the water? the water, say the modern geographers, objective and humble, and so the begin to recompose the identity of the rivers,
an example: the mississippi of new orleans is not the extension of the mississippi that rises from lake itasca in minnesota, as they teach at school, but of
a stream that rises in western montana with the name jefferson red rock and then becomes the mississippi-missouri in st louis, the number of kilometres
upstream is greater on the missouri side, but in fact this “scientific” method is applied only to the large and prestigious rivers, those likely to compete for
records of length, the methodological rethinking is not wasted on minor rivers (less than 800km) which continue to be called, and measured, only
according to their given name, even if, where there are two source course (with two other given names), the longer of the two could be rightly included in
the main course, the current classification reflects this double standard, this follows the laws of water and the laws of men, because that is how the
relevant information is given, in short, it reflects the biased game of information rather than the fluid life of water, this classification was began in 1970 and
ended in 1973, some data were transcribed from famous publications, numerous data were elaborated from material supplied non-european geographic
institution, governments, universities, private research centres, and individual accademics from all over the world, this convergence of documentation
constitutes the the substance and the meaning of the work, the innumerable asterisks contained in these thousand record cards pose innumerable doubts
and contrast with the rigid classification method, the partialness of the existing information, the linguistic problems associated with their identity, and the
irremediably elusive nature of water all mean that this classification, like all those that proceeded it or that will follow, will always be provisional and
illusionary

Anne-marie Sauzeau-Boetti

(TN the text is published without capital letters) 44


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