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Page 1: Rr reflections

R. Rigon, G. Formetta

GEOtop, NewAge and BeyondMontpellier, October 21, 2011

Cez

ann

e, P

ine

Tre

e n

ear

Aix

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The good old Hydrological cycle

Introduction

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Every Hydrologist would like to have THE MODEL of IT

But in reality everybody wants just to investigate a limited set of

phenomena: for instance the discharge in a river. Or landsliding , or

soil moisture distribution.

Any problems requires its amount of prior information to

be solved: some problems needs more detailed information of others

Introduction

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So we use different models

Introduction

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So we use different models

GEOtopFu

lly

dis

trib

ute

dG

rid

bas

ed

Introduction

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So we use different models

GEOtopFu

lly

dis

trib

ute

dG

rid

bas

ed

NewAge

Larg

e sc

ale

mod

elli

ng

Hil

lslo

pe

- St

ream

An

thro

pic

In

fras

tru

ctu

res

Introduction

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Boussinesq

Full

y C

ou

ple

dSu

bsu

rfac

e- S

urf

ace

Gri

d B

ased

So we use different models

GEOtopFu

lly

dis

trib

ute

dG

rid

bas

ed

NewAge

Larg

e sc

ale

mod

elli

ng

Hil

lslo

pe

- St

ream

An

thro

pic

In

fras

tru

ctu

res

Introduction

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Boussinesq

Full

y C

ou

ple

dSu

bsu

rfac

e- S

urf

ace

Gri

d B

ased

PeakFlow

GIU

HPea

k f

lood

s

So we use different models

GEOtopFu

lly

dis

trib

ute

dG

rid

bas

ed

NewAge

Larg

e sc

ale

mod

elli

ng

Hil

lslo

pe

- St

ream

An

thro

pic

In

fras

tru

ctu

res

Introduction

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Boussinesq

Full

y C

ou

ple

dSu

bsu

rfac

e- S

urf

ace

Gri

d B

ased

PeakFlow

GIU

HPea

k f

lood

s

So we use different models

GEOtopFu

lly

dis

trib

ute

dG

rid

bas

ed

NewAge

Larg

e sc

ale

mod

elli

ng

Hil

lslo

pe

- St

ream

An

thro

pic

In

fras

tru

ctu

res

Introduction

The complexity arrow

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Every one of them:

Perform the mass budget (and preserves mass)

Make hypotheses on momentum variations

Simplify the energy conservation (and its dissipation)to a certain degree

(Implicitly delineates a way to entropy increase)

Introduction

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A first question:

• How can we manage the set of activities behind all of this modeling ?

(-;

doing the models using sound science,

modern informatics,

validating them against data,

assessing their uncertainty

;-)

Questions

•Without reinventing the wheel any time

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GEOtop(Rigon et al., Jour. Hydromet., 2006)

This model focuses on the water and energy budgets at few

square meters scale with the goal of describing catchment

hydrology including (a reasonable parameterization) all

known processes. (Whatever this means)

GEOtop

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We are aware that:

“ You cannot deny that our universe is not a

chaos; we discern in it beings, things, stuff that we

name with words. These beings or things are

forms, structures endowed with a certain

stability; they fill a certain portion of space and

perdure for a certain time ...”

R. Thom, Structural stabity and morphogenesys,1975

And therefore a fully reductionist approach is stupid. However facing with the fundamental law teaches us many thing about the reduction of complexity with scales that naive intuition or pedestrian simplification does not allow.

Remarks

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1. Radiation

4. surface energy balance

- radiation- boundary-layer interaction

2. Water balance

- effective rainfall- surface flow (runoff and channel routing)

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

3. Snow-glaciers

- multilayer snow scheme

- soil temperature- freezing soil

5. soil energy balance

- multi-layer vegetation scheme- evapotranspiration

6 . v e g e t a t i o n interaction

GEOtop structure

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snow, ice, permafrost

water cycle in complex terrain

landslidingevapo-transpiration, energy fluxes

Bertoldi et al., 2006Bertoldi et al 2010

Endrizzi 2007Dall’Amico 2010Endrizzi et al, 2010a,b in preparation

Simoni et al 2008Lanni et al, 2010

Rigon et al., 2006

Why this complexity ?

GEOtop structure

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Meteo

Rainfall/Snow

Snow/Energy budget

Atm. TurbulenceRadiation

For each time stepGEOtop, NewAgeBoussinesq

Al the models the same strategy but w i t h d i f f e r e n t a m o u n t o f information flowing

GEOtop structure

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Richards ++

Surface flows

Channel flow

Next time step

GEOtop

GEOtop structure

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What I mean with Richards ++

First, I would say, it means that it would be better to call it, for

instance: Richards-Mualem-vanGenuchten equation, since it is:

Se = [1 + (��⇥)m)]�n

Se :=�w � �r

⇥s � �r

C(⇥)⇤⇥

⇤t= ⇥ ·

�K(�w) �⇥ (z + ⇥)

K(�w) = Ks

⇧Se

⇤�1� (1� Se)1/m

⇥m⌅2

C(⇥) :=⇤�w()⇤⇥

GEOtop structure

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What I mean with Richards ++

First, I would say, it means that it would be better to call it, for

instance: Richards-Mualem-vanGenuchten equation, since it is:

Se = [1 + (��⇥)m)]�n

Se :=�w � �r

⇥s � �r

C(⇥)⇤⇥

⇤t= ⇥ ·

�K(�w) �⇥ (z + ⇥)

K(�w) = Ks

⇧Se

⇤�1� (1� Se)1/m

⇥m⌅2

Water balance

C(⇥) :=⇤�w()⇤⇥

GEOtop structure

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What I mean with Richards ++

First, I would say, it means that it would be better to call it, for

instance: Richards-Mualem-vanGenuchten equation, since it is:

Se = [1 + (��⇥)m)]�n

Se :=�w � �r

⇥s � �r

C(⇥)⇤⇥

⇤t= ⇥ ·

�K(�w) �⇥ (z + ⇥)

K(�w) = Ks

⇧Se

⇤�1� (1� Se)1/m

⇥m⌅2

Water balance

ParametricMualem

C(⇥) :=⇤�w()⇤⇥

GEOtop structure

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What I mean with Richards ++

First, I would say, it means that it would be better to call it, for

instance: Richards-Mualem-vanGenuchten equation, since it is:

Se = [1 + (��⇥)m)]�n

Se :=�w � �r

⇥s � �r

C(⇥)⇤⇥

⇤t= ⇥ ·

�K(�w) �⇥ (z + ⇥)

K(�w) = Ks

⇧Se

⇤�1� (1� Se)1/m

⇥m⌅2

Water balance

ParametricMualem

Parametricvan Genuchten

C(⇥) :=⇤�w()⇤⇥

GEOtop structure

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What I mean with Richards ++

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

GEOtop structure

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Landsliding

After Lanni et al, 2010 submitted

Landsliding

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Landslidingdry case - low intensity precipitation

Landsliding

After Lanni et al, 2010 submitted

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Landslidingwet case - high intensity precipitation

Landsliding

After Lanni et al, 2010 submitted

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Landsliding

The experiments also show that triggering happens

when approximately the same critical weight of

water has been stored in the hillslope, and that the

antecedent soil moisture condition and rainfall

intensity determine the rainfall duration needed to

achieve this critical volume of water.

Landsliding

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What I mean with Richards ++

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

Unsaturatedunfrozen

Freezingstarts

Freezingprocedes

UnsaturatedFrozen

GEOtop structure

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Unfrozen water content

Soil water retention curve

thermodynamic equilibrium (Clausius Clapeyron)

+

⇥w =pw

�w gpressure head:

�w(T ) = �w [⇥w(T )]

What I mean with Richards ++

+

Freezing = drying hypothesis

GEOtop structure

M. Dall’Amico et al., The Cryosphere, 2011

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T � := T0 +g T0

Lf�w0

� = ⇥r + (⇥s � ⇥r) · {1 + [�� · ⇤w0]n}�m

ice content: �i =⇥w

⇥i

��� �w

⇥w = ⇥r + (⇥s � ⇥r) ·⇤

1 +���⇤w0 � �

Lf

g T0(T � T ⇥) · H(T � T ⇥)

⇥n⌅�mliquid water

content:

Total water content:

depressed melting

point

What I mean with Richards ++

GEOtop structure

M. Dall’Amico et al., The Cryosphere, 2011

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Unsaturatedunfrozen

UnsaturatedFrozen

Freezingstarts

Freezingprocedes

What I mean with Richards ++

Freezing = Drying

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What I mean with Richards ++Freezing = Drying

M. Dall’Amico et al., The Cryosphere, 2011

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What I mean with Richards ++Freezing = Drying

M. Dall’Amico et al., The Cryosphere, 2011

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25water content [−]

so

il d

ep

th [

mm

]

Tot Water profile: comparison with Hansson et al−

20

0−

16

0−

12

0−

80

−6

0−

40

−2

00

0.25 0.30 0.35 0.40 0.45 0.50 0.55

after 50 hours●

Sim

● Meas

M. Dall’Amico et al., The Cryosphere, 2011

Freezing = Drying

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Obviously this makes it possible to simulate a lot of new phenomenologies

Sisik, river in the artic tundra

Runoff on Frozen SoilEn

dri

zzi

et A

l., JH

R, 2

01

0

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44

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

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

Runoff on Frozen Soil

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The model allows to show that the runoff

properties of a basin dramatically change when

soil freeze.

Runoff on frozen soil

Runoff on Frozen Soil: main result

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Arabba

Pordoi

Caprile

Malga Ciapela

Pescul

Ornella

Saviner

Snow generated runoff

Frozen soil can be combine with the snow module

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Frozen soil can be combine with the snow module

Snow generated runoff

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02

46

810

1214

Date (dd/mm)

Dis

char

ge [m

3/s]

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

measuredGEOtop

Discharge at Saviner year 2006−2007

We have to work more here!

Snow generated runoff

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A second set of questions:

Questions

•Is Richards equation true ?

•Is the van Genuchten-Mualem theory true ?

•What actually means “true” ?

•Where is “structure” (beside texture) in soil parametrization ?

•Are there methods for accounting the spatial and temporal

variability of soil hydraulic characteristics ?

•Soil thermodynamics .... what is it ?

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The perfect model does not exist !

Well,

Pic

asso

, Dora

Maa

r

Deconstructing models

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JGrass-NewAGE (Formetta et al., GTD, 2011)

This model focuses on the hydrological budgets of medium

scale to large scale basins as the product of the processes

averaged at the hillslope scale with the interplay of the river

network.

JGrass-NewAGE

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Hillslope Storage Dynamics

Surface flows Aggregation

Channel flow

Next time step

JGrass-NewAge

The structure of NewAge

(Formetta et al., GTD, 2011

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Input Data treatment

Goodness of fit

Next time step

JGrass-NewAge

The structure of NewAge

Calibration tools(Formetta et al., GTD, 2011

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Input Data treatment

Goodness of fit

Next time step

JGrass-NewAge

The structure of NewAge

Data assimilation(Formetta et al., GTD, 2011

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Hillslope Storage Dynamics

Surface flows Aggregation

Channel flow

Next time step

JGrass-NewAge

The structure of NewAge

(Formetta et al., GTD, 2011

Evapotranspiration

Radiation

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Rin

ald

o, G

eom

orp

hic

Flo

od

Res

earc

h, 2

00

6

Someone call them Hydrologic Runoff Units

we call them hillslope-link partition of the basin

The structure of NewAge

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Rin

ald

o, G

eom

orp

hic

Flo

od

Res

earc

h, 2

00

6

For each of the variable of the hydrological cycle

a statistics is made for each hillslope and a single value is returned

so, we have 5 values of the prognostics quantities here, that are space time-averages of what happens inside each hillslope

The structure of NewAge

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They are estimatedfor each hillslope

•mean rainfall

•mean radiation (we exploit some old idea by Ian Moore)

•mean evapotranspiration

•mean snow cover

•mean runoff production

The structure of NewAge

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When runoff is collected

then is routed, for small basins, with a modification of the Muskingum-Cunge algorithm, or directly with a semi-implict solver of the de Saint-Venant 1D

The structure of NewAge

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Thus we have discharges

Rinaldo, Geomorphic Flood Research, 2006

Here, Here ... and here again

The structure of NewAge

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Remind that, in general, you cannot

assume constant flow velocity through the network in all conditions of flow. So the simplifications that brings to the W-GIUH (Rinaldo et al., 1991,1995; Saco and Kumar, 2002; D’Odorico and Rigon, 2003) cannot be made.

And the complexity of Richards equations ?

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Observe,that I did not mention the complexity implies by the

Richards equation.

WHERE IS IT NOW ?

And the complexity of Richards equations ?

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IT WAS ASSUMED more than DERIVED*

- that something averages out*

- that the same averages modify the structure of the equations and the parameters (which could possibly

vary seasonally)

for a derivation of part of it see Cordano and Rigon, 2008

And the complexity of Richards equations ?

Can we built a statistical theory that rigorously derives the simplified equations ?

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A rigorous statistical theory would be needed that allows for

•doing rigorously such simplifications*, not just on the basis of the personal Art of modelling^;

•quantify the uncertainty remained after the simplifications**

*for a derivation of part of it see Cordano and Rigon, 2008 and BTW compare it with the abstract view Reggiani et al., 1999

The need for a statistical theory

^This will be remain, however ...

** The distribution around the mean quantities could not be sharp. Variances can be important ...

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However, the more “reductionist” GEOtop

could be used to test the solutions implemented in the simplified NewAGE and evaluate the non-acceptable behaviors.

Obviously, this is not as simple as it can be, because GEOtop itself

comes with its simplifications and errors

The need for a statistical theory

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Assume that now a reservoir

is made here

Rinaldo, Geomorphic Flood Research, 2006

The structure of NewAge

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Well, you can have the discharges also there

once you embeds the characteristics of the reservoirs in the model

Rinaldo, Geomorphic Flood Research, 2006

The structure of NewAge

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However

for doing it seamlessly you need to made a topological description of the network and capture it in a suitable object-oriented-geographic infrastructure.

NewAge DOES it!

details in the upcoming papers and manual

The structure of NewAge

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The modeling by component paradigm was adopted

Modeling by component

automagically inside the udig GISThis interface was automatically created from OMS v3 annotations

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The modeling by component paradigm was adopted

Modeling by component

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.

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

Resources

KnowledgeBase

DevelopmentTools

Products

OMS

http://www.javaforge.com/project/oms

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Is the mean value for a hillslope enough ?

from the point of view of the prognostic variable it could be. It Depends on what the observer is looking for and for what.

from the point of view of the input data, inferring the space-time mean could not be enogh. In fact:

•for evaluating evapotranspiration properly we need for accountng of the subgrid variability of soil moisture distribution, vegetation and radiation.

•for evaluating the snow pack evolution we need to account, at least, for the variability of radiation

Questions

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So

Any hillslope is subdivided in

- zone of about the same elevation (elevation classes)

- areas that receives the same amount of radiation (radiation classes)

- soil cover classes

An this subgrid variability is used to estimated the mean values for each hillslope.

The structure of NewAge

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A third set of questions:

Questions

• Is it possible (and how) to identify sets of spatial points that behave

hydrologically in a similar way ? (a question that pervades Hydrology since many years:

google hydrological symilarity)

•What is explained by the form, topology, and geometry of catchments ?

•Is really possible to work cooperatively building, we dwarfs, on the

shoulder of each other, and maybe of some giant ? Or is hydrology

condemned to an endemic dilettantism ? (e.g Klemes, WRR, 1986)

•What we can do to characterize uncertainties in hydrological modeling ?

And which is the acceptable degree of confidence to say that a model is a

good model ?

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Peakflow (Rigon et al., HESS, 2011)

Is a “minimalistic effort” when compared to the others. It is

an event based GIUH (width function flavor) model of

rainfall runoff which try to use the topographic information

for appropriate modeling.

Peakflow

Hoku

sai, 1

82

9-3

2

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Effective rainfall

Surface flows Aggregation (Width function)

Diffusive wave

Peakflow (a W-GIUH) model

The structure of Peakflow

(Rigon et al., HESS, 2011)

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The main news is that during flood peaks

•Radiation and evapotranspiration are neglected (what is relevant is included in the iniital conditions)

•you can assume very simplified mechanisms of runoff production

•flood wave celerity can be kept constant (as a first approx.)

•the most of the variance of flood hydrograph is explained by the geometry and topology of the basin (and the space-time variation of rainfall

The structure of Peakflow

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The main news is that during flood peaks

•Radiation and evapotranspiration are neglected (what is relevant is included in the iniital conditions)

•you can assume very simplified mechanisms of runoff production

•flood wave celerity can be kept constant (as a first approx.)

•the most of the variance of flood hydrograph is explained by the geometry and topology of the basin (and the space-time variation of rainfall

The structure of Peakflow

• well, I did not talk about the runoff coefficient

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You can assume very simplified mechanisms of runoff production

Well, more based on heuristics, since evidence shows that initial

condition for large floods (don’t want to talk of return period!) in a

basin, and rainfall space-time distribution (but mostly timing counts,

Rinaldo et al., 200X) are similar for a given basin.

The structure of Peakflow

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Flood wave celerity can be kept constant (as a first approx.)

Leopold and Maddock, 1953

The structure of Peakflow

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62

Flood wave celerity can be kept constant (as a first approx.)

Follows also from theory of

minimum energy dissipation:

- Rodriguez-Iturbe et al., Energy dissipation, runoff production and the three-dimensional structure of river networks, WRR, 1992

- Rodriguez-Iturbe and Rinaldo, Fractal River Basin, CUP 1997

- Rinaldo et al., Channel Networks, Rev. Earth and Plan. Sciences, 1998

The structure of Peakflow

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63

The most of the variance of flood hydrograph is explained by the geometry and topology of the basin (and the space-

time variation of rainfall)

- Rinaldo et al., Geomorphological Dispersion, WRR, 1992

- Rinaldo et al, Can you gauge the shape of a basin ? , WRR, 1995

- D’Odorico and Rigon, Hillslope and channel contributions to the hydrologic response, WRR, 2003

The structure of Peakflow

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64

Good resultsFort Cobb, OK USA

05/26/2008

Aft

er P

erat

hon

er, 2

01

1Results with Peakflow

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Aft

er P

erat

hon

er, 2

01

1

Less good result*Little Washita, OK

19/06/2007

* On Little Washita we had also good results

Results with Peakflow

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66

Aft

er P

erat

hon

er, 2

01

1

Less good resultPassirio, Italy23/07/2008

Results with Peakflow

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67

Observations

There was a big trick: the runoff coefficient was estimated “a -priori”

and was:

Fort Cobb <- 0.14

Little Washita <- 0.7

Passirio <- 0.2

Results with Peakflow

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68

Observations

It seems that in some situations there is a delayed production of runoff which

produces large recession curves with local maxima of discharges that do not

correspond to rainfall impulses. Therefore the “tricky runoff coefficient” could

be different from surface and subsurface flows. In the case of Passirio, it could

be snow melting.

PBIAS is always negative, meaning that a systematic underestimation of flow

discharge.

Results with Peakflow

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69

Questions

•How, the hell, can you estimated that damned runoff coefficient ?

A fourth set of questions

•Is there really there the minimal information for forecasting floods or can we do even better ?

•We used everywhere (with some tricks but with ) with success. Why we did not systematize the parameters choice ?

•Can we modify the model structure to include spatial variability of storms ?

•Which storms should be use for envisioning extreme events ?

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GEOFRAME 201* Vision

GEOFRAME

GEOtop NewAge Boussinesq PeakFlowModels

SHALSTAB GEOtop-FS The Horton Machine

J G r a s s - u d i g - OMS3- NetCDF

Out R NWW

JGrass-udig- OMS3- NetCDF

Environmental Data Center (Postgres/Postgis/Ramadda/H2)Data

In

METEO/IO

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71

Find this presentation at

http://abouthydrology.blogspot.com

Ulr

ici, 2

00

0 ?

Other material at

http://www.slideshare.net/GEOFRAMEcafe/rr-reflections

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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 man’s 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 one’s 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)

Thank you for your attention

Monday, October 24, 11


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