danube floodrisk ii

About the Guidelines for Hazard MappingRiccardo Rigon, Silvia Franceschi, Giuseppina Monacelli, Giuseppe Formetta

Segan

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Mez

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Danube FloodRisk Project, Trento, September 26, 2012

Monday, October 1, 12

Rigon et Al.

Danube Flood Risk Conference - Trento 26 September 2012

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Credits of This Research

Besides, being completed under the Danube Flood Risk EU Project

is based on studies developed during the IRASMOS EU project and

during a conjoint work with the “Servizio Bacini Montani” of the

Autonomous Province of Trento


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Credits for these Slides

Most of the slides picture were produced during pilot studies by:

Hydrologis - ing. Silvia Franceschi, dr. ing. Andrea Antonello

ingTerritorio - ing Christian Tiso and dott. geol. Alessandro Sperandio

Mountainain-eering - dr. ing Silvia Simoni, ing. Fabrizio Zanotti, dr. ing.

Matteo Dall’Amico

Research used is much derived from common work with dr. ing Silvia Simoni

and dr. ing. Cristiano Lanni

who I thanks and acknowledge all.


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This presentation

the last year presentation, and related material can be found at:

http://abouthydrology. blogspot.com

search the blog for landslide triggering


http://about

http://about

Riccardo Rigon

Danube Flood Risk Conference - Trento 3-4 October 2011

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Low


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Preliminary Analisys

Low


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Potential Risk

High Low

In the average

Low


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Potential Risk

High Low

In the average

Low

Further Assessment considering uncertainties

High


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Low

Indicative analysis


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Medium-Low

Simplified analysis

Simplified Hydraulic analysis

High

Detailed analysis

Hydraulic analysis

Geological Analysis

Hydrological analysis

Geological Analysis


Low

Indicative analysis


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Medium-Low

Simplified analysis

Simplified Hydraulic analysis

High

Detailed analysis

Hydraulic analysis

Geological Analysis


Geological Analysis


Low

Indicative analysis

Comparison with other hazard maps


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Preliminary Analysis

Geology, Simplified Hydrology

and (no) Hydraulics

Hazard Maps

Steps in this presentation


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Field Survey, Data

Collection, Maps analysis

Geological techniques , Hydrological

models, Hydraulic models

GIS tools

Tools behind


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Summary of the Procedure


I. Geomorfological description of the Basin

II. Data Review

III. Historic Data Collection


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Analysis

I. Geological Analysis (orthophotos, existing cartography, field survey,

geomorphological analysis, geophysical analysis, geotechnical analysis)

II. Estimation of available sediment

III. Hydrological analysis and models’ choice

Summary of the Procedure


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La caccia al pericolo


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quota max: 2890 m

•Basin Area: 13.4 km2

•Min elevation: 924 m

•Max Elevation: 2890 m

•Two networks, torrents

Rio Corda

•Mean slope ....

Basin Classification

Courtesy of Mountain-eering


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Cismon - Canali


Courtesy of Hydrologis


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Wor

ldW

ind4

JGra

ss -

Cismon - Canali



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Data InventoryCismon - DEM eith the main hydrography

I would suggest in a map like this to indicate also some relevant points as peaks, etc.


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Canali - Idrografia P.A.T

Hydrography can be improved by using Strahler ordering

Data Inventory


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Data InventoryOrhophoto

By itself the ortophoto is not very

informative if other information is not

superimposed


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Technical Map

rio Corda

Data Inventory


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19From PAT 2003.

Val di Casa - Land Cover

Data Inventory


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This is Land Cover

grass, in this case


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This is land use

grazing, in this case


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Rio Corda - Geological Maps

Data Inventory


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Summary

Carta

DTM Hydrography Orthophoto

Technical Maps Land Cover- Land Use Geological Maps

Data Inventory


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Data InventoryHistorical data

Franceschini, 2003

This landslide was referred in

March 2003 from Servizio di

Sistemazione Montana.

The landslide involves a surface

of 15500 m2 and cover around

100m of elevation, from the

channel bed to ca. 1653 m a.s.l.


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25Franceschini, 2003

The depth of the movable

s e d i m e n t h a s b e e n

estimated to be around 10 m.

The material of the landslide

i s made by c las t s and

boulder of sand matrix

w h i c h o f t e n t u r n i n t o

limestone.

Data InventoryHistorical data


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Going a little Deeper


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Missing data a little of survey can help. This is Val di Casa

Past Events:

1. Flooding 1906 (missing source)

2. looding1987(missinf source)

In both the case the sediment that arrived to Carderzone was between 30.000 and 40.000 cubic meters

This levee was realized in 1908 after the flood of 1906

Data Inventory


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Geological AnalysisSinthesis- Val di Casa

In Val di Casa catchments are present five main lithological typologies: 1. Granite, granodiorite and tonalite Adamello 2. Mica schists, phyllites and paragneiss 3. lakes and rivers; 4. moraines coarse 5. detritus deposits with gravel prevalent;

Always cite the source !


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Identification of the quaternary cover, in the low part of the basin with the use of orthophoto relative to different years: from left to right 2006, 2000, superposition of geology to the 2006 ortophoto.

Geological AnalysisSinthesis- Val di Casa


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Di sintesi - Val di Casa

Same as previous slide for the upper part of the basin: 2000, 2006 ortophotos, superimposition of geology tho 2006 orthophoto

Geological Analysis


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Using LIDAR maps a good geologist is able to give an estimate of quaternary covers.

Lidar Data - Val di Casa

Geological Analysis


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Can be made a little more specific with a little of field survey - Case Cismon

Cismon catchment is composed by

two main geostructural domains:

• the dolomitic domain (oriental):

which is the Pale i S. Martino Area

• the metamorph ic doma in

(western): the area of mount

Tognola.

The river network developed close

to the fault line.

Geological Analysis


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Litostratigraphy of Cismon

torrent.


Geological Analysis


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34Quaternary Formations


Geological Analysis


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Landsliding: on the left the landslide at Pian delle Sfelde and at

the right the deep landslide of Mount Tognola


Geological Analysis


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GPS mapping (in yellow) of the first surveys on the basin

Geological Analysisin the field


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Three dimensional view of the

survey with georeferencing of

the photos.



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Geological surveygeophysics - rio Corda

Objective:

Give information about:

• soil depth in some points (gray

rectangles);

• water table positions and main

directions of subsurface flows;

• stratigraphy and lithology.


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Where to do the survey

• area close to the head water and

where there were landslides;

• springs (light blue rectangles);

• confluences of channels.



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Geological SurveyGeomechanics - rio Corda

Objectives

We want to know:

• soil texture i.e. the fraction of sand, silt

and clay;

• the particle size of sediment in the bed of

the torrents ;

• strength parameters of soils (as proven in

the lab);

• hydrological parameters in situ hydraulci

conductivity, residual water content, and

porosity.


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Where (red circles)

• slopes prone to instabilities from

qualitative indications: steep, concave, with

high topographic index;

• areas with quaternary cover not very

much consolidated;

• torrents bed in more steep areas.



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Where

•Point 1 is localized on the bed of Poia

torrent, close to a slit dam,

•Point 2 is on the landslide of june 2008;

•Point 3 and 4 are close to a landslide

deposit, close to a detachment niche.



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Geological AnalysisGeomorphology - Canali

Slopes


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Sintesys:

mean slope: 34°

max slope: 87°

min slope: 0°

Statistics

Geological AnalysisGeomorphology - Canali


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Networks from DEM in red and ufficial network from P.A.T. (blue)

Geological AnalysisGeomorphology - Val di Case

Network delineation


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Subnetworks

From the resuts of the previous analsys follow the decision to consider some basins which are those

from which the sediment delivery is assumed to mainly come.

Geological AnalysisGeomorphology - Val di Casa


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Now the Choice of models


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Two directionsSubsurface waters - Surface waters

Sediment is generated by landslides that

subsequently turn into debris flow

Sediment is found in the

bed of torrents and areas close by


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bed of torrents and areas close by

Subsurface water flowmodel

Rainfall-Runoff Modeling


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bed of torrents and areas close by and by hillslope

inputs

Subsurface water flowmodel

Rainfall-Runoff Modeling


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Use empirical lawsSubsurface waters

A prototype is


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There is a geotechnical model

where:

FS =c�

�s z cos ⇥s sin ⇥s+

�s z cos2⇥s

�s z cos ⇥s sin ⇥stan⌅c �

�w⇤w cos2 ⇥s

�s z cos ⇥s sin ⇥stan⌅c

Symbol Name nickname UnitFS Factor of Safety fos [/]c⇥ cohesion chsn [M L2 T�2]⌅c columbian friction angle cfa [/]⇤w position of the water table surface pwts [L]z depth of soil ds [L]�s soil/terrain density std [M L�1 T�2 ]�w density of liquid water dlw [M L�1 T�2 ]⇥s slope of terrain surface sts [/]


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And a hydrological modeloften assuming stationary hydrology


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Sediment availabilityplaying with simplified models

One idea is to use to make reasonable experiments models like SHALSTAB and

SINMAP (the method itself is not rigorous, but its exploration allows to frame the

quantities).

For instance assigning a rainfall with a certain duration and intensity (according to

Intensity-duration-frequency curves), Equation for stability can be inverted ... In the

hypothesis that short term rainfall do not destabilize the hillslopes:

A/b ⇤ T sin �s

q

⇥w

⇥s

�1� tan �s

tan⇤c+

c�(1 + tan2 �s)tan⇤c ⇥s g · z

⇥


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where:

Symbol Name nickname UnitFS Factor of Safety fos [/]c⇥ cohesion chsn [M L2 T�2]⌅c columbian friction angle cfa [/]⇤w position of the water table surface pwts [L]z depth of soil ds [L]�s soil/terrain density std [M L�1 T�2 ]�w density of liquid water dlw [M L�1 T�2 ]⇥s slope of terrain surface sts [/]

Sediment availability


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From which one can derive an estimate of

A/b ⇤ T sin �s

q

⇥w

⇥s

�1� tan �s

tan⇤c+

c�(1 + tan2 �s)tan⇤c ⇥s g · z

⇥

tan⇤s � f(ks, z, q, �s, ⇥w, ⇥s)

a minimal value of the critical angle tan�s



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and obtain maps like this one



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At this point using the reference value of the critical angle one can obtain those

point where the contributing area is unstable.

Where indicates that the value has been obtained in “back analysis” with

precipitation of 24 hours of duration 24 hours and return period of 5 year.

�c(5, 24)

A/b ⇤ T sin ⇥s

q

⇤w

⇤s

�1� tan ⇥s

tan⌅c(5, 24)+

c�(1 + tan2 ⇥s)tan⌅c(5, 24) �s · z

⇥



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Analisi GeologicaAnalisi del sedimento disponibile - rio Corda

Analisi di stabilità condotta con Shalstab per diversi tempi di ritorno. Sono riportati i dati relativi a

precipitazioni con un tempo di ritorno di 30 anni.


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The method can be improved under many aspects

•one can consider instead of a single value for a critical angle many values,

depending on lithology;

•one can consider different couples of rainfall-duration

•instead of considering SHALSTAB one can use QD-SLAM (es. Borga et al., 2002)

or CI-SLAM (Lanni et al., 2012) models that remove the hypothesis of stationarity

Improving the methodSubsurface waters


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Different choice of the geotechnical model

where:


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Different choice of the hydrological model

34

1 2

3

4

5

6

7 8 9

Figure 1. A flow chart depicting the coupled saturated/unsaturated hydrological model 10

developed in this study. 11

12 Lanni et al., 2012


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Improving the methodSubsurface waters

Lanni et al., 2012


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Rio Corda sxRio Corda sx Rio Corda dxRio Corda dx

soil volumesoil volume soil volumesoil volume

Return period 1m 2m 1m 2m

30 years 4.02E+05 8.03E+05 4.66E+05 9.32E+05

100 years 4.13E+05 8.27E+05 4.77E+05 9.55E+05

200 years 4.20E+05 8.41E+05 4.87E+05 9.75E+05

This is an exemplificative table. The error can be very large but gives, at least, an order of magnitude

SummarySubsurface waters


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Gological AnalysisSediment available- Cismon

When the geological analysis gave soil depth, These can (must) be used in the procedure.


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The sediment availability can be given also for any subbasin:

Geological AnalysisSediment available- Val di Casa


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The volumes of movable sediments for the Val di Casa basin. In this case the soil depth is taken constant. But clearly a better estimation can be done. The volumes obtained are consisten with the historical analysis.

Therefore:

Geological AnalysisSediment available- Val di Casa


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Can this sediment arrive to the river and being transported downstream ?

We do not have at the moment rigorous analysis for assessing this. However some empirical formula can help.

http://www.illustrationsource.com


http://www.illustrationsource.com/

http://www.illustrationsource.com/

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Sediment availableCismon

On the left the areas which are thought to supply sediment to the network; on the right: the same areas with depicted the soil depth.


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This can be considered a zeroth-order estimation of the

possibility of the subsequent transport in channels estimated

with the good old method by Takahashi (1978).

The result in the next page

Symbol Name nickname UnitC� Concentrazione in volume particelle sedimento cvps [/]h0 tirante idrico superficiale tis [L]n numero di strati di particelle movimentati nsp [/]d granulometria del sedimento gs [L]

tan ⇥s ⇤ tan⇤cC�(�s/�w � 1)

h0/n d + C ⇥ (�s/�w � 1) + 1



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According Takahashi (1978) the values of the ratio ho/nd that cause a debris

flows are between 0 e 1.33. For values less than 0 the debris is dry, and with slope

allowing a landslide is generated. According to the method the values of slopes

which generate debris flow are in between:

tan⇤cC�(�s/�w � 1)

C ⇥ (�s/�w � 1) + 1⇤ tan ⇥s ⇤ tan⇤c

C�(�s/�w � 1)1.33 + C ⇥ (�s/�w � 1) + 1

For slopes less than the right limit, the transport is usually normal solid

transport (hyperconcentrated); for slopes larger than the left limit the movent

happens also in dry conditions, and therefore the sediment accumulate with

difficulty on the slopes.



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T h e n e t w o r k c l a s s i f i e d

according to Takashi. In red the

channels where debris flow is

possible, in light blue the

channe l s where poss ib l y

sediment transport is possible



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T h e s a m e a s t h e

previous side but with

the sources of sediment

enlightened.



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Surface Hydrology


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Now the sediment is in the channels

We need the water to move it !


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Rainfall-Runoff Analysis

•There are many models that produce discharge at a catchment closure. As soon as they are appropriately calibrated, many of them are good.

The problems arise when we do not have data to calibrate them


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One important question is: how do we estimate the rainfall volumes that

transform into discharges (i.e. the effective rainfall) ?

There exists many methods. Some are better.We cannot rely on methods introduced for agricultural

settings.

Obviously the choice of this method and its appropriateness affect the final

result.


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Rainfall-Runoff AnalysisThere are some issue related to the problem under analysis,

and some issue related to rainfall-runoff in general

This problem: one wants

discharges in several

point, for instance for

estimating sediment

transport in the channel

highlighted in blue


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Uphill basin

Interbasin

So, the basin needs to be

appropriately subdivided

a n d t h e h y d r o l o g y

appropriately estimated.

This is trivial indeed ...

if the model parameters

d e p e n d s o n s p a t i a l

knowledge, and can be

rescaled!


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Please keep also in mind that having liquid discharges are just one step of the process that involve also sediment and the use of hydraulic models

I prefer those methods which use explicitly the knowledge of geomorphology


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Hydrological Analysisdo it the PeakFlow way!

Peakflow:

•Assume saturation excess mechanism (and estimate the saturated areas with the

topografic index, e.g. Beven, 2001)

•Use the rescaled width function (Rinaldo et al., 1995, D’Odorico e Rigon,

2003) to obtain the surface and the subsurface hydrographs


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•Peakflow

•Allows to estimate the maximum discharges (and the peak time and the critical

duration of rainfall) generated by uniform precipitation with assigned return

period (using a power law type of IDF)

uDig implements it!


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Distances from the outlet (on the left) and rescaled (on the right). Only 40% of the areas is actually colored according to the Beven and Kirby’s (1979) topographic index.

Hydrological AnalysisRescaled distances (Rinaldo et al., 1995)


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Histogram of areas that affects overland flow, assuming just 40% of area saturated.



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Knows your parameters (e.g. D’Odorico and Rigon, 2003):

• The fraction of saturated area is a critical parameters with which the peak discharge grows approximately linearly

•Velocity of water in channels and hillslope are some average in space (over the basin) and time (during the hydrograph) of the real (local) velocity

•rescaled factor between channel flow velocity and overland flow in hillslope (and the ratio between s channel flow and subsurface velocity)



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The question of solid discharges

We need now to invent a model for associating the solid discharges to the liquid

ones that we have obtained so far. We do not have ...

but we could envision how to do it:

•Built the total quantity of sediment available at distance say, x, to build the

sediment width function (normalized by the total volume)

•Assume that water and sediment in channel have the same velocity

•Built the sediment hydrograph


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Solid Discharges

•Assume that all the sediment movements trigger at the same instant

•The sediment width function (after transforming space into time) IS the

sediment hydrograph, and you add it to the water hydrograph for the final result.

Do it but with care!


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Hydraulics


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•Sediment concentration could be too high. In this case the sediment deposit.

It is clear that from the point you add sediment and water in input one should

use an effective hydraulic model to move it along channels.

Solid Discharges

This is actually another Job

and

we do not talk about here


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A minimal approach

to sediment delivery on alluvial fans


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A minimal approach

to sediment delivery on alluvial fansSheidl and Rickenmann (2009)

Will be explained in the next talk


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And in short the last steps


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Squeeze it in three colors

PROBABILITY THRESHOLDS and CORRESPONDING RETURN PERIODS

Low probability Tr=200 years

Medium probability Tr=100 years

High probability Tr=30 years

Where observed events show an intensity that is reasonably

greater than that corresponding to a return period of 200 years,

then it may be worthwhile considering these observed situations

as a further class of extraordinary hazard (residual or potential).

8.1.4 Hazard Class Matrix

At this point the probability of occurrence of the event (return period) must be associated to the in-

tensity value that has been assigned. For each cell of the domain, therefore, there are three pairs of

values (intensity, return period) that, once inserted into the hazard class matrix, as shown in Figure

8.2, give three hazard values (one for each return period).

9 8 7

6 5 4

3 2 1

Figure 8.2 – Hazard class matrix.

The Hazard Class Matrix (Figure 8.2) proposes two different levels of intensity (red or blue for

level 6; yellow or blue for level 2) for two different statistical conditions – therefore there will be

different scenarios depending on the choices made. In these circumstances the least favourable

scenario is always considered. It is good practice, however, to document the modelling results in the

final report and the values of the matrix shown in Figure 8.2 associated to each calculation cell (val-

ues from 1 to 9).

In this way the three Hazard Maps, relative to the three different return periods, are obtained. The

complete Hazard Map is then drafted by assigning to each cell the highest hazard value relative to

all return periods. Each colour identifies a level of hazard, as defined in Table 8.5. In Figure 8.3 an

example of a complete hazard Map is shown.

Intensity

Probability/Frequency

High

High

Medium

Medium

Low

Low

Return PeriodLow Medium High


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Depending on the type of event the choice of the probability bins change.

PROBABILITY THRESHOLDS and CORRESPONDING RETURN PERIODS

Low probability Tr=200 years

Medium probability Tr=100 years

High probability Tr=30 years

Where observed events show an intensity that is reasonably

greater than that corresponding to a return period of 200 years,

then it may be worthwhile considering these observed situations

as a further class of extraordinary hazard (residual or potential).

8.1.4 Hazard Class Matrix

At this point the probability of occurrence of the event (return period) must be associated to the in-

tensity value that has been assigned. For each cell of the domain, therefore, there are three pairs of

values (intensity, return period) that, once inserted into the hazard class matrix, as shown in Figure

8.2, give three hazard values (one for each return period).

9 8 7

6 5 4

3 2 1

Figure 8.2 – Hazard class matrix.

The Hazard Class Matrix (Figure 8.2) proposes two different levels of intensity (red or blue for

level 6; yellow or blue for level 2) for two different statistical conditions – therefore there will be

different scenarios depending on the choices made. In these circumstances the least favourable

scenario is always considered. It is good practice, however, to document the modelling results in the

final report and the values of the matrix shown in Figure 8.2 associated to each calculation cell (val-

ues from 1 to 9).

In this way the three Hazard Maps, relative to the three different return periods, are obtained. The

complete Hazard Map is then drafted by assigning to each cell the highest hazard value relative to

all return periods. Each colour identifies a level of hazard, as defined in Table 8.5. In Figure 8.3 an

example of a complete hazard Map is shown.


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Table 8.1 - Index quantities as defined by the Provincial Resolution DGP 2759 (22/12/2006)

Index quantities

h Depth of liquid and/or solid outside watercourse [m]

vVelocity of the liquid and/or solid flow outside

watercourse [m/s]

vh Unitary discharge (drag force) [m2/s]

M Thickness of debris outside watercourse [m]

d Depth of erosion in the watercourse [m]

8.1.2 Intensity thresholds

The hazard level can be defined on the basis of a number of intensity classes, ranging from 3 to 5,

each corresponding to a different destructive potential for the event. Each of these classes is identi-

fied by means of a specific colour or symbol on the Hazard Map. Each intensity class is defined on

the basis of damage caused (or causable) by the event. In the table below (Table 8.2) the correlation

between intensity level and damage caused (or causable) is shown.

Table 8.2 – Description of intensity levels in relation to damage caused

Intensity Level of damage

High Loss of human life and destruction and/or permanent damage of structures and infra-

structure (hardly ever reversible)

Medium Serious damage to structures and infrastructure (without destruction), injuries to people

that are rarely fatal

Low Minor damage to structures and infrastructure with temporary outages of their services,

no injuries to people

Table 8.3 presents the threshold values prescribed for torrential phenomena by the Provincial Resol-

ution of the Province of Trento, which not only considers the physical quantities of velocity and

depth of the flow, but also the thickness of depositions and depth of scouring.

If, in applying Table 8.3, there are various scenarios with different hazards and equal probability,

then the least favourable scenario is considered.

Table 8.3 – Definition of threshold values as prescribed in the Province of Trento (Italy).


The Intensity can be categorised subjectively according to Levels of Damage


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Or more objectively according to the values of the dynamical parameters involved

Intensity of the

torrential phe-

nomenon

Depth of the flow

h [m]

Velocity of flow

outside the water-

course

u [m/s]

Thickness of de-

position outside

the watercourse

M [m]

Depth of scouring

d[m]

High h > 1 or u > 1 or M > 1 d > 2

Medium 0.5 < h ≤ 1 or 0.5 <u ≤1 or 0.5 < M ≤ 1 0.5 < d < 2

Low h ≤ 0.5 or u ≤ 0.5 or M ≤ 0.5 d < 0.5

8.1.3 Probability thresholds

Linked to the intensity threshold, the probability threshold indicates the probability of occurrence of

an event. The probability of a certain event occurring is evaluated on the basis of a time series of

observations.

The probability p[h>hr] that the intensity h of a certain event exceeds the threshold value hr can be

expressed in terms of the return period Tr of the event, in other words, the statistical-probabilistic

interval, expressed in years, that passes between two subsequent events with the same characterist-

ics. This can be expressed as:

The return periods are usually defined in a scale which distinguishes three classes corresponding to

decreasing probability of occurrence as the Tr increases (Table 8.4). In the case of fluvial and tor-

rential phenomena, reference return periods can be Tr=30, Tr=100, and Tr=200.

With relation to ordinary sediment transport, the return periods of the probability of occurrence gen-

erally coincide approximately well with the return periods of the rainfall events associated to the

more dangerous events. This method is acceptable unless there are sufficient historical data of dis-

charges to evaluate specifically the probability of occurrence for the discharges.

In the case of debris flows and mudflows, the rainfall statistics do not coincide with the flow statist-

ics. This is because under most circumstances, the debris flow or mudflow also depends on the level

of saturation of the terrain; in other words, they depend on the statistics of the antecedent rainfall as

well as the one that triggers the flow. It is convenient, however, to take the statistics of the rainfall

as reference while considering the terrain completely saturated (as was explained in Chapter 5).

Table 8.4 – Probability thresholds and the corresponding return periods as designated by the Province of Trento, 2006.

From P.A.T. DGP 2759 (22/12/2006)


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100


Table 8.5 – Colours and filles to be assigned to each hazard class on the Hazard Map.

Hazard Symbol Fill

Ordinary classes high H4 red

medium H3 blue

low H2 yellow

negligible H1 white

Extraordinary classesresidual HR

potential HP grey

Figure 8.3 – Example of Hazard Map that can be drafted with the methods proposed in these Guidelines.

8.1.5 Final Assessments

The Hazard Map resulting from the intensities and probabilities of occurrence must undergo some

considerations and assessments before the final Hazard Map is drafted. The Hazard Map furnishes

important indications for the urban and rural planning of an area. For this reason it cannot be limited

to those areas that have been subject to hydraulic analyses. In fact, it will have to furnish an exten-

ded representation of the hazard even to those areas of the alluvial fan that are not characterised by

index quantities. For these areas, an evaluation should be made of whether a hazard classification

can be applied according to the ordinary hazard classes. Where this is not possible, reference is

made to the extraordinary class of residual hazard, HR.


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101

Table 8.5 – Colours and filles to be assigned to each hazard class on the Hazard Map.

Hazard Symbol Fill

Ordinary classes high H4 red

medium H3 blue

low H2 yellow

negligible H1 white

Extraordinary classesresidual HR

potential HP grey

Figure 8.3 – Example of Hazard Map that can be drafted with the methods proposed in these Guidelines.

8.1.5 Final Assessments

The Hazard Map resulting from the intensities and probabilities of occurrence must undergo some

considerations and assessments before the final Hazard Map is drafted. The Hazard Map furnishes

important indications for the urban and rural planning of an area. For this reason it cannot be limited

to those areas that have been subject to hydraulic analyses. In fact, it will have to furnish an exten-

ded representation of the hazard even to those areas of the alluvial fan that are not characterised by

index quantities. For these areas, an evaluation should be made of whether a hazard classification

can be applied according to the ordinary hazard classes. Where this is not possible, reference is

made to the extraordinary class of residual hazard, HR.



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Thank you for your attention

Read the Guidelines and the Papers for details


Rigon et Al.


104

Bibliografia

•Beven, K J and Kirkby, M J. 1979, A physically based variable contributing area model of basin hydrology Hydrol. Sci. Bull., 24(1),43-69

•Beven, K, Rainfall-runoff modelling: the primer, Wiley, 2001

•Borga, M., G. Dalla Fontana, F. Cazorzi, Analysis of topographic and climatic control on rainfall-triggered shallow landsliding using a quasi-dynamic wetness index, Jour. Hydrol., 268, 56-71, 2002

•D’Odorico, P. and R. Rigon, Hillslope and channels contribution to the hydrologic response, Water Resour Res, 39(5) , 1-9, 2003

•Lanni, C.; McDonnell, J. J.; Rigon, R., On the relative role of upslope and downslope topography for describing water flow path and storage dynamics: a theoretical analysis, Hydrological Processes Volume: 25 Issue: 25 Pages: 3909-3923, DEC 15 2011, DOI: 10.1002/hyp.8263

•Lanni C., J. McDonnell JJ, Hopp L., Rigon R., "Simulated effect of soil depth and bedrock topography on near-surface hydrologic response and slope stability" in EARTH SURFACE PROCESSES AND LANDFORMS, v. 2012, (In press). - URL: http://onlinelibrary.wiley.com/doi/10.1002/esp.3267/abstract . - DOI: 10.1002/esp.3267

•Lanni C., Borga M., Rigon R., and Tarolli P., Modelling catchment-scale shallow landslide occurrence by means of a subsurface flow path connectivity index, Hydrol. Earth Syst. Sci. Discuss., 9, 4101-4134, www.hydrol-earth-syst-sci- discuss.net/9/4101/2012/ doi:10.5194/hessd-9-4101-2012, (in press at HESS)


http://onlinelibrary.wiley.com/doi/10.1002/esp.3267/abstract

http://onlinelibrary.wiley.com/doi/10.1002/esp.3267/abstract

http://www.hydrol-earth-syst-sci-

http://www.hydrol-earth-syst-sci-

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Bibliografia•Montgomery, DR and Dietrich, WE (1994), A physically based model for the topographic control on shallow landsliding , Water Resources Research, Vol. 30, no. 4, pp. 1153-1172. 1994.

•R. Rigon - Basic Notations, Un Real Books di Idrologia, DICA, Università di Trento, 2009

•Rinaldo A., G. K. Vogel, R., Rigon and I. Rodriguez-Iturbe, Can one gauge the shape of a basin?, Water Resources Research, (31)4, 1119-1127, 1995

•Sheidl, C and Rickenmann, D., (2009) Empirical prediction of debris-flow mobility and deposition on fans, Earth Surface Processes and Landforms, Volume 35, Issue 2, pages 157–173, February 2010


http://onlinelibrary.wiley.com/doi/10.1002/esp.v35:2/issuetoc

http://onlinelibrary.wiley.com/doi/10.1002/esp.v35:2/issuetoc

End of Appendix


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