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About the Guidelines for Hazard MappingRiccardo Rigon, Silvia Franceschi, Giuseppina Monacelli, Giuseppe Formetta
Segan
tin
i -
Mez
zogio
rno s
ull
e A
lpi
Danube FloodRisk Project, Trento, September 26, 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
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Low
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Riccardo Rigon
Danube Flood Risk Conference - Trento 3-4 October 2011
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Preliminary Analisys
Low
Monday, October 1, 12
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Danube Flood Risk Conference - Trento 3-4 October 2011
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Preliminary Analisys
Potential Risk
High Low
In the average
Low
Monday, October 1, 12
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Danube Flood Risk Conference - Trento 3-4 October 2011
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Preliminary Analisys
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
Hydrological analysis
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
Hydrological 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
Preliminary Analysis
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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Preliminary Analysis
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
Basin Classification
Courtesy of Hydrologis
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Wor
ldW
ind4
JGra
ss -
Cismon - Canali
Basin Classification
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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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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.
Can be made a little more specific with a little of field survey - Case Cismon
Geological Analysis
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Can be made a little more specific with a little of field survey - Case Cismon
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
Can be made a little more specific with a little of field survey - Case Cismon
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.
Geological Analysisin the field
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Geological Analysisin the field
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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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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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Geological surveygeophysics - rio Corda
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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.
Geological surveygeophysics - rio Corda
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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.
Geological surveygeophysics - rio Corda
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Geological surveygeophysics - rio Corda
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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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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.
Geological SurveyGeomechanics - rio Corda
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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.
Geological SurveyGeomechanics - rio Corda
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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.
Geological SurveyGeomechanics - rio Corda
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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.
Geological SurveyGeomechanics - rio Corda
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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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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
Subsurface water flowmodel
Rainfall-Runoff Modeling
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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 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
Sediment availability
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and obtain maps like this one
Sediment availability
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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
⇥
Sediment availability
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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
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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
Sediment availableCismon
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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.
Sediment availableCismon
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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
Sediment availableCismon
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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.
Sediment availableCismon
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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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Rainfall-Runoff Analysis
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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Rainfall-Runoff Analysis
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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Hydrological Analysisdo it the PeakFlow way!
•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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Hydrological AnalysisRescaled distances (Rinaldo et al., 1995)
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Histogram of areas that affects overland flow, assuming just 40% of area saturated.
Hydrological AnalysisRescaled distances (Rinaldo et al., 1995)
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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)
Hydrological Analysisdo it the PeakFlow way!
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Hydrological Analysisdo it the PeakFlow way!
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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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Squeeze it in three colors
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).
Squeeze it in three colors
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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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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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.
Squeeze it in three colors
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SentieriLA RIVISTA DELLA SEZIONE TRENTINODELL’ISTITUTO NAZIONALE DI URBANISTICAIssn: 2036-3109Urbani
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Monday, October 1, 12
Thank you for your attention
Read the Guidelines and the Papers for details
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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 sta- bility" 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)
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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
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End of Appendix
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