Database and Model for Dynamic scenario ... - CRISMA project

Database and Model for Dynamic scenario assessment V1

ADAI: Miguel Almeida, Valeria Reva, Domingos Xavier Viegas AMRA: Alexander Garcia-Aristizabal, Maria Polese, Giulio Zuccaro AEE: Agnes Cabal, Christophe Coulet, Armonie Cossalter FMI: Karoliina Pilli-Sihvola VTT: Liisa Poussa, Riitta Molarius

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The research leading to these results has received funding from the European Community's Seventh Framework Programme FP7/2007-2013 under grant agreement no. 284552 "CRISMA“

42.2

Deliverable No. Subproject No.

4

Work package No.

42

Models for MultiSectorial Consequences Cascade Effects on Work package Title Crisis-Dependent Space-Time Scales ADAI: Miguel Almeida, Valeria Reva, Domingos Xavier Viegas AMRA: Alexander Garcia-Aristizabal, Maria Polese, Giulio Zuccaro AEE: Agnes Cabal (AEE), Christophe Coulet (AEE), Armonie Cossalter (AEE) FMI: Karoliina Pilli-Sihvola VTT: Liisa Poussa, Riitta Molarius F Database and Model for Dynamic scenario assessment V1 PU

Subproject Title

Authors

Status (F = Final; D = Draft) File Name Dissemination level (PU = Public; RE = Restricted; CO = Confidential)

Contact

[email protected] [email protected]

Project Keywords Deliverable leader

Contractual Delivery date to the EC Actual Delivery date to the EC

www.crismaproject.eu

Name:

Miguel Almeida, Valeria Reva

Partner:

ADAI

Contact: [email protected], [email protected] 31.10.2013 31.10.2013

http://www.crismaproject.eu

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Disclaimer The content of the publication herein is the sole responsibility of the publishers and it does not necessarily represent the views expressed by the European Commission or its services. While the information contained in the documents is believed to be accurate, the authors(s) or any other participant in the CRISMA consortium make no warranty of any kind with regard to this material including, but not limited to the implied warranties of merchantability and fitness for a particular purpose. Neither the CRISMA Consortium nor any of its members, their officers, employees or agents shall be responsible or liable in negligence or otherwise howsoever in respect of any inaccuracy or omission herein. Without derogating from the generality of the foregoing neither the CRISMA Consortium nor any of its members, their officers, employees or agents shall be liable for any direct or indirect or consequential loss or damage caused by or arising from any information advice or inaccuracy or omission herein.


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Table of Contents TABLE OF CONTENTS ................................................................................................................ III LIST OF FIGURES ........................................................................................................................ IV LIST OF TABLES .......................................................................................................................... VI GLOSSARY OF TERMS .............................................................................................................. VII ACRONYMS ................................................................................................................................ VIII EXECUTIVE SUMMARY ............................................................................................................... IX 1.

INTRODUCTION ................................................................................................................... 1

2.

DATABASE OF CASCADE EVENT CHAINS ....................................................................... 2 2.1. Methodology to define the possible scenarios of cascading effects............................... 2 2.2. Description of cascade event chain diagrams ............................................................... 4 2.2.1. Earthquake cascade event chain....................................................................... 6 2.2.2. Flood cascade event chain .............................................................................. 11 2.2.3. Forest fire cascade event chain ....................................................................... 16 2.2.4. Extreme weather cascade event chain ............................................................ 18 2.2.5. Cascade event chain for release of chemical substance ................................. 22 2.3. Database description .................................................................................................. 24

3.

PRELIMINARY PROTOTYPE VERSION ............................................................................ 28 3.1. Database management system for dynamic scenario assessment ............................. 28 3.2. Example of implementation of the concept model for dynamic scenario assessment due to cascade event .................................................................................................. 30 3.2.1. Assessing the direct effects of the first event (Earthquake 1)........................... 33 3.2.2. Assessing possible cascade effects: Triggered landslide ................................ 34 3.2.3. Assessing the effects of a second earthquake occurring at time T2................. 36 3.2.4. Final remarks .................................................................................................. 38 3.3. Implementation in pilot cases – future steps ............................................................... 39 3.3.1. Selection of event chains important in the scope of reference scenario and probabilistic models that permit to quantify the probability of the event chains. 39 3.3.2. Integration of socio-economic and environmental data for vulnerability assessment ..................................................................................................... 40

4.

CONCLUSIONS .................................................................................................................. 42

5.

REFERENCES .................................................................................................................... 43

APPENDIX (A) AVAILABLE INFORMATION CONCERNING PROBABILISTIC MODELS FOR RELEASE OF CHEMICAL SUBSTANCES ......................................................................... 44


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List of Figures Figure 1: Scenario structuring following a “Forward logic” approach: (a) definition of main triggering events; (b) for each triggering event identified, the sequence of triggered events is defined (after Garcia-Aristizabal et al., 2013). ................................................................................. 3 Figure 2: Structure following a “Backward logic”: after the definition of the outcome of interest (i.e. the effect), the model is built backwards exploring the most likely paths towards the initiating events (after Garcia-Aristizabal et al., 2013)...................................................................... 3 Figure 3: Diagram of cascade event chains identified for the occurrence of an earthquake............. 7 Figure 4: Diagram of earthquake cascade event chain with decision nodes incorporated. ............ 10 Figure 5: Diagram of flood cascade event chain............................................................................ 12 Figure 6: Diagram of flood cascade event chain with decision nodes incorporated ....................... 15 Figure 7: Diagram of forest fire cascade event chain..................................................................... 16 Figure 8: Diagram of forest fire cascade event chain with decision nodes incorporated. ............... 18 Figure 9: Diagram of extreme weather cascade event chain. ........................................................ 19 Figure 10: Diagram of extreme weather cascade event chain with decision nodes incorporated... 22 Figure 11: Diagram of cascade event chain for release of chemical substance............................. 23 Figure 12: Diagram of cascade event chain for release of chemical substance with decision nodes incorporated. ...................................................................................................................... 24 Figure 13: Entity – Relationship model of event chain database. ................................................. 25 Figure 14: Table TB_EventChain representing the interrelation between events/damage nodes. . 26 Figure 15: Table TB_DN that represents decision nodes incorporated into sequence event/damage event/damage. .................................................................................................. 26 Figure 16: Table TB_Eventchain_DN that links decision nodes and corresponding sequences event/damage event/damage. .................................................................................................. 26 Figure 17: Table TB_TM with transition matrix data. ..................................................................... 27 Figure 18: Database management system (a). ............................................................................. 28 Figure 19: Database management system (b). ............................................................................. 28 Figure 20: Database management system (c)............................................................................... 29 Figure 21: Database management system (d). ............................................................................. 29 Figure 22: Database management system (e). ............................................................................. 30 Figure 23: Scenarios of cascade effects considered in quantitative example of implementation of the concept model for dynamic scenario assessment due to cascade events. .......................... 30 Figure 24: Definition of the virtual study area for the illustrative example: (a) DEM of the area; (b) footprints of the exposed elements (buildings) and calculation grid. Topography is overlaid in false color; (c) Detail of the footprints of the exposed elements in the virtual area and calculation grid. ............................................................................................................................. 31


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Figure 25: Simulated peak ground acceleration (pga) for the (a) Earthquake 1 and (b) Earthquake 2 events. .................................................................................................................... 32 Figure 26: Logic for the damage assessment considering the cascading effects within the CRISMA concept model. The triggering event is an event happening at a given time that is likely to produce a chain of adverse events. The direct effects of the triggering event (assessed e.g., using the CRISMA platform), are assessed in order to compute the direct consequences. Using the information from the database of cascading effects and the respective transition matrices (TM), the expected consequences of the chains of events can be quantified (Figure from D42.1 of Garcia-Aristizabal et al., 2013). ................................................................................................. 33 Figure 27: Assessment of the direct effects (in terms of damage probability) after the occurrence of the first earthquake (damage state: collapse)............................................................................ 34 Figure 28: Examples of different long-term scenarios of landslides simulated, with assigned return periods of (a) 50, (b) 100, (c) 200, and (d) 400 years. ......................................................... 35 Figure 29: Assessment of the effects (in terms of damage probability) associated with the potential triggering of landslides after the occurrence of the first earthquake (damage state: collapse). Note that this map present just the values associated with the landslides, and have not been yet combined with the direct effects of the earthquake. .................................................. 36 Figure 30: Assessment of the direct effects (in terms of damage probability) after the occurrence of the second, more destructive earthquake (damage state: collapse). ......................................... 37 Figure 31: Assessment of the effects (in terms of damage probability) associated with the potential triggering of landslides after the occurrence of the second earthquake (damage state: collapse). Note that this map present just the values associated with the landslides. .................... 37 Figure 32: Representation of the updating procedure provided by the implementation of the dynamic scenario assessment of cascading effects. ..................................................................... 38 Figure 33: Comparison of the results (damage probabilities) obtained in a grid element randomly selected. ....................................................................................................................................... 39 Figure 34: Diagram of extreme weather cascade event chain with incorporated impacts on vulnerable systems, namely, casualties, damages to human health, structures or environment.... 41


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List of Tables Table 1: List of events considered within database of cascade event chains. ................................. 4 Table 2: Symbols used in diagrams of cascade event chains.......................................................... 5 Table 3: List of damages considered within database of cascade event chains. ............................. 6 Table 4: Description of chain blocks identified for possible cascade event chains after an earthquake. ..................................................................................................................................... 8 Table 5: Description of decision nodes (DN) considered within the cascade event chains for the earthquake case. ............................................................................................................................ 9 Table 6: Description of chain blocks identified for possible cascade event chains after a flood. ... 13 Table 7: Description of decision nodes (DN) considered within the cascade event chains for the flood case. .................................................................................................................................... 14 Table 8: Description of chain blocks identified for possible cascade event chains after a forest fire................................................................................................................................................. 17 Table 9: Description of decision nodes (DN) considered within the cascade event chains for the forest fire case. ............................................................................................................................. 17 Table 10: Description of chain blocks identified for possible cascade event chains for a case of extreme weather conditions. ......................................................................................................... 20 Table 11: Description of decision nodes (DN) considered within the cascade event chains for the extreme weather case. ............................................................................................................ 21 Table 12: Description of blocks of cascade event chain identified for possible cascade event chains after a release of chemical substances. ............................................................................. 23 Table 13: Description of decision nodes (DN) considered within the cascade event chains for the case of the release of chemical substances. ........................................................................... 24 Table 14: Existing probabilistic models for release of chemical substances. ................................. 44


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Glossary of terms Term Damage

Adverse event

Risk source

Event

Definition Definition 1 (context of socio-economic vulnerability, related with concept of impact): the amount of destruction or losses, either in health, financial, environmental functional and/or other terms as a consequence of an occurred hazard (Marzocchi at al. 2009, 2012) Definition 2 (context of structural damages): physical harm that impairs the value, usefulness, or normal function of something (Oxford Dictionaries, http://oxforddictionaries.com/definition/english/damage) Anything produced by a risk source in a certain area that can generate phenomena with potentially adverse consequences. The adverse event can be due to a risk source located inside or outside the site where the event takes place (Marzocchi at al. 2009). Element which alone or in combination has the intrinsic potential to give rise to risk (ISO/Guide 73:2009(en) Risk management — Vocabulary https://www.iso.org/obp/ui/#iso:std:iso:guide:73:ed-1:v1:en) Occurrence or change of a particular set of circumstances. An event can be one or more occurrences, and can have several causes. An event can sometimes be referred to as an “incident” or “accident”. (ISO/Guide 73:2009(en) Risk management — Vocabulary https://www.iso.org/obp/ui/#iso:std:iso:guide:73:ed-1:v1:en)


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Acronyms Abbreviation

Definition

ADAI

Associacao para o Desenvolvimento da Aerodinamica Industrial (Portugal) – CRISMA partner

AEE

Artelia Eau et Environnement (France) – CRISMA partner

AMRA

Analisi e Monitoraggio del Rischio Ambientale (Italy) – CRISMA partner

FMI

Finnish Meteorological Institute (Finland) – CRISMA partner

VTT

Teknologian Tutkimuskeskus VTT (Finland) – CRISMA partner


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Executive Summary This document has been produced by the consortium of the European Project FP7SECURITY-284552 CRISMA: Modelling crisis management for improved action and preparedness. This deliverable (D42.2) is strongly linked to deliverable D42.1 (GarciaAristizabal et al., 2013), focused on the concept model for the dynamic scenario assessment due to cascade effects, where possible strategies for the identification and structuring of cascading events scenarios and further development of database of cascade events were presented and extensively discussed. Applying the methodology that was presented in D42.1 (Garcia-Aristizabal et al., 2013) a number of cascading events scenarios was elaborated. In particular, considering the possible events that are significant for pilot applications in CRISMA, i.e. earthquakes, forest fires, floods, extreme weather conditions and release of chemical substance, the related cascading events chains were determined and described. In addition, the possible effect of mitigation measures was considered and included in suitably defined decision nodes. This document presents the database of cascade event scenarios and the transition matrices, defined as two key elements within the concept model presented in D42.1 (Garcia-Aristizabal et al., 2013). In order to exemplify the possible use of those databases and of the transition matrices in the framework of the concept model for dynamic scenario assessment, a detailed example is discussed. Moreover, a prototype version of application to integrate cascade events in a multi-risk assessment scheme has been developed and is also presented in this deliverable. The database and model described and exemplified in this deliverable will have to be integrated as a Federated Simulation Tool in CRISMA, and will serve as support for simulation of cascading events in a multi-risk framework.


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1. Introduction The work performed under the CRISMA Project to analyse the cascade effect as divided in three steps: 1) survey of the existing multi-risk assessment methods; 2) identification of possible adverse events chains; and 3) development of a concept model and tool of dynamic scenario due to cascade events. The first deliverable D42.1 ”Dynamic scenario concept models” (Garcia-Aristizabal et al., 2013), that is a report describing the concept model for dynamic scenario assessment due to cascade events, including the effects of time dependent mitigation actions, was finalized in august 2013 (Garcia-Aristizabal et al., 2013). The present deliverable D42.2 contains a first version of Database and Model for Dynamic scenario assessment, while D42.3 (Almeida et al., 2014) shall update those database and model and shall allow for integration in the CRISMA framework. This deliverable builds upon the concept model for dynamic scenario assessment that was proposed and thoroughly described in D42.1 (Garcia-Aristizabal et al., 2013) and elaborates based on those concepts presenting a database of cascading events scenarios and a prototype version of application to integrate cascade events in a multi-risk assessment scheme. Moreover, an example application of the implemented concept model for dynamic scenario assessment due to cascade event is discussed. In particular, chapter 2 presents, after a summary of the methodology to identify possible cascading effect scenario (proposed in Garcia-Aristizabal et al., 2013), the cascading events scenarios that were elaborated. Considering the possible events that are significant for pilot applications in CRISMA, i.e. earthquakes, forest fires, floods, extreme weather conditions and release of a chemical substance, the related cascading events chains were determined and described in sections 2.2.1 to 2.2.5. Next, the Access database that was built based on the identified cascading events scenario is described. The database contains records of all sequences of cascade events that have been developed, with associated decision nodes and transition matrices. Chapter 3 presents the main features of the prototype application to integrate cascade events in a multi-risk assessment scheme. The prototype was implemented using Visual Basic and with a dedicated user interface that provides functionalities to customize sequence of events and visualize data of transition matrix for each node of the chain of events. In addition, a detailed example illustrating the step by step implementation of the concept model for dynamic scenario assessment due to cascade event is discussed, making reference to the cases of (1) earthquake-triggered landslides and (2) aftershocks or triggered earthquakes occurring after a former seismic event (taking in account timedependent fragilities). Finally, an outline of future steps of the analysis to be performed in order to facilitate pilot applications and testing is proposed.


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2. Database of cascade event chains This chapter presents the cascading events scenarios that were developed and the resulting database that was built. In the next paragraph (section 2.1) the methodology to identify cascading events scenarios, that was elaborated in D42.1 (Garcia-Aristizabal et al., 2013) is briefly described, while sections 2.2 and 2.3 present, respectively, the elaborated scenarios and the database structure.

2.1. Methodology to define the possible scenarios of cascading effects To achieve the required complete set of scenarios, different strategies can be adopted. Given the complexity and diversity of scenarios that can be derived, especially for the diversity of test cases considered in CRISMA, a unique single approach could represent a limitation and could not ensure an exhaustive exploration of potential scenarios. Then, the selection of a specific approach for scenario identification may be a case-specific problem. We consider that a good start point can be found among one of the following “logical” approaches: Using “Forward logic” approaches, as for example, event-tree like structures; Using a forward logic strategy implies to start identifying the possible initiating (triggering) events (natural and non-natural). This kind of approach will follow a forward logic in the sense that for each initiating event (e.g. a flood or an earthquake) it will identify the possible outcomes (endpoints) following an eventtree-like structure (see Figure 1) Using “Backward logic” approaches, as for example, fault-tree like structures (see Figure 2); The backward logic strategy begins with and endpoint, outcome or result, and works backwards to find the most likely causes of the effect, following a faulttree-like structure. This approach starts considering the effects that have been selected for the analysis (i.e. the objective(s) of the risk analysis and the ‘metric’ identified). As with the forward logic analysis, in this case the nodes are uncertain or chance events and the structure commonly focus on identifying the most likely path from an endpoint back to its originating events. Apply both approaches, and overlay them to identify the most exhaustive set of scenarios (or highlight the most important ones). The strategy outlined in this section is based on the concept of adaptive hierarchical modelling. The idea is to iteratively use both, the forward logic and the backward logic approaches, and combine the results obtained in order to exhaustively identify all the relevant scenarios for the specific problem analysed.


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Figure 1: Scenario structuring following a “Forward logic” approach: (a) definition of main triggering events; (b) for each triggering event identified, the sequence of triggered events is defined (after Garcia-Aristizabal et al., 2013).

Figure 2: Structure following a “Backward logic”: after the definition of the outcome of interest (i.e. the effect), the model is built backwards exploring the most likely paths towards the initiating events (after Garcia-Aristizabal et al., 2013).


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2.2. Description of cascade event chain diagrams Adopting the methodology described in Garcia-Aristizabal et al. (2013) and synthetically resumed in section 2.1, and considering the possible events that are significant for pilots application in CRISMA, i.e. earthquakes, forest fires, floods, extreme weather conditions and release of a chemical substance, a number of cascading events scenarios were elaborated, as synthetically resumed in Table 1. Different symbols were used to present events managed and non-managed by CRISMA tool (Table 2). Extreme weather conditions and release of chemical substances suppose a variety of cases, as it is specified in Table 1. Only some of the listed incidents will be tested in CRISMA pilots. During the development of the event chain diagrams, the damages listed in Table 3 were considered, as leading to “activation” of certain risk source. It was noticed that the same damage-type has its own characteristics for a specific hazard, i.e., building damage caused by earthquakes is not the same as that caused by floods. To reflect such particularities, a table with the description of event chain blocks is also presented to support each diagram of the cascade event chain. Likewise, tables with the description of the decision nodes identified within the event chains are also provided. Some events/damages were defined as final elements of a chain (Table 2), however it is related with levels of cascade event chain to be considered by the user. Diagrams of the cascading event chains developed for seismic crisis, forest fire, flood, extreme weather conditions and release of chemical substances are presented in Figure 3 to Figure 12, with the respective description of event chain blocks and decision nodes presented in Table 4 to Table 13. Table 1: List of events considered within database of cascade event chains. Label

Diagram with detailed sub-chain for event when it is triggered by other events or damages

Events managed by CRISMA Flood

Figure 5: Diagram of flood cascade event chain

Earthquake

Figure 3: Diagram of cascade event chains identified for the occurrence of an earthquake

Forest fire

Figure 7: Diagram of forest fire cascade event chain

Release of chemical substance: Release of toxic gas plume / dust cloud Release of gas / liquid flammable substances Release of solid / liquid substances

Figure 11: Diagram of cascade event chain for release of chemical substance

Extreme weather conditions: Heat waves Cold waves Drought Strong winds Heavy rain Snow storm Lightning strike

Figure 9: Diagram of extreme weather cascade event chain


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Label

Diagram with detailed sub-chain for event when it is triggered by other events or damages

Events non-managed by CRISMA Landslide

Figure 3: Diagram of cascade event chains identified for the occurrence of an earthquake Figure 5: Diagram of flood cascade event chain

Disability of transport infrastructures Explosion

Figure 3. Diagram of cascade event chains identified for the occurrence of an earthquake Figure 9: Diagram of extreme weather cascade event chain Figure 11: Diagram of cascade event chain for release of chemical substance Figure 5: Diagram of flood cascade event chain

WUI / urban fire


Industrial fire


Long-term power supply interruption Water contamination Soil contamination

Figure 3. Diagram of cascade event chains identified for the occurrence of an earthquake Figure 11: Diagram of cascade event chain for release of chemical substance Figure 5: Diagram of flood cascade event chain

Tsunami

Figure 3. Diagram of cascade event chains identified for the occurrence of an earthquake

Smoke cloud


Collapse / leaning of trees

Figure 9: Diagram of extreme weather cascade event chain

Table 2: Symbols used in diagrams of cascade event chains. Symbol

Description Damage when defined as a final element of sub-chain, and further triggered effects are not considered. Damage when triggered by other damages or events. This symbol is used to designate the sub-chain already developed in diagram in terms of triggered events. Events managed by CRISMA triggered by other damages or events. This symbol is used to designate the sub-chain already developed in diagram in terms of triggered events. Events not managed by CRISMA when defined as a final element of sub-chain, and further triggered effects are not considered Events not managed by CRISMA when triggered by other damages or events. This symbol is used to designate the sub-chain already developed in diagram in terms of triggered events. Decision node with prevention actions Decision node with response actions


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Table 3: List of damages considered within database of cascade event chains. Damage Dam 1 - Damage to transport (road / rail) infrastructure Dam 2 - Building damage Dam 3 - Damage to gas (pipeline) network Dam 4 - Damage to electricity network Dam 5 - Damage to water (river) network Dam 6 - Damage to industrial facility Dam 7 - Damage to drinking water network Dam 8 - Damage to waste water network Dam 9 - Damage to telecommunication network Dam 10 - Damage to irrigation network Dam 11 - Damage to agriculture Dam 12 - Damage to structural protection (dam/dike)

2.2.1. Earthquake cascade event chain Earthquakes may produce a variety of triggered hazards creating complex chains of triggered events. A possible cascade event chain triggered by earthquakes is presented in Figure 3. As it can be observed, this cascade event chain links almost all events managed by the CRISMA tool, namely, forest fires, floods, and release of chemical substances. Detailed description of diagram blocks and decision nodes is given, respectively, in Table 4 and Table 5. Likewise, a diagram with the decision nodes considered is presented in Figure 4.


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Figure 3: Diagram of cascade event chains identified for the occurrence of an earthquake.


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Table 4: Description of chain blocks identified for possible cascade event chains after an earthquake. Block name Dam 1 – Damage to road/rail transport infrastructure Dam 2 – Building damage Dam 3 – Damage to gas (pipeline) network Dam 4 – Damage to electricity network

Dam 5 – Damage to water (river) network Dam 6 – Damage to industrial facilities Dam 7 – Damage to drinking water network Dam 8 – Damage to waste water network

Dam 12 – Damage to structural protection (dam/dike) Landslide Flood Disability of transport infrastructures Explosion WUI/ urban fire Forest fire Industrial fire Release of gas/ liquid flammable substances Long term power supply interruption Release of chemical substances

Water contamination Soil contamination Tsunami


Description The roads and rails infrastructures including bridges can be damaged or destroyed by the horizontal actions due to earthquake. Horizontal actions produced by the earthquake can damage or destroy the buildings Ground accelerations may cause pipelines failure with consequent leakage of gas by provoking possible fire ignitions All the structural elements for the transmission of electrical power (both overhead and underground power cables ) as well as power plants and electrical substations located near demand centers can be affected by the earthquake by causing possible blackouts River diversions may occur due to movements of the ground Industrial equipment and systems can suffer structural damage when hit by earthquakes, so that accidental events as fire, explosion and dispersion of toxic substances can take place. Ground accelerations may cause pipelines failure with consequent leakage of water in the soil Earthquake may cause significant damage to wastewater network (also including the pumping stations and the treatment plants) and as a result causes water and soil pollution as well as difficulties for residents of affected urban areas Both natural and artificial structures for the containment of river can be damaged or destroyed by the earthquake Due to earthquake, the ground can be overloaded by water. This can cause a landslide when the slope is important. Landslides as well as damages to dikes can provoke the overflow of water with submersion of the neighboring areas Partial or total collapse of buildings facing the roads/railways may cause disability to transport infrastructures Damage to gas network as well as to industrial facility that make use of inflammable material could initiate an explosion Damage to gas network could initiate an ignition Fire caused by explosions or short circuits that could affect the electricity network may spread to forest areas Industrial facilities that make use of inflammable material could initiate an ignition Damages to the stocks in industrial facilities as well as failure to the gas pipeline due to earthquake could generate the release of several kinds of flammable substances Severe damages to the power grid may cause a long term power supply interruption (people trapped in the lifts, surgery problems, etc.) Damages to the stocks in industrial facilities due to earthquake could generate the release of several kinds of dangerous/pollutant chemical substances When a pipe is broken, some intrusions (salinity, bacteria or other) can be observed in the water (both potable as non-potable) When a pipe is broken, some intrusions (salinity, bacteria or other) can be observed in the soil Sometimes the earthquake cause a fast deformation of the seafloor than it could happen that the overlying water is displaced vertically and a tsunamis can be generated

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Table 5: Description of decision nodes (DN) considered within the cascade event chains for the earthquake case. DN code

DN description

DNEQ1

Structural reinforcement

Prevention

DNEQ2

Adopting the seismic-resistant building code

Prevention

DNEQ3

Evacuation of people in pre-damaged structures

Response

Dam 3 – Damage to gas (pipeline) network Explosion

DNEQ4

Installation of firefighting equipment close to critical infrastructure

Prevention

Dam 3 – Damage to gas (pipeline) network Release of gas / liquid flammable substances

DNEQ5

Closing valves when overcoming a critical shacking threshold

Prevention

Dam 4 – Damage to electricity network Forest fire

DNFF5

Creation of fuel-breaks or firewalls close to critical elements of the Electric network (e.g., transformers)

Prevention

Dam 4 – Damage to electricity network Urban fire

DNEQ6

Installation of firefighting equipment close to critical elements of the electric network

Prevention

Earthquake Dam 4 – Damage to electricity network

DNEQ7

Interruption of energy supply when overcoming a critical shacking threshold

Prevention

Dam 4 – Damage to electricity network Long term power supply interruption

DNEQ8

Installation of back-up systems for electricity blackouts

Prevention

DNEQ9

Design proper river banks and/or check the maintenance status of existing ones

Prevention

DNEQ10

Reinforcement of critical facilities

Prevention

DNEQ11

Check stability of slopes

Prevention

DNEQ12

Building an effective drainage system

Prevention

Sub-chain identification

Earthquake Dam 2 – Building damage

Earthquake Dam 5 – Damage to water (river) network

DN type

Earthquake Dam 6 – Damage to industrial facility Earthquake Dam 12 – Damage to structural protection (dam/dike) Earthquake

Landslide


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Figure 4: Diagram of earthquake cascade event chain with decision nodes incorporated.


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2.2.2. Flood cascade event chain The kind of flooding events considered within the CRISMA Project is related to coastal flood events. However, the flood cascade events mentioned in Figure 5 and Figure 6, as well as in Table 6 and Table 7 can be applied to other types of flood events than the coastal floods.


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Figure 5: Diagram of flood cascade event chain.


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Table 6: Description of chain blocks identified for possible cascade event chains after a flood. Block name Dam 12 - Damage to structural protection (dike) Dam 1 - Damage to transport (road/rail) infrastructure Dam 2 - Building damage Dam 3 - Damage to gas (pipeline) network

Dam 4 - Damage to electricity network Dam 5 - Damage to water (river) network Dam 6 - Damage to industrial facility Dam 7 - Damage to drinking water network

Dam 8 - Damage to waste water network Dam 9 - Damage to telecommunication network Dam 10 - Damage to irrigation network Dam 11 - Damage to Agriculture Landslide Disability of transport infrastructure Explosion

Release of chemical substance WUI / urban fire Industrial fire Water contamination Soil contamination

Description The pressure forces applied on the dikes due to high water level or strength of waves can make them breach or collapse. The water level is higher than dikes, therefore, the dikes are overtopped and can breach. The roads or rails infrastructures as well as traffic signals can be destroyed due to high water velocities. The flood can spread to building areas and they can be flooded or even destroyed. Floods could generate scour around pipeline support and by consequence breaches in the pipe that can origin release of toxic gas plume, dust cloud or gas/liquid flammable substances. The vent holes can be flooded. The production or transformation posts can be flooded. These kinds of failures can totally or partially stop the service. The electricity distribution system (power lines) can be destroyed. High water discharges cause large river bed loads and sedimentations. These discharges can also destroy the banks. A flood could also force a closure of the industry and potentially some damages to the stocks or the machinery. The pipes can be flooded and intrusions (salinity, bacterium or other) can be observed in the drinking water network. Pumps can be destroyed due to the overload of water or just not working due to electricity failure. The transportation pipes can be flooded. The pumping stations can be destroyed by the overload of water or just not working due to electricity failure. These effects are followed by the spill of waste water outside the network. The cables which are put in the core of dikes could be cut when the dikes breach.

The high water velocities can damage the irrigation network infrastructure. Flooding of agricultural land could destroy plantings. In the case of marine flood, this could generate a salinization of soils. Due to flood, the ground can be overloaded by water. This can cause a landslide when the slope is important. The roads or rails can be flooded and thus impracticable. Flooding of industrial facility could generate electric shortcuts which could initiate an explosion. Damages to gas network or destruction of industrial stocks with inflammable material could initiate an explosion. Flooding of industrial facility and damages to the stocks could generate release of different kinds of chemical substances Flooding of buildings could generate electric shortcuts which could initiate a fire. Flooding of industrial facility could generate electric shortcuts which could initiate a fire. Intrusions (salinity, bacterium or other) can be observed in the water (both potable as non-potable) Intrusions (salinity, bacterium or other) can be observed in the soil


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Table 7: Description of decision nodes (DN) considered within the cascade event chains for the flood case. Sub-chain identification

DN code

DN description

DN type

DNFL1

Survey the dikes, Increase the level and/or strengthen the dikes

Prevention

DNFL2

Use sand bags to enforce the most fragile dikes

Response

DNFL3

Survey the infrastructure, Increase the level if possible and ensure a high level of hydraulic transparency

Prevention

Flood Dam 2 Building damage

DNFL4

Use sand bags or similar protection to avoid the water to enter the buildings

Response

Flood Dam 4 Damage to electricity network

DNFL5

Raising the height of production and transformation posts

Prevention

Flood Dam 6 Damage to industrial facility

DNFL6

Use sand bags or similar protection to avoid the water to enter in the most sensible place (stocks, machinery, …)

Response

DNFL7

Place the most important infrastructure on protected place (pumping station)

Prevention

DNFL8

Improve the drainage system of the territory to ensure a good removal of the water en minimize the duration of flood

Prevention

Flood Dam 12 Damage to structural protection (dam/dike) Flood Dam 1 Damage to transport (road / rail) infrastructure Flood

Disability of transport infrastructures

Flood Dam 7 Damage to drinking water network Flood Dam 8 Damage to waste water network Flood Dam 11 Damage to agriculture


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Figure 6: Diagram of flood cascade event chain with decision nodes incorporated


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2.2.3. Forest fire cascade event chain In the context of events managed by the CRISMA tool, fires/forest fires mainly occur related to explosions and extreme weather conditions (heat waves, droughts, extreme winds with consequent damage to the electricity network, and release of chemical substances). The main problems of a forest fire event are related to the smoke release and dispersion, and to the spread of the fire front causing a wildland urban interface (WUI), an urban or an industrial fire. In high concentrations, smoke can reduce the visibility hindering the use of certain facilities such as a road. Effects of intoxication by smoke can drive to casualties. The spread of the fire front can be direct (radiation, conduction or convection) or indirect (spot fires). The effects are normally related to destruction by burning. The main scenarios of cascade events triggered by forest fires are presented in Figure 7. Detailed description of the diagram blocks and the decision nodes is given in Table 8 and Table 9, respectively. Finally, a diagram with decision nodes incorporated is presented in Figure 8.

Figure 7: Diagram of forest fire cascade event chain.


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Table 8: Description of chain blocks identified for possible cascade event chains after a forest fire. Block name

Description

Smoke cloud

Large forest fires, WUI/urban fires and Industrial fires normally release smoke clouds with concentration and mass that can cause other adverse events such as intoxication or disability of transport infrastructures.


Interruption of transport communication due to smoke cloud that reduce visibility or due to fallen objects (trees, electricity pillows, etc.), flames and spotting (firebrand projection).

WUI/ urban fire

Forest or industrial fires can spread to WUI zone (the physical space where vegetation and structures coexist in a fire prone environment) and consequently to urban zone. On the other hand, a forest fire can pass directly to an urban zone by spotting (firebrand projection).

Industrial fire

Forest or WUI/urban fires can spread to industrial zone and cause fire on industrial facilities or storage materials.

Dam 2 - Building damage

Combustible building materials may be burned by the effect of the fire. Noncombustible materials may be thermal expanded leading to building damage or even collapse.

Dam 6 - Damage to industrial facilities

Combustible industrial facility materials may be burned by the effect of the fire. Noncombustible industrial facility materials may be thermal expanded leading to damage or even collapse.

Forest fire

WUI/urban or industrial fires can pass to forest fire directly by flame spreading or by spotting.

Table 9: Description of decision nodes (DN) considered within the cascade event chains for the forest fire case. Sub-chain identification Forest Fire

Smoke cloud

Forest Fire

WUI / Urban fire

WUI / Urban fire

DN description

DN type

DNFF1

Creation of fuel breaks

Prevention

DNFF2

Fire fight by terrestrial and aerial means

Response

WUI / Urban fire Dam 2 Building damage

DNFF3

Fuel management near the buildings and installations of fire fighting devices (sprinklers, fire extinguishers, etc.)

Prevention

Industrial Fire Dam 6 - Damage to industrial facility

DNFF4

Fire fight by indoor and outdoor means

Response

Industrial Fire

Industrial Fire

DN code

WUI / Urban fire

WUI / Urban fire Industrial Fire Forest Fire

Forest Fire Forest Fire

Disability of transport infrastructure

WUI / Urban fire Disability of transport infrastructure Forest Fire

Industrial Fire


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Figure 8: Diagram of forest fire cascade event chain with decision nodes incorporated.

2.2.4. Extreme weather cascade event chain Extreme weather conditions can occur under a variety of situations, generally related with a temperature or moisture boundary and instability in the atmosphere. Therefore, the development of the extreme weather cascade event chains begins with the specification of weather conditions considered within database of cascade event chains. Thus, the first block “EW – Extreme weather conditions” is a general block of initial event followed by seven blocks specifying the type of initial event, namely, “EW1 – Heat waves”, “EW2 – Cold waves”, “EW3 – Drought”, “EW4 – Strong winds”, “EW5 – Heavy rain”, “EW6 – Snow storm”, “EW7 – lightning strike”. Blocks of the diagram following the blocks mentioned above represent cascade events or damages.


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Figure 9: Diagram of extreme weather cascade event chain.


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Table 10: Description of chain blocks identified for possible cascade event chains for a case of extreme weather conditions. Block name

Description

EW1 - Heat waves EW2 - Cold waves EW3 - Drought EW4 - Strong winds EW5 - Heavy rain

Specific extreme weather conditions. Meteorological drought defined as precipitation's departure from normal over some period of time (Assessment of the Regional Impact of Droughts in Europe, p. 3)

EW6 - Snow storm EW7 - Lightning strike Forest fire

Heat waves and droughts cause drying of plants and trees, and sparking forest fires. Lightning strikes can start a forest fire by bringing the wood to its flash point.

Explosion

Under the condition of heat waves, overheating of chemical substances (or combustible materials) may lead to explosion.

Collapse / leaning of trees

Collapse / leaning of trees due to strong winds or snow accumulated on the tree crowns. It depends on the tree species, soil, and other characteristics.

Flood

Coastal flooding can be caused by strong winds blowing waves onto the land. Floods caused by heavy rains near rivers, lakes, basins and sea.


Disability of transport infrastructure due to falling trees, which cause blocking of transport infrastructures. Disability of transport network due to heavy snowfall accumulating on the streets.

Landslide

Due to heavy rain, the ground can be overloaded by water. This can cause a landslide when the slope is important.

Dam 1 - Damage to transport (road / rail) infrastructure

Cold waves cause damage to rail transport systems.

Dam 4 - Damage to electricity network

Strong winds can bring down power lines by damaging the poles. Damage to electricity network due to both collapsed and leaning trees which damage power lines causing power outages. Damage to electricity network due to snow accumulating on power lines, causing power outages. Lightning strikes can damage fuses, transformers and other electricity distribution systems.

Dam 7 - Damage to drinking water network

Prolonged cold waves cause freezing of water pipes. Damage to drinking water network due to power outages in water delivery plants.

Dam 9 - Damage to telecommunication network

Damage to telecommunication network due to power outages in mobile telephone base stations

Dam 11 - Damage to agriculture

Damage to crops due to drought

Dam 12 - Damage to structural protection (dam/dike)

The pressure forces applied on the dikes due to high water level or strength of waves can make them breach or collapse. The water level is higher than dikes, therefore, the dikes are overtopped and can breach.


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Table 11: Description of decision nodes (DN) considered within the cascade event chains for the extreme weather case. DN code

Sub-chain identification Dam 4 - Damage to electricity network Dam 7 - Damage to drinking water network

DN description

DN type

DNEW1

Repairing the electricity network

Response

DNEW2

Development of ground electricity network

Prevention

Collapse / leaning of trees Disability of transport infrastructures

DNEW3

Remove collapsed trees

Response

Snow storm Disability of transport infrastructures

DNEW4

Cleaning of streets of snow

Response

DNEW5

Use sand bags or similar protection to avoid the water to enter in the most sensible or fragile places (dam/dike, buildings, stocks, machinery, …)

Response

DNEW6

Improve the drainage system of the territory to ensure a good removal of the water

Prevention

DNEW7

Cooling of chemical containers with water

Response

Dam 4 - Damage to electricity network Dam 9 - Damage to telecommunication network Strong winds Dam 4 - Damage to electricity network Snow storm Dam 4 - Damage to electricity network Collapse / leaning trees Dam 4 Damage to electricity network Lightning strike Dam 4 - Damage to electricity network

Heavy rain Strong winds

Flood Flood

Heavy rain Dam 12 - Damage to structural protection (dam/dike) Heat waves

Explosion


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Figure 10: Diagram of extreme weather cascade event chain with decision nodes incorporated

2.2.5. Cascade event chain for release of chemical substance Release of chemical substances can occur under different ways and can be related with different types of chemical substances. Therefore, the first block “RCS – Release of chemical substance” of the diagram of cascade event chains for the release of chemical substances is a general block of initial event followed by three blocks specifying the type of initial event, namely, “RSC1 – Release of toxic gas plume / dust cloud”, “RSC2 – Release of gas / liquid flammable substances”, “RCS3 – Release of solid / liquid substances”. Blocks of the diagrams following the blocks mentioned above represent cascade events or damages.


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Figure 11: Diagram of cascade event chain for release of chemical substance. Table 12: Description of blocks of cascade event chain identified for possible cascade event chains after a release of chemical substances. Block name

Description

RSC - Release of chemical substance

Loss of containment due to any type of event. Chemical substance may be in gaseous, liquid or solid form.

RSC1 - Release of toxic gas plume/dust cloud

Release of specific chemical substance. Chemical substance releases in gaseous form or dust to the air forming gas plume/dust cloud. The dispersion of the plume/cloud depends on the meteorological circumstances and the physical properties of the released substance.

RSC2 - Release of gas / liquid flammable substances

Release of specific chemical substance. Flammable chemical substance releases in gaseous or liquid form. The released chemical ignites can cause fire (jet fire, pool fire) leading to forest fire, WUI/urban fire or industrial fire. In case of flammable gas release an explosion can occur.

RSC3 - Release of liquid / solid substance

Release of specific chemical substance. Chemical substance releases in liquid or solid form. Release causes soil contamination and/or water contamination depending on the release point and environment. Liquid chemical may evaporate from the chemical pool on the surface of the soil and form toxic or flammable gas cloud.

Water contamination

Chemical substance may dissolve, mix or react with water causing pollution of water. Contamination refers to the presence of harmful or toxic chemicals in water.

Soil contamination

Chemical substance may soak into the soil. Contamination refers to the presence of harmful or toxic chemicals in soil. Contaminated soil may cause ground water / water contamination.


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Table 13: Description of decision nodes (DN) considered within the cascade event chains for the case of the release of chemical substances. Sub-chain identification RCS1 - Release of toxic gas plume/dust cloud [Water contamination] or [Soil contamination]

DN code

DN description

DN type

DNRCS1

Block or reduce the release.

Response

RCS2 - Release of gas / liquid flammable substances [Forest fire] or [WUI / urban fire] or [Industrial fire] or [Explosion]

DNRCS2

Remove chemical substance with appropriate material (remove vapor / dust with fine water spray or absorb liquid in inert material (e.g. sand)). Collect solid/liquid substances into sealable containers.

Response

RCS3 - Release of liquid / solid substance [RCS1 - Release of toxic gas plume/dust cloud] or [RCS2 - Release of gas / liquid flammable substances] or [Water contamination] or [Soil contamination]

DNRCS3

Evacuation of people

Response

Figure 12: Diagram of cascade event chain for release of chemical substance with decision nodes incorporated.

2.3. Database description The Entity–Relationship model presented in Figure 13 provides a visual overview of the event chain database created using Microsoft Access and the relations between the tables with data. The database contains data from diagrams and tables previously presented in Section 2.2.


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Figure 13: Entity – Relationship model of event chain database.

Table TB_Event_Chain (Figure 14) comprises associated nodes (triggering event/damage and triggered event/damage) of event chains representing the interrelation between events/damages. The first record corresponds to the sequence earthquake damage to transport (road/rail) infrastructure of the earthquake cascade event chain; the second sequence corresponds to the sequence earthquake building damage and so on. Table TB_Event_Chain contains all the data records of diagrams describing chain of events for earthquake, forest fires, flood, extreme weather conditions and release of chemical substances. Each interlink between nodes has an identification code (column ID_Event_Chain), which is a primary key that uniquely identifies each record. It is used for table relationship in entity-relationship model. In column Type, a type of triggering event is specified. The type “CRISMA event” consists in the events that are directly covered (managed) by the CRISMA Project. Other events are of the type “event” and in the future can also be an integrating part of the CRISMA Platform. Column ID_TM contains identification codes of corresponding transition matrices that links table TB_Event_Chain and table TB_TM of transition matrices. Table TB_DN (Figure 15) comprises decision nodes integrated into the sequence event/damage event/damage. For example, decision node DNEQ1 (Figure 4, Table 5) is integrated into sequence earthquake building damage that is represented as DNEQ1 building damage. Column ID_DN contains identification code of earthquake decision node in accordance to the corresponding event chain diagram. Decision node DNEQ1 has identification code EQ001. Column Description contains explanation of the respective decision node; and, in column Type, the decision node type (prevention or response) is specified. Table TB_Eventchain_DN (Figure 16) aims at linking the decision nodes (Table TB_DN) and corresponding sequences event/damage event/damage of the event chains (Table TB_Event_Chain). This table is necessary as the relation between the other two tables is to or “n” to “n” because one decision node can be applied to more than one event/damage and one damage/event can be associated to more than one decision node. Columns of TB_Eventchain_DN contain the identification codes used to establish the relationship between abovementioned elements.


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Figure 14: Table TB_EventChain representing the interrelation between events/damage nodes.

Figure 15: Table TB_DN that represents decision nodes incorporated into sequence event/damage event/damage.

Figure 16: Table TB_Eventchain_DN that links decision nodes and corresponding sequences event/damage event/damage.


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Table TB_TM (Figure 17) contains the data of the transition matrices such as the intensity of the triggering event (column Triggering_Event_intensity), the intensity of the triggered event (column Triggered_Event_intensity), and probabilistic information that allows quantifying the specific interaction in consideration (column TM_Value). Figure 17 shows an example of data (non-realistic) of transition matrix for sequence earthquake landslide.

Figure 17: Table TB_TM with transition matrix data.


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3. Preliminary prototype version 3.1. Database management system for dynamic scenario assessment A preliminary version of application to integrate cascade events in a multi-risk assessment scheme has been developed in the context of the event chain diagrams previously described (Section 2.2), which consider possible cascading effects concerning a seismic crisis, a forest fire, a flood, extreme weather conditions and a release of chemical substances. Developed in Visual Basic, this application allows users to customize a chain of events and a number of levels after a given triggering event for posterior analyses of cumulated consequences due to cascading effects. The application starts with a menu that, after the initial click by the user, visualizes different “CRISMA events” that can be chosen as the initial triggering event (Figure 18).

Figure 18: Database management system (a).

Menus that appear after choosing the initial (triggering) “CRISMA event” ( earthquake as an example given in following figure) show possible triggered events/damages of the first, second and further levels of the cascade event chain in a maximum of 10 event/damages chain levels (Figure 19). The data presented in the menus are in accordance to the diagram of cascade event chain corresponding to chosen initial event. Clicking on the right mouse button, on a selected event/damage, it is possible to visualize the options Decision Nodes and Transition Matrix. In this application the activation of transition matrices and decision nodes data, correspondent to the link between two events/damages, is done after selection of the final event of the pair.

Figure 19: Database management system (b).

Clicking on the Decision Nodes option (Error! Reference source not found.) drives to a table with all the possible mitigation actions that may be applied to the link of the respective pair of events/damages selected. Types of decisions, i.e., prevention or response, are also indicated.


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Figure 20: Database management system (c).

Clicking on the Transition Matrix option (Figure 21) drives to the intensity of events landslide) considered within the selected sequence of events (in this case, earthquake and corresponding conditional probability for each pair of the intensities selected for the triggering and triggered events/damages. An example with fake data for the link earthquake->landslide is given on Figure 21.

Figure 21: Database management system (d).

Finally, the user visualizes a menu with the sequence of events/damages selected (Figure 22). The sequence of events/damages chosen is highlighted in blue, and all the possible choices keep visible allowing the User to return back in the definition of a new sequence.


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Figure 22: Database management system (e).

3.2. Example of implementation of the concept model for dynamic scenario assessment due to cascade event In this section, the practical implementation of the concept model for dynamic scenario assessment due to cascade event is exemplified. This simple example considers some hypothetical scenarios of cascade effects after the occurrence of an Earthquake in a generic area in which a set of exposed elements (buildings) are present. The scenarios considered for quantification are represented in Figure 23. The cases analyzed can be summarized as follows: the initial triggering event is an earthquake (Earthquake 1 in Figure 23). Among the other identified scenarios, two possible triggered events that can be considered are (1) earthquake-triggered landslides and (2) aftershocks or triggered earthquakes (Earthquake 2 in Figure 23) occurring after the former event.

Figure 23: Scenarios of cascade effects considered in quantitative example of implementation of the concept model for dynamic scenario assessment due to cascade events.

Note that in this example, the occurrence of two earthquakes is simulated at times T1 and T2. Time To represents the world state before the occurrence of the first event. To illustrate the practical implementation of the model, we have defined a virtual area and created


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synthetic data to run the model. The virtual study area is presented in Figure 24. The configuration of the virtual study area is represented by a hilly area in the Eastern part of the domain, as shown in Figure 24a. A virtual city is located at the SE of the hills, as shown in Figure 24b. Figure 24b shows also a grid which represents the discretization of the domain for the calculations of the effects of the adverse events. In practice, the obtained results are aggregated within each area defined by the grid. Figure 24c is a detailed view of the virtual city and the calculation grid. The virtual city is represented by a set of footprints of the buildings located in the area.

Figure 24: Definition of the virtual study area for the illustrative example: (a) DEM of the area; (b) footprints of the exposed elements (buildings) and calculation grid. Topography is overlaid in false color; (c) Detail of the footprints of the exposed elements in the virtual area and calculation grid.

Following the description of the concept model presented in D42.1 (Garcia-Aristizabal et al., 2013), when a given event happens (in this case the Earthquake 1 event), the predefined models in the CRISMA tool (working as “black boxes” into the systems) calculate and propagate spatially the intensities of the event into the area of interest. In the case of an earthquake, for example, it creates the “shake maps” showing the distribution of the intensity measure selected for the analyses (e.g., the acceleration of the ground motion). The simulated intensity parameter in this case is the peak ground acceleration (pga). Results for the Earthquake 1 and are shown in Figure 25a. This seismic event in this example is characterized by a shallow medium-size earthquake.


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Figure 25: Simulated peak ground acceleration (pga) for the (a) Earthquake 1 and (b) Earthquake 2 events.

The model also combines the fragility models and the databases of exposed elements in order to calculate the maps of the expected impacts (due to the direct effect of the first event). This concept is represented in Figure 26 (from D42.1 - Garcia-Aristizabal et al., 2013), where the direct consequences (damages) of a triggering event are represented along the vertical arrow running out of the “triggering event” box. In the worked example, it corresponds in Figure 23 to the “assessment of direct effects” at time T1, when the Earthquake 1 occurs.


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Figure 26: Logic for the damage assessment considering the cascading effects within the CRISMA concept model. The triggering event is an event happening at a given time that is likely to produce a chain of adverse events. The direct effects of the triggering event (assessed e.g., using the CRISMA platform), are assessed in order to compute the direct consequences. Using the information from the database of cascading effects and the respective transition matrices (TM), the expected consequences of the chains of events can be quantified (Figure from D42.1 of Garcia-Aristizabal et al., 2013).

3.2.1. Assessing the direct effects of the first event (Earthquake 1) The first action is then assessing the expected effects on the area of interest due to the action of the Earthquake 1 event. This can be assessed for example calculating the expected losses or damage probabilities. In this example, we present the results of the probability of reaching a given damage state (collapse of structures in this case), aggregated for each sub-area of the calculation grid (see Figure 24). The results of the damage probabilities within each grid element are shown in Figure 27. The damage state considered in this example is the collapse of the structures.


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Figure 27: Assessment of the direct effects (in terms of damage probability) after the occurrence of the first earthquake (damage state: collapse).

3.2.2. Assessing possible cascade effects: Triggered landslide After assessing the direct impacts after the occurrence of the Earthquake 1, at time T1 it is also possible to assess the possible impacts of possible cascade effects. In this example we have considered (1) the occurrence of landslides, and (2) the occurrence of new triggered earthquakes. Examples of simulated scenarios of landslide events in the virtual area are represented in Figure 28. For the case of triggered landslides, and after considering the information from the transition matrix relating the conditional probabilities of the triggered event given the intensity of the triggering event, a new set of damage probabilities associated with the potential occurrence of landslides can be calculated. The obtained results are presented in Figure 28. It is worth noting that the damage probabilities presented in Figure 28 represent just the damages associated with the triggered landslides. The combination of the direct expected damages and those from the triggered events are straightforward.


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Figure 28: Examples of different long-term scenarios of landslides simulated, with assigned return periods of (a) 50, (b) 100, (c) 200, and (d) 400 years.

The results, presented in Figure 27 and Figure 29, represent the assessment that a decision-maker could be able to perform at time T1 in order to assess the expected effects after the occurrence of a given event and the successive triggering effects. In the second step of the analysis we will simulate the occurrence of a second, bigger-size earthquake.


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Figure 29: Assessment of the effects (in terms of damage probability) associated with the potential triggering of landslides after the occurrence of the first earthquake (damage state: collapse). Note that this map present just the values associated with the landslides, and have not been yet combined with the direct effects of the earthquake.

3.2.3. Assessing the effects of a second earthquake occurring at time T2 The example follows with the occurrence of a second, bigger-size earthquake occurring at time T2 (see Figure 23). This event is assumed to be a more energetic one, and that has been triggered by the first event. This example allows us (1) to implement a new cycle of cascade effects, and (2) to consider the effects of the pre-damaged structures because the occurrence of the earthquake 1 (time-dependent vulnerabilities). The intensity distribution (in pga) for the Earthquake 2 event is presented in Figure 25b. As in the previous cases, at time T2, it is possible to assess the direct impact of the Earthquake 2, as well as the expected damages considering the cascade effects scenario represented by the triggered landslides. The damage probabilities associated with the occurrence of the Earthquake 2 are presented in Figure 8. Note that this bigger event has higher probabilities to cause damages in the study area. The results have not been aggregated yet with the damage probabilities of the previous events. Likewise, the damage probabilities considering the possibility of landslides triggered by the second earthquake can be calculated. The results are shown in Figure 31.


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Figure 30: Assessment of the direct effects (in terms of damage probability) after the occurrence of the second, more destructive earthquake (damage state: collapse).

Figure 31: Assessment of the effects (in terms of damage probability) associated with the potential triggering of landslides after the occurrence of the second earthquake (damage state: collapse). Note that this map present just the values associated with the landslides.


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3.2.4. Final remarks The sequence of damage probabilities presented from Figure 27 to Figure 31 represents an example of the updating procedure that the dynamic scenario assessment of cascading effects can provide. This process is summarized in Figure 32. Note the highlighted event times T1 and T2, and the assessment produced as direct effects of occurring events (red boxes in Figure 23 and Figure 32) and those associated with specific paths of a given scenario of cascade effects (in this case, earthquake-triggered landslides, blue boxes in Figure 23 and Figure 32). This step by step process allows us to perform a comparative analysis of the effects of events occurring at different times, as well as the potential effects of triggered sequences of events. Taking for example in consideration a given area element of the calculation grid, it is possible to analyze and compare the effects of the different events in that area. An example of the specific results in a randomly selected grid element is shown in Figure 33. The damage probabilities from the different events of the chain are summarized in the central box of the figure. Those values are calculated as the probability to have a building collapse within the grid element.

Figure 32: Representation of the updating procedure provided by the implementation of the dynamic scenario assessment of cascading effects.


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Figure 33: Comparison of the results (damage probabilities) obtained in a grid element randomly selected.

3.3. Implementation in pilot cases – future steps This section describes the concept model and tool of dynamic scenario due to cascade events, which are related to the integration and testing of the conceptual model and the prototype version in first evaluation round of the CRISMA Project. 3.3.1. Selection of event chains important in the scope of reference scenario and probabilistic models that permit to quantify the probability of the event chains Pilot cases suppose only few sequences within the scenarios presented in Section 2.1. Therefore, implementation of the prototype version starts with the selection of the event chains important within the reference scenario. For example, release of a chemical substance may be triggered by an earthquake, a flood, a forest /urban or an industrial fire or by extreme weather conditions. In all those cases the


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most probable consequence of the event is damage to industrial facility. The release of a chemical substance is usually in the far end of the cascading event chains reaching the final consequences. Only different types of fire and new chemical releases may be triggered by release of chemical substance. In CRISMA reference scenario C: accidental pollution, the released chemical substance is Bromine (Br2). Considering the chemical properties of the Bromine, the most likely event chain using the aforementioned RCSevent chain description is: RCS3-Release of liquid/solid substance RSC1-Release of toxic gas plume Water/soil contamination Water/soil contamination. A different situation takes place in CRISMA reference scenario A: Cross-Border Emergency, where a Snow storm is followed by (but not triggers) Cold waves. Each of these extreme weather conditions is represented by their own cascading event chain (Figure 9). Consecutive occurrence of these events (considered as initial events in cascade event chain for extreme weather condition) supposes overlapping of corresponding cascade event chains. The case of reference scenario A signs up the necessity to include, within a prototype of application which integrate cascade events in a multi-risk assessment scheme, a possibility of interaction between different (initial) events and corresponding cascading event chains. After selection of event chain, proper probabilistic models should be applied to assess event intensities and the effects (in terms of damage probability) associated to events within a chain under analysis. For example, available information concerning probabilistic models for release of chemical substances is presented in Appendix A. Different models are applied to different chemical cases due to specific characteristics of chemicals. 3.3.2. Integration of socio-economic and environmental data for vulnerability assessment The identification of event/damages that “activate” risk sources leading to increase of consequences is very important for compilation and estimation of damages (impacts) on vulnerable systems, namely, casualties, damages to human health, structures or environment, which are of a main interest for end-users (rescue services) (Figure 34). The integration of socio-economic and environmental data for vulnerability assessment in accordance to identified and described in deliverable D41.1 ( existing hazard and vulnerability/losses models.


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Figure 34: Diagram of extreme weather cascade event chain with incorporated impacts on vulnerable systems, namely, casualties, damages to human health, structures or environment.


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4. Conclusions This document contains the detailed information concerning two key elements of a concept model, namely, (i) the database of cascade event scenarios and (ii) the transition matrix, whose development has particular importance for development of the prototype version of application to integrate cascade events in a multi-risk assessment scheme. A preliminary version of application was designed to give a broad perspective concerning possible cascading effects for a set of initial events such as earthquake, forest fire, flood, extreme weather conditions and release of chemical substances. In the development of diagrams of cascade event chains, particular attention was given to the identification of damages that constitute risk sources and lead to risk amplification and consequent drastic increase of impacts, such as casualties, damages to human health, structures or environment. An example of implementation of the conceptual model for dynamic scenario assessment due to cascade events provided a detailed description of step by step process that allows performing a comparative analysis of the effects of events occurring at different times, as well as the potential effects of triggered sequences of events.


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5. References Almeida, M., Ribeiro, L.M., Viegas, D.X., Garcia-Aristizabal, A., Zuccaro, G., Polese, M., Nardone, S., Marcolini, M., Cabal, A., Grisel, M., Coulet, C., Pilli-Sihvola, K., 2014. Database and Model for Dynamic scenario assessment V2. Deliverable D42.3 of the European Integrated Project CRISMA, FP7-SECURITY- 284552. Garcia-Aristizabal, A., Polese, M., Zuccaro, G., Almeida, M., Reva, V., Viegas,D. X., Rosqvist, T., Porthin, M., 2013. Dynamic scenario concept models. Deliverable D42.1 of the European Integrated Project CRISMA, FP7-SECURITY- 284552. Marzocchi, W., Mastellone, M.L., Ruocco A.Di., Novelli, P., Romeo, E. & Gasparini, P. 2009. Principles of multi-risk assessment. Interaction amongst natural and man-induced risks. Project Report, FP6 SSA Project: Contract No. 511264. Marzocchi, W., Garcia-Aristizabal, A., Gasparini, P., Mastellone, M.L. & Ruocco, A.D. 2012. Basic priciples of multi-risk assessment: a case study in Italy, Nat Hazards DOI 10.1007/s11069-0120092-x. Zuccaro, G., Cacace, F., Spence, R.J.S. & Baxter, P.J. 2008. Impact of explosive eruption scenarios at Vesuvius. J Volcanol. Geotherm. Res., No.178, pp. 416-453. ISO/Guide 73:2009(en) Risk management — Vocabulary. https://www.iso.org/obp/ui/#iso:std:iso:guide:73:ed-1:v1:en


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APPENDIX (A) Available information concerning probabilistic models for release of chemical substances Table 14: Existing probabilistic models for release of chemical substances. Model name

Description

Owner

Availability

Possible limitations

BREEZE AERMOB

Air quality modeling system used to support both regulatory and nonregulatory modeling requirements worldwide. Software program is designed to predict the potential toxic, fire, and explosion impacts of chemical releases. Also meteorological, terrain and GIS data services available. The program ESCAPE (Expert System for Consequence Analysis using a PErsonal computer) evaluates the releases, source terms and atmospheric dispersion of hazardous materials. The model is applicable to both continuous and instantaneous releases of toxic and flammable gases into the atmosphere. ESCAPE can be utilized in release cases which are a consequence of a sudden rupture of a container or the rupture of a pipe or container wall. The program can also be used for estimating dosages and blast wave overpressures, and the effects resulting from a BLEVE explosion. The program is applicable both to the heavier-than-air and passively-dispersing (dispersion due to atmospheric turbulence) gas and aerosol clouds. Industry hazard analysis software tool to analyze situations which present hazards to life, property and the environment, and to quantify their severity. Hazard analysis of these scenarios: discharge and dispersion models, including DNV's proprietary Unified Dispersion Model (UDM); flammable models, including resulting radiation effects, for jet fires, pool fires and fireballs; explosion models, to calculate overpressure and impulse effects. Available models include the Baker Strehlow, TNO Multi-Energy and TNT explosion models, models for the toxic hazards of a release including indoor toxic dose calculations.

Trinity Consultants

commercial

Not mentioned.

Finnish Meteorological Institute

Probably commercial. The model is utilized by FMI, many Finnish public authorities and many Finnish inspection and rescue operations.

ESCAPE-model is not applicable to the estimation of the atmospheric dispersion of pollutants emitted from typical fires in warehouses and chemical stores. Terrain effects are not considered, only in their effect on the atmospheric conditions through the surface roughness parameter. The model is not suitable for transient releases.

DNV

commercial

Not mentioned.

ESCAPE

Phast


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Model name

Description

Owner

Availability


ALOHA

ALOHA (Areal Locations of Hazardous Atmospheres) is a program designed to model chemical releases for emergency responders and planners. It can estimate how a toxic cloud might disperse after a chemical release and also features several fires and explosions scenarios. The program generates a variety of scenario-specific outputs, including threat zone plots, threats at specific locations, and source strength graphs (also threat zones on MARPLOT maps)

EPA (Environmental Protection Agency)

free

ALOHA doesn't account for some effects: very low wind speeds; very stable atmospheric conditions; byproducts from fires, explosions, or chemical reactions; particulates; chemical mixtures; wind shifts and terrain steering effects; terrain; hazardous fragments.

Rijkswaterstaat, part of the Dutch Ministry of Infrastructure and the Environment

The inquiry form on this website freely available.

DNV

commercial

In some specific situations, extra attention must be paid to the appropriate application: special situations with regard to sources of ignition, situations with complex nodes, etc., RBM II is suitable for making a rough estimations. (Notice: The text has been translated from Dutch into English by google.) Not mentioned.

RBM II

Safeti-NL

ALOHA allows you to model many release scenarios: toxic gas clouds, BLEVEs, jet fires, vapor cloud explosions, and pool fires. RBM II is a program that calculates the risks of transporting dangerous substances. Input data: population data, accident frequencies and numbers of transports hazardous materials. The program calculates risks for different transport type: road, rail and inland waterway. (Notice: The text has been translated from Dutch into English by google.)

Industry standard method for carrying out QRA of onshore process, chemical and petrochemical facilities. Safeti analyses complex consequences from accident scenarios, taking account of local population, land usage and weather conditions, to quantify the risks associated with the release of hazardous chemicals.


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Model name

Description

Owner

Availability


Shepherd

Shepherd desktop incorporates a number of tools to provide rapid consequence assessment and risk ranking. FRED (Fire, Release, Explosion and Dispersion) is used to predict the consequences of the accidental or intended release of chemical products from process, storage, transport, or distribution operations. SCOPE (Shell Code for Overpressure Prediction in gas Explosions) predicts the likely overpressure explosion, generated when a gas cloud ignites in a congested region. QRA takes multiple accident scenarios with multiple equipment into account and quantifies the total risk it has to human life. The calculated risks are expressed in terms of individual- and societal Risks. Input data: population distribution, weather statistics and failure frequencies of equipment.

Shell Global Solutions

commercial.

Not mentioned.

TNO

A license of RISKCURVES comes with an extensive database of over 2000 components based on DIPPR2010®, and the full consequence analyses software EFFECTS. The software itself is free to install and use as a viewer of already calculated projects. A valid license is needed for saving projects, doing calculations and having access to the extended chemical database.

Not mentioned.

RISKCURVES 9


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Model name

Description

Owner

Availability


EFFECTS 9

EFFECTS calculates and presents in tables, graphs and on geographical maps, the physical effects of any accident scenario with toxic and/or flammable chemicals. Different calculation models for release, evaporation, fire, explosion, dispersion and damage. Industry standard chemical database and GIS tool included.

TNO

Not mentioned.

ARIA Risk

ARIA Risk is a 3D software for the evaluation of industrial risks linked to the airborne dispersion of toxic releases (storage accidents, pipe failure, fire clouds). The software outputs maps of instantaneous or integrated concentration and deposition, it also enables the determination of safety limits and zones of threshold exposure and IDLH. ARIA Risk can be incorporated in an alert system. Input data: spatial scale, meteorological data and emission data. Fluid dynamics simulation in various applications. ANSYS Fluent software contains the broad physical modeling capabilities needed to model flow, turbulence, heat transfer, and reactions for industrial applications ranging from air flow over an aircraft wing to combustion in a furnace, from bubble columns to oil platforms, from blood flow to semiconductor manufacturing, and from clean room design to wastewater treatment plants. PHOENICS can analyze the spread of pollution and therefore ensure intelligent design to reduce emissions at the point of generation. It can also help evaluate discharge into the atmosphere, seas, lakes or rivers.

ARIA Technologies

Licensing is flexible: the software is free to install and use as a viewer of already calculated projects. A valid license is needed for saving projects, doing calculations and having access to the extended chemical database. Special conditions apply for governmental-, noncommercialand educational use. commercial

ANSYS Inc.

commercial

Not specially designed into hazard analysis.

CHAM

commercial

ANSYS Fluent

PHOENICS


Not mentioned. ARIA Risk CBRN also available. Rescube3D for realtime monitoring of dispersion of hazardous plumes.

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Model name

Description

Owner

Availability


TRACE 9.0, also TREACE Version 9.1

TRACE is an air dispersion model which evaluates the impact of hazardous chemical release into the atmosphere. TRACE™ incorporates an intelligent wizard feature that allows the user to easily and rapidly describe a scenario. Once processed, results can be viewed in tabular or graphical formats.

SAFER Systems

commercial

Not mentioned.

RCAP, EPA

free

Analyze the consequences of the release of a hazardous gas and the loss of operating assets for drinking water and wastewater systems

WHEAT

Events that can be modelled include: Fireball (BLEVE), Liquid pool fire, Jet fire, Stack flare, Flash fire, Toxic compound release, Pressure Vessel Burst (BLEVE), Vapour Cloud Explosion. The Water Health and Economic Analysis Tool (WHEAT) estimates consequences for both drinking water and wastewater utilities. Better respond to human-caused threats and natural disasters. WHEAT assists utility owners and operators in quantifying public health impacts, utility financial costs and regional economic impacts of an accidental or adverse event. WHEAT generates consequence results for both wastewater utilities and drinking water utilities based on two scenarios: 1) release of a hazardous gas and 2) loss of operating assets.


Database and Model for Dynamic scenario ... - CRISMA project

Database and Model for Dynamic scenario ... - CRISMA project

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