Report on Methodology

Ref. Ares(2020)86590 - 08/01/2020

www.improdiret.eu

Report on methodology

Project acronym: ImProDiReT Improving disaster risk reduction in Project full title: Transcarpathian region, Ukraine

Grant agreement no.: 783232 Responsible: Rafał Wróbel Joanna Kozioł, Karolina Tyrańska-Wizner, Contributors: Stella Shekhunova Document Reference: D1.9 Dissemination Level: PU Version: Draft Date: 24/12/19

Disclaimer: The content of this document represents the views of the author only and is his/her sole responsibility. The European Commission does not accept any responsibility for use that may be made of the information it contains.

This project is funded by the European Union Civil Protection, under grant agreement No 783232

D1.9 Report on methodology

2 | Page

D1.9 Report on methodology

3 | Page

D1.9 Report on methodology

History

Version Date Modification reason Modified by

0.1 Initial draft Rafał Wróbel

Final reviewed deliverable Izabella Grabowska-Lepczak

0.9 Quality check Edmunds Akitis

1.0 Final reviewed deliverable

4 | Page

D1.9 Report on methodology

5 | Page

D1.9 Report on methodology

Table of contents

History 2 Table of contents 3 List of tables 4 List of charts 5 List of abbreviations 6 Executive summary 7 Introduction 8 1 Risk identification 10 2 Risk analysis 11 3 Risk evaluation 15 4 Hierarchisation of risk and risk treatment 17 5 Tool used to source, collect process and visualize risk data 19 6 Conclusions 23 7 References 24 APPENDIX I 25

6 | Page

D1.9 Report on methodology

7 | Page

D1.9 Report on methodology

List of tables

Table 1: A qualitative and semi-quantitative description of probabilities 12 Table 2: A qualitative the classification of consequences. 13 Table 3: Classes of consequences with the points 13 Table 4: The weight value of the every consequences category 14 Table 5: Classes of consequences along with the quantitative range 14 Table 6: Risk matrix tool 15 Table 7: Risk acceptance criteria and risk level criteria 16 Table 8: Risk levels for identified 8 hazards for every districts of the Transcarpathian region 18

8 | Page

D1.9 Report on methodology

9 | Page

D1.9 Report on methodology

List of charts

Chart 1. Transcarpathia regions in the QGIS map background 20 Chart 2. Possibilities of QGIS software presenting different values of colors for each of regions of Transcarpathia 21 Chart 3. Flood risk map for each of the Transcarpathian regions. 21

10 | Page

D1.9 Report on methodology

11 | Page

D1.9 Report on methodology

List of abbreviations

C – Consequences D – Deliverable GIS – Geographic Information System IGS NASU – Institute of Geological Sciences National Academy of Sciences of Ukraine ImProDiReT – Improving disaster risk reduction in Transcarpathian region, Ukraine MSFS – The Main School of Fire Service (Poland) P – Probability R – Risk SIP – Spatial Information System QGIS – Quantum Geographic Information System WP 1 – Work package 1

12 | Page

D1.9 Report on methodology

13 | Page

D1.9 Report on methodology

Executive summary

Project ImProDiReT (Improving disaster risk reduction in Transcarpathian region, Ukraine) has clearly defined goals and methodology. They are defined in detail in the project proposal. The project falls under the policy area of prevention, and the priorities are focused on implementing multi-hazard assessments of risks, risk management capabilities assessments, risk management planning and risk awareness campaigns, with a particular focus on cross- border and regional dimensions (proposal, part B, page 3).

The implementation of the project will result in in a better informed population and government of the region. This will increase the resilience of the region and will lay the fundament for action to reduce the existing risks, leading to a lower risk of disasters and less impact of occurring disasters.

Among others, the specific objectives (expected outcomes) of the project are:

1. To make Hazard and Risk map of the region of all disaster types (Multi hazard/ risk assessment anticipating on climate change).

2. To conduct a Public awareness campaign based on the risk map of the region.

3. To develop a transparent risk evaluation and decision-making method* which includes all stakeholders, especially communities and inhabitants. The method described also addresses the necessary capacities to keep it sustainable.

It should be noted that deliverable D.1.9. is very closely related to other previously prepared deliverables prepared under WP 1.

Preparation of deliverable D.1.9 is intended to be developed for the needs of the project steering committee. It represents the approach of the project team to determine how they conduct their research in the Hazard and risk mapping (Work package 1) part of the project. Presentation of this methodology allows, first of all, to define the significance of individual deliverables (D.1.1.-D1.8.) provided under Work package 1 (WP 1) in the general approach to hazard and risk mapping.

14 | Page

D1.9 Report on methodology

15 | Page

D1.9 Report on methodology

Introduction

WP 1 Hazard and risk mapping has been divided into four main parts: 1.1. Identifying possible sources for hazard and risk data. 1.2. Hazard identification. 1.3. Consequences for the population in relation to hazard types. 1.4. Development of a risk mapping methodology.

Each of the indicated parts has been divided into a number of activities that are to ultimately result in the development of specific deliverables. The effect of research carried out under individual parts are/will be1: 1. In case Identifying possible sources for hazard and risk data and Hazard identification – deliverables: ● D.1.1. List of Hazards in Solotvyno, ● D.1.2. List of hazards in Transcarpathia, ● D.1.3. Data collection on hazards in Solotvyno, ● D.1.4. Data collection on hazards in Transcarpathia. 2. In case Consequences for the population in relation to hazard types – deliverables: ● D.1.5. Data collection on consequences Solotvyno, ● D.1.6. Data collection on consequences Transcarpathia, 3. In case Development of a risk mapping methodology – deliverables: ● D.1.7. Risk map of Solotvyno, ● D.1.8. Risk map of Transcarpathia, ● D.1.9. Report on methodology, ● D.1.10. Scientific article on risk mapping in Transcarpathia.

Deliverable D.1.9. Report on methodology covers issues related to the concept of the risk assessment process corresponding to the adaptation of ISO 31000: 2009. In the view of the interpretation of the aforementioned ISO 31000: 2009, deliverable D.1.9. in the area of risk assessment approach, adopts a three-step procedure of activities related to risk identification, risk analysis and risk evaluation. From the perspective of the project assumptions described in the proposal in WP 1, the methodology is based on the implementation of ten activities, i.e.

1 Deliverable D.1.10. Scientific article on risk mapping in Transcarpathia is still being developed - the deadline for its completion - by 28/02/2020.

16 | Page

D1.9 Report on methodology

1. Identification of necessary data (partly done in activity 1.1, extra meeting for finding gaps). 2. Choice of mapping form in relation to hazard and consequences (GIS vs description). 3. Assembling GIS data. 4. Identification of GIS data gaps. 5. Assembling other data. 6. Digitalisation of data. 7. Unification of GIS data. 8. Selection of GIS tools. 9. Data risk analysis (hazard vs losses). 10. Risk analysis visualization.

The goal of Deliverable D.1.9 is to specify the method (methodology) of risk assessment in the Transcarpathian region.

In the course of research carried out under WP 1, ten activities described in the project proposal were described in the form allowing for better presentation of the work done and more precise visualization of results.

The Deliverable D.1.9 structure is based on mapping the elements of the defined risk assessment method in the Transcarpathian region. From a practical point of view, it describes the individual stages of the risk assessment process, which then allows it to be prioritized and the appropriate risk treatment strategy applied. The deliverable structure D.1.9 in the main part of the research refers to such elements as: 1. Risk identification. 2. Risk analysis. 3. Risk evaluation. 4. Gradation of risk and risk treatment Ways and tools used to source, collect process and visualize risk data.

17 | Page

D1.9 Report on methodology

1 Risk identification

Risk is defined in many ways. This is confirmed by numerous studies made by literature researchers. The research team (MSFS) for the ImProDiReT project also carried out extensive literature analysis. The results in the form of a Literature review were presented during a meeting of the consortium implementing the project in June 2018 in Kyiv.

Risk is closely correlated with the hazard, and more precisely risk is a measure of the hazard. Obtaining the answer to the question of how much a given phenomenon, event or situation hazards defined protected values (e.g. life, health, property, environment) is possible due to assessing the value of risk. The risk can be estimated qualitatively (more general, descriptive) or quantitative (more precise, based on indexes / values).

Identification of risk in the view of design is nothing but identification of hazards in the adopted area. With the above in mind, the first major step in the work of the research team (MSFS) was to identify the hazards: ● in a narrow context - for the city of Solotvyno, ● in a wide context - for the Transcarpathian region. Hazards can be identified in many ways, e.g. by: ● heuristic methods (brainstorming), ● interviews with people living in the study area, ● expert judgment, ● analysis of statistical data on past hazards in a specific area.

In the course of ongoing work, the research team (MSFS) has developed a method for identifying and selecting hazards (Annex no 1), for which it will subsequently obtain and analyze data that will then allow visualization of hazards, their consequences and the level of risk of their occurrence. The method of hazard identification in Solotvyno and in the Transcarpathian region was presented at the consortium meeting the project in June 2018 in Kiev. At this meeting, after a long discussion, it was agreed that the following hazards would be analysed in the course of further work: 1. Chemical hazards. 2. Heavy snowfalls. 3. Heavy rains. 4. Black ice. 5. Drought. 6. Mudflow.

18 | Page

D1.9 Report on methodology

7. Landslide. 8. Flood. At the same time, it was noted that the case of Solotvyno is special due to the abandoned salt mine located within the village area. It contains numerous problems related to the process of closing the salt mine.

19 | Page

D1.9 Report on methodology

20 | Page

D1.9 Report on methodology

2 Risk analysis

With Risk analysis it becomes possible to understand the risks. At the same time, it provides input data, which in subsequent stages are used for risk evaluation, priority setting and selection of appropriate risk management strategies. Risk analysis can be carried out in various aspects and using different techniques, but its idea is based on determining the possibility (probability) of hazard occurrence and the strength of its impact on the local society (effects / consequences).

For the purposes of the analyses for defined hazards, it was assumed that the risk analysis will concern its two main attributes: the probability of occurrence (1) of possible consequences (2). At the same time, after many discussions in both Kiev (June 2018) and Solotvyno (October 2018) and Uzhgorod (March 2019), it was assumed that the analysis of the occurrence of hazards to the city of Solotvyno and the Transcarpathian region in order to determine the possible consequences will be carried out in the following categories: 1. Number of death people. 2. Number of injured people. 3. Number of evacuated people. 4. Material losses (finance). 5. Losses in the environment. 6. Disruption of functionality. 7. Number of people affected by the disruption. 8. Duration of (local) critical infrastructure damage. Defining categories of consequences helps to collect more precise impact data. Performing a risk analysis is possible when the input data for conducting the analysis (measuring) is obtained, as well as when the input data obtained for the analysis can be referred to a defined reference point (data classification). If data classification is not defined, it is only possible to register the data without further analysis.

Risk analysis requires, first and foremost, an analysis of the individual attributes that define this risk, i.e. probabilities (1) and consequences (2). The analysis of probability (1) and consequences (2) is possible when it is preceded by obtaining input data.

Probability estimation Determining the input data describing the probability value is possible in many ways. To calculate the probability of existing or possible hazard can be used:

21 | Page

D1.9 Report on methodology

● analysis of statistical data containing information on the frequency of hazards in the past, ● poisson distribution for the risks related with the forces of nature, ● event tree (eg. in the case of events related to industrial failures) and fault trees, ● probit function, ● nature game.

The measurement of the probability value can also be obtained by conducting an expert interview. The measurements obtained as a result of the interview should be referred to the probability classification.

Adopted for the needs of the project five steps qualitative and semi-quantitative the classification probability.

Class Value Name of class

5 0.81 - 1 Events almost certain (less than once a year)

4 0.51 -0.80 Very probable events (from 1 to 10 years)

3 0.31 - 0.5 probable events (from 10 to 50 years)

2 0.11 - 0.3 low probability of occurrence (from 50 to 100 years)

1 0 - 0.1 Very rare events (> 100 years)

Table 1: A qualitative and semi-quantitative description of probabilities

Source: The Main School of Fire Service based on W. Skomra (edit.), Risk assessment methodology for the needs of the crisis management system of the Republic of Poland, p. 191 Warsaw 2015.

Consequences estimation Obtaining input data on the consequences is also possible in many ways, but when estimating the consequences of possible hazards, it is worth using the people who have the most knowledge in this field, i.e. people who know the specificity of hazards in a city and in a neighbourhood area.

Considering the above, in the course of the conducted research a questionnaire was prepared, in which the experts estimated the probability values of one of the eight hazards and the values of the possible consequences of each of these hazards.

22 | Page

D1.9 Report on methodology

Adopted for the needs of the project five steps qualitative the classification of consequences.

Class Name of class Description

E Disastrous A large number of deaths. A large number of seriously injured. A large number of patients hospitalized. General and long-term displacement of the population. Extensive destruction. Impossibility of functioning of the community without significant external help. Great consequences on the environment and / or permanent damage. External financial assistance of considerable size is needed.

D Big Deaths and / or serious injury to persons, some of macros require hospitalization. Evacuation of people to designated places with the possibility of returning after 24 hours. Helping people in the evacuated place. Identification destruction that requires routine repair. The functioning of the community with little inconvenience more than a day. Larger consequences in the environment, but short-term or low consequences with a long-lasting consequence. Significant losses financial without external assistance. There is a need for specific resources to help people and to remove damage. A partially non-functioning community, some services are not available.

C Average A small number of wounded, no deaths. First aid is required. Some human movements occur (less than 24 hours). Some people need help. There is some destruction. Difficulties occur (not longer than 24 hours) in the functioning processes. Low environmental consequences with a short- term consequence. Small financial losses.

B Small No deaths or injuries. A small number of people displaced for a short period. Nobody or a small number of people needing help (does not apply to financial or material help). Small, practically meaningless destruction. No influence or very little consequence on the functioning of the local community. A virtually unmeasurable consequence in the natural environment. Small financial losses.

A Neglected Discomfort. No human movements. No damage. Unimpeded functioning of people or only to a small extent. Uninterrupted processes. No consequences on the environment.

Table 2: A qualitative the classification of consequences.

Source: The Main School of Fire Service based on W. Skomra (edit.), Risk assessment methodology for the needs of the crisis management system of the Republic of Poland, p. 189-190, Warsaw 2015.

23 | Page

D1.9 Report on methodology

In the case of the city of Solotvyno, eight Ukrainian-language surveys were prepared, each devoted to a separate hazard. The survey was carried out using an on-line questionnaire (form) placed on a public disc. The addressees of the form were the representatives of the local authorities of Solotvyno, who provided their contact details during the meeting in Solotvyno on October 25, 2018 (Annex no 2).

In the case of the Transcarpathian region, 1 questionnaire was prepared along with a template (card) to answer, which, together with a cover letter signed by the project manager, was sent to the recipients indicated. The questionnaire sent via e-mail sent to the local authorities of Transcarpathian districts contained queries about the classes of individual categories of consequences and the probability class. The answers were marked on the answer cards and then sent by e-mail to the research team MSFS (Annex no 3).

The probability value obtained as a result of expert judgment provided knowledge about the possibility of a hazard.

As a result of expert judgment, classes of individual categories of consequences were obtained. Due to the fact that 8 categories of consequences were identified in the research process, it was finally necessary to aggregate these categories into one representative value of the risk attribute, which are the consequences.

To this end, two tables have been defined, enabling one consequences value to be obtained. The first of them (Table No. 3) indicated the value of points assigned to each of the consequences classes, while the second one indicated the weight value of every category of consequences (Table No. 4).

Class of consequences Points

A 1

B 2

C 4

D 8

E 16

Table 3: Classes of consequences with the points

Source: The Main School of Fire Service based on W. Skomra (edit.), Risk assessment methodology for the needs of the crisis management system of the Republic of Poland, p. 189-190, Warsaw 2015.

24 | Page

D1.9 Report on methodology

No Class of consequences Weight criterion Percentage

1 Number of death 0,2 20 %

2 Number of injured people 0,2 20 %

3 Number of evacuated people 0,1 10 %

4 Material losses 0,1 10 %

5 Losses in the environment 0,2 20 %

6 Disruption of functionality 0,05 5 %

7 Number of people affected by the disruption 0,05 5 %

8 Duration of (local) critical infrastructure 0,1 10 % damage

Sum 1 100 %

Table 4: The weight value of the every consequences category

Source: The Main School of Fire Service based on W. Skomra (edit.), Risk assessment methodology for the needs of the crisis management system of the Republic of Poland, p. 189-190, Warsaw 2015.

In order to calculate the value of aggregated worth of the consequences, formula should be used:

C = P1 * (value of class with the first category of consequences) + P2 * (value of class with the second category of consequences) + P3 * (value of class with the third category of consequences) + ...... + P8 * (value of class with the eight category of consequences)

The obtained numerical value should be located in the classification of consequences defined by the ranges of achievable values (round up to the nearest above class of consequences according range of worth presented in Table No. 5).

Class of consequences Quantitative range

A < 1,00

B 1,01 – 2,00

C 2,01 – 4,00

D 4,01 – 8,00

E > 8,00

Table 5: Classes of consequences along with the quantitative range

Source: R. Wróbel and others, Deliverable D.1.6. Survey data on hazard consequences in Transcarpathia, p. 15, May 2019.

25 | Page

D1.9 Report on methodology

The result of risk analysis is to estimate the probability class and estimate the consequences class for each of the considered hazards. Knowing the values of these attributes allows the risk value to be determined and, consequently, to check its acceptability level.

Apart from the analysis mentioned above, for the city of Solotvyno an independent analysis of the possibility of occurrence and possible consequences of hazards related to the specificity of the salt mine located there was carried out. This analysis was conducted by IGS NASU.

26 | Page

D1.9 Report on methodology

27 | Page

D1.9 Report on methodology

3 Risk evaluation

The final result of risk analysis is to estimate the probability class and estimate the consequences classes for each of the considered hazards. Knowing the values of these attributes allows the risk value to be determined and, consequently, to check its acceptability level.

Risk is defined as the value of multiplying probability and consequences (R=P*C).

Risk evaluation is carried out using the results of the risk analysis and its acceptance criteria. Risk evaluation is a comparison of the recorded (estimated) results related to risk with the agreed criteria (acceptability) of risk. The effect of risk evaluation is to determine the level of risk. Risk levels are determined based on probability and consequence values, using a risk matrix tool (Table No. 6). Conseqences

Probability 5 5 10 20 40 80 4 4 8 16 32 64 3 3 6 12 24 48 2 2 4 8 16 32 1 1 2 4 8 16 A (1) B (2) C (4) D (8) E (16)

Legend risk neglected low risk medium risk big risk catastrophic risk

Table 6: Risk matrix tool

Source: R. Wróbel and others, Deliverable D.1.6. Survey data on hazard consequences in Transcarpathia, p. 15, May 2019.

Defining the levels presented in the risk matrix tool was possible thanks to the adopted risk acceptance criteria and risk level criteria (Table No. 7).

Risk acceptance Risk levels Risk level criteria criteria

28 | Page

D1.9 Report on methodology

Unacceptable risk Catastrophic risk - the probability of materializing a hazard is defined as one of four classes 1-4, and at the same time it has catastrophic consequences, - the probability of materializing the hazard is defined as almost certain and it has significant consequences,

Unacceptable risk Big risk - the probability of materializing the hazard is described as very rare, and at the same time it has catastrophic consequences, - the probability of materializing a hazard is defined as one of four classes 1-4, and at the same time it has large consequences, - the probability of hazard materializing is determined to be at least very probable, and at the same time it has medium consequences.

Acceptable risk Medium risk - the probability of hazard materializing is defined as one of three classes 1-3, and at the same time it produces medium consequences, - the probability of hazard materializing is at least very probable, and at the same time it has low consequences, - the probability of hazard materializing is defined as almost certain, and at the same time it produces negligible consequences,

Acceptable risk Small risk - the probability of materializing a hazard is defined in one of three classes 1-3, and at the same time it has low consequences, - the probability of materializing the hazard is defined as unlikely, probable or very likely, and at the same time it produces negligible consequences,

Acceptable risk Negligible risk - the probability of hazard materializing is defined as very rare and at the same time it produces negligible consequences.

Table 7: Risk acceptance criteria and risk level criteria

Source: R. Wróbel and others, Deliverable D.1.6. Survey data on hazard consequences in Transcarpathia, p. 15, May 2019.

29 | Page

D1.9 Report on methodology

30 | Page

D1.9 Report on methodology

4 Gradation of risk and risk treatment

The distribution of risk levels of individual hazards defines priorities in ensuring the safety of protected values.

In the first place, intervention requires risks for which risks are unacceptable. In such a situation, the actions are focused to reduce the risks to an acceptable level. This is possible in three ways through: ● reducing of probability, ● reducing of consequences, ● reducing both probability and consequences. The "upper” level of risk is never accepted and therefore in case of unacceptable risk, extraordinary and immediate measures should be taken to increase safety. There are needs to introduce additional or new solutions, which cause minimalization risk to acceptable level.

In cases where the value of the risk materializing hazard is at an acceptable level, it is considered that there are no required additional extraordinary and immediate safety measures. There are accepted current solutions and their assigned powers and resources. Monitoring activities complied with applicable procedures are carried out.

As a result of analyses based on the previously mentioned questionnaires, the highest risk levels (catastrophic risk) identified in Transcarpathia region were achieved for the following hazards: ● flood, ● heavy rains, ● chemical hazards. This is evidenced by the results (risk levels) obtained for the identified hazards in individual districts of the Transcarpathian region, presented in Table No. 8.

Chemical Heavy Heavy Black Drought Mudflow Landslide Flood District hazards snowfalls rains ice Berehove 2 4 5 2 3 2 2 5 Velykyi Bereznyi 2 4 4 3 3 3 3 4 Vinogradov 2 3 4 2 3 3 3 5 Volovets 2 4 4 3 3 3 4 5 Irshawa 2 4 4 2 3 3 3 5 Mukachevo 2 3 5 2 3 2 2 5

31 | Page

D1.9 Report on methodology

Rachiv 2 4 4 4 3 3 4 3 Svaliava 5 4 4 2 3 3 4 4 Tiachiw 2 4 5 3 3 3 4 5 Uzhhorod 5 3 5 2 3 2 2 5 Khust 2 3 4 2 3 2 2 5 Mizhhirskii 2 4 4 4 3 3 4 3 Perechyn 2 4 4 3 3 3 4 4

Number of level risk Name of risk level 1 risk neglected 2 low risk 3 medium risk 4 big risk 5 catastrophic risk

Table 8: Risk levels for identified 8 hazards for every districts of the Transcarpathian region. Source: Elaboration based on K. Tyrańska-Wizner and others, Deliverable D.1.7. Risk map Transcarpathia, p. 20, November 2019.

32 | Page

D1.9 Report on methodology

33 | Page

D1.9 Report on methodology

5 Tool used to source, collect process and visualize risk data

As part of planning work on the preparation of the project proposal, it was assumed that the risk maps for the city of Solotvyno and the Transcarpathian region would be prepared using Risk Mapping Methodology. The data collection and risk mapping methodology was planned to do closed collaboration with the Institute Geological Science of National Academy of Sciences of Ukraine (IGS NASU). The following stages of work are planned: 1. Identification of necessary data. 2. Choice of mapping form in relation to hazard and consequences (GIS vs description). 3. Assembling GIS data. 4. Identification of GIS data gaps. 5. Assembling other data. 6. Digitisation data. 7. Unification of GIS data. 8. Selection of GIS tools. 9. Data risk analysis (hazard vs losses). 10. Risk analysis visualization.

GIS (ang. Geographic Information System) – it is a system consisting of hardware (computers, network, graphic peripherals), software (applications, databases, operating systems), data (vector, raster, remote sensing, descriptive), people (decision makers, administrators, GIS specialists, users), and procedures (specifications, standards, rules of conduct).

GIS is intended for collecting, storing, analyzing and visualizing data that is spatially referenced to the Earth's surface in order to solve complicated planning and organizational problems.

We can also update and edit spatial data using GIS. The main advantage of GIS is the ability to link descriptive information to individual map elements. This assigns attributes (a feature of a given object) together with values.

Two types of data dominate in GIS systems: 1. Vector type data: ● plot boundaries, ● streets, ● buildings, ● energy, ● gas,

34 | Page

D1.9 Report on methodology

● water supply, ● address points, ● hydrant points, ● etc. 2. Data of the raster type – the raster map is similar to the photo. The raster image is made of points arranged in rows and columns forming a grid. Each point may have different values (colors), which results in an image)2.

The tool used in the implementation of this project (development) is QGIS software (Quantum Geographic Information System).

QGIS – It is a cross-platform program created in 2002 under an Open Source license used to view, edit, perform spatial analyses and create your own maps (Davis 2004). It allows the use of data from many sources, and most importantly is subject to regular updates and bug fixes. Changes can be made at the request of any user with the consent of the administrators3.

As a result of the analyses and data collection, thanks to materials obtained by the research team MSFS from the Ukrainian partner (IGS NASU), it was possible to import a map background for the Transcarpathian region. QGIS software allows you to visualize the imported map background (Chart No. 1).

2 K. Tyrańska-Wizner and others, Deliverable D.1.8. Risk map Transcarpathia, November 2019.

3 Ł. Litwin, The use of the Georeferenced Information System to improve the activities of the State Fire Service on the example of the Świętokrzyskie Province, engineering work, Warsaw, April 2019.

35 | Page

D1.9 Report on methodology

Chart 1. Transcarpathia regions in the QGIS map background Source: Elaboration based on K. Tyrańska-Wizner and others, Deliverable D.1.7. Risk map Transcarpathia, p. 10, November 2019.

QGIS software gives the opportunity to differentiate each region with different values, consequently, with colours, which can be used, for example, to prepare a list on which the hierarchy of risk values will be made. These capabilities of QGIS software are shown in Chart No. 2.

36 | Page

D1.9 Report on methodology

Chart 2. Possibilities of QGIS software presenting different values of colors for each of regions of Transcarpathia

Source: K. Tyrańska-Wizner and others, Deliverable D.1.7. Risk map Transcarpathia, p. 10, November 2019.

In delivered deliverable D.1.9. Risk map Transcarpathia risk visualization was made separately for each of the identified eight hazards. Risk, according to the classifications and markings defined in Table No. 8, was defined in categories: ● risk neglected (acceptable), ● low risk (acceptable), ● medium risk (acceptable), ● big risk (unacceptable), ● catastrophic risk (unacceptable).

37 | Page

D1.9 Report on methodology

Chart 3. Flood risk map for each of the Transcarpathian regions.

Source: K. Tyrańska-Wizner and others, Deliverable D.1.7. Risk map Transcarpathia, p. 10, November 2019.

The results presented on the chart no. 3 indicate that the unacceptable level of flood risk was estimated in almost all regions of the Carpathian region: 1. The highest level of risk (catastrophic risk) was achieved in eight regions (Berehove, Vinogradov, Volovets, Irshawa, Mukachevo, Tiachiw, Uzhhorod, Khust). 2. A lower, but still unacceptable risk class, ie high risk was estimated in three regions of Transcarpathia (Velykyi Bereznyi, Svaliava, Perechyn). An acceptable level of risk exists only in two regions, i.e. Rachiv and Mizhhirskii.

The risk classes presented in Chart No. 3 overlap with the risk classes set out in Table No. 8.

The development of risk maps using QGIS was possible after a sequence of specific activities. These steps boiled down to: ● identification of hazards, ● gaining access to map data, ● verifying acquired materials, ● obtaining missing information through the use of a questionnaire, ● choosing a visualization tool, ● analysing received materials, ● importing obtained information into QGIS software,

38 | Page

D1.9 Report on methodology

● visualizing data to form risk maps for the Transcarpathian region.

39 | Page

D1.9 Report on methodology

40 | Page

D1.9 Report on methodology

6 Conclusions

Deliverable 1.9. Report on methodology is a document that combines the scope of work undertaken by research team The Main School of Fire Service (MSFS) and Institute Geological Science of National Academy of Sciences of Ukraine (IGS NASU).

At the same time, its elaboration emphasizes the role of individual deliverables 1.1.–1.8 - constituting individual elements of the methodology The methodology presented in deliverable 1.9 includes the stages of: 1. Hazard identification. 2. Definition of risk attributes (probability and consequences). 3. Obtaining hazard data to assess the level of risk. 4. Setting priorities for action based on the hierarchy of risk values for specific hazards. 5. Selection of risk visualization tool.

The added value of the document is the presentation in the form of annex to the survey questionnaires, which were used to: 1. Defining the list of hazards that require determining the level of risk first. 2. Obtaining information on the probability and consequences of hazards in Solotvyno and in the region of Transcarpathia. The obtained data, analysed, allow determining the regions of Transcarpathia in which the unacceptable risk value occurred most often, as well as identify the hazards for which unacceptable risk values were obtained.

The regions of Transcarpathia in which the unacceptable risk value most often occurred were: 1. Uzhhorod - risk values at the level of catastrophic risk were obtained for 3 hazards (Chemical hazards, Heavy rains, Flood). 2. Berehove, Mukachevo, Tiachiw - risk values at the level of catastrophic risk were obtained for two hazards (Heavy rains, Flood). 3. In the Berehove and Tiachiw regions, the value of high risk, which is also an unacceptable risk, was obtained for the Heavy snowfalls. In the latter region (Tiachiw) a high risk was also estimated for the Landslide.

Hazards for which unacceptable risk values were obtained were: 1. Flood: ● catastrophic risk in 8 regions, i.e. Berehove, Vinogradov, Volovets, Irshawa, Mukachevo, Tiachiw, Uzhhorod, Khust, ● high risk in 3 regions, ie Velykyi Bereznyi, Svaliava, Perechyn.

41 | Page

D1.9 Report on methodology

2. Heavy rains: ● catastrophic risk in 4 regions, i.e. Berehove, Mukachevo, Tiachiw, Uzhhorod, ● high risk in 9 regions, i.e. Velykyi Bereznyi, Vinogradov, Volovets, Irshawa, Rachiv, Svaliava, Khust, Mizhhirskii, Perechyn.

42 | Page

D1.9 Report on methodology

43 | Page

D1.9 Report on methodology

7 References

[1] http://erra.pprd-east.eu/

[2] http://pprdeast2.eu/en/regionalnyy-yelektronnyy-atlas-risk/

[3] http://www.ukrstat.gov.ua/

[4] EUCPT, Risk Assessment report on the Solotvyno mine and surrounding, November 2016

[5] Kozioł J., Jarzynka K., Literature review, June 2018.

[6] Litwin Ł., The use of the Georeferenced Information System to improve the activities of the State Fire Service on the example of the Świętokrzyskie Province, engineering work, Warsaw, April 2019.

[7] Skomra W. (edit.) Risk assessment methodology for the needs of the crisis management system of the Republic of Poland, pub. Bell Studio Sp. z.o.o., Warsaw, 2015.

[8] Tyrańska-Wizner K. and others, Deliverable D.1.7. Risk map Solotvyno, March 2019.

[9] Tyrańska-Wizner K. and others, Deliverable D.1.8. Risk map Transcarpathia, November 2019.

[10] Wróbel R., Risk and business continuity management of nuclear power plants [in:] Smolarkiewicz M., Piec R., Chmielewska-Łukaszek A. (edit.), Nuclear security, pub. MSFS, Warsaw 2017.

[11] Wróbel R. and others, Deliverable D.1.5. Survey data on hazard consequences in Solotvyno, October 2018.

[12] Wróbel R. and others, Deliverable D.1.6. Survey data on hazard consequences in Transcarpathia, May 2019.

44 | Page

D1.9 Report on methodology

45 | Page

D1.9 Report on methodology

APPENDIX I

Annex 1. Method for identifying and selecting hazards for risk analysis

Procedure: 1. Designation of an expert group. 2. Assigning hazards to specific areas (groups) by source of origin. 3. Members of the group, without agreeing their assessments with others, create their own hazard ranking lists, awarding them points in this way, that the risk for which in his opinion should first be drawn a risk map is awarded a number of points equal to the number of hazards assessed.

For example: ● A maximum of 17 points are awarded for 17 hazards. ● Other hazards (selection in the table at the discretion) receive one less point. ● The "last" hazard on the prepared list receives 1 point. ● Every hazards in this case should be assigned a different score on a scale of 1-10 points (points cannot be repeated). 4. Points awarded by individual members of the group are added together and a ranking of hazards is created starting from the one that received the most points.

The results of the analysis are presented in a table, the model of which is given below.

Optional: 1. To express the result obtained in percent, the number of points that a given risk area has received is divided by the number of points that the first area on the list received, and then multiplied by 100%. 2. The first hazard on the list gets the value equal to 1 (100%), and each subsequent one is less. It is possible to obtain the same score by two or more hazards.

46 | Page

D1.9 Report on methodology

Source of No Hazards Points The sum Position in Estimated hazard of the the value4 points ranking N1 N2 N3 N4 N5 obtained

1 Chemical 1 14 15 11 0,54 Man- Hazard made 2 Radiation 2 10 12 14 0,43 Hazards Hazard (Human made 3 Fire and 4 6 10 15 0,36 Impact) Explosion Risks

4 Hydrodynamic 7 12 19 8 0,68 Hazards

5 Tailing and 5 1 6 16 0,21 Sludge Damp

6 Pipelines 3 2 5 17 0,18

7 Hazardous 9 4 13 13 0,46 wastes

8 Meteorological 8 7 15 11 0,54 Hazards

9 Earthquake 11 5 16 9 0,57

10 Landslide 13 3 16 9 0,57 Natural 11 Karst 15 9 24 6 0,86 Hazards 12 Flood 17 8 25 4 0,89

13 Flooding 16 11 27 2 0,96

14 Mudflow 14 13 27 2 0,96

15 Ground 10 15 25 4 0,89 erosion + slop

4 Round up to two decimal places.

47 | Page

D1.9 Report on methodology

steepness + deforestation

16 Fire in 6 17 23 7 0,82 Ecological Systems

17 Biomedical 12 16 28 1 1,00 Hazards Annex 2. Exemplary questionnaire used for research at Solotvyno for gathering information about fire, explosion or hazardous substances.

1. Please indicate how many accidents occurred at the Solotvyno industrial plant......

2. Please indicate how many explosions took place in Solotvyno......

3. Please provide the number of occurrences due to the substance escaping from pipelines transferring chemicals in Solotvyno......

4. Please indicate the number of people who died due to fire, explosion or hazardous substances at industrial plants in Solotvyno. Number of people 1 2-5 5-10 >10 Time Directly (first year) C D E E Increased (within 20 years) A A B C

5. Please indicate the number of people injured due to fire, explosion or hazardous substances at industrial plants in Solotvyno. Number of people <10 10-100 101-1000 1001-10 000 > 10 000

48 | Page

D1.9 Report on methodology

Category A B C D E

6. Please provide the number of people who were evacuated due to fire, explosion or hazardous substances at industrial plants in Solotvyno. Number of people <100 101-1000 1001-10 000 10 001-100 000 >100 000 Time Less than 6 months A A B C D

Longer than 6 months A B C D E

7. Please mark the% of budget losses of a given administrative unit (Solotvyno) due to the occurrence of fire or explosion hazards or with hazardous substances in industrial plants in Solotvyno (the amount of losses sought is related to the occurrence in Solotvyno of all fire, explosion and hazardous hazards) in industrial plants within 1 year).

Cost in % of budget <1 1-5 6-10 11-30 >30

Category A B C D E

8. Please mark the% of losses in the natural environment of the given administrative unit due to the occurrence of fire and explosion hazards, or with the participation of hazardous substances in industrial plants in Solotvyno (the amount of losses sought is related to the occurrence in Solotvyno of all fire, explosion and hazardous hazards in industrial plants within 1 year).

Area of destruction % <1 1-5 6-10 >10 Time to recovery (year)

<1 A B C D

>1 B C D E

49 | Page

D1.9 Report on methodology

9. Please indicate the risk of interference for individual services due to fire or explosion hazards, or with hazardous substances in industrial plants in Solotvyno (risk levels: low, medium-low, medium, medium-high, high, extremely high - select one risk level in each row).

Level of influence on risk Very Low Low Medium High Extremely high Disrupted processes lack of communication with the use of regular IT systems b c d e e no possibility of getting to a b c d e school or work no access to important a b c d e public services no possibility of supplying the necessary things b c d d e loss of at least one of the functions resulting from the b c d e e competence of the unit

Damage to one of the critical infrastructure systems c d e e e

10. Please indicate what% of people felt the effects in Solotvyno (from the whole Solotvyno community) due to the occurrence of fire, explosion or hazardous substances in industrial plants (the value sought is measured in% of the entire population of the given administrative unit). Number of people (%) <1 1-5 6-10 11-30 >31 Time Less than one week A B C D E Week - month B C D E E More than one month C D E E E

50 | Page

D1.9 Report on methodology

11. Please indicate the duration of the dysfunction (destruction or disruption in operation) of the local critical infrastructure due to the occurrence of fire, explosion or hazardous substances in industrial plants. Duration of damage < 1 day To 3 days 4 days to 7 days To month More than month

Category A B C D E

51 | Page

D1.9 Report on methodology

Annex 3. Questionnaire used for research at district of Transkarpatia region

OBLAST:

INSTITUTION:

NAME:

SURNAME

KONTAKT:

E-MAIL:

CARD OF PROBABILITY:

1 2 3 4 5 6 7 8

C He He Bla Dr Mu La Flo Name of categories he avy avy ck ou dfl nd od mi sn rai ice gh ow sli ca ow ns t de l fall ha s za rd s

Please indicate how many …* …* …* …* …* …* …* …* accidents took place in your oblast in period las year?

What do you think is the …** …** …** …** …** …** …** …** probability of a certain event occurring in your oblast? Indicate a number from 1 to 5, where: 1 - Very rare events (> 100 years) 2 - low probability of occurrence (from 50 to 100

52 | Page

D1.9 Report on methodology

years) 3 - probable events (from 10 to 50 years) 4 - very probable events (from 1 to 10 years) 5 - events almost Certain (often than once a year)

* fill in according to your knowledge ** use numbers from 1 to 5 to asset class of probability for every hazard according to classification

CARD OF CONSEQUENCES:

1 2 3 4 5 6 7 8

Che He He Bla Dr Mu Lan Flo Name of categories mical avy avy ck ou dfl dsli od haza sn rai ice ght ow de rds ow ns fall s

Fatalities people (death) …*

Injured people

Evacuated people

Material losses (finance)

Losses in the environment

Disruption of functionality

Number of people affected by the disruption

53 | Page

D1.9 Report on methodology

Duration of (local) critical infrastructure damage * use numbers from A to E to asset class of consequences for every category.

CLASSIFICATION OF CONSEQUENCES:

Class Name of Description class

54 | Page

D1.9 Report on methodology

A Neglected Discomfort. No human movements. No damage. Unimpeded functioning of people or only to a small extent. Uninterrupted processes. No consequences on the environment.

55 | Page