Integrated assessment of socio-economic risks of dangerous hydrological phenomena in Russian coastal

zones of the Azov and the Black Seas

Vyacheslav Baburin

Mariya Goryachko

Inna Krylenko

Natalya Yumina

Stepan Zemtsov

Lomonosov Moscow State

University

Faculty of Geography

Natural Risk Asessment

Laboratory (NRAL)

European Geosciences Union General Assembly 2013

Vienna | Austria | 07 – 12 April 2013

Object – aqua-territorial systems Subject – influence of natural processes (flood, high level

of ground water, surges) on aqua-territorial systems Purpose – estimation of influence (risk and damage

assessment) of natural processes on aqua-territorial systems

Actuality - integrated damage from floods in Russia in

2012 was about 1 billion euros, floods have caused the death of over 200 people

Object and purpose

Risk for Russia (World Risk Index) is quiet low but very differentiated between regions

Map of typological zoning of Russia on the degree of flood risk

(N. Frolova and others, 2011, Russia)

Main area of research Area of research

Study area

Asov and Black sea coastal area of

Russia

Region Krasnodarsky kray

(76 th. sq. Km, 5,3 mln. people)

Case study

Slavyansk municipal district

Number of floods and some examples of Flood damage in the Kuban River

Basin

Date Flood

reason Damage

1998, march

Haivy rains and groundwater level rise

Around 500 000 ga, 132 setlements, more than 22 500 houses were flooded, 113 economic objects were damaged in Krasnodar region. Huge flood activated landslide processes in Temryuk city. Around 107 privat houses were damaged and 300 people were injured in Temryuk region.

2001, december — 2002, january

Ice jams, haivy rains and reservoir releases

Huge area along the river and part of Temryuk city were flooded (around 74 ga). 3283 people were injured

2002, july

Snow melting and haivy rains

One of the river dam was broken. 1,5 km2 of rice fields and pump station were flooded

2011, february

Surge Water level rised on 1,5 m

1740

1770

1800

1830

1860

1890

1920

1950

1980

2011

0

1

2

3

4

5

6

period of time

nu

mb

er

of

flo

od

s p

er

10 y

ears

Cuban river flood event (Temryuk, 2002; Krymsk, 2012)

Potential flooding zones and observed flooding areas

Ecological risks

Profit loss, budget loss, etc.

Psychological risks

Natural hazards

Atmosphere Hydrosphere Litosphere Biosphere

Social-ecological system

The basic framework of Russian approach

Forest, grasslands, soil degradation, etc.

Damages of infrastructure (roads, power stations, etc.) and fixed funds

Death, health problems, poverty, etc.

Political risks

Economic risks

Technological risks

Social risks

Corruption, rebellion of citizens, etc.

Psycological malfunction

Risk Asessment Methodology in Russia

R = p*D

R - integrated socio-economic risk, or risk of potential annual loss

p - probability of a natural hazard (in shares)

D - integral potential damage, which can be expressed in rubles, persons, etc.

Dj = ΣdIi * Vij * Sj

dI - maximum potential damages per unit area, according to the type of risk

V - indicator of vulnerability, depending on properties of the object

S - area of the different flood zones

I - type of risk (ecological, technological, social, economic, etc.)

i - type of damage according to risk types

j - flood zones according to their hazard: 1 – ground water level rise, 2 - surges and

flooding with dam outbreak, 3 - catastrophic flooding

Vij = f (Susij - Cij)

Sus - object susceptibility to natural hazards,

C - ability of an object to resist (coping and adaptive capacities)

Municipal Risk Index

• Methodology of World Risk Index (EHS-UNU)

• Data for vulnerability assessment from the Russian Statistical Service

(Rosstat) for municipal districts (local level); federal ministries, departments of

Krasnodar region administration, and etc.

• Database with more than 300 indicators for 14 municipal districts from 2007 to

2011 years

Vulnerability

Susceptibility

Public infrastructure Housing

conditions Poverty and dependencies Economic capacity Index

Length of

improved water

source / people

Length of

improved

sanitation /

people

The share of the

inhabitants in

fragile dwellings

The share of the

population with

incomes below

the subsistence

minimum

The share of the

population

benefiting from

social

assistance to

pay for housing

services

The share of the

population served by

the departments of

social services at

home for senior

citizens and disabled

Sales of own-

produced goods,

works and services /

people

0,075 0,075 0,15 0,15 0,15 0,15 0,25 0,33

Lack of coping capacity

Government and authoritiees Medical services Social networks Material coverage Index

Unemployment

rate

The share of

own revenues of

local budgets

Number of

hospital beds

per 10000

inhabitants

Number of

physicians per

10000

inhabitants

Share of

participants in

voluntary groups

for the protection

of public order

Average monthly

wages per capita

0,1 0,10 0,22 0,22 0,26 0,1 0,33

Lack of adaptive capacity

Education Environmental

management

Adaptation

strategies Investment Index

Share of

employed

people with

good education

Observed

/Maximum flood

area

Diversification of

the labour

market

(Herfindahl–

Hirschman

Index)

Private

investment /

people

0,25 0,25 0,25 0,25 0,33

Selected indicators and weights

Municipal

Risk Index

Exposure Vulnerability Susceptibility Lack of coping

capacity Lack of adaptive

capacity

Novorossiysk 0,02 0,05 0,40 0,26 0,37 0,58

Gelendzhik 0,03 0,07 0,42 0,47 0,25 0,55

Sochi 0,03 0,06 0,51 0,66 0,39 0,47

Tuapsinsky 0,04 0,09 0,50 0,45 0,56 0,49

Sherbinovsky 0,08 0,11 0,70 0,65 0,68 0,79

Kanevsky 0,09 0,14 0,62 0,40 0,70 0,77

Eysky 0,10 0,16 0,65 0,67 0,66 0,63

Anapa 0,13 0,28 0,47 0,49 0,36 0,56

Krymsky 0,14 0,24 0,58 0,67 0,59 0,49

Krasnoarmeysky 0,23 0,32 0,70 0,56 0,83 0,72

Temryuksky 0,26 0,53 0,49 0,45 0,74 0,27

Kalininsky 0,35 0,47 0,74 0,63 0,86 0,75

Primorsko-Akhtarsky

0,39 0,7 0,56 0,63 0,65 0,40

Slavyansky 0,45 0,75 0,59

0,43 0,71 0,65

Lack of capacity and susceptibility indeces

Exposure and vulnerability indeces

Municipal Risk Index (MRI)

• Most of the districts have higher value

of MRI than Russia in WRI (3.8)

• MRI is higher in Cuban river basin

• Slavyansk district has the highest

level of risk (0.45), the same level of

vulnerability as Krymsky district (0.59)

and higher than Russia in WRI

• Sensitivity analysis shows that some

indicators can be excluded but finally it

doesn’t affect greatly value of the

index

• The level of MRI will increase due to

processes of coastal zone

development (Sochi, Novorosiysk,

etc.)

Slavyansk district

2179 km2 131 000 citizens (50% urban)

Industries: oil, rice, wheat, fish, tourism.

80% of the territory exposed to annual ground water level rise

Field data collection

Some respondents' answers to questions about preparedness and responses to flooding (%)

Slavyansk

district

Anastasievskaya Achuevo Zaboyskiy Prikubanskiy Slavyansk-on-

Cuban

Training activities were not

carried out by EMERCOM

55 56 32 42 68 57

Do not know evacuation routes 69 79 21 43 61 77

Do not know safe place 58 66 14 35 41 69

Will ignore an alarm system 14 6 14 16 18 15

Do not participate in voluntary

groups for protection

93 95 86 90 86 95

Do not have any transport

vehicles

44 35 57 62 63 50

Count only on themselves in

case of flooding

45 54 43 47 45 43

In event of flooding do not take

any action

9 9 18 12 6 7

• Data where collected in 6 settlements by interviewing of people on the streets

• 274 respondents, which is the representative indicator for the district.

• Gender and age structure of the forms coincide with the real structure of the population.

30,7

51,8 54,5

55,8 60,8

62,9

14

23

43 46 47

49

0

10

20

30

40

50

60

70

80

90

100

Percentage of respondents by answers in settlements, %

Do not participate in voluntary groups forprotection

Do not know evacuation routes

Do not know safe place

Training activities were not carried out byEMERCOM

Count only on themselves in case of flooding

Do not have any transport vehicles

Will ignore an alarm system

In event of flooding do not take any action

Integral index

Vulnerability index

Vulnerability groups assessment

Combination of answers for groups of people with different value of vulnerability

The most

vulnerable

Less vulnerable Weakly vulnerable

Can you provide the safety of

your life?

No In part

Do not know

Yes

What is your age? 0-16

>66

56-65 > 16

< 56

How many years do you live

in the area?

Less than 1

1-5

5-20 > 20

Did you experienced flood? No Once More than once

• Four questions (from 30 overall) were extracted by component analysis from social poll data to

reveal the groups.

Vulnerability indices assessment

The distribution of the groups for Slavyansk municipal district

• These percentages may be used as an index of vulnerability (0.42, 0.58) for district

population respectively for medium (percentage of most vulnerable) and catastrophic

destructive floods (percentage of most vulnerable and vulnerable).

• The result (0.58) is corresponding with vulnerability index in Municipal Risk Index

(0.59).

• For settlements the scheme for calculation was the same.

Index of vulnerability

Frequency Percent Valid Percent Cumulative Percent

Valid Most vulnerable 192 40,5 41,5 41,5

Vulnerable 74 15,6 16,0 57,5

Less vulnerable 197 41,6 42,5 100,0

Total 463 97,7 100,0

Missing System 11 2,3

Total 474 100,0

Victims and death rate assessment (by EMERCOM Methodology)

• Exposed population were assessed by areas of flooding and density of population on them. More accurate assessment of exposure index (from 0.7 in MRI to 0.3)

• The number of victims of medium flood is 2% of the vulnerable population, and 5% - for catastrophic flood.

• Death rate is 5% of victims for medium flood, and 10% for strong

Medium flooding Catastrophic flooding

Exposed

population

Vulnerability

index

Vulnerable

people Victims Death

Exposed

population

Vulnerability

index

Vulnerable

people Victims Death

Total 16481 0.46 6922 138 7 60575 0.58 35134 1757 176

Achuevo 403 0.14 57 2 0 403 0.21 85 4 0

Zaboyskiy 2306 0.23 530 11 5 2306 0.38 876 44 4

Prikubanski

y 297 0.43 128 3 0 297 0.51 151 8 0

Slavyansk-

on-Cuban 0 0.49 0 0 0 38305 0.6 22983 1149 115

Financial estimations of social loss: two approaches

Medium flooding Catastrophic flooding

Real loss for society

Government estimation

Real loss for society

Government estimation

Victims Death Victims Death Victims Death Victims Death

Total 690000 10500000 165600 350000 8785000 264000000 2108400 8800000

Achuevo 10000 0 2400 0 20000 0 4800 0

Zaboyskiy 55000 7500000 13200 250000 220000 6000000 52800 200000

Prikubanskiy 15000 0 3600 0 40000 0 9600 0

Slavyansk-on-

Cuban 0 0 0 0 5745000 172500000 1378800 5750000

Medium flooding with probability 0.01 Catastrophic flooding with probability 0.001

Real loss for society Government estimation Real loss for

society

Government

estimation

Total

potential

damage

Annual risk

Total

potential

damage

Annual risk Total potential

damage Annual risk

Total

potential

damage

Annual risk

Total 11190000 111900 515600 5156 272785000 272785 10908400 10908.4

Achuevo 10000 100 2400 24 20000 20 4800 4.8

Zaboyskiy 7555000 75550 263200 2632 6220000 6220 252800 252.8

Prikubanskiy 15000 150 3600 36 40000 40 9600 9.6

Slavyansk-on-

Cuban 0 0 0 0 178245000 178245 7128800 7128.8

Victims Methodology Death Methodology

Real loss for society, euro 5000 Guriev S. Based on comparison with

average health insurance in the USA

1500000 Guriev S. Based on comparison with life

insurance in the USA

Government estimation, euro 1200 Methodology of EMERCOM 50000 Methodoloy of EMERCOM

Comparison of social and economic damage

Total potential damage (million euro) Total real damage (million

euro)

Slavyansk municipal district Krymsk disaster

Medium flooding Catastrophic flooding

Economic and technological

damage (EMERCOM

methodology)

4.3 142 1000

Government estimation

(direct loss for economy)

0.5 10.9

Real loss for society

(indirect losses)

11.1 272.7 259

• Social damage can be underestimated by assessment of direct losses of man as a an

economic tool of several years. But indirect losses for society is much wider

(demographic, cultural effects, etc.)

• Indirect losses can be even higher than potential economic damages.

Conclusion

• Krasnodar region has one of the highest level of flood hazard in Russia, but nowadays integral risk in coastal zone is even increasing

• Most of the population is unaware and is not ready for a flooding

• Both external (MRI) and internal (component analysis of opinion polls) techniques can quite accurately determine the value of vulnerability for local communities but the second one is preferred for risk index

• Social risks can be underestimated in comparison with economic due to low ‘value of life’, which in turn will continue to negatively affect the vulnerability, especially coping capacity in Russia

Future directions

1. Seasonal and day / night vulnerability

2. Verification of methodology

3. Resilience estimation (methodology, indicators, etc.)

Thank you for your attention!