About methods of assessment of socio-economic risks of hazardous hydrological phenomena in Russian coastal zones of the Azov and the Black Seas

1. 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

2. 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

3. 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)

4. Main area of research
Area of research

5. 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

6. Number of floods and some examples
of Flood damage in the Kuban River
Basin
Date
Flood
reason
Damage
1998,
march
Haivy
rains and
groundw
ater 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
numberoffloodsper10years

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

8. Potential flooding zones and observed
flooding areas

9. 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

10. 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)

11. 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

12. 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

13. 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

14. Lack of capacity and
susceptibility indeces

15. Exposure and vulnerability
indeces

16. 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.)

17. 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

18. 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.

19. 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 for
protection
Do not know evacuation routes
Do not know safe place
Training activities were not carried out by
EMERCOM
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

20. 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.

21. 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

22. 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

23. 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

24. 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.

25. 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

26. Future directions
1. Seasonal and day / night vulnerability
2. Verification of methodology
3. Resilience estimation (methodology, indicators, etc.)

27. Thank you for your attention!