Zemtsov S. Socio economic risk assessment of flooding for Russian coastal regions

SOCIO-ECONOMIC RISK ASSESSMENT OF FLOODING FOR RUSSIAN COASTAL REGIONS

Lomonosov Moscow State University Faculty of Geography

Natural Risk Asessment Laboratory (NRAL)

Zemtsov Stepan Kidyaeva Vera Fadeev Maxim

Main purpose • Purpose – risk and vulnerability assessment of hazardous hydrological

phenomena for Russian coastal regions • Social-economic approach for assessment (meanwhile damage

assessment prevails in Russia)

Timeliness: • More than 10 million people, or 7.2 per cent of the population, are

affected by hazardous hydrological phenomena; flooding zone is over 0.5 million sq. km, or 2.9 per cent of Russian territory

• Integrated damage from floods in Russia in 2012 was about 1 billion euros, floods have caused the death of over 200 people (Krymsk tragedy in Krasnodar region)

• In August 2013 approximately 102 000 people are affected by the flooding in Far Eastern regions

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

Structure of the presentation • Research area • Assessment of social risk and vulnerability of municipal

communities in Krasnodar region • Verification of social risk assessment method by field data

on an example of Slavyansk municipal district in Krasnodar region

• Conclusions

Risk for Russia (World Risk Index) is quiet low (0.038) 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

Case study area Asov and Black sea

coastal area of Russia

Region Krasnodar region (76 th. sq. Km, 5,3 mln.

people)

Case study Slavyansk municipal

district

Method of 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.

• Database with more than 300 indicators for 14 municipal districts from 2007 to 2011 years

Exposed areas. Potential flooding zones and observed flooding areas

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 high 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 (0.038)

• 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 is increasing 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

• 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 respondents coincide with the real structure of the population.

Field data collection

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 index 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 populatio

n

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

Prikubanskiy 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 Death Methodology Real loss for society, euro 5000 1500000 Guriev S.

Based on comparison with life insurance in the USA

Government estimation, euro 1200 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

Social loss. Government estimation (direct loss for economy)

0.5 10.9

Real social loss (including 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.).

Conclusion • In Russia, probability growth of hazardous natural events (caused by climate

change) has coincided with increasing risk of technogenic catastrophes because of errors in territorial planning, organization of warning and prevention systems and underinvestment of protection systems

• Krasnodar region has one of the highest level of flood hazard in Russia, but nowadays integral risk in coastal zone is even increasing because of concentration of economic activity (marine ports, recreation), especially during preparations for Sochi Olympic Games

• The index can be used for estimation of territorial priorities • Most of the population in one hazardous area (Slavyansk district) is unaware and

is not ready for a flooding. It can be common for other regions • Both external (MRI) and internal (component analysis of opinion polls)

techniques can determine the value of vulnerability of local communities but the second approach is preferred for financial estimations

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

Thank you for your attention!