natural risk assessement
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Risk assessment of coastal zones in the European part of Russia.
Asov and Black Seas study (Krasnodar region).
Inna Krylenko Natalya Yumina
Stepan Zemtsov
Lomonosov Moscow State University
Faculty of Geography
Natural Risk Asessment Laboratory (NRAL)
Object – aqua-territorial systems as a type of social-ecological systems
Subject – influence of natural processes (river flooding) on aqua-territorial systems
Purpose – an estimation of influence (risk and damage assessment) of natural processes on aqua-territorial systems
Object and purpose
The study areaAsov and Black
sea coastal area ofRussia
RegionKrasnodarsky kray
(76 th. sq. km5,3 mln. people)
Case studyTemryuk municipal
district
Municipal districts and main cities of
Krasnodar region
(Krasnodarsky kray)
Some Examples of Flood Damage in the Kuban River Basin
Date Flood reason Damage
1998, marchHaivy 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
Number of significant flood events during the observation period (from XVIII century)
Black SeaRivers
Kuban RiverMouth
0
1
2
3
4
5
6
period of time
nu
mb
er o
f flo
od
s p
er 1
0 ye
ars
012345678
period of time
nu
mb
er
of
flo
od
s p
er
10 y
ears
Potential flooding zones and observed flooding areas
Cuban and Eya rivers areas
Black sea rivers areas
Cuban river flood event (July, 2002)
Ecological sphere
Technosphere1. Infrastructure 2. Fixed funds
Sociosphere1. Socio-demographic
2. Ecomomy3. Political-administrative
4. Cultural
Psychological sphere
Social-economic geosystemor
social-ecological system
Natural hazards
AtmosphereHydrosphereLitosphereBiosphere
Antroposphere
The basic concepts of Russian approach
Risk Asessment Methodology in Russia
R = p*D R — risk p — hazard probability (%) D — expected damage
D = d*S + C
d — real damage per exposure area (rub*km2) — depends on flood depth, velocity, duration and land development
S — exposure area (km2) C — costs of preventive measures (rub)
The scheme for selection of indicators to assess risk of flooding on regional level
(N.Frolova and others, 2011, Russia)
Flood risk assessment
Vulnerability assessmentAssessment of natural hazards
Natural factors Socio-economic factors
1. Probability of flooding of coastal areas
2. Scales of the phenomenon - maximum excess of the flooding level - flood duration - exposure area
3. Riverbed factor
1. Average population desity
2. Proportion of the population in the flood zone
3. Anthropogenic conditionality of emergencies
4. Main funds in the economy
5. Human development index
Map of the index of the natural hazards of flooding
Map of the socio-economicvulnerability index
Map of flood risk
Map of the index of the natural hazards of flooding (N.Frolova and others, 2011, Russia)
Index of the natural hazards of flooding
Map of the sociol-economic vulnerability of the territory during floods (N.Frolova and others, 2011, Russia)
Socio-economic vulnerability index
Map of typological zoning of Russia on the degree of flood risk (N.Frolova and others, 2011, Russia)
Classes of flood riskLow risk
Insignificant risk
Average riskHigh risk
Very high risk
Extremely high risk
D=Dφ×θ ∑ Si Кi Pi
I – hazard level (1≤ i ≤3),Dφ×θ – damage coefficient for different types of damageSi – exposure area for each level of hazardКi – level of destruction coefficientPi – concentration coefficient:
ρi - density of population in each hazardous zoneρфон – density of population in the region, М – population of the region, mi – population in the zones of low (i=1), medium (i=2) and high (i=3) hazard
Сreg - net assets value of fixed production assets for year of census, n – years from census data, Ki – level of destruction coefficient.
Damage Asessment Methodology of Russian Emergency ministry
Destruction coefficients
Type of building
High level of destruction Medium level of destruction Low level of destruction
Depth, m
Velocity, m / s
Duration, hours
Depth, m
Velocity, m / s
Duration, hours
Depth, m Velocity,
m / sDuration,
hours
Brick buildings(1-3 stages)
4 2,5 170 3 2 100 2 1 50
Industry buildings with light metal
construction 5 2,5 170 3,5 2 100 2 1,5 50
Brick buildings (more than 4
stages)6 3 240 4 2,5 170 2,5 1,5 100
Industry massive construction
7,5 4 240 6 3 170 3 1,5 100
Integral aproach.Scheme for indicators collection
Exposure Vulnerability DamageSphere Dimension Spatial
objectsCost
parameters for damage
Susceptibility
Coping capacity
Adaptive capacity
I. Environment
Description: Name Indicator Level Source
II. Technosphere
Infrastructure
Fixed funds; industry and
serviceIII.
Sociosphere
Social-demographi
c EconomyPolitical-
administrative
Cultural
Database
• Data from the Russian Statistical Service (Rosstat) for municipal districts (local level), federal ministries, departments of Krasnodarsky region administration, and etc.
• More than 300 indicators for 14 municipal districts from 2007 to 2011 years
• Seasonal data
SphereDimension
Spatial objects Cost
parameters for damage
Susceptibility Coping
capacity Adaptive capacity
Name Indicator Name Indicator Name Indicator Name Indicator Name Indicator
I. Environment
Rare landscapes
Share of all area Ecological
capacity
Landscape recovery
time
Ecological enthusiast
s
Number of members
of ecological organizati
ons
Biodiversity
Concentration Index
for landscape
s
Wild animals
areas
Share of all area Ecological
capacity
Share of endangered species
Polluted area
Share of all area Pollution Ecologic
al fines Pollution
Quantity of
chemical fertilizers
Ecological investmen
t
Pollution
Number of waste
processing factories
DimensionSpatial objects
Cost parameters for damage Susceptibility
Coping capacity
Adaptive capacity
Name Indicator Name Indicator Name Indicator Name Indicator Name Indicator
II. Technosphe
re
Infrastructure
RoadsLength of improved
roadsRoads
Cost of kilometer
Susceptibility of different
roads
Share of improved
roads
Recovery crews
Share of population
DamsLength and
location
Water supply system
LengthWater supply
systemCost of
kilometer
Alarm systems
Number Bulk rollsLength and
location
Sewerage system
LengthSewerage
systemCost of
kilometer
Evacuation plans
Irrigation system
Area and location
Heating system
LengthHeating system
Cost of kilometer
Siren
networks
Hydro and meteorologic
al stations
Industry
Agricultural lands
Share of all area
Agricultural enterprises
Cost of fixed funds
Agricultural management
?
Share of different
crops
Susceptibility of different
crops
Share of susceptible
plants
Forest lands
Share of all area
Forest enterprises
Cost of fixed funds
Forest
management?
Share of different
trees
Susceptibility of different
trees
Share of susceptible
trees
Fixed funds
Fixed funds of industries
Industrial area
Funds Cost
Susceptibility of different
types of buildings
Share of susceptible buildings
Fixed funds of service
Service objects
Funds Cost
Susceptibility of different
types of buildings
Share of susceptible buildings
Fixed funds of dwellings
Dwellings area
Funds
Cost
Susceptibility of different
types of buildings
Share of fragile
dwellings
Sphere DimensionSpatial objects
Cost parameters for damage Susceptibility
Coping capacity
Adaptive capacity
Name Indicator Name Indicator Name Indicator Name Indicator Name Indicator
III. Sociosphere
Sociol-demographic
Population exposed to
hazardsPeople
Value of peoples life
? Susceptible
people
Share of old and young
people
Emergency crews
Share of population
EducationLevel of primary
education
Poor people
Percentage of population
with incomes below the
subsistence minimum
Emergency public crews
Number of participants in
voluntary groups for the protection of public order
Diversification of labour
market
Herfindahl–Hirschman
Index
Unemployme
nt rate
Income per
capita
Average monthly wages
Social
networks?
Economy
Industry enterprises
Volume of production
Cost of production
Sales of own-produced goods and services
Insurance Diversification of economy
IncomeIncome of
enterprises
Profits of budget
Share of different
sources of budget profits
The share of own revenues
of local budgets
Herfindahl–Hirschman
Index
Investment
Political-administrative
Medical service
Number of hospital bed per 10000 inhabitants
Administration efficiency
Time for building license
Number of physicians per
10000 inhabitants
Private health expenditure
?
Administratio
nSuspicious
transactions
Cultural
Susceptibility of different
nations
Share of migrants
VulnerabilitySusceptibility
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 0,33Lack 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
WorldRiskIndex approach. Selected indicators from database
I = (X - Xo)/(X*-Xo) (1) – monotonic increasing dependence
between variable X and index I
I =1-(Xo - X)/(X*-Xo) (2) – monotonic decreasing dependence
Xo – minimum of variable X among N municipal districts,
X* – maximum
Index I belongs to [0,1]
Unification of variable indicator X
MunicipalRiskIndex
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 0,55Sochi 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 0,77Eysky 0,10 0,16 0,65 0,67 0,66 0,63Anapa 0,13 0,28 0,47 0,49 0,36 0,56Krymsky 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 0,27Kalininsky 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
Future directions
1.Seasonal or day / night vulnerability
2. Damage estimation (Russian methodology) for case area
3. Workshop (elaboration of indicators)
4. Survey (verification of methodology, search for some indicators) on the case area
5. Experts‘ interviews (Emergency ministry, Hydrological service, Economic department of local government, etc.)
6. Resilience estimation (methodology, indicators, etc.)
Map from the GIS cadastral register. Temryuk city
Thank you for your attention!