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Developing Climate Resilient Flood and Flash Flood
Management Practices to Protect Vulnerable
Communities of Georgia – The Role of Risk Modelling in
the Development of Flood Insurance Model for Georgia
Dr. Margaretta Ayoung
Presented at: DRR financing regional conference
Istanbul, Turkey, 4-5th October 2018
Presentation Outline
• Project Overview
• Flood Hazard Modelling and
Mapping Approach
• Flood Socio-economic risk
Modelling
• Development of Weather Index
Insurance Model
• Lessons Learned
• Next Steps
Project Overview
Project Objective
“To improve resilience of highly exposed regions of Georgia to hydro-meteorological threats that are increasing in
frequency and intensity as a result of climate change.”
Risk Knowledge – hazard and risk
modelling and mapping
Floodplain
zoning policy
Flood resilient
building codes
Flood Insurance
Scheme
Structural
interventions
CB Adaptation
measures
Agro-forestry
schemes
Multi-hazard
Risk
Assessment
Rehabilitated
hydrometric
network
Flood
forecasting and
EWS
Integrated
Flood Risk
Management
Enhancing
legislative and
policy
framework
Technology
transfer and
capacity
building
FRM
intervention
measures
Enhanced
monitoring,
forecasting
and early
warning
systems
Improved
community
resilience
Flood Insurance Approach
• Hazard
Modelling
• Flood Mapping
• Flood Zoning
Stage 1 – Flood
Modelling
• Risk Score
Calculation
• Damage and Loss
Calculation
Stage 2 - Risk
Modelling • Risk Based
Premium Setting
• Index-based pay
out principles
Stage 3 - Insurance
Scheme
Stage 1 - Flood Modelling
EUFD
Methodology
• Directive 2007/60/EC
• Assess of risk from flooding, mapping of the
flood extent and assets and humans
Hydrological
Modelling
•Detailed rainfall-runoff modelling based on
hydrometric data from 1935-Present
•Combined with soil, geology, landuse data,
topography
Hydraulic
Modelling
•Detailed 1D-2D model - Mike Flood
•> 300 river cross-section surveys
•10m DEM of floodplain
Flood
Mapping
•2, 5, 10, 20, 50, 100, 100 + CC, 500, 1000 year
•Flood zones defined
Flood hazard
maps and
receptor
datasets
Receptor data
(people,
property,
Infrastructure,
agric etc.)
Socio-
economic data
Flood Risk to
People,
Agriculture,
Infrastructure,
etc
Socio-
economic risk
model
GIS based socio-economic risk model
A bespoke tool developed in ESRI’s ArcGIS Desktop environment encapsulating business logic and
utilising spatial analytical functions.
Stage 2 - Risk Modelling
Socio-economic Risk Score
Damage Flood Risk
Property
Risk
Agricultural
Flood Risk
Physical
Infra-
structure
Social
Rioni
River
Basin
Risk Score
Flood Risk Socio-economics
Stage 3 – Insurance Scheme
Weather Index Insurance (WII) - financial instrument to mitigate losses - replace the need for Government/Donor
intervention after flood events
Weather
Index
Insurance
Equates
premiums to
risk exposure
Compares
annual
average
anticipated
losses
River gauging
to confirm
flood levels
Works in
tandem with
new structural
measures
Flood
protection
improve lead
to lower flood
premiums
Works in
tandem with
flood zoning
and FFEWS
Community co-
operation is
vital to success
Risk-based premium setting
A B
Flood
Zone
Premium
Agricultural
CategorySize (ha)
Property
Category
Number
Affected
• Crop type (e.g. Vegetables, Wheat, etc)
• Yield
• Price
• Flood seasonality
• Small Residential
• Large Residential
• Apartment
• Commercial
• Designated Floodways
• Functional Flood plains
• High Risk Zone
Pay out Principles
Index
• River Gauges
• Flood zoning 2-5 confirmed
• Trigger payout
Payment
calculation
• Property - compensation
based on depth of flooding
for registered house type
• Agricultural yield loss
based on flood month for
registered crop
Payout
• Extensive consultations with private insurance companies, with
insurance association, government.
• Hesitation/scepticism in the beginning, especially from state agencies,
and more interest at a later stage
• Despite strong interest from the partner national institutions, piloting of
insurance scheme in Rioni basin did not take place during the lifecycle of
the UNDP Project
WII Consultation and Outcome
• Piloting of the Insurance scheme in Rioni basin did not take place during the
lifecycle of the UNDP Project for a number of reasons including:
• Political readiness - Insufficient political readiness to ‘push’ it forward.
Frequent changes and reforms within the Government are delaying the
processes, requiring from UNDP to revisit the topic, and advocate for
introduction on a regular basis
• Financial – Lack of financial commitment expected from the state (central
or municipal)
• Technical - Single peril insurance scheme and single geographic focus were
potential drawbacks; under-developed insurance culture - low awareness,
insufficient understanding and a general mistrust.
WII Lessons Learned
Disaster Risk Transfer Mechanisms in Georgia:
Challenges and Opportunities
Market share per insurance type (%) Government subsidized agri. insurance scheme
0
10
20
30
40
50
60
70
80
90
100
2010 2011 2012 2013 2014 2015 2016
Source: L. Shekasheli, Sh. Jadugishvili, 2017 Insurance Market Research 2010-2016
Health Property Land transport Life Civil liability Other
Disaster Risk Transfer Mechanisms in Georgia:
Challenges and Opportunities
Natural Hazard Loss Assessment and Recovery System:
• A flood insurance model was developed based on detailed hazard and
risk modelling as part of an IFRM framework
• Rioni project successfully scaled up – $27 Million GCF funding secured
• Nationwide project to address multi-hazards through policy
interventions including risk financing, development of a multi-hazard
early warning system, implementation of structural and non-
structural measures, strengthening of institutional capacity and
community adaptive capacity
• All hydro meteorological hazards and risks to be modelled and
mapped - basis of project interventions
• Provides to climate risk information basis for further development
and implementation of the insurance scheme
Conclusions & Next Steps
Thank you

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Developing Climate Resilient Flood Management in Georgia

  • 1. Developing Climate Resilient Flood and Flash Flood Management Practices to Protect Vulnerable Communities of Georgia – The Role of Risk Modelling in the Development of Flood Insurance Model for Georgia Dr. Margaretta Ayoung Presented at: DRR financing regional conference Istanbul, Turkey, 4-5th October 2018
  • 2. Presentation Outline • Project Overview • Flood Hazard Modelling and Mapping Approach • Flood Socio-economic risk Modelling • Development of Weather Index Insurance Model • Lessons Learned • Next Steps
  • 3. Project Overview Project Objective “To improve resilience of highly exposed regions of Georgia to hydro-meteorological threats that are increasing in frequency and intensity as a result of climate change.” Risk Knowledge – hazard and risk modelling and mapping Floodplain zoning policy Flood resilient building codes Flood Insurance Scheme Structural interventions CB Adaptation measures Agro-forestry schemes Multi-hazard Risk Assessment Rehabilitated hydrometric network Flood forecasting and EWS Integrated Flood Risk Management Enhancing legislative and policy framework Technology transfer and capacity building FRM intervention measures Enhanced monitoring, forecasting and early warning systems Improved community resilience
  • 4. Flood Insurance Approach • Hazard Modelling • Flood Mapping • Flood Zoning Stage 1 – Flood Modelling • Risk Score Calculation • Damage and Loss Calculation Stage 2 - Risk Modelling • Risk Based Premium Setting • Index-based pay out principles Stage 3 - Insurance Scheme
  • 5. Stage 1 - Flood Modelling EUFD Methodology • Directive 2007/60/EC • Assess of risk from flooding, mapping of the flood extent and assets and humans Hydrological Modelling •Detailed rainfall-runoff modelling based on hydrometric data from 1935-Present •Combined with soil, geology, landuse data, topography Hydraulic Modelling •Detailed 1D-2D model - Mike Flood •> 300 river cross-section surveys •10m DEM of floodplain Flood Mapping •2, 5, 10, 20, 50, 100, 100 + CC, 500, 1000 year •Flood zones defined
  • 6. Flood hazard maps and receptor datasets Receptor data (people, property, Infrastructure, agric etc.) Socio- economic data Flood Risk to People, Agriculture, Infrastructure, etc Socio- economic risk model GIS based socio-economic risk model A bespoke tool developed in ESRI’s ArcGIS Desktop environment encapsulating business logic and utilising spatial analytical functions. Stage 2 - Risk Modelling
  • 7. Socio-economic Risk Score Damage Flood Risk Property Risk Agricultural Flood Risk Physical Infra- structure Social Rioni River Basin Risk Score
  • 9. Stage 3 – Insurance Scheme Weather Index Insurance (WII) - financial instrument to mitigate losses - replace the need for Government/Donor intervention after flood events Weather Index Insurance Equates premiums to risk exposure Compares annual average anticipated losses River gauging to confirm flood levels Works in tandem with new structural measures Flood protection improve lead to lower flood premiums Works in tandem with flood zoning and FFEWS Community co- operation is vital to success
  • 10. Risk-based premium setting A B Flood Zone Premium Agricultural CategorySize (ha) Property Category Number Affected • Crop type (e.g. Vegetables, Wheat, etc) • Yield • Price • Flood seasonality • Small Residential • Large Residential • Apartment • Commercial • Designated Floodways • Functional Flood plains • High Risk Zone
  • 11. Pay out Principles Index • River Gauges • Flood zoning 2-5 confirmed • Trigger payout Payment calculation • Property - compensation based on depth of flooding for registered house type • Agricultural yield loss based on flood month for registered crop Payout
  • 12. • Extensive consultations with private insurance companies, with insurance association, government. • Hesitation/scepticism in the beginning, especially from state agencies, and more interest at a later stage • Despite strong interest from the partner national institutions, piloting of insurance scheme in Rioni basin did not take place during the lifecycle of the UNDP Project WII Consultation and Outcome
  • 13. • Piloting of the Insurance scheme in Rioni basin did not take place during the lifecycle of the UNDP Project for a number of reasons including: • Political readiness - Insufficient political readiness to ‘push’ it forward. Frequent changes and reforms within the Government are delaying the processes, requiring from UNDP to revisit the topic, and advocate for introduction on a regular basis • Financial – Lack of financial commitment expected from the state (central or municipal) • Technical - Single peril insurance scheme and single geographic focus were potential drawbacks; under-developed insurance culture - low awareness, insufficient understanding and a general mistrust. WII Lessons Learned
  • 14. Disaster Risk Transfer Mechanisms in Georgia: Challenges and Opportunities Market share per insurance type (%) Government subsidized agri. insurance scheme 0 10 20 30 40 50 60 70 80 90 100 2010 2011 2012 2013 2014 2015 2016 Source: L. Shekasheli, Sh. Jadugishvili, 2017 Insurance Market Research 2010-2016 Health Property Land transport Life Civil liability Other
  • 15. Disaster Risk Transfer Mechanisms in Georgia: Challenges and Opportunities Natural Hazard Loss Assessment and Recovery System:
  • 16. • A flood insurance model was developed based on detailed hazard and risk modelling as part of an IFRM framework • Rioni project successfully scaled up – $27 Million GCF funding secured • Nationwide project to address multi-hazards through policy interventions including risk financing, development of a multi-hazard early warning system, implementation of structural and non- structural measures, strengthening of institutional capacity and community adaptive capacity • All hydro meteorological hazards and risks to be modelled and mapped - basis of project interventions • Provides to climate risk information basis for further development and implementation of the insurance scheme Conclusions & Next Steps