Download - UKRAINIAN AGRICULTURAL WEATHER RISK MANAGEMENT WORLD BANK COMMODITY RISK MANAGEMENT GROUP
UKRAINIAN AGRICULTURAL WEATHER
RISK MANAGEMENT
WORLD BANK COMMODITY RISK MANAGEMENT GROUP
Ulrich HessJoanna Syroka PhD
January 20 2004
UKRAINIAN AGRICULTURAL WEATHER
RISK MANAGEMENT
WORLD BANK COMMODITY RISK MANAGEMENT GROUP
IFC PEP Ukraine
Ulrich HessJoanna Syroka PhD
January 22 2004
Developments in Flood Index Insurance
COMMODITY RISK MANAGEMENT GROUPThe World Bank
December 2007
ERIN BRYLABased on work by William Dick, Alex Lotsch, and Ornsaran
Manuamorn
Flood is the major natural risk impacting GDP
Flood is a key risk in South East Asia
World Bank interest in flood World Bank has a focus on disaster relief and
reduction and one of the major issues is the risk of flood
The World Bank hotspot analysis identifies four major areas as flood prone including:
South/Central America Southern/Eastern Europe South East Asia South Asia
Primary interest is in poverty reduction and agriculture is key
There is a need to expand applications of flood insurance from property to agriculture
WB is developing innovative instruments to help farmers and agricultural banks to manage flood risk
New products harness technology including flood modeling and remote sensing
Focus on flood modeling
FLOOD MODELING
FLOOD WARNING
FLOOD MITIGATION
INSURANCE FOR PROPERTY
INSURANCE FOR
AGRICULTURE
FLOOD MANAGEMENT
Property catastrophe facility: example of Romania
WB assisting in development of Romanian Catastrophe Insurance Program
• Earthquake and flood
• National flood risk modeling and vulnerability/asset assessment
• Addition of cat perils to conventional property policies
Source: RMSI
Clients for agricultural flood insurance
Micro level insurance product Insured is the individual farmer, or a group of
farmers, in homogenous risk areas A micro product would identify flooded areas at high
resolution and reduce basis risk Challenge: can flood risk zones, and flood loss
assessment, be developed to allow micro insurance product ?
Macro level insurance product Insured is a holder of aggregate risk, e.g. agricultural
bank, micro-finance organisation, or processor Index based on wider indicator of flood, e.g. river
gauge data Aggregator sets rules for application of claims
payouts
Example Flood Risk Management for Agriculture: Implementing Index
Insurance Challenge
Design an alternative, efficient and cost-effective crop failure insurance program that facilitates risk transfer and is feasible for small farmers in low-income countries.
Index Insurance Suited to some widespread catastrophe perils Overcomes many problems of traditional insurance Main shortcoming is “basis risk”
Index insurance experience to date Mainly for drought risk (rainfall deficit index) Micro applications - individual farmer contracts Limited macro experience for aggregate risk transfers Not developed yet for flood insurance
Index Based Flood - Work in Progress
Thailand – CRMG technical assistance- Pasco Study 2006- Flood index – additional development in progress
Vietnam- ADB funded development project leading to macro product design for agricultural bank- CRMG collaborating for implementation of pilot
Bangladesh - CRMG- Feasibility study undertaken 2006
Technical study – CRMG and subcontractors- Product design, underwriting, loss assessment and technical requirements
Conceptual approach
Test parametric approach for flood Design flood index to proxy crop losses Harness technology to support insurance
underwriting and operation Flood Modeling (FM) Earth Observation (EO) Geographic Information Systems (GIS)
Design a flood index to proxy losses caused to crop
In Thailand rice has been chosen as the strategic crop most exposed to flood
Flood impact is dependent on variety, time of occurrence, depth and duration of flood water
Combining the Technology Components
FM+EO+GIS Define flood risk zones and pricing, farm locations
FM + AMM Design a flood index that proxies rice loss
EO+ GIS Loss adjustment for payout determination according to the index
IND
EX
DE
SIG
NO
PE
RA
TIO
NA
L P
HA
SE
Steps in product design
1. Defining the Hazard FM: define the flood risk zones EO: validate FM output with archive EO imagery
2. Defining the Vulnerability AMM: flood parameters and extent of yield loss according
to crop growth phase and planting date
3. Design options for index phases and payouts Design index thresholds, incremental payouts, limits Economic data: Review the required insured values
(production cost or output values) by crop phase
4. Pricing the index FM: time series of flood extent and duration for each zone
5. Validating the index Correlate against other known damage or yield data
Objectives of Flood Analysis
Support design of ‘mircro’ insurance scheme
Simulate historical floods Define flood risk zones Define critical rainfall
levels Agric. loss assessment
with remote sensing
“High Risk” Pricing Zone
“Medium Risk” Pricing Zone
Pasak
River
LA4
LA2
LA3
LA1
LA5
“Low Risk” Pricing Zone
Petchaboon
Risk Zoning for Pricing and Loss Adjustment
Flood Detection using Satellites
Land Use Stratification
Surface water estimates
Inundated Paddy
A PROTOTYPE FLOOD INDEX
Payout Index
Days of inundation of 60 cm. flood
Yield Damage
3 days No damage
4 days 20% loss
5 days 60% loss
6 days 80% loss
7 days 100 % loss
Claim Eligibility Trigger
One time excess of “Bench Mark Level” at 115.89 cm. at the Pasak River Water
Gauge station (ID: S4:B)
OR177 mm. from average 4 day rainfall at 3 stations
(Upper: 379002; Middle: 379401; Lower: 379201)
Data Requirements: How Met Office Can HelpData Needs (Source, years,
integrity)
Flood Modeling Historical rainfall data, real time data feeds from gauges throughout catchments
Agro-meteorological Modeling Reliable crop models, including damage factors from flood
Earth Observation Historical satellite data series (in order to validate the modeling), timely post event definition of extent and duration of flooding
GIS Geo-referencing databases of insured households to allocate to flood risk zones
CHALLENGES Flood Risk Zoning --Using
a flood model to zone flood risk for insurance pricing on agricultural land
Validation of Model -- Creating objective methods which are acceptable for international risk transfer to reinsurers (e.g. river gauges, or earth observation)
Modeling Flood Risk -- Complexity of flood risk and flood modeling (inundation flood, cyclone/coastal flood, flash flood…)
Digital Terrain Data Hydro-meteorological and
streamflow data Computation and Model
Choice
Meet needs for flood insurance for agriculture
Could provide insurance to smaller farmers and businesses
Could support objective disaster payments outside formal insurance
Settlement could made on an objective trigger (EO)
The cost of reaching farmers drops significantly
BENEFITS