UKRAINIAN AGRICULTURAL WEATHER RISK MANAGEMENT WORLD BANK COMMODITY RISK MANAGEMENT GROUP Ulrich Hess Joanna Syroka PhD January UKRAINIAN AGRICULTURAL WEATHER RISK MANAGEMENT WORLD BANK COMMODITY RISK MANAGEMENT GROUP IFC PEP Ukraine Ulrich Hess Joanna Syroka PhD January Review of Weather Index Insurance Project Developments in Thailand World Bank Bangkok Office Seminar October 13, 2006 By Ornsaran Pomme Manuamorn The Commodity Risk Management Group

 Overall Thailand Project Background  Drought Index Insurance for Maize, Pak Chong  Flood Index Insurance for Rice, Petchaboon OUTLINE

Overall Thailand Project Background

WHY WEATHER RISK MANAGEMENT FOR THAILAND?  Importance of agriculture  Vulnerability to hydro-meteorological risks  Ranked among the top 6 countries in the world affected by floods; also frequent droughts (EM-DAT,OFDA/CRED)  Burden on public resources  Between , MOF spent approximately $102 million on ad-hoc disaster relief  Strong agricultural bank  BAAC reaches over 80% of farm households  Growing insurance sector  Over 70 non-life insurance companies with $1.3 billion in gross written premium (2003) and 54% loss ratio  Good weather data infrastructure  118 synoptic stations, 1025 rainfall stations, and 34 agro-meteorological stations  Strong interest from stakeholders

PILOT PROJECT STATUS 2006  There are 2 pilot locations for 2006  Pak Chong District, Nakorn Ratchasrima Crop: Maize Peril: Drought  Muang District, Petchaboon Crop: Rice Peril: Flood

PROJECT MODEL  Bank-intermediated weather insurance contracts to farmers Insurance Company/ Syndicate Global Reinsurance Companies Reinsurance treaty Thailand International Farmers Weather insurance contracts Agricultural Bank Contractual relationship (risk transfer, services, operations etc.)

Project Components Technical Financial Regulatory BAACExpertsGIAGIA/DOI Risk Identification/Marketing/ Operationalization Risk Quantification (Indexing) Policy Drafting/Pricing/Risk Transfer Product Approval Operational Design process TA to players Facilitate Implementation

Drought Index Insurance for Maize

8 Tambons PAK CHONG –The PILOT AREA Pak Chong Agrometeorological Station: ID ,000 rais of maize

Crop Calendar and Rainfall Pattern Pak Chong – Maize Crop Calendar Second Crop Pilot

The Maize Contract Coverage Period 11 dekads = 110 days Seeding Emergence The Main Production Cycle Once the rainfall of 25 mm has been received within 3-5 days during July 20- September 7 Phase One Phase Two Phase ThreePhase Four Seedlings/ Knee Height Physiological Maturity Harvest 3 dekads2 dekads3 dekads No RiskDrought Risk Current Contract Period: July 26 – Oct 14, 2006

The Pak Chong Maize Rainfall Index Reference Station Pak Chong Agrometeorologi- cal Station (ID ) Phase 1Phase 2Phase 3 Seedling Emergence to Knee High ( ช่วงปลูก ) Knee Height ( ช่วงเริ่มเติบโต ) Physiological Maturity ( ช่วงออกดอก ออกหัว ) Days Trigger (mm.) Exit (mm.) Tick size (Baht/mm./rai) 4221 Sum Insured (Baht/rai) 1,2001,6001,700

The Payout Structure Rainfall (mm) Payout (Baht) Phase 1 Phase 2 Phase Pure Risk Premium = 3%

Comparing the Rainfall Index With Historical Rainfall Historical Average Rainfall between July 20-Sept 29 (37 years) TriggerExit Phase mm.35 mm. (28%) 15 mm. (12%) Phase mm.50 mm. (43%) 20 mm. (17%) Phase mm.60 mm. (26%) 30 mm. (13%) The contract provides coverage only for a very serious drought

Pak Chong Historical Maize Yield,

Payout Performance of the Current Rainfall Index

Farmer Education

Approximately 110 farmers and 5000 rais of maize enrolled during the 2006 “dry run” pilot

Phase One: 71.4 mm. Phase Two: mm. Phase Three: mm. Rainfall between July 26- October 8, 2006

Possible Revisions of the Drought Index  Integrate farmer feedback during the dry-run  Introduce dynamic starting date  Include more weather stations  Cover water stress in addition to catastrophic drought (i.e. more generous triggers and exits)  Introduce rainfall caps: minimum and maximum  exclude daily run-off rainfall from the index calculation  capture rainfall distribution within a given phase

Flood Index Insurance for Rice, Petchaboon

Project Highlights  First project to apply the index approach to flood risk  New methodological development  Application of technology for insurance underwriting and operation Flood Plain Modeling (FM) Agro-meteorological Modeling (AMM) Earth Observation (EO) Geographical Information System (GIS)  Attempted balance between vision and practicality  Attempted balance between technicality and simplicity  Significant upfront research activities with medium-term pilot potential

Objectives of Current Research Activity 1. Define the Hazard - Identify major insurable flood risk - Identify flood risk zones 2. Define the Vulnerability - Identify critical period for insurance coverage - Identify the extent of crop loss during the insured period 3. Design options for index, phases and payouts 4. Design an operational system for the program 5. Price the index 6. Validate the index  Correlate against other known damage or yield data

1. Define the Hazard – River Flood 17 Tambons 200,000 rais of rice

2. Define the Vulnerability - the Pre-Harvest Period Not Flood-prone Season Flood-prone season Land Preparation PlantingGrowth Stage (Germination  Vegetative) Growth Stage 2 (Flowering) Growth Stage 3 (Harvest) Late May- June * June 1-July 1July 2 – Mid- August Mid-August – Mid Oct Mid-October onwards * Land preparation could be assumed to have started once 3 day-accumulative rainfall of 40 mm. is received after the rainy season has started in May

3. Design the Index – the Prototype Duration Index Payout Index Days of inundation of 60 cm. flood Yield Damage 3 daysNo damage 4 days20% loss 5 days60% loss 6 days80% loss 7 days100 % loss Claim Eligibility Trigger One time excess of “Bench Mark Level” at cm. at the Pasak River Water Gauge station (ID: S4:B) OR 177 mm. from average 4 day rainfall at 3 stations (Upper: ; Middle: ; Lower: )

4. Design an Operational System – Using EO for Loss Assessment

Non Flood-prone Waiting Period (80 days ) Flood-prone Season ( 35 days) Sales Time Contract Coverage Period 3 day accumulative rainfall of 25 mm. is received = “Official Contract Inception Date” A Flood Event (60 cm. inundation of 4 days or more) of 4 days or more) Claims eligible period 80 days One time excess of “Bench Mark Level” at at reference river gauge OR 177 mm. of average 4 day-rainfall at three stations Claims Eligibility Trigger EO Capture

Summary of Phase 1 Research Results 1) Preliminary understanding of a major potentially insurance flood risk in Petchaboon  Use Rainfall-Runoff Model to simulate streamflow in Pasak catchment area  Validate the simulated streamflow with river gauge observations  Use Inundation/Flood Plain Model to simulate inundation in flood plain for 2002  Cross-validate the simulated inundation with satellite-based observations of flood extent  Estimate (a) critical water levels at Pasak river gauge and (b) critical accumulated rainfall in catchment 2) Preliminary prototype product 3) Vision of objective loss assessment using remote sensing (radar data)

Outstanding issues  Flood Risk Zoning  Digital terrain data insufficient to model flood properties at farm/village/tambon level  Frequency analysis using longer hydro-meteorological records  Model validation  Segmentation of risk  Mitigation of seasonal flood risk  Extreme events and risk exposure  Human intervention in flood risk  Transferability to other watersheds  Operationalization of EO-based loss adjustment

Outstanding issues  Flood Risk Zoning  Digital terrain data insufficient to model flood properties at farm/village/tambon level  Need to conduct requency analysis using longer hydro- meteorological records  Model validation  Pricing of the insurance contract  Segmentation of risk  Mitigation of seasonal flood risk  Extreme events and risk exposure  Human intervention in flood risk  Transferability to other watersheds  Operational issues of EO-based loss adjustment

Proposal for Next Steps  Investigate additional/alternative data sources to improve flood modeling and flood zoning in Petchaboon (shorter-term)  Research on flood plain modeling (longer-term)  Study flood risk mitigation strategies in the region  Review alternative approaches for design of flood insurance scheme with insufficient data  Evaluate implications for technology transfer to other watersheds  Produce technical paper (targeted summer 2007)

Proposal for Next Steps  Investigate additional/alternative data sources to improve flood modeling and flood zoning in Petchaboon (shorter-term)  Research on flood plain modeling (longer-term)  Study flood risk mitigation strategies in the region  Review alternative approaches for design of flood insurance scheme with insufficient data  Evaluate implications for technology transfer to other watersheds  Produce technical paper (targeted summer 2007)