UKRAINIAN AGRICULTURAL WEATHER RISK MANAGEMENT WORLD BANK COMMODITY RISK MANAGEMENT GROUP Ulrich Hess Joanna Syroka PhD

1. UKRAINIAN AGRICULTURAL WEATHER RISK MANAGEMENT WORLD BANK COMMODITY RISK MANAGEMENT GROUP Ulrich Hess Joanna Syroka PhD January 20 2004 UKRAINIAN AGRICULTURAL WEATHER RISK MANAGEMENT WORLD BANK COMMODITY RISK MANAGEMENT GROUP IFC PEP Ukraine Ulrich Hess Joanna Syroka PhD January 22 2004 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

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

3. Overall Thailand Project Background

4. 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 1995 -1999, 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

5. 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

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

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

8. Drought Index Insurance for Maize

9. PAK CHONG –The PILOT AREA Pak Chong Agrometeorological Station: ID 431301 8 Tambons 320,000 rais of maize

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

11. The Maize Contract Coverage Period Drought Risk No Risk 11 dekads = 110 days Current Contract Period: July 26 – Oct 14, 2006

12. The Pak Chong Maize Rainfall Index

13. 1700 840 630 630 The Payout Structure 2400 Pure Risk Premium = 3% 2000 Phase 1 Phase 2 Phase 3 1600 Payout (Baht) 1200 800 400 0 60 0 15 20 25 30 35 40 45 50 55 Rainfall (mm)

14. Comparing the Rainfall Index With Historical Rainfall The contract provides coverage only for a very serious drought

15. Pak Chong Historical Maize Yield, 1992-2005

16. Payout Performance of the Current Rainfall Index

17. Farmer Education

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

19. Rainfall between July 26-October 8, 2006 Phase One: 71.4 mm. Phase Two: 152.6 mm. Phase Three: 171.2 mm.

20. 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

21. Flood Index Insurance for Rice, Petchaboon

22. 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

23. 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

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

25. 2. Define the Vulnerability - the Pre-Harvest Period * 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

26. 3. Design the Index – the Prototype Duration Index

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

28. 80 days Claims eligible period 3 day accumulative rainfall of 25 mm. is received = “Official Contract Inception Date” One time excess of “Bench Mark Level” at 115.89 at reference river gauge OR 177 mm. of average 4 day-rainfall at three stations Claims Eligibility Trigger EO Capture Time Contract Coverage Period Sales A Flood Event (60 cm. inundation of 4 days or more)

29. Summary of Phase 1 Research Results • 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)

30. 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

31. 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

32. 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)

33. 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)