Joseph Alcamo* Genady Golubev ** Nikolai Dronin** Marcel Endejan* Andrei Kirilenko***

1. A New Approach to Assessing Climate Change Impacts on Russian Agriculture and Water Resources Invited PaperWorld Climate Change ConferenceMoscow29 September – 3 October 2003 Joseph Alcamo* Genady Golubev ** Nikolai Dronin** Marcel Endejan* Andrei Kirilenko*** * Center for Environmental Systems Research, University of Kassel, Germany ** Department of Geography, Moscow State University *** Center for Ecology and Forest Production, Russian Academy of Science (currently, Purdue University, USA)

2. Objectives of Study An integrated assessment that takes a new approach to assessing climate change impacts on Russian agriculture and water resources ... • Focus on extreme climate events such as droughts. • Take into account food dependency of regions. • Uses a new type of integrated model – GLASS model integrates agriculture and water resources

3. 2 Climate models Climate scenarios Population, economic trends GLASS Model - WaterGAP model - GAEZ model Indicators of water use and availability Indicators of food security (frequency of bad harvest years) Indicators of crop production and trade Indicators of water security (frequency of runoff extremes) Food Geography Methodology 2 IPCC Scenarios (A2, B2)

4. GLASS Model:Taking into Account Extreme Climate Events • “Climate Variability Generator” • (Alcamo et al 2000) • Combine ... • historical climate variability (from global data base) with ... • decadal average climate change (from GCMs) • To produce new climate scenario with year-to-year variability

5. Assumptions of IPCC Scenarios for Russia (2025)

6. 0C 2020s Climate Change A2 Scenario 2070s HADCM3model

7. Part I. Climate Impacts on Water Resources

8. Computing Climate Impacts on Water Resources: the WaterGAP 2 Model • Water Availability • (by 0.5° grid-cell) • Runoff • Recharge WaterAvailability • Land Cover • Climate Watershed Water Stress • Population • Income • Technology • Climate • Water Withdrawals • Domestic(by country) • Industrial (by country) • Irrigation (by grid-cell) • Livestock (by grid-cell) Water Withdrawals

9. Testing the WaterGAP Model River Discharge of Volga at Volgograd (km3/a) Observed Computed

10. Water withdrawals in Russia Households Industry Agriculture 1995 A2 (2025) B2 (2025) (c) Center for Environmental Systems Research, University of Kassel, February 2003 – Water GAP 2.1D

11. Changes in Water Resources A2 Scenario 2020s Change in Annual Water Withdrawals (relative to 1995) Change in Annual Water Availability (relative to climate normal)

12. withdrawals availability

14. Main Points Climate Change & Water Resources Lower risk to water security ... • Under climate change, water becomes more plentiful. • Under some scenarios, withdrawals decrease almost everywhere Higher risk to water security ... • Under some scenarios, water withdrawals rapidly increase in North, Siberia, Far East  increasing pressure on water resources • Extreme events increase (low runoff in Southwest, high runoff in Siberia & the North) • Southwest already under severe water pressure (agricultural, industrial, domestic users) + increase in low runoff events  New water sources for irrigation projects? Water security problems?

15. Some Coping Strategies Climate Change & Water Resources “Supply-side”, for example: • Increase water storage. • Using lower quality water. • Build river dikes. • Construct floodways. “Demand-side”, for example: • Water conservation. • Reduce municipal, irrigation leakages. • Early warning systems for droughts and floods.

16. Part II. Climate Impacts on Food Production

17. Computing Climate Impacts on Potential Crop Production The “GAEZ” Model (Fischer et al., IIASA) • Computes potential production for a particular climate. • For prescribed climate conditions, can crop grow? (Uses existing knowledge). • If yes, then computes photosynthesis and respiration. • Adds in agricultural technology, and other factors. • Model tested against data around the world. • Tested with data from Central Chernozem region.

18. Production of Most Important Crop Average Production relative to current (%) A2 Scenario 2020s decrease increase 2070s Model: HADCM3 IPCC A2

19. Change in Total Russian Potential Grain Production (Relative to Current, %) Range: HADCM3 & ECHAM climate models

20. Strong Year-to-Year Variability of Crop Production

21. Extreme Climate Events and Food Production:Estimating Occurrence of“Bad Harvests” “Bad harvest” definition If potential production < 50% mean potential production (climate normal period) then “bad harvest”. For food importing regions: A harvest is “bad” if ... • Annual production is low in the food importing region, or • Annual production is low in the food exporting region, or both Production is weighted according to the percentage of food imported.

22. Main crop  50% grain export regions production

23. potential production in year x potential production long term average How to Take Into Account Food Dependency of Regions? Example: 1984 *Food stress = 1 -

24. Number of Years in Decade with Bad Harvests A2 Scenario HadCM Model

25. Number of Years in Decade with Bad Harvests A2 Scenario Comparison of Scenarios from 2 Climate Models Climate from Hadley Model Climate from Max Planck Model

26. Main Points Climate Change & Agriculture Lower risk to food security ... Climate becomes more favorable ... Small decrease or increase in total potential crop production up to 2020s Higher risk to food security ... • The South getting drier ... • Bad harvest years: Increase from 1 to 2 x per decade  2 to 3 x per decade • Because of reliance of Siberia, Far East, ... on South, bad harvests propagate throughout Russia. • People affected by 1 or more bad harvests per decade: • Now: 58 million • 2020s: 77 million • 2070s 141 million HADCM3 model, IPCC A2 scenario

27. Some Coping Strategies Climate Change & Agriculture Substitute crops rye  wheat, wheat  maize, potatoes  rye, Brings only slight yield increase? Expand rainfed crop area, But limited by bad soils & other costs Expand irrigated crop area -- Water resources already under severe pressure?. Diversification of crops Improving agricultural management Strategic food reserves – Storing surpluses Early warning systems – Combine climate prediction and expert knowledge Genuine free world trade for food-- A new ethic ... Take world food trade off the political agenda

28. Coping is Not the Only Strategy • Reducing greenhouse gases  slows down climate change. • Russia should: • Ratify the Kyoto Protocol. • Join with industrialized countries to stringently reduce emissions. • Encourage developing countries to slow down their emission increases.

29. What will be the Impacts of Climate Change on Food and Water Security in Russia?Conclusions Average changes may not be negative (increased water availability, better crop growing conditions) ... but climate change will generally not benefit Russia because ... Extreme events such as droughts will increase in frequency at sensitive locations and are possible threats to water and food security. A strategy is needed for coping with these threats.

30. A New Approach to Assessing Climate Change Impacts on Russian Agriculture and Water Resources Invited PaperWorld Climate Change ConferenceMoscow29 September – 3 October 2003 Joseph Alcamo* Genady Golubev ** Nikolai Dronin** Marcel Endejan* Andrei Kirilenko*** * Center for Environmental Systems Research, University of Kassel, Germany ** Department of Geography, Moscow State University *** Center for Ecology and Forest Production, Russian Academy of Science (currently, Purdue University, USA)

32. GLASS Model:Taking into Account Extreme Climate Events • “Climate Variability Generator” • (Alcamo et al 2000) • Combine ... • historical climate variability (from global data base) with ... • decadal average climate change (from GCMs) • To produce new climate scenario with year-to-year variability • Disadvantage • Assumes, e.g., 2020s have same year-to-year relative variability as in climate normal period. (But absolute variability, i.e. number of events, changes) • Advantage • Does not depend on GCM estimates of year-to-year variability (very uncertain) • Can simulate geographic extent of future droughts

33. Support for the Study Max Planck Society, Humboldt Foundation ... to support international cooperation. 2000 - 2002 Organizers: Joseph Alcamo, Genady Golubev Cooperating Organizations: • Center for Environmental Systems Research, University of Kassel, Germany • Department of Geography, Moscow State University • Center for Ecology and Forest Production, Russian Academy of Science

34. The Impacts of Climate Change on Food and Water Security in Russia Methodology Climate models Emission trends IPCC Scenarios Historical climate variability Population, economic trends Climate scenarios Water withdrawals Water availability Extremes of river runoff GLASS Model - WaterGAP model - GAEZ model Future climate variability • Area affected: • by severe pressure on water resources • by increasing extremes of runoff • Area affected • by bad harvest years • Number of people affected by bad harvest years. Potential crop production Import/export between regions • Analysis of Food Geography • Food import/export • Consumption patterns

37. “Food stress” = deviation of potential production in year x from long term average Total stress in region = (1-a) “Local” stress (local crop production) + a “External” stress (stress in food exporting region) a = share of total food consumed in region that is imported

38. “Food stress” = deviation of potential production in year x from long term average Total stress in region = (1-a) “Local” stress (local crop production) + a “External” stress (stress in food exporting region) a = share of total food consumed in region that is imported

39. How to Take Into Account Food Dependency of Regions? Example: 1984 *“Food stress” = deviation of potential prodution in year x from long term average

40. “Food stress” = deviation of potential production in year x from long term average 1994Stress in Export Regions = 0,05