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1 Vulnerability and Adaptation Assessment Agriculture Sector Jakarta, Indonesia 23 March 2006 Ana Iglesias Universidad Politécnica de Madrid.

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Presentation on theme: "1 Vulnerability and Adaptation Assessment Agriculture Sector Jakarta, Indonesia 23 March 2006 Ana Iglesias Universidad Politécnica de Madrid."— Presentation transcript:

1 1 Vulnerability and Adaptation Assessment Agriculture Sector Jakarta, Indonesia 23 March 2006 Ana Iglesias Universidad Politécnica de Madrid

2 2 Objective To provide participants with information on V&A assessment for the agriculture sector A general discussion on the impacts of climate variability and change on agriculture and food security Methods, tools and issues to assess V&A PC based training on methods, tools, issues

3 3 Outline 1.Climate variability and change, agriculture and food security (½ h) 2.Key differential vulnerabilities (½ h) 3.Key issues (½ h) 1.Integration and cooperation (social, water) 2.Calibration 3.Extreme events 4.Uncertainties 4.PC based training: Models, assisting tools for stakeholders, risk management (3 h) 1.Designing the framework (½ h) 2.Participatory evaluation and prioritization of adaptation (½ h) 3.PC based training (2 h) Total: (4 ½ h)

4 4 Agenda 9:15 – 10:451.Climate variability and change, agriculture, and food security 2.Key differential vulnerabilities 3.Key issues 10:45 – 11:00Coffee 11:00 – 12:304.Models, assisting tools for stakeholders, risk management 1.Designing the framework 2.Participatory evaluation and prioritization of adaptation 12:30 – 13:30Lunch 13:30 – 15:004.Models, assisting tools for stakeholders, risk management 3.PC based training

5 5 Climate, agriculture, and food security Climate change is one stress among many affecting agriculture and the population that depends on it

6 6 Observations: Increased drought Persistent drying trend in parts of Africa has affected food production, including freshwater fisheries, industrial and domestic water supplies, hydropower generation (Magazda, 1986; Benson and Clay, 1998; Chifamba, 2000; Iglesias and Moneo, 2005) Maize production, Zimbabwe

7 7 Drought in the Mediterranean Q/ha Cereal Yields Source: R. Mougou, INRGREF Correlation betwen total rainfall and agricultural production r= mm 624mm Kairouan (Tunisia) Rainfall

8 8 Drought in the Mediterranean Source: Iglesias and Moneo, 2004

9 9 Longer growing seasons … In Australia, climate change appears to have increased wheat yield by about 10 to 20% since 1952 (Nicholls, 1997)

10 10 Multiple interactions, vulnerability and adaptation Social vulnerability Climate change Economic, social, demographic, land use changes Systems and social groups that need to adapt

11 11 Social vulnerability “Starvation is the characteristic of some people not having enough food to eat. It is not the characteristic of there being not enough food to eat. While the later can cause the former, it is but one of many possible causes.” A. Sen, Poverty and Famines, An Essay on Entitlement and Deprivation, 1981, pg 1

12 12 Multiple interactions: Stakeholders define adaptation Scientists Policy makers Civil stake- holders

13 13 Concepts are important: The big picture … Conclusions for policy Models Assumptions Data Theory

14 14 Agriculture: empirical evidence

15 15 Source: Wei Xiong, Erda Lin, Xiu Yang, et al., 2006

16 16 Possible benefits Possible drawbacks

17 17 Weeds, pests and diseases Weeds, pests, and diseased damage about one half of the potential production every year

18 18 Climate change affects crop production Changes in biophysical conditions Changes in socio-economic conditions in response to changes in crop productivity (farmers’ income; markets and prices; poverty; malnutrition and risk of hunger; migration)

19 19 Percentage change in average crop yields for the Hadley Center global climate change scenario (HadCM3). Direct physiological effects of CO 2 and crop adaptation are taken into account. Crops modeled are: wheat, maize, and rice. Source: NASA/GISS; Rosenzweig and Iglesias, 2002; Parry et al, s 2050s 2080s Yield Change (%) How might global climate change affect food production?

20 20 Limits to adaptation Technological limits (i.e., crop tolerance to water-logging or high temperature; water reutilization) Social limits (i.e., acceptance of biotechnology) Political limits (i.e., rural population stabilization may not be optimal land use planning) Cultural limits (i.e., acceptance of water price and tariffs)

21 21 Developed-Developing country differences ScenarioA1FIA2aA2bA2c B1aB2b CO2 (ppm) World (%) Developed (%) Developing (%) Developed- Developing) (%) Potential change (%) in national cereal yields for the 2080s (compared with 1990) using the HadCM3 GCM and SRES scenarios ( Parry et al., 2004)

22 22 Additional people at risk of hunger Parry et al., Additional Millions of People A2 - Regional Enterprise B2 - Local Stewardship

23 23 Interaction and integration: Water Population (millions) Additional population under extreme stress of water shortage University of Southampton

24 24 Conclusions While global production appears stable, regional differences in crop production are likely to grow stronger through time, leading to a significant polarization of effects, with substantial increases in prices and risk of hunger amongst the poorer nations Most serious effects are at the margins (vulnerable regions and groups)

25 25 Agenda 9:15 – 10:451.Climate variability and change, agriculture, and food security 2.Key differential vulnerabilities 3.Key issues 10:45 – 11:00Coffee 11:00 – 12:304.Models, assisting tools for stakeholders, risk management 1.Designing the framework 2.Participatory evaluation and prioritization of adaptation 12:30 – 13:30Lunch 13:30 – 15:004.Models, assisting tools for stakeholders, risk management 3.PC based training

26 26 Key differential vulnerabilities Climate change is one stress among many now affecting agriculture and the population that depends on it Integration of results and stakeholder definition of adaptation strategies are essential to formulate assessments relevant to policy Potential future consequences depend on: The region and the agricultural system [Where?, The baseline is important] The magnitude [How much? Scenarios are important] The socio-economic response [What happens in response to change? Adaptive capacity (internal adaptation) and planned stakeholder adaptation and policy]

27 27 Map of the night-time city lights of the world (DMSP: NASA and NOAA) Where? Systems and social groups

28 28 How much? Climate and SRES scenarios Precipitation change Temperature change Had CM2 model, 2050s

29 29 What happens in response to change? Adaptive capacity (internal adaptation) Planned adaptation

30 30 Definition of key vulnerabilities Expert judgement Stakeholder consultation Empirical evidence Scientific knowledge of processes Models are assisting tools

31 31 Check list and ranking of potential vulnerabilities - Examples Components of the farming system particularly vulnerable Stress on water/irrigation systems Domestic agricultural production Food shortages that lead to an increase in hunger Agricultural exports Prices to consumers Government policies such as agricultural pricing, support, research and development Greater stress on natural resources or contribute to environmental degradation (e.g., through land-use change, soil degradation, changes in water supply and water quality, pesticide use, etc.) Research/extension system capability for providing adaptation advice to farmers Technological options in place

32 32 Key vulnerabilities Individuals particularly vulnerable to environmental change are those with …. Relatively high exposures to changes High sensitivities to changes Low coping and adaptive capacities Low resilience and recovery potential Who can adapt? Who is vulnerable?

33 33 Agenda 9:15 – 10:451.Climate variability and change, agriculture, and food security 2.Key differential vulnerabilities 3.Key issues 10:45 – 11:00Coffee 11:00 – 12:304.Models, assisting tools for stakeholders, risk management 1.Designing the framework 2.Participatory evaluation and prioritization of adaptation 12:30 – 13:30Lunch 13:30 – 15:004.Models, assisting tools for stakeholders, risk management 3.PC based training

34 34 Key issues Integration and cooperation (social, water) Calibration Extreme events Uncertainties

35 35 Key issues: Pressures and solutions Water Population Economic and social development Technology (water desalination, reuse, efficiency) Agricultural technology Cooperation Improved management

36 36 Water

37 37 Population

38 38 Economic and social development

39 39 Integration and cooperation Population (millions) Source: University of Southampton Additional population under extreme stress of water shortage

40 40 Water The agriculture sector needs water supply scenarios Policy defines how much water can be used by agriculture Water policy and rights are extremely hard to change

41 41 Water conflicts

42 42 Water can lead to political hostilities and many regions with political conflicts also share water resources Transboundary surface and groundwater

43 43 Political and cultural process Source: EEA, CEDEX The political process reflects the view about future of the resources and economies, therefore defines the range of adaptation options Cultural impediments to change traditional water management add complexity to the design of adaptation strategies

44 Current and projected water demand (%) Drinking Irrigation Tourism Industrial Tunisia: National strategy on water management (Source: R. Mougou) Resources management Mobilization, storage (over 1,000 hill reservoirs in 10 years), and transfer of the resources Use of the non conventional resources: saline and waste water for irrigation (95,400 and 7,600 ha) Desalinization Demand management Water saving in irrigation (up to 60% Government subsidies)

45 45 Example: Integrated assessment in Egypt Source: El-Shaer et al., 1997; Strzpek et al., 1999 Aim Analysis of no regret options for the future Current vulnerability Dependence on the Nile as the primary water source Large traditional agricultural base Long coastline already undergoing both intensifying development and erosion Problems derived from population increase Agriculture entirely based on irrigation (water from the Nile, and to lesser degree from groundwater) Soil conditions and water quality deteriorating

46 46 Cooperation and integration Your expert opinion, consultation ……

47 47 Calibration of models This afternoon Documentation

48 48 Extreme events Your expert opinion, consultation …… Large knowledge based on risk management of natural disasters Empirical evidence is essential (external shock, impacts, vulnerability)

49 49 Uncertainties Your expert opinion, consultation …… Climate change scenarios Climate variability Stakeholder adaptation Agricultural models Effects of CO2 on crops Issues of scale Socio economic projections

50 50 Thanks for your attention! Visit MEDROPLAN on the web

51 51 Agenda 9:15 – 10:451.Climate variability and change, agriculture, and food security 2.Key differential vulnerabilities 3.Key issues 10:45 – 11:00Coffee 11:00 – 12:304.Models, assisting tools for stakeholders, risk management 1.Designing the framework 2.Participatory evaluation and prioritization of adaptation 12:30 – 13:30Lunch 13:30 – 15:004.Models, assisting tools for stakeholders, risk management 3.PC based training

52 52 The process: Example Set up a Multidisciplinary Stakeholder Team (Organizational component) Set up a Multidisciplinary Stakeholder Team (Organizational component) Evaluate the legal, social, and political process (Organizational component) Evaluate the legal, social, and political process (Organizational component) Identify risk and potential vulnerabilities (Methodological component) Identify risk and potential vulnerabilities (Methodological component) Select and identify priority actions, based on agreed criteria (Operational component) Select and identify priority actions, based on agreed criteria (Operational component) Public review and Revision Public dissemination (Operational component) Public review and Revision Public dissemination (Operational component)

53 53 Agenda 9:15 – 10:451.Climate variability and change, agriculture, and food security 2.Key differential vulnerabilities 3.Key issues 10:45 – 11:00Coffee 11:00 – 12:304.Models, assisting tools for stakeholders, risk management 1.Designing the framework 2.Participatory evaluation and prioritization of adaptation 12:30 – 13:30Lunch 13:30 – 15:004.Models, assisting tools for stakeholders, risk management 3.PC based training

54 54 Bottom-up stakeholder adaptation Objective of the strategy: To minimize impacts of a warmer and drier climate while maintaining rural agricultural production and minimizing the environmental damage Consideration of effectiveness to minimize the impacts of a warmer and drier climate, cost, and feasibility Adequacy for situation without climate change (win-win strategy)

55 55 Bottom-up stakeholder adaptation Possible tool: MCA WEAP

56 56 Bottom-up stakeholder adaptation Surveys: Adaptation to climate change in Tunisia, Source: R. Mougou

57 57 Bottom-up stakeholder adaptation Stakeholder group Adaptation Level 1 Adaptation Level 2 Adaptation Level 3 Small-holder farmers or farmers' groups Tactical advice on changes in crop calendar and water needs Management of risk in water availability (quantity and frequency) Education on water-saving practices and changes in crop choices Commercial farmers Tactical on improving cash return for water and land units Investment in irrigation technology; Risk- sharing (e.g., insurance) Private sector participation in development of agro-businesses Resource Managers Education on alternatives for land and water management Integrated resource management for water and land Alternatives for the use of natural resources and infrastructure

58 58 Water harvesting Source: T. Oweis, 2004

59 59 Bottom-up stakeholder adaptation Examples 1.Tactical advice crop calendar 2.Tactical advice water needs 3.Improve cash return for water and land units 4.Management of risk in water 5.Investment 6.Integrated resource management for water and land 7.Education 8.Private sector participation 9.Alternatives for the use of natural resources and infrastructure 10.Crop residue incorporation 11.Access to fertilizer 12.Extension services 13.Indigenous knowledge 14.Short-duration varieties 15.Crop diversification 16.New crop varieties 17.New crops 18.Agroforestry 19.Food storage 20.Agrometeorological advice 21.Construction of a dam 22.Irrigation (new scheme) 23.Irrigation (improved system) 24.Water harvesting 25.Water desalination / reutilization 26.Cease activity

60 60 Example: Use MCA WEAP

61 61 Agenda 9:15 – 10:451.Climate variability and change, agriculture, and food security 2.Key differential vulnerabilities 3.Key issues 10:45 – 11:00Coffee 11:00 – 12:304.Models, assisting tools for stakeholders, risk management 1.Designing the framework 2.Participatory evaluation and prioritization of adaptation 12:30 – 13:30Lunch 13:30 – 15:004.Models, assisting tools for stakeholders, risk management 3.PC based training

62 62 Assisting tools to stakeholders Need quantitative estimates Models are assisting tools Surveys to stakeholders are assisting tools for designing bottom-up adaptation options Key variables for agronomic and socio- economic studies: crop production, land suitability, water availability, farm income, …

63 63 Before getting started …. Models are assisting tools, stakeholder participation is essential The use of models requires high degree of technical expertise The merits of each model and approach vary according to the objective of the study, and they may frequently be mutually supportive Therefore, a mix of tools and approaches is often the most rewarding

64 64 Quantitative methods and tools Experimental Analogues (spatial and temporal) Production functions (statistically derived) Agro-climatic indices Crop simulation models (generic and crop- specific) Economic models (farm, national, and regional) – Provide results that are relevant to policy Social analysis tools (surveys and interviews) – Allow the direct input of stakeholders (demand- driven science), provide expert judgment Integrators: GIS

65 65 Experimental Value Spatial scale of resultsSeason to decades Time to conduct analysisSite Data needs4 to 5 Skill or training required1 Technological resources4 to 5 Financial resources4 to 5 Range for ranking is 1 (least amount) to 5 (most demanding). Example: growth chambers, experimental fields.

66 66 Experimental: Effect of Increased CO 2 Near Phoenix, Arizona, scientists measure the growth of wheat surrounded by elevated levels of atmospheric CO 2. The study, called Free Air Carbon Dioxide Enrichment (FACE), is to measure CO 2 effects on plants. It is the largest experiment of this type ever undertaken.

67 67 Analogues (space and time) Value Spatial scale of resultsDecades Time to conduct analysisSite to region Data needs1 to 2 Skill or training required1 to 3 Technological resources1 to 3 Financial resources1 to 2 Range for ranking is 1 (least amount) to 5 (most demanding). Example: existing climate in another area or in previous time

68 68 Analogues: drought, floods Africa vegetation health (VT - index) Vegetation health: Red – stressed, Green – fair, Blue – favorable Source: NOAA/NESDIS

69 69 Production functions Value Spatial scale of resultsSeason to decades Time to conduct analysisSite to globe Data needs2 to 4 Skill or training required3 to 5 Technological resources3 to 5 Financial resources2 to 4 Range for ranking is 1 (least amount) to 5 (most demanding). Example: Derived with empirical data.

70 70 Statistically derived functions (Almeria – Wheat) YieldIrrigation demand Production functions Iglesias, 1999; Iglesias et al., 2000

71 71 Agroclimatic indices Value Spatial scale of resultsSeason to decades Time to conduct analysisSite to globe Data needs1 to 3 Skill or training required2 to 3 Technological resources2 to 3 Financial resources1 to 3 Range for ranking is 1 (least amount) to 5 (most demanding). Example: FAO, etc.

72 72 Agroclimatic Indices Length of the growing periods (reference climate, ). IIASA-FAO, AEZ

73 73 Crop models Value Spatial scale of resultsDaily to centuries Time to conduct analysisSite to region Data needs4 to 5 Skill or training required5 Technological resources4 to 5 Financial resources4 to 5 Range for ranking is 1 (least amount) to 5 (most demanding). Example: CROPWAT, CERES, SOYGRO, APSIM, WOFOST, etc.

74 74 Water Carbon Nitrogen Crop models Based on Understanding of plants, soil, weather, management Calculate Require Growth, yield, fertilizer & water requirements, etc Information (inputs): weather, management, etc

75 75 Models - Advantages Models are assisting tools, stakeholder interaction is essential Models allow to ask “what if” questions, the relative benefit of alternative management can be highlighted: Improve planning and decision making Assist in applying lessons learned to policy issues Models permit integration across scales, sectors, and users

76 76 Models - Limitations Models need to be calibrated and validated to represent reality Models need data and technical expertise Models alone do not provide an answer, stakeholder interaction is essential

77 77 Economic and social tools Value Spatial scale of resultsYearly to centuries Time to conduct analysisSite to region Data needs4 to 5 Skill or training required5 Technological resources4 to 5 Financial resources4 to 5 Range for ranking is 1 (least amount) to 5 (most demanding). Example: Farm, econometric, I/O, national economies, MCA WEAP …

78 78 Economic models Consider both producers and consumers of agricultural goods (supply and demand) Economic measures of interest include: How do prices respond to production amounts? How is income maximized with different production and consumption opportunities? Microeconomic: Farm Macroeconomic: Regional economies All: Crop yield is a primary input (demand is the other primary input) Economic models should be built bottom-up

79 79 Differences in farming systems Small holder farmerCommercial farmer Strategy of production Stabilize food productionMaximize income RiskMalnutrition and migrationDebt and cessation of activity Primary source of risk WeatherWeather, markets and policies Non-structural risk avoidance mechanisms Virtually nonexistentInsurance, credit, legislation Inputs and farm assets Very lowVery significant

80 80 Social sciences tools Surveys and interviews Allow the direct input of stakeholders (bottom-up approach is emphasized) Provide expert judgment in a rigorous way

81 81 Integrators: GIS Value Spatial scale of resultsmonthly to centuries Time to conduct analysisregion Data needs5 Skill or training required5 Technological resources5 Financial resources5 Range for ranking is 1 (least amount) to 5 (most demanding). Example: …. All possible applications ….

82 82 Conclusions The merits of each approach vary according to the level of impact being studied, and they may frequently be mutually supportive Therefore, a mix of approaches is often the most rewarding Data are required data to define climatic, non- climatic environmental, and socio-economic baselines and scenarios Data is limited Discussion on supporting databases and data sources

83 83 Data: Scales, Sources, Reliability

84 84 PC Based examples DSSAT CROPWAT

85 85 Can crop models explain observations? Data: FAOSTAT

86 86 Some crops are more complicated than others ….

87 87 International Consortium for Agricultural Systems Applications Practical Applications: DSSAT

88 88 What components of the farming system are particularly vulnerable, and may thus require special attention? Applications of DSSAT to answer adaptation questions Can optimal management decrease vulnerability to climate? What are the characteristics of optimized crop varieties?

89 89 DSSAT Decision Support System for Agrotechnology Transfer ComponentsDescription DATABASESWeather, soil, genetics, pests, experiments, economics MODELSCrop models (Maize, wheat, rice, barley, sorghum, millet, soybean, peanut, dry bean, potato, cassava, etc) SUPPORTING SOFTWARE Graphics, weather, pests, soil, genetics, experiments, economics APPLICATIONSValidation, sensitivity analysis, seasonal strategy, crop rotations

90 90 Input Requirements WEATHER: Daily precipitation, maximum and minimum temperatures, solar radiation SOIL: Soil texture and soil water measurements MANAGEMENT: planting date, variety, row spacing, irrigation and N fertilizer amounts and dates, if any CROP DATA: dates of anthesis and maturity, biomass and yield, measurements on growth and LAI

91 91 Source: Iglesias, 1999 ESSENTIAL STEP 1. Crop Model Validation

92 92 Key issues Limitations of datasets Limitations of models Lack of technical expertise and resources Limitations of the studies due to lack of integration with: Water availability and demand Social and economic response

93 93 Datasets Data are required data to define climatic, non-climatic environmental, and socio- economic baselines and scenarios Data is limited Discussion on supporting databases and data sources

94 94 Guided examples 1.Effect of management (nitrogen and irrigation) in wet and dry sites (Florida, USA, and Syria) 2.Effect of climate change on wet and dry sites Sensitivity analysis to changes in temperature and precipitation (thresholds), and CO2 levels

95 95 Application 1. Management Objective: Getting started

96 96 Weather SyriaFlorida, USA SR (MJ m2 day-1) T Max (C) T Min (C) Precipitation (mm) Rain Days (num)

97 97 Input files needed Weather Soils Cultivars Management files (*.MZX files) description of the experiment

98 98 Open DSSAT …

99 99 Weather file Soil file Genotype file (Definition of cultivars) Examine the data files …

100 100 Location of the cultivar file …

101 101 Select the cultivar file …

102 102 Examine the cultivar file …

103 103 Examine the cultivar file …

104 104 Location of the weather file …

105 105 Selection of the weather file …

106 106 Examine the weather file …

107 107 Calculate monthly means …

108 108 Calculate monthly means …

109 109 Program to generate weather data …

110 110 Location of the input experiment file …

111 111 Select the experiment file …

112 112 Examine the experiment file (Syria)

113 113 Examine the experiment file (Florida)

114 114 The experiment file can be edited also with a text editor (Notepad).…

115 115 Start simulation …

116 116 Running …

117 117 Select experiment …

118 118 Select treatment …

119 119 View the results …

120 120 Select option …

121 121 Retrieve output files for analysis C:/DSSAT35/MAIZE/SUMMARY.OUT C:/DSSAT35/MAIZE/WATER.OUT C:/DSSAT35/MAIZE/OVERVIEW.OUT C:/DSSAT35/MAIZE/GROWTH.OUT C:/DSSAT35/MAIZE/NITROGEN.OUT There are DOS text files Can be imported into Excel

122 122 Analyse and present results

123 123 Application 2. Sensitivity to climate Objective: Effect of weather modification

124 124 Start simulation …

125 125 Sensitivity analysis …

126 126 Select option …

127 127 Analyse results ….

128 128 Proposed application: Adaptation For advanced participants …

129 129 Pioneer, April Adaptation Management strategy: Explicit guidance to farmers regarding optimal crop selection, irrigation, and fertilization, and should institute strong incentives to avoid excessive water use Use the DSSAT models to evaluate the use of alternative existing varieties and changes in the timing of planting to optimize yield levels or water use

130 130 Applications of CROPWAT to answer adaptation questions Can the water/irrigation systems meet the stress of changes in water supply/demand? Will climate change significantly affect agricultural water demand production?

131 131 CROPWAT is a decision support system for irrigation planning and management.

132 132 Experiments 1.Calculate ET0 2.Calculate crop water requirements 3.Calculate irrigation requirements for several crops in a farm

133 133 Start CROPWAT …

134 134 Retrieve climate file …

135 135 Examine temperature …

136 136 Examine ET0 …

137 137 Calculate ET0 …

138 138 Examine rainfall …

139 139 Retrieve crop parameters …

140 140 View progress of inputs …

141 141 Define and view crop areas selected …

142 142 Define irrigation method …

143 143 Input data completed …

144 144 Calculate irrigation demand …

145 145 Calculate irrigation schedule …

146 146 View results …

147 147 Review Climate variability and change, agriculture and food security Key differential vulnerabilities Key issues Models, assisting tools for stakeholders, risk management Designing the framework Participatory evaluation and prioritization of adaptation PC based training

148 148 Review 1.Climate variability and change, agriculture and food security 2.Key differential vulnerabilities 3.Key issues 1.Integration and cooperation (social, water) 2.Calibration 3.Extreme events 4.Uncertainties 4.PC based training: Models, assisting tools for stakeholders, risk management 1.Designing the framework 2.Participatory evaluation and prioritization of adaptation 3.PC based training


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