Transcript Models, assisting tools for stakeholders, risk management

Vulnerability and Adaptation
Assessment
Agriculture Sector
Jakarta, Indonesia
23 March 2006
Ana Iglesias
Universidad Politécnica de Madrid
1
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
2
Outline
1.
2.
3.
Climate variability and change, agriculture and food
security (½ h)
Key differential vulnerabilities (½ h)
Key issues (½ h)
1.
2.
3.
4.
4.
Integration and cooperation (social, water)
Calibration
Extreme events
Uncertainties
PC based training: Models, assisting tools for
stakeholders, risk management (3 h)
1.
2.
3.
Designing the framework (½ h)
Participatory evaluation and prioritization of adaptation (½ h)
PC based training (2 h)
Total: (4 ½ h)
3
Agenda
9:15 – 10:45
1.
2.
3.
Climate variability and change, agriculture,
and food security
Key differential vulnerabilities
Key issues
10:45 – 11:00
Coffee
11:00 – 12:30
4.
Models, assisting tools for stakeholders, risk
management
1.
2.
12:30 – 13:30
Lunch
13:30 – 15:00
4.
Designing the framework
Participatory evaluation and prioritization of
adaptation
Models, assisting tools for stakeholders, risk
management
3.
PC based training
4
Climate, agriculture, and food security

Climate change is one
stress among many
affecting agriculture
and the population that
depends on it
5
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
6
Drought in the Mediterranean
624mm
Correlation
betwen
total
rainfall and
agricultural
production
r=0.82
Annual Rainfall (mm)
650
Kairouan (Tunisia)
550
111mm
450
Rainfall
350
250
150
50
1951 1955 1959 1963 1967 1971 1975 1979 1983 1987 1991 1995 1999
20
Q/ha
Cereal
Yields
15
10
5
0
1980
1983
1986
1989
Rendement/SE (Qx/ha)
1992 1995
1998
2001
Rendement/SR (Qx/ha)
Source:
R. Mougou,
INRGREF
7
Drought in the Mediterranean
Wheat yield in Spain
Probability of yield (%)
100%
80%
high yield
medium yield
low yield
60%
40%
20%
0%
all years
dry years
normal years
wet years
Source: Iglesias and Moneo, 2004
8
Longer growing seasons …
In Australia, climate change appears to have
increased wheat yield by about 10 to 20%
since 1952 (Nicholls, 1997)
9
Multiple interactions, vulnerability and
adaptation
Climate
change
Systems and
social groups
that need to
adapt
Economic,
social,
demographic,
land use
changes
Social vulnerability
10
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
11
Multiple interactions: Stakeholders
define adaptation
Scientists
Policy
makers
Civil
stakeholders
12
Concepts are important: The big picture …
Conclusions for policy
Models
Assumptions
Theory
Data
13
Agriculture: empirical evidence
14
Source: Wei Xiong, Erda Lin, Xiu Yang, et al., 2006
15
POSSIBLE
BENEFITS
POSSIBLE
BENEFITS
POSSIBLE
BENEFITS
Possible
benefits
CO
CO
CO
222
POSSIBLE
BENEFITS
POSSIBLE
BENEFITS
CO2 2
CO
CARBONDIOXIDE
DIOXIDE
CARBON
DIOXIDE
CARBON
FERTILIZATION
FERTILIZATION
FERTILIZATION
CARBONDIOXIDE
DIOXIDE
CARBON
FERTILIZATION
FERTILIZATION
LONGER
LONGER
LONGER
GROWING
GROWING
GROWING
SEASONS
SEASONS
SEASONS
LONGER
LONGER
GROWING
GROWING
SEASONS
SEASONS
INCREASED
INCREASED
INCREASED
PRECIPITATION
PRECIPITATION
PRECIPITATION
INCREASED
INCREASED
PRECIPITATION
PRECIPITATION
POSSIBLEDRAWBACKS
DRAWBACKS
POSSIBLE
DRAWBACKS
POSSIBLE
Possible
drawbacks
POSSIBLE
DRAWBACKS
PESTS
POSSIBLE
DRAWBACKS
PESTS
PESTS
MORE
MORE
MORE
FREQUENT
FREQUENT
FREQUENT
DROUGHTS
DROUGHTS
DROUGHTS
MORE
MORE
FREQUENT
FREQUENT
DROUGHTS
DROUGHTS
HEAT
HEAT
HEAT
PESTS
PESTS
STRESS
STRESS
STRESS
HEAT
HEAT
STRESS
STRESS
FASTER
FASTER
FASTER
GROWING
GROWING
GROWING
PERIODS
PERIODS
PERIODS
FASTER
FASTER
GROWING
GROWING
PERIODS
PERIODS
INCREASED
INCREASED
INCREASED
FLOODINGAND
AND
FLOODING
AND
FLOODING
SALINIZATION
SALINIZATION
SALINIZATION
INCREASED
INCREASED
FLOODINGAND
AND
FLOODING
SALINIZATION
SALINIZATION
16
Weeds, pests and diseases

Weeds, pests, and diseased damage
about one half of the potential production
every year
17
Climate change affects crop production
POSSIBLE BENEFITS
CO2
CARBON DIOXIDE
FERTILIZATION
LONGER
GROWING
SEASONS
INCREASED
PRECIPITATION
POSSIBLE DRAWBACKS
MORE
FREQUENT
DROUGHTS


PESTS
HEAT
STRESS
FASTER
GROWING
PERIODS
INCREASED
FLOODING AND
SALINIZATION
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)
18
How might global climate change affect
food production?
2020s
Percentage change in
average crop yields for
the Hadley Center global
climate change scenario
(HadCM3). Direct
physiological effects of
CO2 and crop adaptation
are taken into account.
Crops modeled are:
wheat, maize, and rice.
2050s
2080s
Source: NASA/GISS; Rosenzweig and
Iglesias, 2002; Parry et al, 2004
Yield Change (%)
-30
-20 -10
-5
-2.5 0
2.5
5
10
20
30
40
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Limits to adaptation
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
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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)
20
Developed-Developing country differences
Potential change (%) in national cereal yields
for the 2080s (compared with 1990) using the
HadCM3 GCM and SRES scenarios (Parry et al.,
2004)
Scenario
A1FI A2a
A2b A2c
A2c
B1a
B2b
CO2 (ppm)
810
709
709
709
527
561
561
World (%)
-5
0
0
-1
-3
-2
-2
Developed (%)
3
8
6
7
3
6
5
Developing (%)
-7
-2
-2
-3
-4
-3
-5
DevelopedDeveloping) (%)
10
10
8
10
7
9
9
21
Additional people at
risk of hunger
Additional Millions of People
200
160
120
80
40
0
2020
2050
A2 - Regional Enterprise
2080
B2 - Local Stewardship
Parry et al., 2004
22
Interaction and integration: Water
Additional population under extreme stress
of water shortage
Population (millions)
120
80
40
0
2020
2050
2080
University of Southampton
23
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)
24
Agenda
9:15 – 10:45
1.
2.
3.
Climate variability and change, agriculture, and
food security
Key differential vulnerabilities
Key issues
10:45 – 11:00
Coffee
11:00 – 12:30
4.
Models, assisting tools for stakeholders, risk
management
1.
2.
12:30 – 13:30
Lunch
13:30 – 15:00
4.
Designing the framework
Participatory evaluation and prioritization of
adaptation
Models, assisting tools for stakeholders, risk
management
3.
PC based training
25
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]
26
Where? Systems and social groups
Map of the night-time city lights of the world (DMSP: NASA and NOAA)
27
How much? Climate and
SRES scenarios
Had CM2 model, 2050s
Temperature change
Precipitation change
28
What happens in response to change?
Adaptive capacity (internal adaptation)
 Planned adaptation

29
Definition of key vulnerabilities



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
Expert judgement
Stakeholder consultation
Empirical evidence
Scientific knowledge of processes
Models are assisting tools
30
Check list and ranking of potential
vulnerabilities - Examples

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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
31
Key vulnerabilities
Who can adapt?
Who is vulnerable?
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
32
Agenda
9:15 – 10:45
1.
2.
3.
Climate variability and change, agriculture, and
food security
Key differential vulnerabilities
Key issues
10:45 – 11:00
Coffee
11:00 – 12:30
4.
Models, assisting tools for stakeholders, risk
management
1.
2.
12:30 – 13:30
Lunch
13:30 – 15:00
4.
Designing the framework
Participatory evaluation and prioritization of
adaptation
Models, assisting tools for stakeholders, risk
management
3.
PC based training
33
Key issues




Integration and cooperation (social,
water)
Calibration
Extreme events
Uncertainties
34
Key issues: Pressures and solutions



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
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
Water
Population
Economic and social development
Technology (water desalination, reuse,
efficiency)
Agricultural technology
Cooperation
Improved management
35
Albania
0
Yemen
Viet Nam
Vanuatu
Uzbekistan
Tuvalu
Turkmenistan
Tonga
Thailand
Tajikistan
Solomon
Singapore
Samoa
Philippines
Palau
Pakistan
Niue
Nepal
Nauru
Mongolia
Micronesia,Fed
Maldives
Malaysia
Lebanon
Laos
Kyrgyzstan
Kuwait
Korea,
Korea, Dem
Kiribati
Kazakhstan
Jordan
Iran, Islamic
Indonesia
India
Cook Islands
China
Cambodia
Bhutan
Bangladesh
Bahrain
Bahamas
Water
Agricultural water use % of total (2004)
100
80
60
40
20
36
-2
-4
Bahrain
Bahamas
0
Yemen
Viet Nam
Vanuatu
Uzbekistan
Tuvalu
Turkmenistan
Tonga
Thailand
Tajikistan
Solomon
Singapore
Samoa
Philippines
Palau
Pakistan
Niue
Nepal
Nauru
Mongolia
Micronesia,Fed
Maldives
Malaysia
Lebanon
Laos
Kyrgyzstan
Kuwait
Korea,
Korea, Dem
Kiribati
Kazakhstan
Jordan
Iran, Islamic
Indonesia
India
Cook Islands
China
Cambodia
Bhutan
Bangladesh
-6
Albania
Population
Rural population change % (1993-2003)
6
4
2
-8
-10
-12
-14
37
-7,000
Bahrain
Maldives
Malaysia
Lebanon
Laos
Kyrgyzstan
Kuwait
Korea,
Korea, Dem
Kiribati
Kazakhstan
Jordan
Iran, Islamic
Indonesia
India
Cook Islands
China
Cambodia
Bhutan
Bangladesh
3,000
Bahrain
Turkmenistan
Tonga
Thailand
Tajikistan
Solomon
Singapore
Samoa
Philippines
Palau
Pakistan
Niue
Nepal
Nauru
Mongolia
Micronesia,Fed
Maldives
Malaysia
Lebanon
Laos
Kyrgyzstan
Kuwait
Korea,
Korea, Dem
Kiribati
Kazakhstan
Jordan
Iran, Islamic
Indonesia
India
Cook Islands
China
Cambodia
Bhutan
Bangladesh
Vanuatu
Viet Nam
Yemen
Vanuatu
Viet Nam
Yemen
Tuvalu
8,000
Uzbekistan
13,000
Tuvalu
Agricultural trade balance (exportts-imports) value (million $) (2004)
Uzbekistan
Turkmenistan
Tonga
Thailand
Tajikistan
Solomon
Singapore
Samoa
Philippines
Palau
Pakistan
Niue
Nepal
Nauru
Mongolia
Albania
Bahamas
2,000,000
1,800,000
1,600,000
1,400,000
1,200,000
1,000,000
800,000
600,000
400,000
200,000
0
Micronesia,Fed
-12,000
Albania
-2,000
Bahamas
Economic and social development
GDP 2004 (millions of US dollars)
-17,000
-22,000
38
Integration and cooperation
Additional population under extreme stress
of water shortage
Population (millions)
120
80
40
0
2020
2050
2080
Source: University of Southampton
39
Water
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
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
40
Water conflicts
Evolución del balance Demandas - Disponibilidades
1000
900
800
Nuevos pozos
700
Valmayor
El Atazar
Tr. S. Juan Valmayor
Sequía 1982
hm 3
600
500
Sequía 1992
Imp. Picadas
400
300
200
100
0
1970
1975
1980
1985
1990
1995
Capacidad de suministro
2000
2005
2010
2015
2020
Demanda
41
Transboundary surface and groundwater

Water can lead to political hostilities and many
regions with political conflicts also share water
resources
www.bgr.de/app/whymap/
42
Political and cultural process

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
Irrigation Area: 2000 and 2010
4000
Irrig Area (ha x 1000)

2000
2010
3000
2000
1000
0
France
Spain
Italy
Greece
Portugal
Source: EEA, CEDEX
43
Tunisia: National strategy
on water management
(Source: R. Mougou)
Current and projected water demand (%)
Drinking
Irrigation
Tourism
Industrial

2030
17.7
73.5
1.5
7.3
Resources management




1996
11.5
83.7
0.7
4.1
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)
Example: Integrated assessment in Egypt
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
Source: El-Shaer et al., 1997; Strzpek et al., 1999
45
Cooperation and integration

Your expert opinion, consultation ……
46
Calibration of models
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
This afternoon
Documentation
47
Extreme events
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Your expert opinion, consultation ……
Large knowledge based on risk
management of natural disasters
Empirical evidence is essential (external
shock, impacts, vulnerability)
48
Uncertainties
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
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Your expert opinion, consultation ……
Climate change scenarios
Climate variability
Stakeholder adaptation
Agricultural models
Effects of CO2 on crops
Issues of scale
Socio economic projections
49
Thanks for your attention!
Visit MEDROPLAN on the web
www.iamz.ciheam.org/medroplan
[email protected]
50
Agenda
9:15 – 10:45
1.
2.
3.
Climate variability and change, agriculture, and
food security
Key differential vulnerabilities
Key issues
10:45 – 11:00
Coffee
11:00 – 12:30
4.
Models, assisting tools for stakeholders,
risk management
1.
2.
12:30 – 13:30
Lunch
13:30 – 15:00
4.
Designing the framework
Participatory evaluation and prioritization of
adaptation
Models, assisting tools for stakeholders, risk
management
3.
PC based training
51
The process: Example
Set up a
Multidisciplinary
Stakeholder Team
(Organizational
component)
Evaluate the legal,
social, and political
process
(Organizational
component)
Public review and
Revision
Public dissemination
(Operational
component)
Select and identify
priority actions, based
on agreed criteria
(Operational
component)
Identify risk and
potential vulnerabilities
(Methodological
component)
www.iamz.ciheam.org/medroplan
52
Agenda
9:15 – 10:45
1.
2.
3.
Climate variability and change, agriculture, and
food security
Key differential vulnerabilities
Key issues
10:45 – 11:00
Coffee
11:00 – 12:30
4.
Models, assisting tools for stakeholders,
risk management
1.
2.
12:30 – 13:30
Lunch
13:30 – 15:00
4.
Designing the framework
Participatory evaluation and prioritization of
adaptation
Models, assisting tools for stakeholders, risk
management
3.
PC based training
53
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)
54
Bottom-up stakeholder adaptation

Possible tool: MCA WEAP
55
Bottom-up stakeholder adaptation
Surveys: Adaptation to climate change in
Tunisia, Source: R. Mougou
56
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; Risksharing (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
57
Water harvesting
Source: T. Oweis, 2004
58
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.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
Indigenous knowledge
Short-duration varieties
Crop diversification
New crop varieties
New crops
Agroforestry
Food storage
Agrometeorological advice
Construction of a dam
Irrigation (new scheme)
Irrigation (improved system)
Water harvesting
Water desalination /
reutilization
Cease activity
59
Example: Use MCA WEAP
60
Agenda
9:15 – 10:45
1.
2.
3.
Climate variability and change, agriculture, and
food security
Key differential vulnerabilities
Key issues
10:45 – 11:00
Coffee
11:00 – 12:30
4.
Models, assisting tools for stakeholders, risk
management
1.
2.
12:30 – 13:30
Lunch
13:30 – 15:00
4.
Designing the framework
Participatory evaluation and prioritization of
adaptation
Models, assisting tools for stakeholders,
risk management
3.
PC based training
61
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 socioeconomic studies: crop production, land
suitability, water availability, farm income,
…
62
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
63
Quantitative methods and tools


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

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
Experimental
Analogues (spatial and temporal)
Production functions (statistically derived)
Agro-climatic indices
Crop simulation models (generic and cropspecific)
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 (demanddriven science), provide expert judgment
Integrators: GIS
64
Experimental
Value
Spatial scale of results
Season to decades
Time to conduct analysis Site
Data needs
4 to 5
Skill or training required
1
Technological resources 4 to 5
Financial resources
4 to 5
Range for ranking is 1 (least amount) to 5 (most
demanding).
Example: growth chambers, experimental fields.
65
Experimental: Effect of Increased CO2
http://www.whitehouse.gov/media/gif/Figure4.gif
Near Phoenix, Arizona,
scientists measure the
growth of wheat surrounded
by elevated levels of
atmospheric CO2. The study,
called Free Air Carbon
Dioxide Enrichment (FACE),
is to measure CO2 effects on
plants. It is the largest
experiment of this type ever
undertaken.
66
http://www.ars.usda.gov
Analogues (space and time)
Value
Spatial scale of results
Decades
Time to conduct analysis
Site to region
Data needs
1 to 2
Skill or training required
1 to 3
Technological resources
1 to 3
Financial resources
1 to 2
Range for ranking is 1 (least amount) to 5 (most
demanding).
Example: existing climate in another area or in previous
time
67
Analogues: drought, floods
Africa vegetation health (VT - index)
Vegetation health: Red – stressed, Green – fair, Blue – favorable
Source: NOAA/NESDIS
68
Production functions
Value
Spatial scale of results
Season to decades
Time to conduct analysis
Site to globe
Data needs
2 to 4
Skill or training required
3 to 5
Technological resources
3 to 5
Financial resources
2 to 4
Range for ranking is 1 (least amount) to 5 (most
demanding).
Example: Derived with empirical data.
69
Production functions
Statistically derived functions (Almeria – Wheat)
Yield
Irrigation demand
400
Irrigation (mm)
Dryland Yield (kg ha-1)
8000
6000
4000
2000
300
200
100
Irrigation
Dryland Yield
0
-150
Predicted Values
-100
-50
0
50
100
Yr PP Change (%)
150
0
-150
Predicted Values
-100
-50
0
50
100
150
Yr PP Change (%)
Iglesias, 1999; Iglesias et al., 2000
70
Agroclimatic indices
Value
Spatial scale of results
Season to decades
Time to conduct analysis
Site to globe
Data needs
1 to 3
Skill or training required
2 to 3
Technological resources
2 to 3
Financial resources
1 to 3
Range for ranking is 1 (least amount) to 5 (most
demanding).
Example: FAO, etc.
71
Agroclimatic Indices
Length of the growing periods (reference climate, 1961-1990).
IIASA-FAO, AEZ
72
Crop models
Value
Spatial scale of results
Daily to centuries
Time to conduct analysis
Site to region
Data needs
4 to 5
Skill or training required
5
Technological resources
4 to 5
Financial resources
4 to 5
Range for ranking is 1 (least amount) to 5 (most
demanding).
Example: CROPWAT, CERES, SOYGRO, APSIM,
WOFOST, etc.
73
Crop models
Based on
Understanding of plants,
soil, weather, management
Calculate
Water
Growth, yield, fertilizer &
water requirements, etc
Carbon
Require
Information (inputs):
weather, management, etc
Nitrogen
74
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
75
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
76
Economic and social tools
Value
Spatial scale of results
Yearly to centuries
Time to conduct analysis
Site to region
Data needs
4 to 5
Skill or training required
5
Technological resources
4 to 5
Financial resources
4 to 5
Range for ranking is 1 (least amount) to 5 (most
demanding).
Example: Farm, econometric, I/O, national economies,
MCA WEAP …
77
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
78
Differences in farming systems
Small holder farmer
Commercial
farmer
Strategy of
production
Stabilize food production
Maximize income
Risk
Malnutrition and migration
Debt and
cessation of
activity
Primary source of
risk
Weather
Weather, markets
and policies
Non-structural risk
avoidance
mechanisms
Virtually nonexistent
Insurance, credit,
legislation
Inputs and farm
assets
Very low
Very significant
79
Social sciences tools



Surveys and interviews
Allow the direct input of stakeholders
(bottom-up approach is emphasized)
Provide expert judgment in a rigorous
way
80
Integrators: GIS
Value
Spatial scale of results
monthly to centuries
Time to conduct analysis
region
Data needs
5
Skill or training required
5
Technological resources
5
Financial resources
5
Range for ranking is 1 (least amount) to 5 (most
demanding).
Example: …. All possible applications ….
81
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, nonclimatic environmental, and socio-economic
baselines and scenarios
Data is limited
Discussion on supporting databases and data
sources
82
Data: Scales, Sources, Reliability
Iirrg Area (ha x 1000)
450
Irrigation Area Tunisia (1970 - 1998)
350
250
150
50
1970
1975
1980
1985
1990
Year
FAO Data
USDA ERS Data
1995
83
PC Based examples


DSSAT
CROPWAT
84
Can crop models explain observations?
2002
Egypt
Morocco
Spain
Tunisia
Area (1000ha)
Population (1000)
Population 2030 (1000)
Population in agriculture (% of total)
Population in rural areas (% of total)
Population in rural areas 2030
(% of total)
100,145
70,507
109,111
35
57
44,655
30,072
42,505
35
43
50,599
40,977
39,951
7
22
16,361
9,728
12,351
24
33
46
29
15
22
Agricultural Area (% of total)
Irrigation area (% of agricultural)
Wheat Yield (kg/ha) (World = 2,678)
3
100
6,150
69
4
1,716
58
12
2,836
55
4
3,853
Agricultural Imports (million $)
Agricultural Exports (million$)
Fertiliser Consumption (kg/ha)
3,688
774
392
1,740
811
12
12,953
16,452
74
1,022
391
12
No
Low
17
No
Low
14
Yes
High
4
No
Low
12
4,000
3,900
21,200
6,800
Crop Drought Insurance
Agricultural Subsidies
Agriculture, value added (% of GDP)
GDP Per capita (US$) UN derived
from purchasing power parity (PPP)
Data: FAOSTAT
85

Some crops are
more complicated
than others ….
86
Practical Applications: DSSAT
International Consortium for Agricultural
Systems Applications
http://www.icasanet.org/
http://www.clac.edu.eg
87
Applications of DSSAT to answer
adaptation questions
• What components of the farming system
are particularly vulnerable, and may thus
require special attention?
• Can optimal management decrease
vulnerability to climate?
• What are the characteristics of optimized
crop varieties?
88
DSSAT Decision Support System for Agrotechnology
Transfer
Components
Description
DATABASES
Weather, soil, genetics, pests,
experiments, economics
Crop models (Maize, wheat, rice,
barley, sorghum, millet, soybean,
peanut, dry bean, potato, cassava, etc)
Graphics, weather, pests, soil, genetics,
experiments, economics
MODELS
SUPPORTING
SOFTWARE
APPLICATIONS
Validation, sensitivity analysis,
seasonal strategy, crop rotations
89
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
90
ESSENTIAL STEP 1.
Crop Model Validation
Source: Iglesias, 1999
91
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
92
Datasets



Data are required data to define climatic,
non-climatic environmental, and socioeconomic baselines and scenarios
Data is limited
Discussion on supporting databases and
data sources
93
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
94
Application 1. Management

Objective: Getting started
95
Weather
Syria
Florida, USA
SR (MJ m2 day-1)
19.3
16.5
T Max (C)
23.0
27.4
T Min (C)
8.5
14.5
Precipitation (mm)
276.4
1364.3
Rain Days (num)
55.7
114.8
96
Input files needed




Weather
Soils
Cultivars
Management files (*.MZX files)
description of the experiment
97
Open DSSAT …
98
Examine the data files …
Weather file
Soil
file
Genotype file
(Definition of
cultivars)
99
Location of the cultivar file …
100
Select the cultivar file …
101
Examine the cultivar file …
102
Examine the cultivar file …
103
Location of the weather file …
104
Selection of the weather file …
105
Examine the weather file …
106
Calculate monthly means …
107
Calculate monthly means …
108
Program to generate weather data …
109
Location of the input experiment file …
110
Select the experiment file …
111
Examine the experiment file (Syria)
112
Examine the experiment file (Florida)
113
The experiment file can be edited also with
a text editor (Notepad) .…
114
Start simulation …
115
Running …
116
Select experiment …
117
Select treatment …
118
View the results …
119
Select option …
120
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
121
Analyse and present results
Management: Maize Yield Florida and Syria
12000
Grain Yield (kg/ha)
10000
8000
6000
Florida
Syria
4000
2000
0
Rainfed Low N Rainfed High N
Irrig Low N
Irrig High N
122
Application 2. Sensitivity to climate

Objective: Effect of weather
modification
123
Start simulation …
124
Sensitivity analysis …
125
Select option …
126
Analyse results ….
Climate Change: Maize Yield Florida
2500
Grain Yield (kg/ha)
2000
1500
1000
500
0
Florida Base
Florida -50% pp
127
Proposed application: Adaptation

For advanced participants …
128
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
Pioneer, April 00129
- 129
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?
130
CROPWAT is a decision support system for irrigation
planning and management.
http://www.clac.edu.eg
http://www.fao.org/ag/agl/aglw/cropwat.htm
131
Experiments
1. Calculate ET0
2. Calculate crop water requirements
3. Calculate irrigation requirements for
several crops in a farm
132
Start CROPWAT …
133
Retrieve climate file …
134
Examine temperature …
135
Examine ET0 …
136
Calculate ET0 …
137
Examine rainfall …
138
Retrieve crop parameters …
139
View progress of inputs …
140
Define and view crop areas selected …
141
Define irrigation method …
142
Input data completed …
143
Calculate irrigation demand …
144
Calculate irrigation schedule …
145
View results …
146
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
[email protected]
147
Review
1.
2.
3.
Climate variability and change, agriculture and
food security
Key differential vulnerabilities
Key issues
1.
2.
3.
4.
4.
Integration and cooperation (social, water)
Calibration
Extreme events
Uncertainties
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
148