Integrating Climate Variability and Forecasts into Risk-Based Management Tools for Agricultural Production and Resource Conservation

1
Integrating Climate Variability and Forecasts
into Risk-Based Management Tools for Agricultural
Production and Resource Conservation

• Jean L. Steiner
• Jurgen D. Garbrecht
• Jeanne M. Schneider
• X. C. (John) Zhang
• M. W. Van Liew
• USDA-ARS Grazinglands Research Laboratory
• Great Plains Agroclimate and Natural Resources
  Unit
• El Reno, OK

2
Objectives

• Regional context of Southern Great Plains
• research focus
• Methods
• Assessing decision maker needs
• Relevance to GECAFS

3
El Reno, OK
4
(No Transcript)
5
(No Transcript)
6
(No Transcript)
7
(No Transcript)
8
(No Transcript)
9
Research Focus

• Risk-based decision making
• Climate variability as a primary risk factor
• Decadal scale cycles
• Seasonal forecasts
• Levels of analysis
• Regional, watershed
• Farm-scale

10
Methods and Preliminary Analyses
11
El Reno, Oklahoma 1971 to 2000
12
Annual Precipitation in Central Oklahoma
13
Blue River Streamflow and Precipitation
Precipitation
5-yr weighted average
R2 0.84
Streamflow
USGS 07332500
Annual Precipitation in
Annual Streamflow cfs
Average for 1937-2003
Blue River, Oklahoma
Calendar Year
14
Blue River Streamflow
15
(No Transcript)
16
(No Transcript)
17
(No Transcript)
18
CPC precipitation forecasts product
19
Dependability of Wet Forecasts, DN 10 Lead
Time 0.5 months, 58 forecasts from JFM 1997
through OND 2001 lt 50 50-99 100
1/2
1/1
1/2
3/4
1/2
3/3
1/2
2/2
2/2
2/2
2/4
5/7
2/2
1/1
4/5
1/1
4/8
2/2
2/2
2/2
4/6
1/1
2/2
2/3
5/6
3/3
1/1
2/2
6/7
5/7
4/7
2/2
3/3
4/6
5/7
4/5
6/7
4/4
6/6
4/6
5/7
2/2
4/4
5/7
3/3
5/7
3/3
4/4
4/5
3/3
4/5
4/4
4/4
3/4
4/4
20
Dependability of Dry Forecasts, DN 10 Lead
Time 0.5 months, 58 forecasts from JFM 1997
through OND 2001 lt 50 50-99 100
5/5
1/1
1/2
2/3
3/3
1/1
1/1
2/2
2/2
1/1
2/3
1/2
2/3
1/1
1/1
1/1
10/14
1/1
10/14
1/2
7/8
9/14
2/2
3/4
12/18
1/2
1/2
6/6
17/19
2/2
9/13
12/16
5/8
2/2
3/6
10/12
6/8
10/11
21
First Downscale Forecasts toFarm and Monthly
Scales Second Use Weather Generators to
Produce Sequences of Daily Weather Third Use
Models to Produce Forecast Shifts in Odds for an
Application Fourth Incorporate Climate
Information in Decision Support Tools
22
Spatial Downscaling of Forecasts
23
(No Transcript)
24
Evaluating a climate generator (CLIGEN) for
daily precipitation
and wheat growth model sensitivity to
precipitation terciles and initial soil water
condition
25

100
100
What is the relationship between a sequence
of forecasts and outcome?
forecast
forecast
normal
normal
PROBABILITY OF EXCEEDANCE
PROBABILITY OF EXCEEDANCE
50
50
100
100
0
0
Very Low
Very High
Very Dry
Very Wet
forecast yield
PRECIPITATION
3-MONTH PRECIPITATION
normal yield
PROBABILITY OF EXCEEDANCE
50
Currently unknown
0
Very Low
Very High
FORAGE YIELD
26
(No Transcript)
27
Associate baseline and forecast odds for outcomes
with economic factors to define risks.
100
forecast yield
normal yield
50
PROBABILITY OF EXCEEDANCE
0
Very Low
Very High
FORAGE YIELD
28
Models Used

• Regional, watershed
• SWAT
• Neural Networks
• Farm/field Level
• WEPP
• CERES
• Enterprise budgets, market tools

29
Identifying Decision Maker Needs

• Workshops to present findings and engage in
  dialog
• One-on-one discussions of specific issues
• Exploratory work in form of case studies

30
Decision Making Case Study

• Cropping/Grazing Systems in Southern Great Plains

31
(No Transcript)
32
Decision Points Wheat Grazing Systems
buy additional cattle?
graze
sell cattle?
forage quality dip
sow
graze
supplemental feed?
33
Agronomic Decisions

• Crop selection
• e.g., maize/sorghum/millet
• Long vs short season varieties
• Planting density and geometry
• Fertility levels, dates, rates
• Area to be planted

34
Crop/livestock system Decisions

• Future stocking rates
• Forage (grazed or hayed) vs grain harvest
• Intensity and timing of grazing
• Supplemental feed
• Purchase, selling, or movement of animals

35
Business Decisions

• Marketing/hedging
• Diversification of farm enterprises
• Off-farm income

36
Decision Maker Needs

• Work with individual farmers, extension,
  conservationists
• Identify their goals and priorities
• Identify their resources and characterize their
  systems
• Develop climate scenarios relevant to key
  decisions

37
Decision Maker Needs

• Focus on record keeping is essential
• A journaling tool will be used to analyze
  decision points, factors considered in taking
  decisions, building decision trees or decision
  rules

38
Regional Case Study

• Water Release from Reservoirs

39
Decision Maker Needs

• Work with agencies with management
  responsibilities (e.g., U.S. Bureau of
  Reclamation, U. S. Corps of Engineers)
• Understand stakeholders and issues
• Analyze decision criteria and decision trees
  specific to their situation
• Incorporate climate variability and climate
  forecast scenarios

40
Risks in Farming

• Risk is an important aspect of the farming
  business. The uncertainties of weather, yields,
  prices, government policies, global markets, and
  other factors can cause wide swings in farm
  income.
• Risk management involves choosing among
  alternatives that reduce the financial effects of
  such uncertainties. 

http//www.ers.usda.gov/Briefing/RiskManagement/
41
Types of Risks

• Production risk derives from the uncertain
  natural growth processes of crops and livestock.
  Weather, disease, pests, and other factors affect
  both the quantity and quality of commodities
  produced.
• Price or market risk refers to uncertainty about
  the prices producers will receive for commodities
  or the prices they must pay for inputs.
• Financial risk results when the farm business
  borrows money and creates an obligation to repay
  debt. Rising interest rates, the prospect of
  loans being called by lenders, and restricted
  credit availability are also aspects of financial
  risk.
• Institutional risk results from uncertainties
  surrounding government actions. Tax laws,
  regulations for chemical use, rules for animal
  waste disposal, and the level of price or income
  support payments are examples of government
  decisions that can have a major impact on the
  farm business.
• Human or personal risk refers to factors such as
  problems with human health or personal
  relationships that can affect the farm business.
  Accidents, illness, death, and divorce are
  examples of personal crises that can threaten a
  farm business.

http//www.ers.usda.gov/Briefing/RiskManagement/
42
Relevance to GECAFS DSS

• Decision making is individualized process and may
  be approached as case study
• Decision makers have multiple objectives, some
  economic and some not, which must be balanced

43
Recognizing and Adapting to Change