UCD/Embrapa
Assessing the Effects of Alternative
Policies and Conditions in the São
Francisco River Basin, Brazil:
A Multi-Scale Approach
Marco Maneta
Stephen A. Vosti
&
SFRB Team
�ovember 2008
Center for Natural
Resources Policy
Analysis -- CNRPA
UCD/Embrapa
• Objectives of Modeling Exercises
• Basic Components of Predictive Models
– Hydrologic Models
– Economic Models of Agriculture
• Examples of Model Uses
– Plot Level
– Sub-catchment Spatial Extent
– Basin Spatial Extent
• Conclusions and Policy Implications
Presentation Overview
UCD/Embrapa
Key Objectives of Hydro-
Economic Models
• Understand Farmer Behavior and Outcomes
– Cropping patterns, input mix, employment, water use
– Income and poverty
– Surface water and groundwater availability
• Predict the Effects of Proposed Policy and other Changes on Farmer Behavior/Outcomes
• Inform Policy
• Modeling at Three Spatial Extents
– Plot-Level LUS Models
– Buriti Vermelho Models
– Basin-Wide Models
UCD/Embrapa
Basic Components of
Predictive Models
• Hydrology Models
– Plot level
– Sub-catchment spatial extent
– Basin spatial extent
• Economic Models of Agriculture
– Plot level
– Sub-catchment spatial extent
– Basin spatial extent
UCD/Embrapa
Core of the Economic Model of
Agriculture: Farmer Objective Function
Crop
Prices
Agricultural Production Function•Vector of 4on-Irrigation Inputs (x
nirr):
•Fertilizers, seeds, land, pesticides,
machinery etc
•Effective Water – ew
•Function of Irrigation Inputs (xirr
):
•Applied water
•Irrigation Capital
•Irrigation Labor
•Irrigation Energy
4on-Irrigation
Input Cost• Price - wsj
• Quantity - xsij
Effective Water
Cost• Irrigation Input
Prices – pirr
• Irrigation InputQuantities - x
irr
• z – Vector of factors that may
affect irrigation costs(e.g. distance to
river)
)z;,())(,(maxirrtirrt
i i i
ewijtjtirrtitnirrtitit itcxwewqp xpxx∑ ∑ ∑−−
UCD/Embrapa
Hydrologic & Economic Model Links
HYDROLOGIC
MODEL
• Crop-specific
• poduction
• water use
• irrigation efficiency
ECO4OMIC
MODEL•Water available for ag
• rainfall
•surface water
Algorithm to translate
cropping decisions into
water demand
Algorithm to translate
hydrologic consequences
into water availability
Cropping Decisions Hydrologic Consequences
UCD/Embrapa
Land Use System (LUS) Analysis• Space
– Single parcel of land• Time
– Multi-year duration, specific end date, seasonal time steps• Economic Model of Agriculture
– Specific series of cropping activities, specific production and water use technologies
• Hydrology Model– Farmer’s assessments of water availability
• All Data Collected at Farm Level
Field #1
Year 1Field #1
Year 2 Field #1
Year 3 Field #1
Year 4 Field #1
Year 10 Field #1
Year 15
UCD/Embrapa
LUS Results for Alternative
Production Systems in Petrolina
LUS Economic Performance
Labor
Requirements Water for Irrigation
Employ
ment
4PV4PV per
hectare
Excess
Returns
to
Family
Labor
Returns
to Land
Establish
ment
Total
Family
Labor
Used
Establish
ment
Cost --
Property
Establish
ment
Cost --
Plot
(per
hectare)
Opera-
tional
Costs
Water Use
Water
Productivi
ty (4PV/
1000m³)
Operatio
nal
Phase
$R $R/ha
$R/
person-
day
$R/ha
/year
Person-
days /ha
Person-
days/ ha/
year $R $R/ ha
$R/ha/
year
1000M3/
ha/year
$R/
1000m³
person-
days/ha/
year
Goats and Sheep -12 0 0 0 1.5 6.3 0 0 6 4 0.00 0
Melon -Onion 43,963 21,981 11 1,099 28 102 50 25 2,466 21 53.26 229
Manga -- flood
irrigation 3,087 772 1 39 35 45 553 138 1,177 12 3.12 93
Mango -- micro
sprinkler 11,057 2,764 4 138 44 32 4,212 1,053 973 10 14 69
Table grapes
with seeds 778,074 129,679 31.14 6,484 151 208 96,600 16,100 3,157 18 368 524
Table grapes
seedless 1,369,349 228,225 54.81 11,411 151 208 96,600 16,100 3,157 18 648 438
UCD/Embrapa
Policy Experiments Using LUS
UCD/Embrapa
Effects of Uncertainty
Effects of Goat Mortality
Uncertainty on NPV per Year
Effect of Uncertainty in Mango Prices
on 4PV per year
UCD/Embrapa
A Spatially Distributed Hydrologic
Model for Buriti Vermelho
UCD/Embrapa
Modeling the Buriti Vermelho
Sub-Catchment
San Francisco River Basin
Brazil
UCD/Embrapa
Water
Availability
and Use
UCD/Embrapa
Economic Effects of DroughtChanges in Applied Water
Changes in Hired Labor UseChanges in Profits
Changes in Land Allocation
UCD/Embrapa
• Variable Weather Conditions
– Wet year and drought
– Rainfall and evapotranspiration
• Water Policy Setting
– Application of the A4A guidelines
• Price Shock
– Large increase in sugarcane prices
• Use Hydro-Econ Models to Predict:
– Cropping patterns, water use, employment, income
– Water availability in river system
Setting the Policy
Experiment Stage
UCD/Embrapa
A Basin-Wide Hydrology Model
Barreiras
Paracatu
Rio Paranaiba
Petrolina
UCD/Embrapa
Water
Available for
Agriculture
Water Available at the Entrance to Sobradinho Dam
Wet-Year Water
Availability (m3s-1)
Drought-Year Water
Availability (m3s-1)
January 5477.3 2991.8
February 5471.1 2955.0
March 5718.0 2364.9
April 3130.6 1578.3
May 1724.2 681.8
June 1573.5 274.0
July 1391.7 66.9
August 919.1 10.0
September 380.7 10.0
October 621.2 10.0
4ovember 1740.4 627.7
December 3863.4 2153.5
“Available” for Ag =
River Flow Entering
Sobradinho Dam Minus
2000 m3s-1 for
Environmental Flows (following Braga and Lotufo
2008)
Water Available at the Entrance to Sobradinho Dam
UCD/Embrapa
Upstream Water Demand
Upstream Water Demand for Boqueirão
(sample município)
Blue = baseline
Green = Sugarcane Price Increase
Total Demand of all Simulated
Upstream Responses to
Sugarcane Price Increases (m3s-1)January 39.5
February 33.4
March 40.1
April 22.3
May 27.1
June 37.8
July 54.4
August 89.5
September 99.4
October 92.5
November 74.6
December 43.1
UCD/Embrapa
Downstream Water
Availability after
Price Shock
Water Available at the Entrance to Sobradinho Dam
Available Water Downstream after
Sugarcane Price Increase (m3s
-1)
Wet Year Drought
January 5442 2973
February 5388 2927
March 5723 2154
April 3175 1585
May 1743 650
June 1483 222
July 1366 10
August 827 10
September 296 10
October 543 10
November 1718 574
December 3794 2016
UCD/Embrapa
Agricultural
Land Use
UCD/Embrapa
Area in Sugarcane
UCD/Embrapa
Rural
Employment
UCD/Embrapa
Agricultural
Profits
UCD/Embrapa
• Application of A4A Guidelines Will Affect Agriculture– Effects will depend on product mix, irrigation technology, location and
upstream effects, weather conditions, and product prices
• Hydro-Econ Model Can Help Predict:– The location and extent of effects on (say) profits
– Provide estimates of willingness to pay for more water• Hence, help develop water markets
• Effects of Sugarcane Price Increase on Ag– Shift in product mix
– Increased irrigated area
– Profits increase
– Upstream farmers not affected by drought; not so for downstream farmers
• Effects of Sugar Price Increase on Poverty – Bad news: little employment growth, small-scale sugarcane not likely to
participate in boom
– Good news: increased water use in sugarcane does not ‘crowd out’ crops with higher labor demand patterns
Conclusions and Policy
Implications
UCD/Embrapa
Muito Obrigado!
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