Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Assessing Agriculture-Water Links at Basin Scale: A Hydro-Economic Model of the São Francisco River Basin, Brazil
1. Assessing Agriculture-Water Links at
Basin S l
B i Scale: A H d E
Hydro-Economic Model of
i M d l f
the São Francisco River Basin, Brazil
Marco Maneta
Marcelo Torres
Stephen Vosti
Center for Natural Wesley Wallender
Resources Policy
Analysis
A l i -- CNRPA SFRB Team
September 2008 UCD/Embrapa
2. Presentation Overview
• Objectives of Modeling Exercises
• Overview of the Hydro model
• Overview of the Economic Model of Agriculture
• Interaction between Hydro and Econ Models
y
• Geographic Focus of Today’s Presentation
• Setting the Stage for a Two-Part Policy Experiment
– Application of ANA water use guidelines and a sugarcane
price shock
• Simulation Results
– Hydrology
– Agriculture
g
• Conclusions and Policy Implications
UCD/Embrapa
3. Key Objectives of Hydro-
Economic Models
E i M d l
• 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 Model
– Buriti Vermelho Model
– Basin-Wide Model
UCD/Embrapa
5. Core of the Economic Model of
Agriculture: Farmer Objective Function
max ∑ pit qit (x nirrt , ewit (xirrt )) − ∑ w jt xijt − ∑ cewit (pirrt , xirrt ; z)
i i i
Agricultural Production Function Effective Water
•Vector of Non Irrigation Inputs (xnirr):
Vector Non-Irrigation Cost
Crop •Fertilizers, seeds, land, pesticides, Non-Irrigation • Irrigation Input
Prices machinery etc Input Cost Prices – pirr
•Effective Water – ew • Price - wsj • Irrigation Input
•Function of Irrigation Inputs (xirr)
F ti f I i ti I t ( ): •Q
Quantity - xsij
tit Quantities - xirr
Q titi
•Applied water • z – Vector of
•Irrigation Capital factors that may
•Irrigation Labor
g affect irrigation costs
•Irrigation Energy (e.g. distance to
( di t t
river)
UCD/Embrapa
6. Economic Simulation Model
E i Si l ti M d l
max ∑ pit qit (x nirrt , ewit (x irrt )) − ∑ w jt xijt − ∑ cewit (p irrt , x irrt ; z)
ˆ
x
i i i
Land : ∑ land it ≤ Bland t
i
Subject to: Labor : ∑ labor it ≤ Blabor t
i
Surface Water : swm ≤ Bswm
UCD/Embrapa
7. Basin-Wide Models’ Temporal and
B i Wid M d l ’ T l d
Spatial Resolutions and Extents
Spatial Resolution
Hydro model 14 large polygons
Econ model Município
Temporal Resolution
Hydro model month
Econ model agricultural season
Spatial Extent
SFRB, both models
Temporal Extent
Decades, both models
UCD/Embrapa
8. Hydrologic & Economic Model Links
y g
• Crop-specific Algorithm to translate
g HYDROLOGIC
• poduction cropping decisions into MODEL
• water use water demand
• irrigation efficiency
Cropping Decisions Hydrologic Consequences
ECONOMIC • Water available for ag
Algorithm to translate
O
MODEL hydrologic consequences • rainfall
into water availability •surface water
UCD/Embrapa
10. Setting the Policy
Experiment Stage
• Variable Weather Conditions
– Wet year and drought
– Rainfall and evapotranspiration
• Water Policy Setting
– Application of the ANA guidelines
• Price Shock
– Large increase in sugarcane prices
• Use Hydro-Econ Models to Predict:
– Cropping p
pp g patterns, water use, employment, income
, , p y ,
– Water availability in river system
UCD/Embrapa
11. Water Available at the Entrance to Sobradinho Dam
Water
Available for
Agriculture
Water Available at the Entrance to Sobradinho Dam
Wet-Year Water Drought-Year Water
Availability (m3s-1) Availability (m3s-1)
January 5477.3 2991.8 “Available” for Ag =
February 5471.1 2955.0
March 5718.0 2364.9 River Flow Entering
April 3130.6 1578.3 Sobradinho Dam Minus
May 1724.2 681.8
June 1573.5 274.0
2000 m3s-1 for
July 1391.7 66.9 Environmental Flows
August 919.1 10.0 (following Braga and Lotufo
September 380.7
380 7 10.0
10 0 2008)
October 621.2 10.0
November 1740.4 627.7
December 3863.4 2153.5
UCD/Embrapa
12. 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 y 39.5
February 33.4
March 40.1
April 22.3
Mayy 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
13. Available Water Downstream after
Available Water Downstream after
3 ‐1
Sugarcane Price Increase (m s )
Downstream Water January
Wet Year
5442
Drought
2973
February 5388 2927
Availability after March
April
5723
3175
2154
1585
Price Shock May
June
J
1743
1483
650
222
July 1366 10
August 827 10
September 296 10
Water Available at the Entrance to Sobradinho Dam
Water Available at the Entrance to Sobradinho Dam October 543 10
November 1718 574
December 3794 2016
UCD/Embrapa
14. Upstream Cultivated Areas
(by scenario, irrigation)
500,000
400,000 Agricultural
300,000
200,000 Land Use
L dU
100,000
0
Baseline Sugar Price -- Sugar Price -- Wet
Drought Year
Downstream Cultivated Areas
Rainfed Irrigated Total Cultivated Area (by scenario, irrigation)
900,000
800,000
700,000
600,000
500,000
500 000
400,000
300,000
200,000
100,000
0
Baseline Sugar Price -- Sugar Price --
Drought Wet Year
Rainfed Irrigated Total Cultivated Area
UCD/Embrapa
15. Area in Sugarcane
Upstream Sugarcane Areas
(by scenario, irrigation)
30,000
30 000
25,000
20,000
15,000
10,000
5,000
5 000
0
Baseline Sugar Price -- Sugar Price --
Drought Wet Year
Downstream Sugarcane Areas
(by scenario, irrigation)
Total Sugarcane Total Irrigated Sugarcane
50,000
40,000
30,000
20,000
10,000
0
Baseline Sugar Price -- Sugar Price --
Drought Wet Year
Total Sugarcane Total Irrigated Sugarcane
UCD/Embrapa
16. Upstream Agricultural Employment
(by scenario, irrigation) R l
Rural
6,000
5,000
,
4,000
Employment
p y
3,000
2,000
1,000
0
Baseline Sugar Price -- Sugar Price --
Drought Wet Year
Downstream Agricultural Employment
Total Rural Employment
p y Total Irrigated Ag Employment
g g p y ( y
(by scenario, irrigation)
, g )
50,000
40,000
30,000
20,000
10,000
0
Baseline Sugar Price -- Sugar Price --
Drought Wet Year
Total Rural Employment Total Irrigated Ag Employment
UCD/Embrapa
17. Upstream Sugarcane and Total Ag Profits
(by scenario, irrigation)
120,000,000
100,000,000
80,000,000
60,000,000
40,000,000
40 000 000
Agricultural
20,000,000
0
Baseline Sugar Price -- Sugar Price --
Profits
Drought Wet Year
Total Ag Profits Irrigated Ag Profits
Total Sugarcane Profits Irrigated Sugarcane Profits
Downstream Sugarcane and Total Ag Profits
(by scenario irrigation)
scenario,
300,000,000
250,000,000
200,000,000
150,000,000
100,000,000
50,000,000
0
Baseline Sugar Price --
S gar Sugar Price -- Wet
S gar
Drought Year
Total Ag Profits Irrigated Ag Profits
Total Sugarcane Profits Irrigated Sugarcane Profits
UCD/Embrapa
18. Conclusions and Policy
Implications
I li ti
• Application of ANA 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 f S
Eff t of Sugarcane P i Increase on Ag
Price I A
– 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
– B d news: li l employment growth, small-scale sugarcane not likely to
Bad little l h ll l lik l
participate in boom
– Good news: increased water use in sugarcane does not ‘crowd out’ crops
with higher labor demand patterns UCD/Embrapa