Crop Modeling,
The 2012 “Flash Drought”
&
Irrigation Demand
Cameron Handyside
University of Alabama in Huntsville
Earth Systems Science Center
September, 2013
Background
Decline in Alabama commodity crops
was characteristic of Southeast as a
whole
Yield Benefit of Irrigation
Irrigated
Midwest
Yields
Rainfed
Profit while paying for
irrigation infrastructure
How do we run these scenarios?
Crop Model
Soil Conditions
Weather data
Model
Crop Management
Genetics
Simulation
Growth
Development
Yield
Environmental Impact
Natural Resource Use
Net Income
DSSAT
• “Decision Support System for Agro-Technology”
• Computer simulation model of the soil-plantatmosphere system
• Widely accepted crop model
• Used to model “What-if” scenarios incorporating
multiple factors (weather, soil, cultivar,
irrigation…)
• Outputs:
• Inputs:
•
•
•
•
Min/Max Temperature
Precipitation
Insolation (sunshine)
Soil
•
•
•
•
•
Yield
Drought Stress
Irrigation Demand
Fertilizer Demand
Residual Fertilizer
DSSAT to GriDSSAT
Workflow
“X File”:
• Planting Dates
• County Soil Types
• Cultivar
Spatial Weather:
• Insolation
• Temperature
• Precipitation
Run
DSSAT
~36,000
times a
day!
Model Output
• Yield
• Drought Stress
• Irrigation Demand
• Residual Fertilizer
GriDSSAT Website Updated
Daily
http://gridssat.nsstc.uah.edu/
Week of May 29th, 2012
Comparison of the U.S. Drought Monitor to the GriDSSAT
Crop Stress Index and 7-Day Cumulative Precipitation
Week of June 5th, 2012
Week of June 12th, 2012
Week of June 19th, 2012
Week of June 26th, 2012
Week of July 3rd, 2012
Week of July 10th, 2012
Analysis w/ Crop-Scape
Masking
Week of August 31st, 2012
2012 Yields with Irrigation
222 bu/ac
183bu/ac
173 bu/ac
119 bu/ac
45 bu/ac
Irrigation Demand is Dynamic
GriDSSAT
Crop
Model
USDA
NASS
CropScape
Data
Watershed
Irrigation
Withdrawals
Provide both Crop Stress & Water Stress to Stakeholders
Real-time Radar
Derived Precipitation
Satellite derived insolation
NASA land surface
temperatures
Real-time
WaSSICrop
Model
Real-time
Gridded
Model
THANK YOU!
QUESTIONS?