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 Environmental Impact Yield Net Income Development Natural Resource Use

DSSAT

• “Decision Support System for Agro-Technology” • Computer simulation model of the soil-plant atmosphere system • Widely accepted crop model • Used to model “What-if” scenarios incorporating multiple factors (weather, soil, cultivar, irrigation…) • Inputs: • • • • Min/Max Temperature Precipitation Insolation (sunshine) Soil • Outputs: • 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 29 th , 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 12 th , 2012

Week of June 19 th , 2012

Week of June 26 th , 2012

Week of July 3 rd , 2012

Week of July 10 th , 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 NASA land surface temperatures Satellite derived insolation

THANK YOU!

QUESTIONS?