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Climate Variability and Climate Change: Decision Making under Uncertainty. Gerrit Hoogenboom Director, AgWeatherNet & Professor of Agrometeorology Washington State University, USA. AgMIP –Pakistan Kickoff Workshop & International Seminar on Climate Change
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Climate Variability and Climate Change: Decision Making under Uncertainty Gerrit HoogenboomDirector, AgWeatherNet & Professor of Agrometeorology Washington State University, USA AgMIP–Pakistan Kickoff Workshop & International Seminar on Climate Change University of Agriculture Faisalabad, PakistanJune 4-6, 2013
Winter Outlook Weather and Agriculture • Weather has an important impact on agriculture, both crop and animal production. • For dryland agriculture more than 90% of the variability in yield can be explained by weather conditions.
Winter Outlook Climate and Weather • Does a farmer have options to modify or change his production system? • If so, what are these options? • Can weather and climate information play a role? • How do we provide this information?
National Weather Service • Cooperative Weather Station Network • Volunteer data collection network • Limited set of data (temperature and rainfall) • Approximately 85 stations in Georgia • Long-term records • Data collected at Griffin Experiment Station since 1926
Georgia Automated Environmental Monitoring Network • First weather station was installed in 1991 • Air temperature, rainfall, relative humidity, wind speed and direction, solar radiation, soil moisture
Winter Outlook Wind Machines & Frost
Climate Variability and Climate Change 2-3 months Inter-annual Decadal Climate Variability Several decades 50+ years Centuries Climate Change
Changing Ocean Temperatures Impacts the climateacrossthe globe
El Niño and La Niña • El Niño: above-average sea-surface temperatures that develop across the east-central equatorial Pacific. • La Niña: cold phase
Effects of El Niño Why are El Niño and La Niña important?
Effects of La Niña Why are El Niño and La Niña important?
ENSO and Tomato Spotted Wilt Virus (TSWV) severity in peanut Deviation from mean severity (%) (a). Leaf symptoms of TSWV on peanut (b). Western Flower Thrips (vector) Field observations (188 fields, 5 seasons)
Farmers and Climate: Why models? • Traditional agronomic approach: • Experimental trial and error • Systems Approach • Computer models • Experimental data • Understand Predict Control & Manage • (H. Nix, 1983) • Options for adaptive management and risk reduction
Soil Conditions Weatherdata Model Crop Management Genetics Simulation Growth Development Yield
Soil Conditions Weatherdata Model Crop Management Genetics Simulation Growth Development Yield Pollution Net Income Resource Use
Linkage Between Data and Simulations • Model credibility and evaluation • Input data needs: • Weather and soil data • Crop Management • Specific crop and cultivar information • Economic data
Observed and simulated soybean yield as a function of seasonal average rainfall (Georgia yield trials)
Observed and simulated soybean yield as a function of average max temperature (Georgia yield trials)
Spatial Data Alabama, Florida and Georgia • Three representative soil profiles for each county • Soil surface data • Soil horizons • Crop management options: • Crop selection • Variety selection • Planting date • Irrigated versus rainfed • Fertilizer applications • Prices and production costs
Simulations: Cotton Yield Variety “DP555 BG/RR”9 planting dates, rainfed vs irrigated38 – 107 years of daily historical weather data
El Niño La Niña
Farmers and Climate Interviews • 38 farmers • 21 counties in GA • Semi-structured interviews - Risk management strategies - Access of weather & climate information
Farmers and Climate Risk Reducing Options Forecast Use: Irwin County Spring 2006 forecast for summer drought widespread shift from long- to short-cycle peanut variety
ElNiño Farmer Joe’s Questions La Niña
Management Decisions • Crop selection • Variety selection • Planting dates • Acreage allocation • Irrigation • Pest management • Amount and type of crop insurance
Historical weather data (1900-2005) ENSO PhasesPlanting dates Soil typesSelect AL, FL, GAcounties Yield Total amount of irrigation No. of irrigationevents CSM-CROPGROPeanut Model Crop Simulations April 16, 23May 1, 8, 15, 22, 29June 5, 12
Crop Simulations: AgroClimate Extension, Producers and Consultants
Extension Agents& Specialists Farmers/Growers Climate-based Management Options Needs for Specific Commodities Interaction & Participation Crop Models & Climate-based Tools Web-based DSSwww.AgroClimate.org Stand aloneDecision AidTools Forecasts,Climatology Climate in the Southeastern USA: How do farmers make decisions?
Climate Change and Climate Variability The impact of climate change and climate variability on agricultural production and the potential for mitigation and adaptation • Future issues can only be studied with simulation models • “What-If” type of scenarios
Agriculture and Climate ChangeImpact and AdaptationCamilla, Mitchell County, Georgia Maximum and Minimum Temperature Precipitation
Maize Yield (kg/ha) Mitchell County, Georgia, USA4 varieties, 3 soils, rainfed and irrigated Long-term historical weather data
Corn Yield (kg/ha) Agriculture and Climate ChangeMitchell County, Georgia, USA4 varieties, 3 soils, rainfed and irrigated GCM-Modified CSIROMK2, Scenario IS92a, 2010-2039 Historical weather
Agricultural Irrigation Water Demand forecast for 2011 to 2050 • University of Georgia (UGA) and the State of Georgia Environmental Protection Division • Purpose: • Prepare forecasts of irrigation water demand that meet the needs for the agricultural sector of the Georgia economy during the first half of this century.
Model Evaluation DSSAT Version 4.5 Five cropping seasons: 2000-2004 Crop Management : UGA Extension Production Guidelines Field specific water use data: Agricultural Water Pumping (AWP) project