The Southeast Climate Consortium (SECC 1 ):

Transcription

1 The Southeast Climate Consortium (SECC 1 ): Integrating Research and Extension on Climate, Agriculture, and Water Resources James W. Jones Agricultural & Biological Engineering University of Florida 1 Univ. of Florida, Florida State Univ., Univ. of Miami, Univ. of Georgia, Auburn Univ., Univ. Alabama-Huntsville

2 Outline The SECC & How it Works Example Research & Extension Activities Integration Characteristics Some Lessons Learned New Opportunities

3 The SECC Multi-state, multi-disciplinary research and extension program; seven universities; 10 years old One of 8 Regional Integrated Research Assessment (RISA) Centers nationally as designated by NOAA Funding: NOAA, USDA-RMA, USDA-CSREES, Integrates climate, agriculture, water resources research to provide information at local & regional scales on climate risks & management options Past emphasis on climate variability/forecasts & risk management About 60 faculty, post docs, graduate students

4 SECC Universities: PIs Florida State University: J. J. O Brien, E. Chassignet University of Florida: J. W. Jones, K. T. Ingram (SECC Coordinator) University of Miami: D. Letson University of Georgia: G. Hoogenboom University of Alabama-Huntsville: J. Christy Auburn University: J. Novak North Carolina State University: G. Wilkerson

5 SECC Goal Develop climate information and decision support systems for the SE USA that contribute to improved quality of life, increased profitability, decreased economic risks, and more ecologically sustainable agriculture, forestry, and water resources

6 SECC Program Themes Climate (J. O Brien, FSU) Agricultural Research (J. W. Jones, UF) Water Resources (P. Srinivasta, Auburn U) Decision Analysis (D. Letson, UM) Agricultural Extension (C. Fraisse, UF; J. Paz, UGA)

7 Some Climate Research Activities Improve seasonal climate forecasts in the SE for stakeholders Statistical methods Regional climate downscaling models Methods for forecasting drought & other indices for use in agriculture & water resources management KBDI LGMI Ag-relevant climate indices (degree days, chill units, ) Chill Units; La-Niña O Brien, Zierden, Bellow, (FSU); Christy (UAH); Fraisse (UF); Paz (UGA); Stooksbury (UGA) Link climate and crop/land use models

8 Ag Indices Derived From Climate Information LGMI Drought Movie June 05 May 26 J. Christy et al., UAH Examples Keetch-Byram Drought Index (KBDI) Chill Units for vernalization Lawn & Garden Moisture Index (LGMI) Growing Degree Days KBDI>550 Severely Dry

9 Linking Climate, Crop, & Land Use Models Filter GCM/RCM outputs for crop model use Principal Component Analysis (PCA)/Canonical Correlation Analysis (CCA) for adjusting GCM/RCM outputs for crop model use (Baigorria et al.) Multiple GCM/RCM outputs for ensemble of Monte Carlo methods Direct integration of crop and land use models with climate models Other statistical methods and combinations of above FSU and UF Impacts on local/regional temperature of 2 land development scenarios (see MyRegion.org) relative to current FSU conditions and UF

10 Some Agricultural Research Activities Adapt, improve & evaluate climatesensitive crop models Link climate & crop models Forecast yield, irrigation demand and other ag variables Forecast plant diseases Net energy content analysis of biofuel from corn Energy use and CO 2 emissions in production and transport of crops *

11 Crop Models & Climate Uncertainties associated with climate forecasts & crop model predictions Stochastic crop model capabilities Martinez et al. (UF) 30 f < > < > g h 0 < > 3 Error, Mg ha -1 Estimating parameters using Bayesian, Monte Carlo methods Economic value of risk reduction management practices Richard T. McNider, John Christy, Abigail Crane, Katherine Petty (UAH) & Joel Paz (UGA)

12 Decision Analysis in the SECC Objectives Understand how people make decisions, and constraints affecting climate information use Provide feedback for developing new climate information and decision support systems and disseminating information to end-users Integrate climate forecasts into a broader information and decision support system

13 Some Decision Analysis Activities Integrate Climate, Biophysical, Socioeconomic, and Policy Components into comprehensive optimization and simulation models Assess impacts of government intervention on the use of ENSO-based climate forecasts Research to influence users decision or government policy making in order to improve socioeconomic well being and reduce risk Evaluate use and value of SECC information & products

14 Some Water Resources Activities Assess stakeholder needs & establish partnerships Understand and describe effects of climate variability on water resources Integrate hydrological models with down-scaled climate forecasts for water resources decision making Develop and evaluate climate information and decision support tools for water resources management, and extend information and tools to decision makers

15 Example: Impacts of Climate Variability on Surface and Groundwater Quality Link watershed and crop models to assess environmental and economic impacts of BMPs Suwannee & Sante Fe Watersheds Climate predictions to help minimize impacts of surface and groundwater quality

16 Example Water Utility Operational Decisions Integrate rainfall forecasts with utility company hydrology and decision models Assess benefits of seasonal rainfall forecasts on rotating withdrawals among available supplies Assess management options of water supply reservoirs Observed and forecast ground water levels (four weeks ahead)

17 Agricultural Extension Develop climate information & decision support tools Manage DSS (AgroClimate) Conduct training & educational programs for Extension agents & farmers Conduct applied research

18 Example AgClimate Tools ENSO phase effects on corn yields County Regional El Niño La Niña ENSO Phase Effects

19 Agricultural Outlooks (Peanut) - by Extension commodity experts and SECC

20 SECC Integration Characteristics Emphasis on physical, biological, and economic model integration AgClimate as a focal point for extension Proposals across institutions Assessments; social scientist engagement with all themes Bi-annual review and planning meetings Coordinator engaged with all themes, good communication

21 Some Lessons Learned High level of interest in climate variability, but this interest has to be developed locally Individual farmers, ranchers, foresters Institutions (i.e., Extension, researchers) Considerable effort is needed to reach decision makers in agriculture due to its extensive nature, complexity Research alone is not sufficient; participatory, co-learning approach is essential Extension Service involvement need to work with trusted advisors Active involvement of administrators, program managers

22 New Opportunities More emphasis on drought at field, watershed, and regional levels More emphasis on water resources management Move more into climate change arena Longer term forecasts for water, ag and other applications Carbon resources management Optimizing systems for bioenergy production in the context of climate variability and climate change in the SE Tools for environmental services assessments; implications of land use and land management on local/regional climate, energy use, and carbon resources Expand into other states in the SE

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