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A presentation at the launch of CRP1.1 - Dryland Systems on Modeling.

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  • Serve as resource person at invitation of Bill PayneFacilitator for a group of modelers and analysts at Texas A&MHelp set the context for discussion of approaches to an integrated modeling approach for research and managementImportance of further synthesis building on established experience and methods
  • Those involved in the program know these well – the major dimensions of the program make up the Drylands System Matrix – target regions, themes, and interventions
  • Drylands System Program is a “system of systems” where within individual cells of the matrix a system approach is envisioned and can be modeledModeling the overall Dryland Systems matrix has multiple purposes and outcomes including
  • Modeling the overall Drylands system matrix is not for the faint of heart – complex and challenging.Likely involves an evolutionary processVarying levels of success and utility are expectedThe approach helps define the broad dimensions of the system and the relationship of its partsThe approach provides a tool for planning, discovery, management metrics, and outcome estimates
  • Diversity of opinions s on systems approaches calls for up-front definitions in operational termsIn our groups thinking, we define an integrated system as one which links production, environmental, economic and social elements into an interactive set of computations that produce an integrated output relevant to research and users
  • Colleagues at Texas A&M are working together to link a suite of well established models into an integrated system that is reasonably comprehensive and, hopefully, useful. I am suggesting this approach might be one way of moving the Drylands Program towards a consistent modeling system. Here is how it works ---
  • The elements if the integrated system have earlier roots in a project done for USAID in the 90’s under the SANREM CRSP. There was further evolution of the system under the U.S. Department of Homeland Security in livestock biosecurity. Most recently, the BMGF have sponsored a small contract to evaluate the utility of the system for their applications and those they sponsor. A pilot study to demonstrate the utility of the system was done in Ethiopia where our team had substantial experience and where the Foundation has strong ties.
  • Our recent mission to Ethiopia established active interest in the use of the IDSS. This includes national programs where there plans are emerging for application in the MOE and the ATA. CG Centers with locations in Addis are also actively interested in the system. This includes ICARDA and the Drylands System Program
  • Time does not allow a detailed description of the IDSS, but these are the most important general applications that we envision can be made – stated in general terms. The specifics are defined by each application and vary depending on needs of the user
  • Specifically, we suggest that the IDSS be considered by the modeling group as one of the approaches that might be part of a medley of modeling methods that could be linked and tailored to the needs of individual and transcending elements of the Drylands System matrix.
  • I am providing a “two-pager” handout with a brief description of the IDSS. My contacts are shown here along with a website where you will find a description of the IDSS, the draft report we recently completed for the Gates Foundation and an expanded set of slides from this presentation.
  • Modelling

    1. 1. CGIAR Research Programon Dryland SystemsSystems Approach forIntegration of Planning andProduct
    2. 2. Dimensions of Dryland Systems Matrix• Five Target Regions• Four Themes• Integrated Technology and Policy Interventions
    3. 3. Drylands - A System of Systems• Individual cells within the Dryland Systems matrixemploy a systems approach - which can bemodeled individually• Modeling the overall Dryland Systems matrix in acommon integrated modeling environment• Models various dimensions at varying levels of scale• Contributes to a consistent planning framework• Helps define potential synergies and interactions• Contributes to a consistent method for program evaluationand defining outcomes meaningful to investors
    4. 4. Modeling the Integrated Systems• Dryland Systems forms a complex and challengingmodeling matrix• Integrated Systems approach defines the broad dimensionsof the system components and develops explicitrelationships between them• The approach uses an integrated modeling environment for:– Planning– Discovery– Management metrics– Outcome estimates
    5. 5. Integrated Modeling Environment• Dimensions of the system– Production– Environmental– Economic– Social• Linkages and interaction between and across the elements of thesystem is challenging• Many modeling systems exist and could be relevant – all are pacedby limited quality input data• The goals, construct, and planned outcomes of the Drylands Systemcould be well served by an integrated modeling approach
    6. 6. Integrated Decision SupportSystem
    7. 7. Bill and Melinda Gates FoundationProject Evolution• Pilot Study – Demonstration of application of the GDSS (IDSS) fortechnology innovations – subsistence farmers – January 2013• Presentation at BMGF Headquarters – broad interest in applications• Additional funding and short term engagement with stakeholders inEthiopia to validate outputs, sustainability and explore applications• Completion of recent mission to Ethiopia to help validate the utilityand sustainability of the methods in developing countries
    8. 8. Stakeholders Engagement in Ethiopia• Ministry of Agriculture• Agricultural Transformation Agency• CGIAR Centers– IWMI– ILRI– ICARDA– CIMMYT– IFPRI
    9. 9. IDSS Applications•Provide common modeling environment for ex ante analysesto inform investment decisions, evaluate progress duringproject implementation, and forecast integrated impact frominterventions.•Identify optimum outcomes for situations which requiretrade-offs among production, environmental and economicbenefits and costs.•Hydrologists can project how water harvesting for irrigationwill affect stream flows and water quality indicators (e.g.,suspended solids, ortho-phosphate, biological oxygendemand).•Soil scientists can project how alternative cropping systemsaffect indicators of soil fertility (e.g., topsoil pH, organicmatter contents, extractable phosphorus).•Agronomists can anticipate additional nitrogen fertilizerrequired to take advantage of irrigation or the increased yieldpotential of an improved variety.
    10. 10. IDSS Applications•Human nutritionists can project the impacts of interventions(such as small-scale irrigation to grow green and yellowvegetables) during the dry season on family nutrition.•Economists can project impacts of increased investments inadditional land, fertilizer, seed, and/or irrigation on theprobability of farm solvency over the next five years.•Government officials concerned about floods andsedimentation of rivers, lakes and irrigation canals cananticipate impacts of check dams on tributaries supportingsmall scale irrigation projects.•Government policy makers can anticipate impacts fromsubsidizing costs of fertilizers, seeds and other inputs onfamily nutrition and income from sales of agriculturalproducts.
    11. 11. Potential IDSS Engagements withDrylands Systems ProgramUtility of integrated production-environmental-economic assessment– Explore interest/feasibility of application of the IDSS to Drylands SystemProgram– Additional set of tools to augment ongoing modeling– Consider cross cutting themes for 5 regions to enable common linkedassessment of plans and outcomes– Establish a framework to use linkages to relevant models and databaseswithin/across projects– Part of the broader network of CG centers application of the IDSS as acomponent of the larger system
    12. 12. Contacts• Neville P. Clarken-clarke@tamu.edu Overview- Pilot Study Report- Slides from Conference
    13. 13. Scenarios Modeled• Current farming practices in twokebele in the Lake Tana Basin• Enhanced by optimum fertilizationand water• Further enhanced by improvedgermplasm and cropping systems
    14. 14. 0501001502002501/1/19936/1/199311/1/19934/1/19949/1/19942/1/19957/1/199512/1/19955/1/199610/1/19963/1/19978/1/19971/1/19986/1/199811/1/19984/1/19999/1/19992/1/20007/1/200012/1/20005/1/200110/1/20013/1/20028/1/20021/1/20036/1/200311/1/20034/1/20049/1/20042/1/20057/1/200512/1/20055/1/200610/1/20063/1/20078/1/2007Observed Gmera riverSWAT Simulated FlowSWAT Accurately Simulates Stream FlowsGumera River
    15. 15. SWAT Accurately Simulates Teff YieldsSouth Gandor
    16. 16. Teff Yields Increased Dramaticallywith Adequate Fertilizer N
    17. 17. APEX – Yields Respond to FertilizerN, Improved Varieties, and CropRotations
    18. 18. Net Cash Farm Income• Two farming interventions shift the NCFIprobability distribution to the right• Relative risk increased greatly but aroundmuch higher mean incomes• Higher yields more than offset lower prices
    19. 19. Net Cash Farm Income
    20. 20. Family Protein Consumption