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Tradeoff analysis and NUTMON: Linking models for policy analysis

Tradeoff analysis and NUTMON: Linking models for policy analysis. A.P Mora-Vallejo, J.J. Stoorvogel, J. Antle, A. de Jager, C. Crissman. Background.

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Tradeoff analysis and NUTMON: Linking models for policy analysis

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  1. Tradeoff analysis and NUTMON: Linking models for policy analysis A.P Mora-Vallejo, J.J. Stoorvogel, J. Antle, A. de Jager, C. Crissman

  2. Background • NUTMON studies provide a clear characterization of present farming systems and have guided the targeting of integrated nutrient management interventions at the farm level. • Though several INM techniques have been proposed and encouraged locally, effective implementation of agricultural policies to support these new technologies is still lacking. • We linked the NUTMON toolbox to the Tradeoff Analysis Methodology (TOA) in order to draw conclusions from nutrient budgets in Africa and move the discussion in the direction of effective intervention and policy making.

  3. NUTMON process TOA process 1 Priority setting STAKEHOLDER MEETINGS FARM SELECTION 2 Farm data LITERATURE AND ANALYSIS DATA FARM SURVEY FARM SURVEY LITERATURE GIS DATA (soil, climate) Clean up, analysis, debugging MODEL ESTIMATION CLEAN FARM DATA SCENARIO ANALYSIS 3 Simplified model NUTRIENT BALANCE CALCULATIONS ENVIRONMENTAL IMPACT MODEL RESULTS TRADEOFFS STAKEHOLDER MEETINGS RESULTS

  4. The Machakos Case • Machakos application has been carried out as a first attempt of TOA in SSA • It is a case study to solve technical issues of the model in a new environment • It is an application to call attention of local policy makers and researchers for further development in the region

  5. Machakos Study Area

  6. 1. Machakos 2. Kionyweni 3. Kasikeu 4. Kiomo 5. Matuu 6. Kibwezi

  7. 1. Machakos 2. Kionyweni 3. Kasikeu 4. Kiomo 5. Matuu 6. Kibwezi

  8. 1. Machakos 2. Kionyweni 3. Kasikeu 4. Kiomo 5. Matuu 6. Kibwezi

  9. Inherent Productivities • Farmers’ expected output for the growing season is an important driving factor behind their decision making process • The output is a function of the inherent land qualities and current land management in a particular field • Calculated with crop growth simulation models from the DSSAT • Given the complexity of mixed farming systems, crop system were used in the analysis such as mixed, maize, vegetables, grass, maize & beans.

  10. Model Estimation • Inherent productivities are then used to estimate the econometric production model that describes the farmers’ decision making process • Explains the variation in management practices for the different crops based on soil and climate.

  11. Spatial data vcode climate soil

  12. Nitrogen depletion (kg ha-1 year-1) vs Net Returns (KSh ha-1) for a single TOP in a base scenario (aggregation by farm)

  13. Nitrogen depletion (kg ha-1 year-1) vs Net Returns (KSh ha-1) for 5 TOP and 3 scenarios(aggregation by TOP)

  14. Mapping TOA results

  15. Conclusions • NUTMON is an excellent source of data for TOA applications • Time consuming data gathering for TOA can be greatly decrease by using NUTMON data sets • The framework of NUTMON and TOA are perfectly complementary

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