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7 icraf gfsm rome-mmarshall_05202015

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The Global Futures and Strategic Foresight (GFSF) team met in Rome from May 25-28, 2015 to review progress towards current work plans, discuss model improvements and technical parameters, and consider possible contributions by the GFSF program to the CRP Phase II planning process. All 15 CGIAR Centers were represented at the meeting.

The Global Futures and Strategic Foresight (GFSF) team met in Rome from May 25-28, 2015 to review progress towards current work plans, discuss model improvements and technical parameters, and consider possible contributions by the GFSF program to the CRP Phase II planning process. All 15 CGIAR Centers were represented at the meeting.

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7 icraf gfsm rome-mmarshall_05202015

  1. 1. 26 May 2015 Towards the simulation of global crop productivity in IMPACT with geospatial data Michael Marshall World Agroforestry Centre United Nations Ave, Gigiri P.O. Box 30677-00100 Nairobi, Kenya +254207224244 m.marshall@cgiar.org
  2. 2. Global Crop Model Approaches ▪ Local-scale models (e.g. DSSAT and APSIM) aggregated via multiple-site calibration and averaging − Complex − High-input data requirement − Locally accurate − Site specificity (over-fitting) − Non-linearity ▪ Large-area models (e.g. GLOPEM and GLAM) − Simple − Low-input data requirement − Locally less accurate − Generalizable “Essentially, all models are wrong, but some are useful.”
  3. 3. Global crop model for IMPACT 𝐆𝐏𝐏 = 𝐟𝐬𝐭𝐫𝐞𝐬𝐬 𝛆 𝐦𝐚𝐱 𝐟 𝐀𝐏𝐀𝐑 𝐏𝐀𝐑 𝐟 𝐀𝐏𝐀𝐑 = 𝟏. 𝟐 ∗ 𝐄𝐕𝐈 𝐟𝐬𝐭𝐫𝐞𝐬𝐬 = 𝐦𝐢𝐧(𝐟 𝐓, 𝐟 𝐦) 𝛆 𝐦𝐚𝐱 = 𝟏 𝟏𝟐 𝐜 𝐦𝐚𝐱 − 𝚪 𝐜 𝐦𝐚𝐱 + 𝟐𝚪 𝐆𝐏𝐏 = 𝐟𝐬𝐭𝐫𝐞𝐬𝐬 𝜶 𝐦𝐚𝐱 𝐟 𝐀𝐏𝐀𝐑 𝐏𝐀𝐑 𝐟 𝐀𝐏𝐀𝐑 = 𝟏. 𝟐 ∗ 𝐄𝐕𝐈 𝐟𝐬𝐭𝐫𝐞𝐬𝐬 = 𝐦𝐢𝐧(𝐟 𝐓, 𝐟 𝐦) 𝛂 𝐦𝐚𝐱 = 𝟏. 𝟐𝟔 ∆ ∆ + 𝛄 Opti-LU Opti-WU 𝐟 𝐓 = 𝐞 − 𝐓 𝐦𝐚𝐱−𝐓𝐨𝐩𝐭,𝐬𝐞𝐚𝐬𝐨𝐧𝐚𝐥 𝐓𝐨𝐩𝐭,𝐬𝐞𝐚𝐬𝐨𝐧𝐚𝐥 𝟐 𝐟 𝐌 = 𝐟 𝐀𝐏𝐀𝐑 𝐟 𝐀𝐏𝐀𝐑𝐦𝐱 εmax=0.06 mol·mol-1 (C4)
  4. 4. Model Calibration, Sensitivity Analysis, and Validation ▪ Identify most important parameters, remove redundant or insignificant parameters, and potentially integrate new parameters − Model performance statistics − Monte Carlo Simulation − Residual analysis ▪ Multiple scales of validation − Plot (eddy covariance flux tower data) − Field (non-destructive biomass transects) − Landscape → global (high, moderate, and coarse resolution remote sensing)
  5. 5. Eddy Covariance Flux Towers ▪ Three towers (2009-2014) ▪ Alfalfa, rice, and citrus orchard ▪ 30-minute energy balance and meteorological data ▪ FAPAR (MODIS subset tool: http://daac.ornl.gov/) ▪ Daily GPP, RECO, and NPP
  6. 6. Transects 60 m* ▪ 10 quadrats per frame (2011-2012) ─ Alfalfa, cotton, maize, and rice ─ Biophysical data ─ Ground spectra ─ Destructive aboveground wet biomass ─ Empirical (non- destructive) model-building ▪ CIMIS 1 2 3 5 4 6 10 7 8 9 Marshall and Thenkabail (2015)
  7. 7. Tasseled Cap Transformation ▪ Weighted linear combinations of satellite reflectance − Brightness − Greenness − Wetness ▪ Fraction of vegetation, bare soil, and water ▪ Density Kauth and Thomas (1976)
  8. 8. Index of Agreement (yellow = perfect match) Biomass Dark Soil Light Soil PlantsPlants Reference Data ▪ AVHRR (5 km) ▪ MODIS (500 m) ▪ Landsat (30 m) ▪ IKONOS (4 m), WorldView (1.85 m), and GeoEye (1.65 m) Tasseled Cap Biomass Estimation for Validation at Remote Sensing Scales
  9. 9. Muchow (1990) GPP → Crop Yield Prince et al. (2001) expressed yield in terms of GPP: Yield = RS × HI 1 − m0 × SOS EOS GPP Where SOS is start of season, EOS is end of season, RS is the root-to-shoot ratio, HI is the harvest index, and m0 is grain moisture content RS, HI, and m0 are constant by crop type (Xin et al. 2013) OR
  10. 10. Need for systems simulation models in Agroforestry Systems Lloyd et al. (1990) ▪ Agroforestry systems large payoffs, but complex ▪ Systems simulation − Can handle complex systems − Provide targeted and effective intervention − Tunable for “future” climates ▪ Not widely used in SSA, because of data scarcity
  11. 11. ▪ GPP and crop yield model validated at multiple spatial scales in California − Thomas Gumbricht: MODIS-era GPP modeling tool for California − Patricia Masikate: Agro-forestry module (APSIM) and estimates of RS, HI, and m0 − Erick Okuto: SOS and EOS simulation ▪ Next year (2016): Global GPP and crop yield model development, calibration, and validation − @ 5 km resolution 1982 – 2014 (+30 years) Summary
  12. 12. Thank You

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