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T Tennigkeit soil carbon overview and issues july 2010

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T Tennigkeit soil carbon overview and issues july 2010

  1. 1. Soil carbon simulation models for carbon accounting: Overview and research issues FAO, CCAFS and CGIAR joint workshop: Towards a Framework for Smallholder Agricultural Mitigation: Soil Carbon Measurements and Simulation Models, Rome July 13th2010, presented by Timm Tennigkeit; UNIQUE forestry consultants
  2. 2. Steady state of soil carbon accounting methodologies Methodology Status Targeted standard/ applicationand key features Sustainable AgriculturalLand Management (SALM) Developer: World Bank BioCarbonFund 1stvalidationcompleted, except clarification from VSC requested related to the conditions to use of soil carbon models VCS, broad applicabilitywith focus on smallholder agriculture. Production/activity monitoring and model based default values. Adoption of Sustainable Grassland Mgmt through Adjustment of Fire & Grazing Developer:SyracuseUniversity, Soils for the Future LLC, JadoraInt. LLC Public review process, 1stvalidation initiated VCS, broad applicabilitywith focus on unfertilized grasslands, incooperatinglessons learned from SALM methodology. Activity monitoring & model based AND ex-post rectification of ex-ante estimates based on soil C measurements. Others Still in the development/ review process or waiting until related business deals are signed before entering public review/domain VCS, American CarbonRegistry, Panda Standard, Alberta Standard
  3. 3. Means to quantify carbon creditsSource: Coalition of Agricultural GHG (C-AGG) Activity monitoring + Remote sensing based, technology not ready to use Direct emission measurements Direct soil measurements RothC, CENTURY, DNDC
  4. 4. Most widely used carbon simulation models Simulation model Application Input data requirements RothCfrom the RothamstedAgricultural Research Centre in the UK Originallydeveloped for UK for agriculture Mostflexible and less demanding compared with CENTURY or DNDC with regards to input data. In particular the version used in the Australian carbon accounting system is very user friendly. CENTURYfrom Natural Resource Ecology LaboratoryColorado State University in the US Originallydeveloped for grasslands in the US Flexible and less demanding compared with DNDC with regards to input data DNDC i.e. DeNitrification- DeComposition) is a computer simulation model of carbon and nitrogen biogeochemistry in agro-ecosystemsfrom the University of New Hampshire Mainly for projects that aim to improve the use of fertilizer Verydemanding with regards to input data and since the model is updated very frequently in-depth understanding of the model is required
  5. 5. Steps involved to develop a land based carbon accounting system for smallholder agriculture The Western Kenya Smallholder Agriculture carbon project
  6. 6. Flowchart of carbon stock change estimation ΔC Activity data(ha) Emission factor (tCO2/ha/year) = XDefault value development •Literature & expert knowledge •C modeling •Existing data Project inventory & survey system- Soil Organic Carbon BiomassProject BiomassBaseline + Project scenario FactorMANAGEMENT x x FactorLAND-USE SOC ReferenceSOILTYPE Baseline scenario* FactorMANAGEMENT x x FactorLAND-USE SOC ReferenceSOILTYPE -
  7. 7. RothCmodel calibration •Stratification project region based on crop production and soil clay content •Model inputs: Crop productivity Residue production, Clay content, climate parameters, additional residue inputs, additional manure inputs, soil cover in each month (bare or covered) •Modelling equilibrium soil organic carbon stocks and with project stock changes •Validation of model results with available research from similar agro- ecological zones using comparable management practices: “BatjesN.H., GicheruP. (2004). Soil data derived from SOTER for studies of carbon stocks and change in Kenya (ver. 1.0; GEFSOC Project). Report 2004/01, ISRIC -World Soil Information, Wageningen”
  8. 8. Key monitoring parameter of the SALM methodology Crop production and activity monitoring: •Production •Area, crop, amount of production •Residuals use •Burning •Number and type of livestock •Manure use •Cover crops use •Nitrogen fixing species use •Fertilizer use •Estimate N2O emissions from N-fixing species and fertilizer use •Measure woody perennial growth •Trees and shrubs
  9. 9. Crop production and activity monitoring process •Estimate number of farmers and the area where SALM activities will be adopted to generate carbon assets. •Establish a transparent baseline and a monitoring system to reward farmer groups for generating carbon assets •Receive a written commitment from farmers to adopt “climate smart“ land use practices Design features: •Pretesting survey design and sampling size •Annual survey based on 200 farms (permanent samples), plus 20 temporary farm samples for annual retesting (to control biased treatment of permanent samples), plus 5 % additional plots (to consider late adopters) •Structured interview + farm sketch map
  10. 10. RothC: Default value development tC/ ha/ yr for low/ high crop production Residues removed from the field Residues left in the field Residues removed & 1 tC/ ha/ year of manure distributed Residues removed & 2 tC/ ha/ year of manure distributed Residues removed & 4tC/ ha/ year of manure distributed Residues left & 1 tC/ ha/ year of manure distributed Residues left & 2 tC/ ha/ year of manure distributed Residues left & 4 tC/ ha/ year of manure distributed Residues removed from the field 0.28/1.34 0.08/ 0.08 0.33/ 0.33 0.65/ 0.65 0.36/ 1.43 0.61/ 1.67 0.94/ 2.00 Residues left in the field - 0.20/ -1.26 0.04/ -1.02 0.37/ -0.69 0.08/ 0.08 0.33/ 0.33 0.65/ 0.65 Residues removed & 1 tC/ ha/ year of manure distributed 0.57/ 0.57 0.28/ 1.34 0.86/ 1.92 Residues removed & 2 tC/ ha/ year of manure distributed Residues removed & 4tC/ ha/ year of manure distributed -0.29/ 0.77 0.28/ 1.34 Residues left & 1 tC/ ha/ year of manure distributed 0.57/ 0.57 Residues left & 2 tC/ ha/ year of manure distributed Residues left & 4 tC/ ha/ year of manure distributed Kitale (ViA) t/ ha of production Low production 1st season 2nd season Maize 1,01 2,73 Beans 0,39 0,62 Potatoes 2,58 2,16 High production 1st season 2nd season Maize 7,1 11,4 Beans 2,0 2,2 Potatoes 4,9 6,7 C Model sensitiveness: • climate data • soil clay content • crop production/ residues • manure application Example: Mixed cropping with maize, beans, potatoes
  11. 11. Project monitoring costs (US$) Direct soil measurement Activity Cost estimate* Total cost % of carbon revenues Project activity documentation 16 /day 80,000 3.2% Sampling &reporting (incl. transport, contracted tonational research organization) 52/sample 452,400 18.3% Soilsample analysis (laboratory) 18 /sample 156,600 6.3% Sample archiving 0.1 /sample/month 104,400 4.2% Management and administration 10% 79,340 3.2% Activity & productivity monitoring survey (APMS) Survey pretesting and training 16/day 138,048 5.6% APMS survey & reporting 8/survey 24,488 1% Surveyanalysis & database management 8/survey 24,488 1% SOC modeling 50,000 2% Management and administration 10% 23,702 1% * Data sources: Canada’s Greenhouse Gas Offset System 2006: Guide to developing a quantification methodology and protocol; Winrock2004: Measurement and monitoring costs: influence of parcel contiguity, carbon variability, project size and timing of measurement events. Kenya project data.
  12. 12. Total cost comparison Direct measurement Crop production & activity monitoring Project cost item Total cost % of carbonrevenues Total cost % of carbonrevenues Carbon component 316,819 13% 316,819 13% Carbon monitoring 872,740 35% 260,726 11% Project implementation 1,293,600 52% 1,293,600 52% Total costs 2,483,159 100% 1,871,145 76% •Direct measurements would substantially increase carbon monitoring costs for the Kenya BioCarbonFund project without necessarily reducing uncertainty •Major challenge in measuring SOC: measuring small changes against high background levels, sampling costs •Crop production and activity monitoring: Quality assurance mechanisms are important •Model: Application of models has to be standardized; i.e. model parameter should be constant in the baseline and the project scenario run
  13. 13. Related research issues •Long-term controlled soil carbon monitoring plots for all farming systems and agro-ecology zones (or any other more appropriate stratification system) •Critical assessment of agricultural mitigation and adaptation technologies from a agronomy, ecological and socio-economic perspective (considering scale issues from plot to landscape) •Suitable inventory and statistical monitoring design (combining micro- plots, with remote sensing based technologies and direct emission measurements) •Cost/benefit benchmarking for soil carbon models and soil carbon monitoring systems •Implications from soil health research results for agricultural extension (demand specific aggregation & disaggregation of soil research results) •Farmer aggregation mechanisms (cooperatives, farmer groups, farmer field schools, outgrowershemes) and performance based agricultural monitoring and extension

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