GHG and SOC Modelling - Ger Kielly

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GHG and SOC Modelling - Ger Kielly

  1. 1. GHG and SOC Modelling HYDROMET, University College Cork. Rashid Rafique; Xianli Xu; Matthias Peichl; Michael Mishurov; Ger Kiely EPA National WorkshopModelling Efforts for Greenhouse Gas Accounting in Irish Agriculture and Associated Land Use November 24, 2010.
  2. 2. OUTLINE1. Data2. PaSim3. DnDc4. Empirical Scenario modelling for N2O5. RothC
  3. 3. 1. DATA
  4. 4. Eddy Covariance Flux Sites • Three sites with CO2 EC data since 2002 • Two grassland, one peatland • Dripsey grassland with N20 EC since 2002 • 4th site for CO2 EC at Dripsey forest 2009
  5. 5. Chamber N20 Sites 8 chamber N2O sites in Munster with weekly or biweekly data for 2008/09.
  6. 6. Soil Carbon Sampling Sites SoilC SoilH ForestC67 sites (2006/07) 43 sites (2008/09) 38 sites (2006/07)
  7. 7. 2. PaSim
  8. 8. Modelling net ecosystem exchange of CO2 in intensively managed humid-temperate grassland using the PaSim ModelPaSim 3.6 (v5) is a mechanisticallybased ecosystem model whichsimulates the:carbon, nitrogen and water balancesof theatmosphere-plant-soil system andcan be used to predict dry matterproduction of fertilized and cut mixedperennial meadows.The model consists of the five sub-models: - Soil physics - Soil biology - Plant - Animal - Micro-climate
  9. 9. Time series - Comparison of PaSim model estimates to eddy-covariance measurements taken from Lawton et al. (2006)
  10. 10. Annual CO2 exchange – PaSim vs eddy-covariance measurementsYr Measured Modelled T C ha-1 yr-1 taken from Lawton et al. (2006)2002 1.9 2.62003 2.7 2.62004 2.9 3.4
  11. 11. 3. DnDc
  12. 12. 12 DNDC : A process oriented computer simulation model  DNDC components: First component: soil climate, crop growth and decomposition (predicts soil temperature, soil moisture, pH, redox potential) Second component: nitrification, denitrification and fermentation (predicts trace gases i.e. N2O, CH4, NH3 etc)  DNDC Use: Cropping, Grazing, and forest systems. Model validation (validation against experimental data) Regional inventories (estimate GHG at national scales)  Sensitivity of DNDC: Very sensitive to climate, soil, and crop inputs  Results of DNDC: depends on the availability and quality of data. It varies from good agreement to poor agreement with measured data. Reproduces general trends and the annual fluxes but poor reproducibility of instantaneous and daily fluxes
  13. 13. Measured N2O Flux = 11.5 kg N-N2O ha-1 yr-1. DnDc Modelled = 15.4 kg:EFmeasure = 3.4%: EF modelled = 4.6%
  14. 14. 11o W 10o W 9o W 8o W 7o W 6o W 5o W14 Study Sites  Temperate climate with annual precipitation 54o N of 1200 mm  Daily temperature ranges from 5 oC in 53o N winter to 15 oC in summer Pallaskenry Solohead Kilworth Carrairg na bhFear  Soil types were Grey brown Podzolic, Donoughmore 52o N Ballinhassig Brown Podzolic and Gleys Clonakilty  All sites are active pastures and most of them are frequently grazed (LUha-1 1.0-3.0) 1. Ballinhassig 2. Clonakilty 3. Carriag nabhFear  Total N application range from 121 kg N ha- 1 yr-1 to 446 kg N ha-1 yr-1 4. Donoughmore 5. Pallaskenry 6. Kilworth 7. Solohead1 8. Solohead2
  15. 15. 15 N2O Fluxes Time Series (Measured & Modeled) BH SH1 CK Julian Days (2008 & 2009)
  16. 16. 16 Model validation (Measured & Modeled) 16 Statistical Verification Modelled (kg N2O-N ha-1 yr-1) 14 2 R = 0.5083 12 Sites BE MAE RMSE rRMSE R2 10 BH -0.003 0.007 0.010 0.57 0.56 CK -0.032 0.021 0.034 0.67 0.45 8 D 0.016 0.026 0.041 0.90 0.38 6 CF -0.006 0.020 0.024 0.60 0.49 4 PK -0.003 0.020 0.017 0.59 0.44 2 KW -0.004 0.020 0.017 0.59 0.43 0 SH1 0.003 0.007 0.012 0.59 0.58 0 2 4 6 8 10 12 14 SH2 -0.0001 0.070 0.091 0.60 0.32 Measured (kg N2O-N ha-1 yr-1) Overall -0.004 0.024 0.031 0.639 0.456 •Overall the average annual modelled annual Annual flux 1.39 1.75 2.98 0.47 0.51 flux was about 20% higher than measured
  17. 17. N2O flux scenario under different management by using DNDC 18 16 Current management N2O flux (kg N2O-N ha-1 yr-1) 14 50% reduces N input and LU Rough management 12 50% increased N input and LU 10 8 6 4 2 0 BH CK D CF PK KW SH1 SH2 Sites Sites % decrease % increase BH 15.18 9.45 • The % decrease is from current management to CK 33.53 7.55 rough management ranged from 15.18 to 57.31 D 57.31 11.99 • The % increase is from current management to 50% CF 22.11 9.145 increase N input which is ranged from 7.46 to 36.94 PK 19.73 9.40 KW 17.74 10.83 SH1 56.13 36.94 SH2 26.32 7.46 Over all 31.01 12.85Further task: To work with DNDC and up scale N2O emission for Ireland
  18. 18. 4. Empirical Scenarios
  19. 19. Scenario analysis of future N2O emissions• Two time frames: 2020 and 2050 (baseline year 2000)• Input datasets: – Common IPCC SRES scenarios: A1, A2, B1 – Climate predictions: C4I (http://www.c4i.ie/) – Land use change: ATEAM (http://www.pik- potsdam.de/ateam/) – N fertilizer use based on that REPS farms• Emission factors (EF): – Default IPCC Tier 1 EF (fixed 1%) – Climate- and crop-responsive EF (Flynn et al., 2005) – Climate-sensitive EF (Flechard et al. 2007)
  20. 20. Scenario analysis: Main conclusions• Significant drop in grassland area is the major driver of N fertilizers use decrease Croplands + N2O Year Fertilizers• Crop lands become marginally grasslands emissions more prominent both in terms of land area and the amount of 2000 39 365 km2 408 kt N 0.5-39.0 kt N N2O emissions• Climate change would generally 2020 −16 to −28% −40 to −48% −5 to −52% increase emissions, however, its contribution is heavily 2050 −31 to −38% −50 to −55% −13 to −57% dependent on choice of EF methodology
  21. 21. 5. RothC
  22. 22. Modelling the change in soil organic carbon (SOC) of grassland in response to climate change:effects of measured versus modelled carbon pools for initializing the RothC model
  23. 23. RothC model initialization issue The objective of this study was: to test whether the measured carbon fractions with the procedure of Zimmermann et al. (2007) are well related with the modelled pools as required by RothC; to determine the effects of different initializations of the RothC model with measured or modelled carbon pools on the outputs of SOC; to examine the effects of climate change on SOC in the temperate grasslands of Ireland.
  24. 24. Converting measured fractions to carbon poolsZimmermann et al. (2007) RothC Plant inputs DPM=Decomposable Plant material RPM = Resistant Plant DPM+ Material DPM RPM Splitting ratio DPM/RPM POM DOC HUM = Humified Organic calculated by equilibrium scenario Material RPM BIO = Microbial Biomass IOM = Inert Organic Matter HUM+ s+c – BIO Splitting ratio BIO/HUM HUM DPM Zimmermann (2007) S+A calculated by rSOC equilibrium scenario s+c = silt +clay Physically protected BIO RPM S+A = Sand and stable aggregates IOM POM = Particulate OM rSOC IOM RPM DOC = Dissolved OC Chemically protected Fractions Pools rSOC = Resistant SOC
  25. 25. Climate change from 1961-2000 to 2021-2060 from C4I 1961-2000 A1B A2 B1 1961-2000 A1B A2 B1 200 16 180 14 Precipitation (mm) Temperature (°C) 160 12 140 10 120 8 100 6 80 4 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 Month Month In future: wetter winters and drier summers higher temperatures
  26. 26. Measured and modelled carbon pools The measured and modeledModelled DPM (t C/ha) Modelled RPM (t C/ha) 1.5 15 values for BIO and HUM 1:1 line significantly correlated with 1:1 line 1.0 10 SolA each other, while not for DPM SolB and RPM Pall 0.5 5 Drip Ball For Pall, SolA and SolB, good surface drainage due to the 0.0 0 sloping lands and man-made 0.0 0.5 1.0 1.5 0 5 10 15 drainage channels which likely Measured DPM (t C/ha) Measured RPM (t C/ha) accelerated the decomposition Modelled HUM (t C/ha) of the RPM poolModelled BIO (t C/ha) 1.5 60 For Ball and Drip, poor drainage (underlying iron at Drip and 1.0 40 samples taken in flat areas at Ball) is likely to have slowed the decomposition of the RPM pool 0.5 20 0.0 0 0.0 0.5 1.0 1.5 0 20 40 60 Measured BIO (t C/ha) Measured HUM (t C/ha)
  27. 27. 25 Ball A1B_Me A1B_Mo Carr 45 A2_Me A2_Mo 24 B1_Me B1_Mo RothC predicted SOCTotal SOC (t/ha) 44 23 changes 2021 to 2060 43 22 21 1 4 7 10 13 16 19 22 25 28 31 34 37 40 42 1 4 7 10 13 16 19 22 25 28 31 34 37 40 For the sites of Carr, Clon, and Kilw, Year Clon Drip the projected SOC change trends 39 35 from the initialization of the 34 38 33 measured pools were similar to 32 that when RothC was initialized 31 37 30 with the modelled pools 29 36 28 1 4 7 10 13 16 19 22 25 28 31 34 37 40 1 4 7 10 13 16 19 22 25 28 31 34 37 40 For the sites of Ball and Drip, the 35 Kilw 27 Pall projected SOC change trends with initialization of the measured pools, 26 34 rapidly decreased firstly and then 25 slightly increased 33 24 32 1 4 7 10 13 16 19 22 25 28 31 34 37 40 23 1 4 7 10 13 16 19 22 25 28 31 34 37 40 For the sites of Pall, SolA and SolB, the projected SOC change trends Sol SolB 72 A 41 with the initialization of the 71 40 measured pools rapidly increased 70 69 39 firstly and then decreased relatively 68 38 slowly 67 37 66 36 1 4 7 10 13 16 19 22 25 28 31 34 37 40 1 4 7 10 13 16 19 22 25 28 31 34 37 40
  28. 28. RothC Summary  The Zimmermann method has great potential, the measured carbon pools more reasonably reflect the real environmental conditions (i.e. drainage) than the modelled pools  The difference in the predicted SOC outputs among the sites depends on the balance between the measured and modelled RPM pools  In response to a future of rising temperature and expected drier summers and wetter winters, RothC predicts a decrease in the SOC of Irish temperate grasslands
  29. 29. CONCLUSIONS • PaSim shows much promise • DnDc is reasonable over the annual cycle by comparison with sub- daily time scales • Empirical Scenario Analysis show large reductions to be expected in N2O for future climate and land use changes • RothC predicts lower SOC under climate change • Now that we have good data, we should be able to make significant progress in modelling
  30. 30. Thank You
  31. 31. 30 25 DPM SOC (t C/ha) RPM 20 BIO 15 10 HUM RPM controls Total SOC trend IOM 5 Total 0 1 4 7 10 13 16 19 22 25 28 31 34 37 40 Year  Under the conditions that 11 10 Measured facilitating decomposition 9 ModeledRPM (t C/ha) 8 7 •If Measured >Modelled RPM 6 The measured rapidly decrease 5 4 until another new equilibrium 3 0 3 6 9 12 15 18 21 24 27 30 33 36 39 Year •If Modelled > Measured RPM 3.5 The measured rapidly increase 3 until another new equilibriumRPM (t C/ha) 2.5 2 1.5 Measured 1 Modeled 0.5 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 Year

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