Overview of CropSyst

Transcription

1 Overview of CropSyst A cropping systems computer simulation model Claudio O. Stöckle Biological Systems Engineering, Washington State University USA

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10 Soil Weather Cropping systems Simulation-based Estimation and Projection Management ClimGen Biomass Arc GIS CropSyst Cooperator Yield ΔSOC Water, N, C balance GHG emissions

11 Biomass Yield CropSyst- Farm LCA Interaction ΔSOC GHG emissions Life Cycle Assessment Framework Extraction of Raw Materials Goal Definition and Scope Production and Transport Seeds Fertilizer Plant Protection Machinery Inventory Analysis Interpretation Farming Tillage and Sowing Fertilization Plant Protection Irrigation Harvest and Drying System Boundary Impact Assessment 1 Metric Ton of Grain 1 hectare of Farm Land LCA Software

12 CropSyst, from Crop Growth to Agricultural Systems Modeling New demands for computer simulation tools and applications have led to upgrades of CropSyst capabilities and functionalities in the last decade Integration into larger modeling frameworks and spatial scales Upgrades to run simulations under multiple platforms, in addition to MS-Windows, such as Linux based highperformance computer clusters and supercomputers. Specialized tools to inform policy makers and stakeholders such as CropSyst-IST (Irrigation Strategies Tool), a tool to address responses to water shortages, OFoot, an organic farm management model, and CAFE Dairy, a farm energy and nutrient design and management system.

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15 VIC-CropSyst

16 Crop Growth Models in Agriculture

17 What is the model objective? Bottom-up Models Explanatory interest Plant-scale analysis Genotype Analysis Top-down Models Applicationoriented Regional Analysis Agricultural systems analysis

18 The CTP model A mix of top-down and bottom-up approach

19 Average sunlit and shaded leaf photosynthesis

20 More Processes and Parameters Canopy structure Canopy radiation Leaf photosynthesis Stomatal regulation (CO2, VPD, water) Canopy energy balance Root water uptake Canopy transpiration Biomass accretion (respiration, partitioning)

21 Kremer et al., 2008 CTP simulation of transpiration (lysimeter data from Bushland TX)

22 CTP model output Stöckle and Kemanian, 2009

23 CropSyst, a Process-oriented Top-Down Model

24 CropSyst, a Process-oriented Top-Down Agricultural Systems Model Top-down resource-capture modeling approach Plant transpiration (T) - Atmospheric water demand - Soil water and roots - Stomatal control - Daily and hourly water uptake - Water stress Biomass accretion (BA) - Radiation-use efficiency (RUE) - Transpiration-use efficiency (TUE) Interaction CO2 x T X BA - Changes in stomatal conductance - Changes in transpiration - Changes in RUE and TUE

25 CropSyst Biomass Growth

26 CropSyst, a Process-oriented Top-Down Model First, let us take a look at transpiration and water uptake modeling

27 Maximum Transpiration Weather Maximum Plant Hydraulic Conductance Crop Coefficient P-M ETo Canopy Radiation Interception Attainable Transpiration Water Demand Potential Transpiration Maximum Transpiration Potential Water Supply

28 Water Uptake = Actual Transpiration Maximum Transpiration Plant Hydraulic Conductance Root Fraction by Soil Layer Water Potential by Soil Layer Canopy Water Potential Canopy Conductance Actual Transpiration

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31 Root Fraction Relative Soil Depth

32 Low (4.8 mm/day) high (8.4 mm/day) Very high evaporative demand (12 mm/day) Two soils: SaL and SiL Root depth =1.8 m

33 Jara and Stöckle, 1999

34 Water uptake simulation, nonirrigated maize, fully recharged deep soil (data from Davis CA) Jara and Stöckle, 1999

35 Pears (data from Lleida, Spain) Marsal and Stockle, 2012

36 ET simulation with varying degrees of water stress Stockle et al., 2003

37 Biomass and yield simulation with varying degrees of water stress Stockle et al., 2003

38 Biomass Accretion

39 Dual Approach Radiation-use efficiency at low D a (upper limit) B = ef i S t Modified transpiration-use efficiency B = α T β D a

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42 Biomass Accretion under Elevated CO2

43 The implementation relies on experimental evidence of crop growth responses to CO 2. These experiments report the ratio (r e ) of biomass production for a specified elevated CO 2 concentration (C e ) to the production for a baseline concentration (C b ). With this information, the biomass growth ratio at any CO2 concentration relative to the baseline ( r CO2 ) can be obtained by assuming that r CO2 and [CO2] are related by a Michaelis-Menten type of expression: r CO rf [ CO = 2 K + [ CO 2 2 ] ] K = C C r e e C b b (1 r C e e ) r F = K + Cb C b

44 The future values of TUE and RUE at any CO 2 concentration must be adjusted with respect to the values at the specified [CO 2 ] (C S ) at which they were determined, which is not necessarily the baseline [CO 2 ] defined for biomass response to elevated carbon dioxide. r Sp = r CO 2 ( K + r F C S C S ) RUE CO rsp RUE CS 2 =

45 The determination of TUE CO2 is more involved given that biomass production, canopy resistance to vapor transfer, and transpiration will change with elevated [CO 2 ]. Experimental data for a number of C3 and C4 crops reported by Morison (1985) showed a linear reduction of canopy conductance as a function of increasing [CO 2 ] with a slope (S) of per ppm of [CO 2 ].

46 The [CO2] adjusted canopy resistance is given by the following equation, where r cfao is the FAO Irrigation and Drainage Paper #56 (Allen et al., 1998) standardized canopy resistance ( d/m) for use with the FAO version of the Penman-Monteith reference ET, C c is current [CO2], C FAO is [CO2] when the FAO56 was published (~359 ppm), and S was defined previously. rc r c = FAO adj 1 ( C C ) S c FAO

47 Given the change of canopy resistance as a function of [CO2], crop transpiration calculated based on the standard FAO56 PM-ETo must be multiplied by the following adjustment factor (FT). F T = Δ + γ ( r c Δ + γ ( r c FAO adj + r + r a a ) / r ) / r a a Finally, TUE CO2 is given by TUE CO2 = TUE F C T S r Sp (Actually, only α T B = is adjusted) β D a α in

48 1.5 Biomass Ratio Atmospheric CO2 Conc. (ppm)

49 Transpiration Adjustment Factor Atmospheric CO2 Conc (ppm)

50 TUE RUE Atmospheric CO2 Conc (ppm) TUE RUE

51 Carbon and Nitrogen Budgets Calculated daily for all soil layers Carbon and nitrogen cycling are interactive Crop residues and all types of organic materials are considered in cycling calculations Nitrogen demand and uptake included Phosphorus not yet fully implemented

52 Nitrogen Demand

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54 90 N soil organic C at Pendleton data data 0-30 model model Organic C (Mg/ha) Year

55 0 N soil organic C at Pendleton data data 0-30 model model Organic C (Mg/ha) Year

56 Change in 0-30 cm soil organic C Organic carbon (kg C/ha) Othello Pullman St. John Lind Year of simulation

57 Simulated annual nitrous oxide emission N2O loss (kg N/ha) CropSyst IPCC estimate 0.00 Lind_CT_WW-SF Lind_RT_WW-SF SaintJohn_CT_WW-SW-SF SaintJohn_RT_WW-SW-SF Pullman_CT_WW-SW-SB Pullman_RT_WW-SW-SB Pullman_NT_WW-SB-SW Pullman_CT_WW-SW-SP Pullman_RT_WW-SW-SP Pullman_NT_WW-SP-SW Othello_Rep_SC-SC-P-WW Othello_Red_SC-SC-P Othello_Min_SC-SC-P

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60 1.2 GHG emission (Mg CO 2e /ha/year) Probability of Exceedence Historical RCP RCP RCP RCP