Presentation is loading. Please wait.

Presentation is loading. Please wait.

APSIM Agricultural Production Systems Simulator Mehrnoosh Eghtedari Decamber 2013 1.

Similar presentations

Presentation on theme: "APSIM Agricultural Production Systems Simulator Mehrnoosh Eghtedari Decamber 2013 1."— Presentation transcript:

1 APSIM Agricultural Production Systems Simulator Mehrnoosh Eghtedari Decamber

2 Introduction APSIM:  is a modeling environment that uses various component modules to simulate cropping systems in the semi-arid tropics. Modules can be biological, environmental, managerial or economic and are linked via the APSIM "engine".  can simulate the growth and yield of a range of crops in response to a variety of management practices, crop mixtures and rotation sequences, including pastures and livestock. 2

3 Goals of APSIM  To simulate of biophysical processes in farming systems.  To assist the search for better farming strategies and the development of aids to better production decision making under risk.  To require a tool to accurate predictions of crop production in relation to climate, genotype, soil, and management factors regarding long term management of resources. 3

4 History of APSIM Commonwealth Scientific and Industrial Research Organisation In the early 1990s. 4

5 Capabilities of APSIM  Growth and yeild simulation of more than 25 crops.  Growth and biomass simulation of pastures.  Growth and biomass simulation of trees.  Crop Competition with weeds simulation.  Weed population dynamics. 5

6 Capabilities of APSIM  Intercropping systems simulation.  Systems simulation in irrigated and rainfed conditions.  The impact of management factors simulation. (Tillage, Irrigation, Fertilizing, Date of sowing)  Rotation and fallow simulation. 6

7 Capabilities of APSIM  Agroforestry systems simulation.  Key processes simulation in the soil.  Carbon decomposition and surface residues simultion.  Systems simulation in various scales (gene to ecosystem).  The effect of climate change simulation.  Production socio-economic effects simulation. 7

8 Combining with Different Models CABALA: A model for predicting forest growth 8

9 The APSIM Model Framework  A set of biophysical modules that simulate biological and physical processes in farming systems,  A set of management modules that allow the user to specify the intended management rules.  Various modules to facilitate data input and output to and from the simulation.  A simulation engine that drives the simulation process and controls all messages passing between the independent modules. 9

10 STRUCTURE of APSIM ( Mathematical-Mechanistic- Dynamic-Code based ) Manag er ClockReport Met SoilWat SoilN SoilPH SoilP Erosion Manure Residue Economics Manager Fertilize Irrigate Other Crops Legume Sorghum Maize Canopy Wheat System Control Climate Soil Management Crops 10

11 APSIM Modules  Crop  Soil  Climate  Mangement  System Control 11

12 Crop Modules  APSIM contains an array of modules for simulating growth, development and yield of crops, pastures and forests and thier interactions.  The plant modules simulate key physiological processes and operate on a daily time step in response to input daily weather data, soil characteristics and crop management actions.  All plant species use the same physiological principles to capture resources and use these resources to grow. The main differences are the thresholds and shapes of their response functions. 12

13 Crop Modules  Crop ontogeny is simulated via relationships defining responses to temperature and photoperiod.  Leaf area production and senescence is simulated via relationships of leaf initiation rate, leaf appearance rate and plant leaf area with temperature.  Potential crop water uptake is simulated via relationships with root exploration and extraction potential, which depends on soil and crop factors. 13

14 Crop Modules  All coefficients for general crop responses and crop/cultivar specific coefficients are stored external to the code to allow ease of use and transition across crops/cultivars.  Constants and parameters from the code are stored in crop parameter files. Each file consists of two major parts: crop-specific constants and cultivar-specific parameters. 14

15 Physiology of Yield Formation Climate Soil Mangement Yield Dry Matter Light Interception Leaf Area Phenology °C k RUE HI 15

16 Physiology of Yield Formation 16 Harvest Index × Dry Matter= Yield HI = f(phenology, temperature, water,nutrients, management) HI (Grain Number x Grain size )/Dry Matter Linear function of biomass accumulation after anthesis

17 Crop Modules AgPasture Growth PlantCropsSlurpCanopy 17

18 Crop Submodules  AgPasture : A pasture growth model, Based on the physiological model of Thornley & Johnston (2000), Designed for the simulation of mixed pastures of C3 and C4 grasses and legumes, Requirement: Micromet, Soil (SoilN and SoilWat or SWIM), Surface Organic Matter (SurfaceOM) and Fertiliser, and optionally Irrigation and pasture Managers. 18

19 Crop Submodules  Canopy (Intercropping): Simulates light and water competition between crops, On a daily basis, finds the number of crops in the simulation and their canopy heights, Canopy layers are then defined, with the layer boundaries being defined by the top of each canopy. Thus there are as many layers as canopies. 19

20 Crop Submodules  Canopy (Intercropping): Then each layer in turn is taken from the top, in the combine canopy, to get the combined (extinct_coeff * LAI) value of the canopies present in that layer. The fraction of light transmitted out of the bottom of that layer can be calculated. The total radiation intercepted in a layer is divided amongst the canopies occupying the layer, being done on the basis of (extinct_coeff * LAI) of each canopy. 20

21 Crop Submodules  Canopy (Intercropping): LAI is distributed with height in the canopy using normalized height and integration of a specific function. This results in 47% of the leaf area in the top 10% of height, 27% in the next 10%, 15% in the next 10%, and so on. 21

22 Crop Submodules  Growth: A simplified plant growth module developed for simulating pasture and forestry systems module. Major classes of biomass pools: 1.Growth pool responsible for most growth processes 2.Structural pool provides sinks for assimilate and nutrients and are used to describe plant properties such as plant height. 22

23 Crop Submodules  Growth: Growth Calculation: : Daily Growth : Daily intercepted solar radiation (MJ/m2) : The light use efficiency (g/MJ) : Growth modifiers for temperature : Growth modifiers for nitrogen : Growth modifiers for vapour pressure deficit : Soil water supply 23

24 Crop Submodules  Growth: variation in root:shoot ratio Partitioning structural fraction of above-ground growth 24

25 Crop Submodules  Plant : Simulates the growth of a number of different species on a daily time-step (on an area basis not single plant). Plant growth in this model responds to climate (temperature, rainfall and radiation from the Met module), soil water supply (from the Soilwat module) and soil nitrogen (from the SoilN module). 25

26 Crop Submodules  Slurp: a model for calculating soil water uptake by plants. Inputs : a)plant root ( root length profile and extraction potential ) b) canopy (live LAI, dead LAI, extinction coefficients and canopy height) 26

27 Crop Modules  Crops 27

28 Crop Modules  Crops 28 Biomass accumulation 1.Water-nonlimiting dlt_dm_rue = RUE *radiation_interception (1) 2.Water-limiting dlt_dm_water = soil_ water_ supply * transpiration_efficiency (2) dlt_dm = min(dlt_dm_water, dlt_dm_rue)

29 Soil Submodules  Eroison Daily soil erosion, and its effect on the soil profile  Map It maps simulation soil layers onto output layers  SoilN The dynamics of both carbon and nitrogen in soil  SoilP The availability of phosphorus in soil  SoilTemp Soil temperature 29

30 Soil Submodules  SoilWat The soil water balance model  Solute Solute balance model  Surfac Surface water conductivity changes with time  SurfaceOM The effect of surface organic matter  SWIM Infiltration and water movement in soil  WaterSupply The role of water-source for the Irrigate module 30

31 Soil Erosion Module  Sub model 1: Freebarin E: Event soil loss (t/ha) COV: Cover (%) Q: Event runoff (mm) K: Soil erodibility factor LS: Slope length and steepness factor P: Supporting practice factor Sine of slope angle Length of catchment (m) 31

32 Soil Erosion Module  Sub model 1: Rose E: Event soil loss (t/ha) S: Sine of slope angle cov: Fractional surface cover (0-1) Q: Event runoff (mm) λ: Factor approximating efficiency of entrainment λ bare : Efficiency of entrainment (bare surface) COV: Surface cover (%) 32

33 SoilN Module  FOM - fresh organic matter (crop residues, dead roots)  BIOM – the more labile, soil microbial biomass  HUM – the bulk of soil organic matter 33

34 SoilN Module  Decomposition of Soil Organic Matter Pools 34

35 SoilTemp Module Air temperature depth thermal conductance boundary layer heat storage temperature number of nodes annual average soil temperature Method: 1- Heat storage in nodes 2- Resistance to heat transfer in layers 35

36 SoilWat Module The Water Balance INPUT = OUTPUT 36

37 SoilWat Module Methods of water movement Cascading Layer Richard ΄s equation Daily time step 37

38 SoilWat Module The thickness of each layer by the user 100 or 150 mm the uppermost layer 300 or 500 mm the base of the profile The whole profile by up to 10 or more layers 38

39 SoilWat Module Processes represented in SOILWAT, adapted from water balances such as WATBAL and CERES, include:  Runoff: USDA curve number (CN) runoff model, include effect of : a.soil water content b. soil cover both from crop and crop residue c.roughness due to tillage  Evaporation: based on potential evaporation (Priestly/Taylor or Penman/Monteith) 39

40 SoilWat Module  Saturated flow : Sw i+1 = Sw i+1 + SWCON i x (SW i - DUL i ) for layer i, SW i > DUL i  Unsaturated flow : Between LL and DUL, water can move between layers in proportion to the water content gradient.  Movement of solutes associated with saturated and unsaturated flow of water are calculated using a ‘mixing’ algoritm. 40

41 Met Module  The APSIM Met module provided daily meteorological information to all modules within an APSIM simulation. 41

42 Management Module  Fertilizer Effect of fertilizer application on a system  Irrigation Irrigation scheduling  Economics Maintains a cash balance through the simulation, which monitors all financial activity (e.g. income, expenses, loan repayments). 42

43 System Control  Manager Capability to specify a set of rules using conditional logic during simulations to control the actions of modules.  Clock Simulation time  Report Creates a columnar output file to record data from an APSIM simulation. 43

44 44

Download ppt "APSIM Agricultural Production Systems Simulator Mehrnoosh Eghtedari Decamber 2013 1."

Similar presentations

Ads by Google