Survey Major Crop Models System Effects Climate Change ...
Transcript of Survey Major Crop Models System Effects Climate Change ...
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Survey of Major Crop Modelsin Thailand and Indonesia
to Develop Evaluation Systemfor Effects of Climate Change on Agriculture
Kei TANAKA, Takuji KIURA,Hiroe YOSHIDA (NARO, Japan),
Kiyoshi HONDA (Chubu Univ., Japan), and Budi I. Setiawan (IPB, Indonesia)
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Contents
1. Research plan2. Evaluation system3. Survey of major crop models4. Visiting fields5. Collaboration network
2012/3/4 21st GRENE Workshop
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Rice cultivation possibility prediction tool
Collecting crop models & params.(for Asian Monsoon Region)
AER2: Elucidation of the effects of climatic changes on major crops in Asian monsoon region ‐ Construction of an Evaluation System Using Meteorological Data and Crop Models ‐ (NARO)
Rice Cultivar A
Spinach Cassava ・・・
・・・
Developing cultivation simulators with flexibility which can exchange a crop model
Simulator execution↓
Climate change evaluation
Results of Climate Change ResearchMeteorological Data +Climate Change Coef.
• Clop models• Web applications• Framework for developing applications
Previous Results2011
2012
2013‐
2014
Improvement of the framework
VerificationCorrection
Implementing Web applications→ Deploying to DIAS
2015Improvement of simulators
Rain Fed Rice Field
Rice Cultivar B
2012/3/4 1st GRENE Workshop 3
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Structure of Evaluation System for Effects of Climate Change on Agriculture
2012/3/4 1st GRENE Workshop 4
Agro‐ClimateDatabase
・ Air Temp.・ Solar Radiation・ Soil Moisture・ ・・・
MetBroker
Result Data・ Crop Yield・ Growth Periodwith Effects of Climate Change
Data Viewer App
Rice
Cassava
Maize
Sugarcane
Oil Palm
Rubber
Crop ModelsMeteorological Data
Climate Change Parameters
Field Data
Adaptation and Mitigation Strategies
AER1
CCR1, AER3
compare to validate
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Agricultural Model Framework The functions provided by the framework
• Model Execution Engine• Data Structure• Weather Generator• GUI Components
2012/3/4 1st GRENE Workshop 5
Model Execution Engine
(Repetition calculation until conditions are satisfied)
Execution Data・Parameter
(Location・Cultivar)・Kind of met. data
Result Data・DVI, Dry weight(sequential data)
・Harvest date, Yield(date, value)
Result display, save
Chart Table
Map
Download(XML, CSV)
Model Calculation
Weather Generator
MetBroker
Normal year data
Estimation dataMeteorological
model
Weather database
Normal year XML file
User dataCSV file
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MetBroker
• Unified access method to a weather databases
• about 20 weather databases, 100,000 weather stations
• Java class library to treat meteorological data
2012/3/4 1st GRENE Workshop 6
Driver Program
Meteorological data mediation software
Rice Model
Application Layer
Cassava Model
Corn Model
Sugarcane Model
Database Layer
Agro‐Climate DB
Data from Field
GD‐DR&TR
MetBroker
Mediation Layer
Meta data・・・
・・・
AER1
CCR1AER3
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Cultivation Possibility Predicting System
(Data Viewer)
2012/3/4 1st GRENE Workshop 7
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Thread N
Cultivation Possibility Predicting System(Data Generator)
2012/3/4 81st GRENE Workshop
Start
Execution condition setup
Acquisition of the meteorologicalstation list from MetBroker
Thread partitioningThread 1 Thread 2 Thread N
All threads finished
Output summary results of allstations
Finish
Execution of station id: 00001
Meteorological data acquisitionfrom MetBroker
Setup parameters
Model Execution
Output result
Repetitionwithparameterchange
17520times
Repetitionwithstationchange
15000/Ntimes
Thread finish
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Survey of Major Crop Models
• Countries– Thailand, Indonesia
• Crops– Rice, Cassava, Corn, Sugarcane, Maize, Oil Palm, Rubber Plantation
• Survey Methods– Collecting literature, Interview to experts,Analysis on the model characteristics
2012/3/4 1st GRENE Workshop 9
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Thailand
by Dr. Honda (former Associate Professor of Asian Institute of Technology: AIT)• RICE
– DSSAT–CERES‐Rice, SWAP‐WOFOST, ORYZA 2000, H08, CATCHCROP
• Sugarcane– DSSAT‐Canegro
• Cassava– DSSAT‐GUMCAS
2012/3/4 1st GRENE Workshop 10
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DSSATDecision Support System for Agrotechnology Transfer
2012/3/4 1st GRENE Workshop 11
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• A plant module in DSSAT
• Estimate rice yield under different crop conditions: rainfed, irrigation and rice varieties.
• Simulate crop water use under difference environments
• Ability to simulate nitrogen transformation under different crop conditions.
Crop Environmental Resource Synthesis (CERES) Rice
122012/3/4 1st GRENE Workshop 12
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DSSAT‐CanegroSugarcane Model
2012/3/4 1st GRENE Workshop 13
DSSAT‐GUMCAS Cassava model
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Indonesiaby Dr. Budi I. Setiawan (Bogor Agricultural University)
Dynamic Rice Model(Makarim 2012)
2012/3/4 1st GRENE Workshop 14
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Expert Meetings
Bangkok
Bogor2012/3/4 1st GRENE Workshop 15
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Visiting Fields in Chiang Mai
2012/3/4 1st GRENE Workshop 16
Rainfed Rice Field Irrigated Rice Field
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Visiting Fields in Chiang Mai
2012/3/4 1st GRENE Workshop 17
Longan Potato
Maize
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Development Collaboration Network•Agriculture WG, Sensor Network WG– 33rd Meeting, Chiang Mai, 13‐17 Feb 2012
– 34th Meeting, Colombo, 25‐29 Aug 2012– 35th Meeting, Hawaii, 13‐20 Jan 2013– 36th Meeting, Korea, 19‐23 Aug 2013– 37th Meeting, Indonesia, Jan/Feb 2014
2012/3/4 1st GRENE Workshop 18