Improvement of ORYZA2000 Execution Environment

for a Decision Support System to Optimize Planting Date

of Rice Farming in Rainfed Area

NARO Agricultural Research Center (NARO/ARC)

Kei TANAKA, Takuji KIURA

2014/1/21 1 APAN 37th Meeting, Bandung

Contents 1. Backgrounds

– GRENE-ei CAAM Project

2. Evaluation System for the Effects of Climate Change on Agriculture

3. ORYZA

– Execution Method

– Simulation Flow

– Results & Problems

4. Summary

2014/1/21 2 APAN 37th Meeting, Bandung

Backgrounds • Asian monsoon region

– 60 % or more of the world's population lives in

– Most of the countries are agrarian

– Effects of climate change will be quite serious

2014/1/21 APAN 37th Meeting, Bandung 3

Thailand, 2011 Philippines, 2013

GRENE-ei CAAM

1. Climate change research (CCR)

2. Agricultural effect research (AER)

• Development of “Evaluation System” to clarify the influence of the climate change on major crops

2014/1/21 APAN 37th Meeting, Bandung 4

Thailand

Vietnam Philippines

Indonesia

4 Target Countries

Evaluation System for the Effects of Climate Change on Agriculture in the Asian Monsoon Region

2014/1/21 APAN 37th Meeting, Bandung 5

Agro-Climate Database

・ Air Temp. ・ Solar Radiation ・ Soil Moisture ・ ・・・

MetBroker

Result Data ・ Crop Yield ・ Growth Period

with Effects of Climate Change

Data Viewer App

Rice

Cassava

Maize

Sugarcane

Vegetables

・・・

Crop Models DSSAT, ORYZA, ...

Meteorological Data

Forecast Meteorological Data under Climate Change

Field Data

Adaptation and Mitigation Strategies

AER1

CCR1 AER3

compare to validate

Crop Model Selection

2014/1/21 APAN 37th Meeting, Bandung 6

SIMRIW DSSAT ORYZA

User

JAPONICA

Japan Thailand Philippines

・・・

・・・

place / area selection

Area

Crop Model

Evaluation System

Model Execution Engine

SIMRIW Simulator for Cultivation Possibility of Rice

2014/1/21 APAN 37th Meeting, Bandung 7

• SIMRIW: rice model for potential production

• 1 degree grid data (15000 points in all over the world)

DSSAT Optimization System for Double Cropping of Rice and Cassava

2014/1/21 APAN 37th Meeting, Bandung 8

Rice (transplanting date: Aug 1, max cultivation period: 4 months)

Cassava (starting date: Dec 1, harvest date: Jul 15)

This system uses 0.05 degree grid weather data, and 0.5 degree result data is shown on maps.

ORYZA2000

• Rice model – to simulate the growth,

development, and water balance – under conditions of potential

production, and water and/or nitrogen limitations

• Bouman BAM, Kropff MJ, Tuong TP,

Wopereis MCS, ten Berge HFM, van Laar HH. 2001. ORYZA2000: modeling lowland rice. Los Baños (Philippines): International Rice Research Institute, and Wageningen University and Research Center. 235 p.

2014/1/21 APAN 37th Meeting, Bandung 9

Schematic Representation of ORYZA

2014/1/21 APAN 37th Meeting, Bandung 10

ORYZA2000 v2.13 • Execution File (ORYZAWin.exe) / FSEWin + ORYZA.fpf

• Data Files

– Control

– Experiment

– Crop

– Soil

– Rerun

• Weather Files

• Result Data Files (op.dat, res.dat, chart.txt)

Specifying data files with relative path

CNTR + ISTN . YEAR (ex. PHIL1.992)

2013/10/11 IRRI 11

Experiment.dat

• Water production situation setting PRODENV = 'POTENTIAL' *PRODENV = 'WATER BALANCE' ! water-limited

• Water balance models WATBAL = 'PADDY' ! for lowland soils *WATBAL = 'SAHEL' ! for freely draining upland soils *WATBAL = 'SAWAH' ! for lowland or upland soils (Water balance model requires soil.dat file & irrigation parameters in experiment.dat file) SWITIR=0 ! rainfed

2013/10/11 IRRI 12

Weather.dat • Longitude, Latitude, Altitude, Ångström parameters (a and b)

Station No., Year, Day, Irradiance(KJ/m2d), Min temp.(C), Max temp.(C), Vapor pressure(kPa), Mean wind speed(m/s), Precipitation(mm/d)

• PHIL1.992 121.25 14.18 21.0 0.00 0.00 1 1992 1 16379 21.6 29.0 2.38 1.9 0.0

• PHIL10.992 121.25 14.18 21.0 0.00 0.00 1 1992 1 16379 21.6 29.0 -99.0 -99.0 -99.0

• PANT1.992 78.47 29.0 243.84 0.29 0.42 1 1992 1 7.5 3.2 18.1 -99.0 -99.0 0.0

when solar radiation is available, Ångström parameters are set to 0

when using Priestley taylor or Makkink method for evapotranspiration calculation , vapor pressure, wind speed and precipitation not required

when using sunshine hours, Ångström parameters are required

2013/10/11 IRRI 13

Rerun.dat

• RUNMODE = 'EXPLORATION'

• In a rerun, ORYZA is executed repeatedly, with new values of selected parameters.

* rerun set 1 STTIME = 2. * rerun set 2 STTIME = 3. ... * rerun set 364 STTIME = 365. moving start time from 1/1 to 12/31

RERUN is a convenient function to execute repeatedly by the exploration mode. However it executes in single thread. It takes time of execution time x frequency. (Ex. 0.4sec. × 365 = 146sec.)

2013/10/11 IRRI 14

Flow to Simulate Yield with ORYZA

↓ input from Web user interface setup ( IYEAR, CNTR, ISTN, Variety, Fertilization, … ); modification of Experiment.dat & Control.dat files for ( STTIME = 1 to 365 ) { ← by rerun run ( ORYZA ) { read ( weather data ); while ( DVS < 2 ) calculation(); } } (about 150sec. by Core i7-2677M 1.8GHz) display or save ( result ); result.dat → chart or DB 2013/10/11 IRRI 15

Result of ORYZA (WRR14: weight of rough rice at 14% moisture) PHIL, 1, STTIME=Jan.～Dec. 1992 every 10 days

Water balance mode (Rainfed)

2013/10/11 IRRI 16

Result of ORYZA (WRR14: weight of rough rice at 14% moisture) PHIL, 1, STTIME=Jan 1 1992 Rainfed - Potential

2013/10/11 IRRI 17

On Demand ORYZA Execution Service

• How can we shorten execute time? (about 150sec. by Core i7-2677M 1.8GHz)

– High-speed computer

– Multi threading

– Every day → Every 5 days in dry season

– It may take more than ten seconds yet.

2013/10/11 IRRI 18

Summary • GRENE-ei CAAM

– Climatic changes and evaluation of their effects on agriculture in the Asian monsoon region

• Evaluation System

– Crop model selection

• ORYZA2000

– Execution method

– Simulation flow

– Problems

2014/1/21 APAN 37th Meeting, Bandung 19

Future Plans • Evaluation system for the effects of climate change

on agriculture in the Asian monsoon region

– Increasing the kinds of the crops (Vegetables, ...)

– Expanding the target area (Indonesia, Vietnam, ...)

– Considering climate changes

– Speed-up of calculation

– Treatment of result files (Hadoop)

• Data viewer application

– As information infrastructure to develop adaptation and mitigation strategies against climate changes for agricultural sectors

2014/1/21 APAN 37th Meeting, Bandung 20