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DSSAT Execution Framework for Prediction System for Double
Cropping Optimization in Thailand
NARO Agricultural Research Center (NARO/ARC)
Kei TANAKA, Takuji KIURA
2013/8/19 1 APAN 36th Meeting, Daejeon
Contents 1. Backgrounds
– GRENE-ei CAAM Project
2. Prediction System to Optimize Double Cropping of Rice and Cassava in Thailand – Structure of system
– Meteorological data
– Execution Method
– Output Data
3. Results
4. Summary
2013/8/19 2 APAN 36th Meeting, Daejeon
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
2013/8/19 APAN 36th Meeting, Daejeon 3
Objectives of CAAM Project
• Improvement of predictive accuracy – digitizing of past agro-meteorological and climate data
– observation of In-situ data
– development of agro-meteorological and climatological data-bases
• Adaptation and mitigation strategies for agriculture – development of evaluation system
– clarification of the influence of the climate change on major crops
– development of information platform to design adaptation and mitigation strategies
2013/8/19 APAN 36th Meeting, Daejeon 4
Structure of Prediction System (Previous Result: DIAS version)
2013/6/26 EFITA WCCA CIGR 2013, Torino 5
GD-DR&TR (1 degree grid)
MetBroker SIMRIW
Cultivation Possibility Data
(XML, KML files)
Data Viewer App Web Browser
Flash, Google Earth
Server Client
15,000 points in all over the world
meteorological data rice growth model
results
Meteorological Data • Northeastern Thailand (100 × 120 points)
• 0.05 degree grid
• Spatial interpolated data against to actual data
2013/8/19 APAN 36th Meeting, Daejeon 6 DIAS version (1 degree grid) Current version (0.05 degree grid)
2000/1/1
DSSAT Decision Support System for Agrotechnology Transfer
2013/8/19 APAN 36th Meeting, Daejeon 7
Structure of Evaluation System for the Effects of Climate Change on Agriculture in the Asian Monsoon Region
(final phase version under development)
2013/8/19 APAN 36th Meeting, Daejeon 8
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
Oil Palm
Crude Rubber
Crop Models Meteorological Data
Climate Change Parameters
Field Data
Adaptation and Mitigation Strategies
AER1
CCR1, AER3 (co-workers)
compare to validate
Structure of Prediction System (current version)
2013/8/19 APAN 36th Meeting, Daejeon 9
Meteorological Data (BSQ file)
・ Air Temp. ・ Solar Radiation ・ Precipitation
WTH file (DSSAT format)
Result Data ・ Crop Yield ・ Growth Period
Simple Data Viewer App
Rice
Cassava
Maize
Sugarcane
DSSAT Crop Models
Meteorological Data
Climate Change Parameters
Field Data
Adaptation and Mitigation Strategies
compare to validate
12,000 points in Northeastern
Thailand 0.05 degree grid
DSSAT Files
• DSSAT v4.5 for Linux
• CSM45 Execution program
• DSS_THNE.v45 Bach file
• THNE0001.RIX Configuration file for rice
• THNE0001.WTH Meteorological data file
• PlantGro.OUT One of result data file 2013/8/19 APAN 36th Meeting, Daejeon 10
DSSAT Execution Method setup crop, year, max growth period
for (120×100 grid points){
met. data of point → THNE0001.WTH (rename)
for (planting date = Jan.1~Dec.31){
modify THNE0001.RIX depending on planting date
execute CSM45 with DSS_THNE.v45
save result files in ZIP file, main result in growth.dat
}
}
create KML file from growth.dat 2013/8/19 APAN 36th Meeting, Daejeon 11
THNE0001.RIX (Configuration
file)
*EXP.DETAILS: THNE0001RI THAI NE 2000 RICE
*TREATMENTS -------------FACTOR LEVELS------------
@N R O C TNAME.................... CU FL SA IC MP MI MF MR MC MT ME MH SM
1 1 0 0 38 kg ha-1 of applied N 1 1 0 1 1 1 1 1 0 0 0 0 1
*CULTIVARS
@C CR INGENO CNAME
1 RI IB0019 RD 7 (cal.)
*FIELDS
@L ID_FIELD WSTA.... FLSA FLOB FLDT FLDD FLDS FLST SLTX SLDP ID_SOIL FLNAME
1 THNE0001 THNE -99 0 IB000 0 0 00000 -99 51 IBRI910024 -99
@L ...........XCRD ...........YCRD .....ELEV .............AREA .SLEN .FLWR .SLAS FLHST FHDUR
1 0 0 0 0 0 0 0 -99 -99
*INITIAL CONDITIONS
@C PCR ICDAT ICRT ICND ICRN ICRE ICWD ICRES ICREN ICREP ICRIP ICRID ICNAME
1 RI 00032 500 -99 1 1 1 0 0 0 100 15 -99
*PLANTING DETAILS
@P PDATE EDATE PPOP PPOE PLME PLDS PLRS PLRD PLDP PLWT PAGE PENV PLPH SPRL PLNAME
1 00032 -99 75 25 T H 20 0 5 0 25 25 3 0 -99
*IRRIGATION AND WATER MANAGEMENT
@I EFIR IDEP ITHR IEPT IOFF IAME IAMT IRNAME
1 -99 -99 -99 -99 -99 -99 10 -99
*FERTILIZERS (INORGANIC)
@F FDATE FMCD FACD FDEP FAMN FAMP FAMK FAMC FAMO FOCD FERNAME
1 00032 FE002 AP016 10 37 -99 -99 -99 -99 -99 -99
*RESIDUES AND ORGANIC FERTILIZER
@R RDATE RCOD RAMT RESN RESP RESK RINP RDEP RMET RENAME
1 00032 RE001 500 .53 -99 -99 -99 15 -99 -99
*SIMULATION CONTROLS
@N GENERAL NYERS NREPS START SDATE RSEED SNAME.................... SMODEL
1 GE 1 1 S 00032 2150 Effects of appl. N & env
@N OPTIONS WATER NITRO SYMBI PHOSP POTAS DISES CHEM TILL CO2
1 OP Y Y N N N N N N M
@N METHODS WTHER INCON LIGHT EVAPO INFIL PHOTO HYDRO NSWIT MESOM MESEV MESOL
1 ME M M E R S C R 1 G S 2
@N MANAGEMENT PLANT IRRIG FERTI RESID HARVS
1 MA R R R R M
@N OUTPUTS FNAME OVVEW SUMRY FROPT GROUT CAOUT WAOUT NIOUT MIOUT DIOUT VBOSE CHOUT OPOUT
1 OU N Y Y 1 Y N Y Y N N Y N N
@ AUTOMATIC MANAGEMENT
@N PLANTING PFRST PLAST PH2OL PH2OU PH2OD PSTMX PSTMN
1 PL 00025 00039 40 100 30 40 10
@N IRRIGATION IMDEP ITHRL ITHRU IROFF IMETH IRAMT IREFF
1 IR 30 50 100 IB001 IB001 10 .5
@N NITROGEN NMDEP NMTHR NAMNT NCODE NAOFF
1 NI 30 50 25 IB001 IB001
@N RESIDUES RIPCN RTIME RIDEP
1 RE 100 1 20
@N HARVEST HFRST HLAST HPCNP HPCNR
1 HA 0 01032 100 0
2013/8/19 APAN 36th Meeting, Daejeon 12
THNE0001.WTH (Meteorological Data File)
*WEATHER : 00-000,ThaiNE,Thai
@ INSI LAT LONG ELEV TAV AMP REFHT WNDHT
THNE 19.00 100.00 160 25.0 28.5 -99 -99
@DATE SRAD TMAX TMIN RAIN DEWP WIND
00001 17.4 29.9 12.7 0.0 16.8 0.3
00002 17.6 30.7 13.3 0.0 17.3 0.3
00003 17.6 30.2 13.7 0.0 17.4 0.2
00004 17.4 31.0 13.8 0.0 18.3 0.2
00005 17.5 31.0 14.9 0.0 18.7 0.0
00006 17.6 31.1 16.7 0.0 19.2 0.1
00007 16.3 31.5 15.5 0.0 18.7 0.3
00008 16.6 31.1 16.8 0.0 19.3 0.1
00009 15.7 30.3 15.2 0.0 18.2 0.0
00010 17.8 32.0 15.1 0.0 18.8 0.2
2013/8/19 APAN 36th Meeting, Daejeon 13
PlantGro.OUT (result file) *GROWTH ASPECTS OUTPUT FILE
*DSSAT Cropping System Model Ver. 4.5.1.023 -Stub DEC 26, 2012; 12:11:26
*RUN 1 : 0-0-0 NPK RICER045 THNE0001 1
MODEL : RICER045 - Rice
EXPERIMENT : THNE0001 RI THAI NE 2000 RICE
DATA PATH :
TREATMENT 1 : 0-0-0 NPK RICER045
!YR Days Days Leaf <--------- Dry Weight -----------> Grain Kernl <------ Stress (0-1) ------>
! and after after Leaf Grow Area <------------ kg/Ha -------------> per wght Harv Tillr <--- Water ---->
! DOY start plant Num Stage Index Leaf Stem Grain Root Panic Crop m2 mg Indx No. Phot Grow Excs Nitr Potas
@YEAR DOY DAS DAP L#SD GSTD LAID LWAD SWAD GWAD RWAD EWAD CWAD G#AD GWGD HIAD T#AD WSPD WSGD EWSD NSTD KSTD
2000 032 1 0 3.0 1 0.15 72 8 0 49 0 79 0 0.0 0.000 75 0.000 0.000 0.000 0.000 0.000
2000 033 2 1 3.0 1 0.15 72 8 0 55 0 80 0 0.0 0.000 75 0.000 0.000 0.000 0.000 0.000
2000 034 3 2 3.0 1 0.15 72 8 0 64 0 80 0 0.0 0.000 75 0.000 0.000 0.000 0.000 0.000
2000 035 4 3 4.0 1 0.15 72 8 0 77 0 80 0 0.0 0.000 75 0.000 0.000 0.000 0.000 0.000
2000 036 5 4 4.0 1 0.15 73 8 0 94 0 81 0 0.0 0.000 75 0.000 0.000 0.000 0.000 0.000
.... ... . . ... . .... .. . . .. . .. . ... ..... .. ..... ..... ..... ..... .....
Leaf Shell Spec <-Canopy-> Root <-- Root Length Density ---><Senesced Mat> Phot
Nit -ing Leaf Hght Brdth Depth <---- cm3/cm3 of soil -----> <--(kg/ha)--> Therm
% % Area m m m 0-5 5-15 15-19 19-28 28-51 Surf Soil Days
LN%D SH%D SLAD CHTD CWID RDPD RL1D RL2D RL3D RL4D RL5D SNW0C SNW1C DTTD
4.35 0.00 208.7 0.00 0.00 0.05 0.84 0.11 0.00 0.00 0.00 0 0 10.96
4.44 0.00 207.9 0.00 0.00 0.07 0.88 0.11 0.00 0.00 0.00 0 0 10.65
4.44 0.00 207.8 0.00 0.00 0.09 0.97 0.13 0.00 0.00 0.00 0 4 11.66
4.44 0.00 207.6 0.00 0.00 0.11 1.09 0.17 0.00 0.00 0.00 0 10 12.55
4.44 0.00 207.4 0.00 0.00 0.13 1.24 0.23 0.00 0.00 0.00 0 16 13.61
.... .... ..... .... .... .... .... .... .... .... .... . .. .....
2013/8/19 APAN 36th Meeting, Daejeon 14
Problems • Execution Time
– 30 sec / points → four days or more × years×crops
• Huge Number of Result Files
– (120×100 points) × 365 days × years×crops
• Treatment Data for Grid Points
– cultivar, irrigation, fertilization, soil
• Data depends on another organization
– meteorological data (2007~)
– field data for validation
2013/8/19 APAN 36th Meeting, Daejeon 15
Evaluation of Optimization for Double Cropping of Rice and Cassava
2013/8/19 APAN 36th Meeting, Daejeon 16
Jan 1 F M
A M J J A S O N D
Cassava Rice Cassava
Period with a little volume of shipment of cassava
Suitable cultivation period of cassava is over 6 months (starch content will be increased )
6 month
Evaluation Conditions • Harvest day of rice is not over end of November • Grain yield of rice • Harvest day of cassava is between May and July • Yield of cassava
Clopping Calendar in Northeastern Thailand
rainy season
Simulation Result
2013/8/19 APAN 36th Meeting, Daejeon 17
Rice (transplanting date: Aug 1, max cultivation period: 4 months)
Cassava (starting date: Dec 1, harvest date: Jul 15)
Summary • GRENE-ei CAAM
– Climatic changes and evaluation of their effects on agriculture in the Asian monsoon region
• Meteorological Data
– 0.05 degree grid data of Northeastern Thailand
• Prediction system to optimize double cropping of rice and cassava in Thailand
– DSSAT Execution Method
– Problems
– Results 2013/8/19 APAN 36th Meeting, Daejeon 18
Future Plans • Evaluation system for the effects of climate change
on agriculture in the Asian monsoon region
– Increasing the kinds of the crops (maize, sugarcane,...)
– Expanding the target area (Indonesia, Vietnam,...)
– Considering climate changes
– Speed-up of calculation
– Treatment of result files
• Data viewer application
– As information infrastructure to develop adaptation and mitigation strategies against climate changes for agricultural sectors
2013/8/19 APAN 36th Meeting, Daejeon 19