(Agricultural Effect Research Team 3) T. Kuwagata, S. Sudo, Y. Takata, K. Minamikawa, T. Takimoto, and E. Matsuura (NIAES) (Bangkok, /3-4)

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1 Development of Information Platform to Design Adaptation and Mitigation Strategies of Major Crops against the Predicted Climatic Changes in Asian Monsoon Region (Agricultural Effect Research Team 3) T. Kuwagata, S. Sudo, Y. Takata, K. Minamikawa, T. Takimoto, and E. Matsuura (NIAES) (Bangkok, /3-4)

2 1. Objective Developing information platform (1) to design adaptation strategies of major crops against the predicted climatic changes and (2) to evaluate the mitigation potential by reducing green house gasses from agricultural sector in Asian monsoon region. 2. Planned benefit Establishment of research platform for adaptation and mitigation policies in Asian agricultural sector against the future global warming in the coming post-kyoto Protocol period.

3 5) Development of Information Platform to Design Adaptation and Mitigation Strategies of Major Crops against the Predicted Climatic Changes in Asian Monsoon Region (Agricultural Effect Research Team 3; AER 3) (NIAES) Collecting data of meteorology, soil, land cover and agriculture Foreign Institutes for joint research Measurement of greenhouse gas emissions from cropland Evaluation of soil temperature and moisture of cropland CCR 1 Rice field 2014 Compilation of agroclimate change scenarios Database for planning adaptation and mitigation strategies 2015 Development of information platform for adaptation and mitigation strategies CCR 2 AER 1, 2

4 Database for planning adaptation and mitigation strategies (Japan)

5 Agro Environmental data in Japan 1. Agro- Meteorological data 2. Soil data 3. Greenhouse gases data (CH 4, N 2 O) 4. Agricultural statistics data

6 Soil Database for agricultural land (Japan)

7 Daily Meteorological data in Agro-meteorological database (MeteoCrop DB) Solar radiation Potential Evaporation Paddy water temperature (LAI=0) (about 850 sites in Japan, )

8 Evolution of air and water temperature in rice paddy (Miyazaki, 2002) 30 (a) Saito (observation) year: 2002 (observation) Temperature ( o C) transplanting Ta (air temperature) Tw (water temperature) Temperature ( o C) /18 4/7 4/27 5/17 6/6 6/26 7/16 (b) Saito (MeteoCrop DB) year: Date Ta (air temperature) Tw (water temperature) 15 transplanting panicle initiation heading 10 3/18 4/7 4/27 5/17 6/6 6/26 7/16 Date (estimation in MeteoCrop DB)

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10 MARCO workshop will be held on September (last week) or October (1st 3rd week) in (Tsukuba in JAPAN) We will plan to hold a small symposium of the GRENE project (1 or 2 days meeting) in the MARCO workshop. Some actual plan and preliminary results will be also introduced by our members

11 Kazunori Minamikawa What is my task in the GRENE project? National-scale estimation of CH 4 emission from rice paddies in Asian monsoon region by a process-based biogeochemistry model (DNDC-Rice) and GIS data Development of greenhouse gas inventory Evaluation of mitigation options Prediction under future climate change Also can be considered as an effective utilization of the output (weather data) from the GRENE project

12 Kazunori Minamikawa What is the DNDC-Rice model? The DNDC (Denitrification-Decomposition) model is an integrated model of C and N biogeochemistry in agricultural ecosystems originally developed by Prof. Changsheng Li (University of New Hampshire, US) in 1990s. Consists of six sub-models: soil climate plant growth decomposition (CO 2 ) denitrification (N 2 O) nitrification (N 2 O) fermentation (CH 4 ) The DNDC-Rice model is a revised version of the original DNDC model by Dr. Tamon Fumoto (NIAES, Japan) to improve its performance in predicting CH 4 emission from a rice paddy.

13 Kazunori Minamikawa Graphic output on the PC screen Weather (input) Soil carbon Rice growth Soil conditions Microbial activity CH 4 emission

14 Kazunori Minamikawa An example of field-scale estimation in Japan Intermittent Drainage Continuous Flooding Seasonal total CH 4 emission (kg C ha -1 ) Site Year Water regimes Data Model Ryugasaki 1991 CF ID CF ID RMSE = 37, R 2 = 0.82 Fumoto et al. (GCB, 2010)

15 Kazunori Minamikawa Necessities to accomplish my task Collection of measured CH 4 data at a field scale Gathering information about national-scale DBs Collaborative research with you and your institution in Asian monsoon region

16 5) Development of Information Platform to Design Adaptation and Mitigation Strategies of Major Crops against the Predicted Climatic Changes in Asian Monsoon Region (Agricultural Effect Research Team 3; AER 3) (NIAES) Collecting data of meteorology, soil, land cover and agriculture Evaluation of soil temperature and moisture of cropland Compilation of agroclimate change scenarios Foreign Institutes for joint research Measurement of greenhouse gas emissions from cropland My works Evaluation of soil temperature and moisture of cropland in Asia by using physical model Validation CCR 1of the model Collection and observation Rice field of measured soil temperature and moisture Application to multipoint across Asia Database for planning adaptation and mitigation strategies Development of information platform for adaptation and mitigation strategies CCR 2 AER 1, 2

17 Soil temperature and moisture model input solar radiation air temperature wind speed precipitation vapor pressure Soil temperature and moisture are estimated by physical process model, which is considered vertical transportation of heat and water over non vegetated soil by Kondo & Xu (1997) Soil temperature and moisture model sensible heat output evaporation (latent heat) Features Soil is divided into multilayer Input data is simple (obtain from general weather observation) Water transportation divided into vapor and liquid phases Soil type depended parameters is needed soil temperature soil moisture

18 Works in 2012 Validation sites in Japan (tentative) Apr. 7, 2001 Collection of observed soil temperature and moisture data from research centers in Japan Model output validation with the observed data Model calibration (if needed) temperature & moisture temperature