Decision Support System for Climate Change Adaptation in Rainfed Rice Areas (CCARA)

Transcription

1 International Conference on Climate Change Impacts and Adaptation for Food and Environmental Security November 2012 Decision Support System for Climate Change Adaptation in Rainfed Rice Areas (CCARA) A.A. Boling, K. Hayashi, J.G. Perez, L.P. Llorca, T. Ishimaru, H. Sakuma, H. Fujii, B.A.M. Bouman, B.Samson, R. Agbisit, Mulyadi, A. Hermawan, C. Boualaphanh, K Mounlamai, T. Inthaphong, F. Hilario, R. de Guzman, T. Iizumi

2 Objective To develop a methodological framework for an integrated decision support system for rainfed rice production.

3 1. Experiments Measurements Crop characteristics Soil chemical and physical properties Hydrology Weather Greenhouse experiment

4 Field experiment

5 N level 1 N level 2 Entry 1 Entry 2 Entry 3 Entry 4 Response to biotic constraints of four rice entries at two N levels under rainfed conditions

6 Characterization of total spikelet number (TSN) NIL (Fujita et al. 2012) IR64: slender panicles New Plant Type: heavy panicles Graphical genotype qtsn4 qtsn4-nil IR64 IR (YP9) Introgression of heavy panicle trait into IR64

7 Simulated (Mg ha -1 ) 16 Irrigated, 0N Irrigated, 120N Irrigated, 144N Rainfed, 0N Rainfed, 120N 12 Rainfed, 144N 1:1 line Measured (Mg ha -1 ) Aboveground biomass RMSE=26% R=0.94**; N= Simulated (Mg ha -1 ) Measured (Mg ha -1 ) Grain yield RMSE=16% R=0.89**; N=31 Measured and simulated aboveground biomass of IR64 at different N levels under rainfed and irrigated conditions at the Jakenan Experiment Station (Agric. Syst. 92: ).

8 2. Weather data CCARA research sites and weather stations

9 Rainfall, solar radiation, and temperature at CCARA sites (a) (b) (c) Rainfall (mm/10d) 120 Los Banos Savannakhet Jakenan J F M A M J J A S O N D Solar radiation (MJ/m 2 ) J F M A M J J A S O N D Temperature ( o C) J F M A M J J A S O N D Month

10 Simulated yield Los Banos Jakenan J F M A M J J A S O N D J Day of seeding Simulated potential rice yield at Los Baños and Jakenan

11 (a) (b) Rainfall (mm/decade) P=0.20 P=0.50 P=0.80 SINTEX-F J F M A M J J A S O N D Sample rainfall forecast and long-term patterns

12 3. Farm survey Farmers risk management practices Key informant interview Focus group discussion Household survey

13 Rainfall amount and farmers crop management practices in three districts. Description District 1 District 2 District 3 Rainfall High Medium Medium Crop establishment Transplanting Direct-seeding Direct-seeding Bund management No Yes Yes Fertilizer - N High Low Medium - P Medium Low Low - K Medium Medium Low Rice variety - Yield Low to medium High High - Stress tolerance Low to high High High

14 Direct-seeding Transplanting Farmers practice of land preparation and crop establishment

15 District 1 District 2 District 3 Source of supplemental water in three districts in Indonesia.

16 Farmers risk management strategy during a drought forecast scenario. Description District 1 District 2 District 3 Crop establishment Direct-seeding Direct-seeding Direct-seeding Bund management Yes Yes Yes Supplemental water Yes Yes Yes Abiotic-stress tolerance High High High Fertilizer, pesticides Reduce Reduce Reduce

17 Data source Statistical analysis Systems analysis and modeling - Parameterization and evaluation - Application Research output Researchers Government offices Farmers Experiments Nutrient manager parameterization and evaluation Nutrient manager Real-time weather Frequency analysis ORYZA2000 model parameterization and evaluation ORYZA2000 model SINTEX-Nutrient manager-oryza2000 evaluation Seasonal weather forecast Statistical downscaling Bias reduction process SINTEX Yield constraint analysis Biophysical and socioeconomic survey Scenario analysis Farmers crop management Risk management analysis Potential management interventions

18 Expected outputs Planting date for the weather scenario forecast Rice variety and promising rice lines Crop establishment methods Nutrient management Supplemental irrigation Tillage

19 4. Other application Alternate wetting and drying (AWD): a technology for resource conservation, climate change mitigation, and adaptation AWD reduces water use by 15 30% without a yield penalty.

20 a b Cumulative CH4 flux (g CH 4 -C m 2 ) Cumulative CH 4 and N 2 O fluxes in terms of CO 2 -equivalent global warming potential (g CO 2 m 2) AWD reduced global warming potential (GWP) by 60 70% (Hosen et al., unpublished data) Early incorporation Early incorporation Continuous flooding AWD20 AWD70 Late incorporation Late incorporation Continuous flooding Dry-season cropping in 2007 (February-May 2007; was monitored every 2 hours with automated closedchamber systems) AWD20 CH 4 N 2 O AWD70 CH 4 declined by 70% in AWD20 and by 90% in AWD70. Early straw incorporation reduced CH 4 emissions by 33 45% compared with late incorporation. Despite the increase in N 2 O, GWP decreased by 60% in AWD20 and by 70% in AWD70.

21 Current collaborators Indonesia Indonesian Agricultural Environment Research Institute (IAERI) Assessment Institute for Agricultural Technology (AIAT) Japan Japan Agency for Marine-Earth Science and Technology (JAMSTEC) Japan International Research Center for Agricultural Sciences (JIRCAS) Lao PDR National Agriculture and Forestry Research Institute (NAFRI) Rice and Cash Crop Research Center (RCCRC)

22 Potential collaborators National Institute for Agro-Environmental Sciences (NIAES) Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA) Department of Meteorology and Hydrology (DMH) Badan Meteorologi, Klimatologi, dan Geofisika (BMKG)

23 Thank you!