APAN Geo ICT and Sensor Network based Decision Support Geo-ICT and Sensor Network based Decision Support Systems in Agriculture and Environment Assessmen 2011.8.24 Development of decision support system for optimal agricultural system for optimal agricultural production under global environment changes M. Mizoguchi and S. Ninomiya M Mi hi d S Ni i U i University of Tokyo it f T k 1
BACKGROUND BACKGROUND • Food shortage in the 21st century – Population increase of 200,000 people daily – the transition to a carnivorous diet – Limits of agricultural land expansion and unstable water Limits of agric lt ral land e pansion and nstable ater supply – Stable agricultural production due to fears of global g p g warming and frequent extreme weather • The need to simultaneously achieve the following The need to simultaneously achieve the following against the Global Environmental Change – High productivity High productivity – High quality – Food safety – Low environmental impact, sustainability 2 – Appropriate regional resource management
Objectives j • Among the long-term warming trend and the freq enc of e treme frequency of extreme weather, in order to achieve a eather in order to achie e a robust and stable agricultural production • We build a support system for optimizing agricultural We build a support system for optimizing agricultural production – Optimal care management support profitable cultivation Optimal care management support profitable cultivation (fertilizer and irrigation, crop rotation system) – Optimal water management in basin area Opt a ate a age e t bas a ea • Expected ripple effect of the study – Stable supply of food production Stable supply of food production – Stable management of the farmers base on food quality – Appropriate water resource management in watershed pp p g – Transition to sustainable agriculture in low-carbon and low 3 environmental impacts
Configuration and Overview of the study Supply of down-scaling data 1 Development of high resolution weather 1. Development of high-resolution weather model for local agricultural use Generation of high-resolution data to in-situ agriculture model Meteorological data Prediction of Land and water resources 3. Development of soil&water model 2. Development of crop quality model Prediction of water resources &soil Accurate predictions of crop quality and yield moisture movement Prediction of crop water demand p Monitoring data for assimilation/tuning Integration of multiple models User-friendly interface 4. Validation of support system by ground monitoring 4. Validation of support system by ground monitoring Construction of the ground monitoring system 5. Optimal Agricultural Production Support System Optimal cultivation management considered the farmer's profitability (Fertilizers and irrigation, crop rotation system) 4 On-site verification of the system Optimal water management in basin area
Previous efforts toward achieving the goals 1. Development of high-resolution weather model for local agricultural use – High-resolution mesh technology for meteorological data and climate model results (Univ. of Tokyo, NIAES) 2. Development of crop quality model – Development of prediction models, such as rice growing in DIAS project (NARO) 3. Development of soil&water model – Investigation of heat and soil moisture transfer model using meteorological model output data (UT) 4. Validation of support system by ground monitoring 4 V lid ti f t t b d it i – Development of Ground monitoring system using field server (NARO) – Database of ground monitoring data in DIAS project (UT) 5. Optimal Agricultural Production Support System – Development of user interface for Growth model in DIAS project (UT) – A Agriculture-related infrastructure for data integration in DIAS project (NARO) i lt l t d i f t t f d t i t ti i DIAS j t (NARO) 5
1. Development of high- 1. Development of high -resolution weather model for local agricultural use resolution weather model for local agricultural use (NIAES) (NIAES) (Uncertainty assessment using multiple climate scenarios) Preparation of daily weather data in the Re-analysis meteorological data target areas Near future climate prediction (CMIP 5) Short&middle-term prediction (Such as seasonal (Such as seasonal Statistical/dynamic Near future climate prediction by forecasting). downscaling of high-resolution atmosphere- Past to near future weather and ocean model prediction · climate data (Innovative Program of Climate (1980 (1980 - 2030) 2030) Change the 21st Century) 1. Spatial resolution Each AMeDAS point ( (Collaboration with research (1 km mesh) 2. Weather elements groups downscaling) Temperature, precipitation, Wind speed, humidity, Solar radiation, longwave radiation Snow radiation, Snow ... (Data input) Data Integration Analysis System Data Integration Analysis System Crop model S&W model 6 （ DIAS ）
2. Development of crop quality model （ NARO) Ground monitoring Agro-meteorological model Crop growth model (assimilation/tuning data) (high-resolution weather data) Biomass growth and yield formation Phenological Summer crop: rice Summer crop: rice development Photosynthesis Development Winter crop: wheat, barley Sugar (Su) DVI Maintenance /Crop growth dynamics respiration Root Root growth Spikelet number /Crop quality as well as yield! Storage starch Differentiation Vegetative Grain Accumulation tissue growth growth Spikelet # Storage starch (ST) / /Forecast of agricultural f l l Degeneration Translocation Vegetative Tissues Grain Yield (V) (Y) meteorological disasters Attainable Yield Plant N dynamics S&W model Spikelet sterility Translocation T l i Translocation (water resources, soil moisture) stem N leaf N Grain N （ crop water demand ） LAI development Senescence Senescence Grain N dead N Expansion accumulation stem N leaf N accumulation accumulation LAI Senescence soil N uptake Decision Support Systems rice-wheat rotation system Decision Support Systems rice wheat rotation system /Optimal configuration of cropping season /Selection of varieties /Risk reduction in agriculture meteorological disaster /Land productivity optimization /Optimal resource utilization 7 Advanced use of rice paddies to improve food self-sufficiency
3. Development of soil&water model in rural area （ UT) Development of material circulation modelunder climate change climate change (Changes in rainfall- Changes in the quality and quantity temperature of local water resources characteristics) Ch Changes in i Available quantity demand for water /Local water cycle Water use plan use patterns /Nutrient cycling /Chemical load Changes in soil environment Changes in soil environment Food Production F d P d i Nutrient water temperature Changes in Crop species/Cultivation system Ecosystem/Land use 40 Temperature( ℃ ) ) 10cm 30 ) Temperature(℃ 20 10 Crop model 0 0 50 100 150 200 250 300 350 -10 Soil&water model under climate change Prediction of quality and quantity of water resources/Rational water planning Prediction of soil hydrothermal environment/Linkages to crop model y g p Evaluation of soil&water environmental changes Development of reducing the environmental impact based on prediction 8
4.Validation of support system by ground monitoring （ UT&NARO) （ UT&NARO) Ground monitoring data Development of the systems Field-level validation of models Data assimilation/tuning (UT) (Agricultural Experiment Station) Accuracy verification Improvement of Field Server p Compact monitoring system Basin-level support System Validation Can be installed in poor infrastructure regions with (Tedori-gawa Land lectrical power and telecommunications Improvement District) Verification support system Verification support system Productivity and profitability 9
5. Optimal Agricultural Production Support System （ UT) Optimal Agricultural Production Support System Hi h High-resolution downscaling climate model l ti d li li t d l Data Crop quality model DIAS database syetem exchang Downscaling data Soil&water model in rural area Ground monitoring data ge platfor Ground monitoring system High-resolution weather data for agriculture rm Optimal cultivation management support tool Regional Water Management Tools User interface The best guidance on how to manage Conscious cultivation profitability Input of fertilizer, irrigation timing, timing of planting, variety selection and crop rotation system 10 Regional water management guidelines
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