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Early Season Crop Prospect Assessment Using Satellite Data Based Rainfall Estimates

Early Season Crop Prospect Assessment Using Satellite Data Based Rainfall Estimates. Jai Singh Parihar Dy. Director Earth, Ocean, Atmosphere, Planetary Sciences and Applications Area Space Applications Area, ISRO Ahmedabad 380015 INDIA jsparihar@sac.isro.gov.in

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Early Season Crop Prospect Assessment Using Satellite Data Based Rainfall Estimates

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  1. Early Season Crop Prospect Assessment Using Satellite Data Based Rainfall Estimates Jai Singh Parihar Dy. Director Earth, Ocean, Atmosphere, Planetary Sciences and Applications Area Space Applications Area, ISRO Ahmedabad 380015 INDIA jsparihar@sac.isro.gov.in 3rd Crop and Rangeland Monitoring Workshop, September 26-30, 2011, RCMRD, Nairobi, Kenya

  2. Outline of Presentation • Introduction • Rainfall Estimation from Satellite Data • Rainfall Based Crop Prospect Assessment • Results and Validation • Research Opportunity to African Researchers

  3. Global Irrigated Area

  4. Typical Annual Precipitation over Africa and Indian Subcontinents

  5. Indian Monsoon, Irrigation and Physiography Monsoon withdrawal normal dates Mean annual rainfall (cm) Monsoon onset normal dates Rainy days ( >= 2.5mm/day) Physiography Command Area Height in m

  6. Kharif Rice and Coarse Cereals Growing Regions in India Rice Growing Region Coarse Cereals Growing Region

  7. Forecasting Agricultural output usingSpace, AgrometeorologyandLand basedobservations (FASAL) Land Observations Conventional Remote Sensing Agro Meteorology RS, Mod. Re. Temporal Cropped area RS, High Re. Single date Crop condition Econometry Crop area & Production Crop acreage Crop area & Production Crop yield MULTIPLE IN-SEASON FORECAST Pre- Harvest District Revised Assessing Damage Pre- Season Early- Season Mid- Season State Pre- Harvest State

  8. Rainfall Estimation from Satellite Data

  9. Precipitation Using - INSAT Multispectral Rainfall Algorithm (IMSRA) • Cloud classification using IR and WV channel observations of INSAT and Kalpana. • Creation of a large gridded data base of IR TB’s from INSAT and Polar orbiting - Microwave Satellite rainfall from TRMM –Precipitation Radar • Applying Environment Correction factor using forecast model outputs of Precipitable water and humidity. • Validation of rainfall using Ground based DWR and rain gauge data, error analysis and fine-tuning of algorithm. • Sensitivity studies to derive QPE over various possible spatial and temporal scales. • Generation of rainfall products on daily, pentad, monthly and seasonal scales.

  10. Flow Chart for IMSRA Algorithm INSAT TIR, WV Data 3 Hourly Image Conversion from Grey Count to TBs Look Up Table for Calibration Grid Average of IR TBs (0.250x0.250) Satellite Microwave Rainfall (TRMM/SSMI) IR and WV - Cloud Classification Collocation of IR TBs and MW Rainfall Grid Avg. Rainfall (0.250x0.250) Estimation of Rainfall PW & RH Correction Model PW & RH Forecast Rainfall Validation/ Fine Tuning (DWR/SFRG) Corrected Rainfall Estimation Final Rain Rate, Daily, Pentad, Monthly & Seasonal Rainfall

  11. Fortnightly Rainfall, June 1-August 24, 2011

  12. Cumulative Total Rainfall, June 1-August 24, 2011

  13. Cumulative Total Rainfall June 1 –August 31

  14. Validation of Satellite Data Derived Rainfall Satellite Data IMD Data

  15. Rainfall Based Soil Moisture and Crop Prospect Assessment

  16. Soil Moisture Availability Modeling Schema

  17. Soil Moisture based Assessment of Crop Situation (SMACS) Available Soil Moisture (ASM) in % Colour Codes: Red to Yellow (ASM < 50 ): Not suitable for sowing of Crops. Requires irrigation for sowing. Green to Blue: Suitable for Coarse Cereals. Deep Blue: Suitable for Rice. Note: Suitability does not imply crops have been sown it depends on various other factors. Not suitable does not imply that no crops are sown as irrigation of the fields is possible. July 01 – 15, 2008 July 01 – 15, 2009 July 01 – 15, 2011 July 01 – 15, 2010

  18. Weekly Assessment of Progress in Kharif Rice Acreage August 31, 2011 August 20, 2011 August 25, 2011 Rainfed rice Area Sown = 30.51 M ha Relative Deviations -7.3 % (w.r.t. 2010) +6.3 % (2009 - poor rainfall year)

  19. Normal and Deficit Monsoon years Comparison

  20. Validation With In-season Crop Area Estimates

  21. Conclusion • Satellite Data Derived Rainfall Provided Good Information on Spatial Distribution. • Soil Moisture based Assessment of Crop Situation (SMACS Model) found to be in effective in Forecasting the Crop Prospect Early in the Season. • Integration of Water Release in Canal Commands would Increase the Effectiveness of Model in Irrigated Areas. • Validation with Mid-Season Estimation of Cropped Area has Confirmed Good Performance of Model.

  22. Opportunity to AFRICAN Researchers Initiated in the year 2010

  23. C V Raman International Fellowship for African Researchers for Research in India • Opportunity to African Researchers to Conduct Collaborative Research / Training for 1 to 12 Months Duration at Universities and Research Institutions in India • Features • Supporting up to one year of research work in India in the area of science and technology • Monthly sustenance allowance • Additional contingency grant • To and fro airfare by economy class • Total of 8 fellowships per country • Types of Fellowships • Post Doctoral Fellowship: Duration 6 months. Maximum of 2 fellowships for each or one fellowship thereof subject to 12 man-months. • Visiting Fellowship: Duration 3 months. Maximum 3 fellowships. • Senior Fellowship: Duration 1 month. Maximum 3 fellowships. • For information see: www.ficci.com

  24. MT-Products Validation using Data over African Sites Megha-Tropiques is a joint ISRO-CNES programme to study the tropical atmosphere including the convective cloud systems known to strongly influence weather and climate. Payloads on Megha-Tropiques • Microwave imager, MADRAS, aimed at measurements for precipitation, cloud liquid water content, ocean surface winds and total water vapour. • Humidity sounder, SAPHIR. • ScaRAB radiometer for top of the atmosphere radiation budget measurements. • Integrated GPS Radio Occultation (GPS-RO) Receiver. Africa has a different vertical temperature, humidity and wind structure compared to Indian region. It is important to understand how the retrieved products are sensitive to the local vertical profiles. African Monsoon Multidisciplinary Analysis (AMMA) and some more sites. For Details Contact: jsparihar@sac.isro.gov.in

  25. THANK YOU Acknowledgements: CRAM Organizers and GEO Secretariat Presentation Material: Dr ManabChakraborty Dr SushmaPanigrahy Dr P.K. Pal

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