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 3 rd Crop and Rangeland Monitoring Workshop, September 26-30, 2011, RCMRD, Nairobi, Kenya

2. Outline of Presentation IntroductionIntroduction Rainfall Estimation from Satellite DataRainfall Estimation from Satellite Data Rainfall Based Crop Prospect AssessmentRainfall Based Crop Prospect Assessment Results and ValidationResults and Validation Research Opportunity to African ResearchersResearch Opportunity to African Researchers

3. Global Irrigated Area

4. Typical Annual Precipitation over Africa and Indian Subcontinents

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

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

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

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.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 RadarCreation 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.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.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.Sensitivity studies to derive QPE over various possible spatial and temporal scales. Generation of rainfall products on daily, pentad, monthly and seasonal 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 (0.25 0 x0.25 0 ) Collocation of IR TBs and MW Rainfall Estimation of Rainfall IR and WV - Cloud Classification PW & RH Correction Corrected Rainfall Estimation Final Rain Rate, Daily, Pentad, Monthly & Seasonal Rainfall Model PW & RH Forecast Satellite Microwave Rainfall (TRMM/SSMI) Grid Avg. Rainfall (0.25 0 x0.25 0 ) Rainfall Validation/ Fine Tuning (DWR/SFRG)

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 DataIMD Data

15. Rainfall Based Soil Moisture and Crop Prospect Assessment

16. Soil Moisture Availability Modeling Schema

17. July 01 – 15, 2008July 01 – 15, 2009 July 01 – 15, 2010 July 01 – 15, 2011 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. Soil Moisture based Assessment of Crop Situation (SMACS)

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

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.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.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.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.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.Microwave imager, MADRAS, aimed at measurements for precipitation, cloud liquid water content, ocean surface winds and total water vapour. Humidity sounder, SAPHIR.Humidity sounder, SAPHIR. ScaRAB radiometer for top of the atmosphere radiation budget measurements.ScaRAB radiometer for top of the atmosphere radiation budget measurements. Integrated GPS Radio Occultation (GPS-RO) Receiver.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. 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. African Monsoon Multidisciplinary Analysis (AMMA) and some more sites. For Details Contact: jsparihar@sac.isro.gov.in For Details Contact: jsparihar@sac.isro.gov.injsparihar@sac.isro.gov.in

25. THANK YOU Acknowledgements: CRAM Organizers and GEO Secretariat Presentation Material: Dr Manab Chakraborty Dr Sushma Panigrahy Dr P.K. Pal