Early Season Crop Prospect Assessment Using Satellite Data Based Rainfall Estimates

Early Season Crop Prospect Assessment Using Satellite Data Based Rainfall Estimates

Jai Singh PariharJai Singh Parihar

Dy. DirectorDy. Director

Earth, Ocean, Atmosphere, Planetary Sciences and Applications AreaEarth, Ocean, Atmosphere, Planetary Sciences and Applications Area

Space Applications Area, ISROSpace Applications Area, ISRO

Ahmedabad 380015Ahmedabad 380015

INDIAINDIA

[email protected]

33rdrd Crop and Rangeland Monitoring Workshop, September 26-30, 2011, RCMRD, Nairobi, Kenya Crop and Rangeland Monitoring Workshop, September 26-30, 2011, RCMRD, Nairobi, Kenya

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

Global Irrigated Area

Typical Annual Precipitation over Africa and Indian Subcontinents

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

< 250

251 - 500

501 - 750

751 - 1,000

> 1,001

Height in m

Kharif Rice and Coarse Cereals Growing Regions in India

Rice Growing Region Coarse Cereals Growing Region

Forecasting Agricultural output using Space, Agrometeorology and Land based observations (FASAL)

Econometry

Agro

Meteorology

LandObservations 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

Crop area & Production

Rainfall Estimation from Satellite Data

Precipitation Using - INSAT Multispectral Rainfall Algorithm

(IMSRA)

• Cloud classification using IR and WV channel observations of INSAT and Cloud classification using IR and WV channel observations of INSAT and

Kalpana.Kalpana.

• Creation of a large gridded data base of IR TB’s from INSAT and Polar orbiting - Creation of a large gridded data base of IR TB’s from INSAT and Polar orbiting - Microwave Satellite rainfall from TRMM –Precipitation Radar Microwave Satellite rainfall from TRMM –Precipitation Radar

• Applying Environment Correction factor using forecast model outputs of Applying Environment Correction factor using forecast model outputs of Precipitable water and humidity. Precipitable water and humidity.

• Validation of rainfall using Ground based DWR and rain gauge data, error Validation of rainfall using Ground based DWR and rain gauge data, error analysis and fine-tuning of algorithm. analysis and fine-tuning of algorithm.

• Sensitivity studies to derive QPE over various possible spatial and temporal Sensitivity studies to derive QPE over various possible spatial and temporal scales. scales.

• Generation of rainfall products on daily, pentad, monthly and seasonal Generation of rainfall products on daily, pentad, monthly and seasonal scales.scales.

Flow Chart for IMSRA Algorithm

INSAT TIR, WV Data3 Hourly Image

Conversion from Grey Count to TBs

Look Up Table for Calibration

Grid Average of IR TBs (0.250x0.250)

Collocation of IR TBs and MW

Rainfall

Estimation of Rainfall

IR and WV - Cloud Classification

PW & RH Correction

Corrected RainfallEstimation

Final Rain Rate, Daily, Pentad, Monthly & Seasonal Rainfall

Model PW & RH Forecast

Satellite Microwave Rainfall (TRMM/SSMI)

Grid Avg. Rainfall (0.250x0.250)

Rainfall Validation/ Fine Tuning (DWR/SFRG)

Fortnightly Rainfall, June 1-August 24, 2011

Cumulative Total Rainfall, June 1-August 24, 2011

Cumulative Total Rainfall June 1 –August 31

Validation of Satellite Data Derived Rainfall

Satellite Data IMD Data

Rainfall Based Soil Moisture and Crop Prospect Assessment

Soil Moisture Availability Modeling Schema

July 01 – 15, 2008 July 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)

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, 2011August 25, 2011

Weekly Assessment of Progress in Kharif Rice Acreage

Normal and Deficit Monsoon years Comparison

Validation With In-season Crop Area Estimates

Conclusion

• Satellite Data Derived Rainfall Provided Good Information on Spatial Satellite Data Derived Rainfall Provided Good Information on Spatial Distribution.Distribution.

• Soil Moisture based Assessment of Crop Situation (SMACS Model) Soil Moisture based Assessment of Crop Situation (SMACS Model) found to be in effective in Forecasting the Crop Prospect Early in the found to be in effective in Forecasting the Crop Prospect Early in the Season.Season.

• Integration of Water Release in Canal Commands would Increase the Integration of Water Release in Canal Commands would Increase the Effectiveness of Model in Irrigated Areas.Effectiveness of Model in Irrigated Areas.

• Validation with Mid-Season Estimation of Cropped Area has Confirmed Validation with Mid-Season Estimation of Cropped Area has Confirmed Good Performance of Model.Good Performance of Model.

Opportunity to AFRICAN ResearchersOpportunity to AFRICAN Researchers

Initiated in the year 2010Initiated in the year 2010

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

MT-Products Validation using Data over African Sites

Megha-Tropiques is a joint ISRO-CNES programme to study the tropical atmosphere Megha-Tropiques is a joint ISRO-CNES programme to study the tropical atmosphere including the convective cloud systems known to strongly influence weather and including the convective cloud systems known to strongly influence weather and climate.climate.

Payloads on Megha-Tropiques Payloads on Megha-Tropiques

• Microwave imager, MADRAS, aimed at measurements for precipitation, cloud liquid Microwave imager, MADRAS, aimed at measurements for precipitation, cloud liquid water content, ocean surface winds and total water vapour. 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 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 Indian region. It is important to understand how the retrieved products are sensitive to the local vertical profiles.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: For Details Contact: [email protected]

THANK YOU

Acknowledgements:

CRAM Organizers and GEO Secretariat

Presentation Material: Dr Manab ChakrabortyDr Sushma PanigrahyDr P.K. Pal