1. CROPPING SYSTEM ANALYSIS
&
CLIMATE CHANGE IMPACT

2. Multi-date Radarsat ScanSAR Narrow-2
DATA USE
Multi-date Resourcesat AWiFS
IRS Advanced Wide Field Sensor (AWiFS) data acquired from October 2004 to May 2005
ScanSAR Narrow Beam-2 (SN2) of RADARSAT
10-day composite (S10) NDVI (Normalized Difference Vegetation Index) product of SPOT Vegetation (VGT)
Ground truth collected for each crop in each state
Survey of 1000 farmers in 100 villages
Soil and water sampling in these villages
Multi-date Radarsat ScanSAR Narrow-2
(22Jun,16 Jul, 09 Aug)

3. 10-DAY COMPOSITE NDVI PRODUCT OF SPOT VGT

4. CROPPING SYSTEM INDICES
ai= area occupied by the i-th crop planted and harvested within a year
n = total number of crops
A= total cultivated land area
1. Multiple Cropping Index (MCI)
2. Area Diversity Index (ADI)
ai= area under each crop
n = number of crops in a season
ai= area occupied by the i-th crop
Di = days that i-th crop occupied
n = total number of crops
A= total cultivated land area
3. Cultivated Land Utilisation Index (CLUI)

5. CROPPING SYSTEM OF PUNJAB STATE
Crop Rotation Statistics
Bathinda
Cropping Intensity: 204%
Diversity
Kharif : 2.23
Rabi: 1.64
Land Utilsation Index: 0.80
Suggestions
Diversification both in Kharif and Rabi
Increase cropping intensity by adopting short-duration summer legume crop

6. CROPPING SYSTEM BATHINDA DISTRICT
Crop Rotation Statistics
Cropping Intensity: 202%
Diversity
Kharif : 2.43
Rabi: 1.39
Land Utilsation Index: 0.78
Suggestions
Diversification both in Kharif and Rabi
Alternative cropping pattern to substitute rice

7. CROPPING SYSTEM OF HARYANA STATE

8. CROPPING SYSTEM OF UTTAR PARDESH

9. CROPPING SYSTEM OF WEST BENGAL

10. CROP ROTATION IN INDO-GANGETIC PLAINS
Rice-Wheat
Sugarcane Based
Cotton-Wheat
Rice-Potato
Maize-Wheat
Pearlmillet-Wheat
Rice-Fallow-Rice
Rice-Fallow-Fallow
Rice-Fallow-Jute
Rice-Wheat-Other
Fallow-Pulse
Fallow-Wheat
Minor Crop Rotations
Fallow
Non-Arable
Punjab
Haryana
Uttar Pradesh
Bihar
West Bengal

11. MAXIMUM NDVI (CROP VIGOUR) PATTERN
Kharif Season Rabi Season

12. RICE PLANTING PATTERN MAP
Very Early (01 July)
Early (28 July)
Medium (17 Aug)
Late (10 Sept)
Non-Rice Area

13. WHEAT SOWING PATTERN MAP
Very Early
Early
Medium
Late
Non-Wheat Area
Map 19

14. Major crop Rotations and number of rotations observed in agroclimatic subregions of IGP through ground survey

17. Alternate Cropping Pattern Planning
Punjab
Rice-Wheat
Cot/Maz/Puls-Wheat
Maize-Sugarcane
Rice-Mustard
Cotton-Mustard
Groundnut/Maize
Bajra-Gram
Baj/Fod- Mustard
Vegetables
Agroforestry
Non-Agriculture
District Boundary
Major Road

18. Climate Change Impact Analysis
State of the Art : Indian Studies
Assumed Temp. Rise, Double CO2, GCM Projection, RCM Projection
Scenario
Statistical Models, Simulation Models, Spatial Mode
Model
Temperature, Temp + CO2, Temp. +CO2+ Rainfall
Inputs
Crops
Rice, Wheat, Soybean, Mustard
Yield Change, Phenolgy Change, Shift of Iso-yield-Lines, Adaptation
Findings

19. Approach Objectives: Sensitivity Analysis : Temperature and Crop Yield
Cropping System Productivity Under Future Climate Scenario
Uncertainty in Impact Assessment
Adaptation Study through Adjustment in Sowing Date
Rice-Wheat
Sugarcane Based
Cotton-Wheat
Rice-Potato
Maize-Wheat
Pearlmillet-Wheat
Rice-Fallow-Rice
Rice-Fallow-Fallow
Rice-Fallow-Jute
Rice-Wheat-Other
Fallow-Pulse
Fallow-Wheat
Minor Crop Rotations
Fallow
Non-Arable

20. Sensitivity Analysis : Temperature
Crop simulation Model used: CropSyst (Stockle et.al., 1994)
Most sensitive crop: wheat (around 66 % reduction with 50C rise in daily temperature)
Least sensitive crop: Maize (around 15 % with 50C rise in daily temperature)
No adaptation and no CO2 impact
Yield Decrease Shown by other Authors:
8-31% decrease in wheat yield with 1-30 Temp. Rise: Pandey et al., 2009
Increase in temperature by 0.5-2°C decreases grain yield by 8- 40% : Patil et al., 2009
Decrease in grain yield per degree rise in temp. ranges from q/ha (UP) to 4.29 q/ha (Haryana): Kalra et al. 2008

21. Cropping System Productivity under Future Climate Scenario
Location
Ludhiana : Rice-Wheat
Bhatinda: Cotton-Wheat
Ballowal: Maize-Wheat
Climate model: HadCM3 (A2)
Impact crop simulation model: CropSyst
Weather parameters: Tmax, Tmin and Rain fall
CO2 : 380 ppm at current situation, 420 ppm at 2020, ppm 2050 and 540 at 2080
Location
Patna : Rice-Wheat
Santiniketan: Rice-Rice
Yield (t ha-1)

22. Impact of Climate Change on Crop Yield
(Current vs. 2080)
Study using yield response model and RCM projection for the period (A2 scenario)
Yield reduction in wheat is maximum in Eastern Rajasthan
Reduction in rice yield is maximum in Haryana followed by Punjab.

23. Cropping System Response (Yield reduction ,%) to Climate change
2020
2050
2080
>Current (-1.12%-0)
Other rotation or non-agriculture
0-5 %
5-10%
10-15 %
15-20 %
20-25 %
25-30 %
30-40 %
40-50 %
50-62 %
R-W
M-W
C-W
Other or NA
C-R Map Punjab
Climate model: HadCM3 (A2)
Impact Model: CropSyst
Weather parameters: Tmax, Tmin and Rainfall
CO2 : 380 ppm at current situation, 420 ppm at 2020, 480 ppm 2050 and 540 at 2080
Major rotation under study: Rice-Wheat, Maize-Wheat and Cotton- Wheat
Crop rotation map: RS Data

24. Uncertainty in the Impact Assessment
Due to climate model
Due to impact model
Change in System productivity of Rice-Wheat cropping system under A2 scenario projected by two climatic GCMs
Temperature sensitivity to rice yield predicted by two crop simulation model
Findings:
CGCM2 model predict more rise in maximum temperature and hence the reduction in yield simulated for the CGCM2 was more than that for the HADCM3 predicted climate scenario
Crop yield predicted by InfoCrop model is less sensitive to temperature as compared to CropSyst

25. Adaptation Study through Adjustment in Sowing Date (R-W System)
Scenario: HadCM3_A2
Scenario: HadCM3_B2
System Yield (Mg ha-1)
NSD: Normal Sowing Date: Wheat (R-W and M-W): 15 November
Rice: 20 June, Maize: 20 July
Findings:
7 days delay in sowing in both rice and wheat may help to reduce the impact by 1.67% and % in A2 and B2 scenarios, respectively during 2020.
For 2050, 15 days delay in sowing under A2 scenario resulted in 6 % increase and 7 days delay in sowing under B2 scenario resulted in 11 % increase.
For 2080, 15 days delay in sowing resulted in maximum improvement in both A2 and B2 (9.27 and 6.48%, respectively) scenarios as compared to normal sowing date.

26. Thank you. Future Studies Impact of Extreme Climates
Understanding the vulnerability of Rainfed Agro- ecosystems
Mitigation: Soil Carbon Sequestration
Thank you.

27. UNCERTAINTY IN IMPACT PREDICTION
Change in weather parameters projected by climate models at Ludhiana
Tmax
Tmin RF
Monthly Change (mm/day)
Monthly Change (0C)

28. UNCERTAINTY IN IMPACT PREDICTION
Change in weather parameters as projected by climate models at Bathinda
Tmax
Tmin RF
Monthly Change (mm/day)
Monthly Change (0C)

29. UNCERTAINTY IN IMPACT PREDICTION
Change in weather parameters as projected by climate models at Ballowal
Tmax
Tmin RF
Monthly Change (mm/day)
Monthly Change (0C)