CROPPING SYSTEM ANALYSIS & CLIMATE CHANGE IMPACT

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)

10-DAY COMPOSITE NDVI PRODUCT OF SPOT VGT

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)

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

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

CROPPING SYSTEM OF HARYANA STATE

CROPPING SYSTEM OF UTTAR PARDESH

CROPPING SYSTEM OF WEST BENGAL

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

MAXIMUM NDVI (CROP VIGOUR) PATTERN Kharif Season Rabi Season

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

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

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

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

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

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

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 0.56 q/ha (UP) to 4.29 q/ha (Haryana): Kalra et al. 2008

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, 480 ppm 2050 and 540 at 2080 Location Patna : Rice-Wheat Santiniketan: Rice-Rice Yield (t ha-1)

Impact of Climate Change on Crop Yield (Current vs. 2080) Study using yield response model and RCM projection for the period 2071-2080 (A2 scenario) Yield reduction in wheat is maximum in Eastern Rajasthan Reduction in rice yield is maximum in Haryana followed by Punjab.

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

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

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 1.55 % 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.

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

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

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)

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)