Presentation at ARRCC-CARISSA workshop 29 Jan 2019 to 31 Jan 2019

1. Climate Change Impact Assessment by Integrating
Climate, Crop and Economics Modeling Approaches:
A Case Study in Cropping System of Punjab,
Pakistan
University
of Agriculture,
Faisalabad
Prof. Dr. Ashfaq Ahmad Chattha
Focal Person for Center for Advanced Studies
(CAS) in Agriculture and Food Security at
University of Agriculture, Faisalabad (UAF)
Head, Climate Change Research Group, UAF
Regional Workshop on Future Climate Projections and their
applications in South Asia
(29-31 January 2019)
ICIMOD, Kathmandu, NEPAL

2. Outline
i. Cropping Systems of Pakistan
ii. Methodology and Map of Study Area
iii. Climate Change Projection for Rice-Wheat and Cotton-wheat
Cropping Systems
iv. Aggregated Gains and Losses in Rice-Wheat Cropping System
v. Impact of Climate Change on Rice-Wheat and Cotton-wheat
Cropping Systems
vi. Impacts of Climate Change on Poverty in Cotton-Wheat System
vii. Socio Economic Impacts of Adaptations
1. Necessity, application and constraints of future climate projections
2. A case study

3. What are your main decisions that require climate
projections?
 Decision for agriculture practices in shifting climate
 Decision for economical reforms in agronomy
 Sowing and harvesting adaptation measures
 Extent of mitigation measures required in future
 Probability of extreme events
 Diurnal variability in climate projections

4. What are the range of sectors where climate
projections are used?
 Decision Support System for Agro-technology transfer
 Tradeoff Analysis Model for Multi-Dimensional Impact Assessment
 Extreme Climate Indices
 Monsoon Onset and Withdrawal projections
 Climate dynamics in future
 Water sector
 Energy sector

5. How did you use climate projections to address
these questions?
 Agriculture Modelling with adaptation and mitigation support
 Hydrological Modelling with impacts assessment
 Water-Energy modelling for optimal use of resources in changing climate
 Runoff and Inundation projections for hazard risk assessments

6. - How did you access the climate projections
for your applications?
 Earth System Grid Federation portals
 CORDEX South Asia Framework
 Pakistan Meteorological Department (R&D) Division

7. - What were the main challenges you have
found in using climate change projections?
 GCM projections are of coarse resolution
 RCMs require big computational power
 Statistically downscaled projections have uncertainties
 Data is huge (sometimes impossible to access on limited bandwidth in
Pakistan)

8. - Level of their satisfaction and convenience to
incorporate projections in sectoral modeling
 Current capacity of incorporating projections in sectoral modeling is
satisfactory
 Examples are AgMIP phases 1 and 2.

9. A CASE STUDY

10. Cropping Systems of Pakistan
Pakistan has two main cropping systems, namely rice-wheat and cotton-wheat
Rice-Wheat
 The rice-wheat cropping zone is the bread basket of Punjab-Pakistan
 Most of the area is irrigated in this system however, it also receives 425-800 mm
annual rainfall
 Comprised of more than 1 million farm families
Cotton-Wheat
 The Cotton-wheat cropping zone is source of food and fiber in Punjab-Pakistan
 It receives 110-250 mm annual rainfall and supplemented through well developed
irrigation system
 Cotton-Wheat zone comprises 2.2 million hectare area and 1.5 million farm
families
Variation in temperatures and uneven distribution of precipitation are affecting our
cropping systems, So there is dire need to assess the impact of climate change

11. Map of Study Area
Rice-Wheat
• Hafizabad
• Gujranwala
• Nankana Sahib
• Sheikhupura
• Sialkot
Cotton Wheat
• Multan
• Lodhran
• Bahawalpur
• Bahawalnagar
• Rahim Yar Khan

12. Methodology
Model parameterization
 Experimental data of Rice-wheat and Cotton-Wheat were used for model parameterization
Socio-economic data
 Yield and socio-economic data were collected by surveying 300 farmers in five districts of
Rice-Wheat and Cotton-Wheat systems
Climate data
 Five General Circulation Models (GCMs) under RCP 4.5 & 8.5 were used to generate future
weather data for mid-century (2040-2069)
 Selection and Statistical downscaling of climate models (CMIP5) were done at study sites
GCMs Middle Cool dry Hot dry Hot wet Cool wet
RCP 4.5 HadGEM2_CC_J CCSM4_E CMCC-CMS_W GFDL-CM3_1 IPSL_CM5A_LR_M
RCP 8.5 BNU-ESM CCSM4_E CMCC-CMS_W GFDL-CM3_1 Inmcm4_L

13. Crop Model
 Two crop models (DSSAT and APSIM) were used to simulate yield and to assess climate
change impact
Representative Agricultural Pathways (RAPs)
 RAPs were developed by series of meeting with the researcher, academia, farmers and policy
makers
Economic Analysis
 Economic model (TOA-MD) was used to quantify the climate vulnerability and adaptation
strategies in the study area

14. CMIP5 GCMs used in the study

15. Climate Change Projection for Rice-Wheat Cropping System
15

16. Climate Change Projection for Cotton-Wheat Cropping System
1616
GCMs Names Categories
GFDL-CM3_1 Hotwet
BNU-ESM Middle
CCSM4_E Cooldry
INMCM4 Coolwet
CMCC-CMS_W Hotdry

17. Climatology for Integrated Assessment of Cotton-Wheat

18. Median changes in Temperatures and Rainfall
COTTON WHEAT ANNUAL
RCP4.5
RCP8.5
COTTON WHEAT ANNUAL
COTTON WHEAT ANNUAL
Tmax (°C) Tmin (°C)
RCP4.5
RCP8.5
Prec. (mm)

19. Impact of Climate Change on Rice-Wheat cropping system
APSIM
Global Climate Models
Current IEXA IIXA IKXA IOXA IRXA
YieldKgha
-1
1000
2000
3000
4000
5000
6000
Current
IEXA-GCM-CCSM4
IIXA-GCM-GFDL-ESM2M
IKXA-GCM-HadGEM2-ES
IOXA-GCM-MIROC5
IRXA-GCM-MPI-ESM-MR
2050s2050s
DSSAT
Global Climate Models
Current IEXA IIXA IKXA IOXA IRXA
YieldKgha
-1
1000
2000
3000
4000
5000
6000
Mean yield reduction in rice by DSSAT and APSIM
was 15.2 and 17.2% respectively
Fig: Rice-Wheat results of APSIM and DSSAT
for 155 farms with 5-GCMs
Mean yield reduction in wheat by DSSAT and
APSIM was 14.1 and 12% respectively

20. Aggregated Gains and Losses in Rice-Wheat Cropping System
-25
-15
-5
5
15
25
Gains Losses Net Impacts
CCSM4 -25
-20
-15
-10
-5
0
5
10
15
Gains Losses Net Impacts
-30
-20
-10
0
10
20
Gains Losses Net Impacts
-25
-20
-15
-10
-5
0
5
10
15
20
Gains Losses Net Impacts
-30
-20
-10
0
10
20
Gains Losses Net Impacts
DSSAT
APSIM
GFDL-ESM2M
HadGEM2-ES
MIROC5
MPI-ESM-MR

21. Adaptations for Rice-Wheat cropping system
 Increase in nitrogen amount (kg ha-1) by 15% in rice and 25% in wheat
 Increase in number of plants (m-2) by 15% in rice and 30% in wheat
 Decrease in volume of irrigation by 15% in rice and 25% in wheat
 Early sowing of wheat by 15 days and early transplanting of rice nursery by 5 days
 Development of heat tolerant cultivars for rice and wheat
Overall productivity would be increased by 45% in rice and 55% in wheat
Results

22. Distribution of Adopters & Non Adopters for all 5
GCMs (With adaptation, with trend)
22

23. Impact of Climate Change on Cotton-Wheat cropping system
Mean yield reduction in cotton by DSSAT and APSIM
was 31 and 63% respectively
Mean yield reduction in wheat by DSSAT and APSIM
was 6%
Fig: Cotton-Wheat results of APSIM and DSSAT
for 165 farms with 5-GCMs

24. 16.8
19.5
16.8
17.9
18.2
17.0
18.4
21.7
20.1
16.2
18.6
23.5
22.6
19.9
21.0
20.6 20.7
26.9
25.7
20.2
15.8
17.8
19.8
21.8
23.8
25.8
27.8
CCSM4 CMCC GFDL HadGEM2 IPSL BNU-ESM CCSM4 CMCC GFDL inmcm4
RCP 4.5 RCP 8.5
Poverty with Climate Change (%)
DSSAT APSIM
Impacts of Climate Change on Poverty in Cotton-Wheat System
Mean poverty of C-W system is 24.54%, SDPI 2010
GCMs Names Categories
GFDL-CM3_1 Hotwet
BNU-ESM Middle
CCSM4_E Cooldry
INMCM4 Coolwet
CMCC-CMS_W Hotdry

25. Adaptations for Cotton-Wheat cropping system
 Increase in nitrogen amount (kg ha-1) by 10% in cotton and 15% in wheat
 Increase in number of plants (m-2) by 15% in cotton and 10% in wheat
 Application of balanced used of fertilizers in cotton-wheat
 Efficient methods of fertilizer application i.e. applied in irrigation water
 Development of heat tolerant cultivars of cotton and wheat
Overall productivity would be increased by 64% in cotton and 53% in wheat
Results

26. -8000008
-6000008
-4000008
-2000008
-8
1999992
3999992
5999992
7999992
0 10 20 30 40 50 60 70 80 90 100
OpportunityCost
Adoption rate
APSIM DSSAT
Crop
Model
Adoption
rate (%)
NR without
adaptation
NR with
adaptation
PCI without
adaptation
PCI with
adaptation
Poverty without
adaptation (%)
Poverty with
adaptation (%)
APSIM 51.11 706077 777629 136853 150694 16.15 13.84
DSSAT 53.86 706077 789978 136853 152756 16.15 13.96
Socio Economic Impacts of Adaptations

27. Key Findings of Rice-Wheat Cropping system
There would be an increase of 2.8°C in day and 2.2°C in night temperature in Punjab for mid-
century (2040-2069)
Rainfall Variability would increase by 25% in summer & 12% decrease in winter mid-century
(2040-2069)
Reduction in Rice yield by about 17% and wheat yield of about 14 % in Rice-Wheat Cropping
Zone
Economic loss of 83% farm household, if they continue to use current production technology in
changed climate
Significant reduction in poverty (5-6%) among farm households, if adaptation takes place
Improvement in the livelihood due to increased in farm income, after adaptation

28. Key Findings of Cotton-Wheat Cropping system
There would be increase in mean max. temperature of 2.5 °C & 3.6 °C and mean min. temperature
2.7 °C & 3.8 °C under 4.5 and 8.5 RCPs, respectively for mid-century (2040-2069)
Decrease in rainfall would be about 33 & 52 % during cotton growing season and 36 & 42 %
during Wheat growing season under 4.5 & 8.5 RCPs, respectively for mid-century (2040-2069)
for hot dry conditions
Reduction in Cotton yield of 42% and wheat yield 4.5% under RCP 4.5 for mid-century (2040-
2069)
Reduction in Cotton yield of about 47% and wheat yield 6% in Cotton-wheat cropping system
under RCP 8.5 for mid-century (2040-2069)
Results indicated that without adaptation, poverty was 16.15 % for both DSSAT and APSIM
according to our survey data
While with adaptation poverty rate would reduce to 13.84 % and 13.96 % for APSIM and DSSAT
respectively

29. Stakeholder Engagement and Dissemination of Results
Workshops for sharing results
Capacity Building
Meetings with policy makers
Meetings with farmers, Cotton-Wheat zone
Meetings with researchers Meetings with farmers, Rice-Wheat zone

30. 30
THANKSashfaqchattha@uaf.edu.pk