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Potential winners and losers in the
agriculture sector of coastal
Bangladesh: preliminary insights from
an integrated modelling approach
2013 ESPA Annual Science Conference
20-21 November 2013
London, UK
Attila N. Lázár, Craig Hutton, Robert J. Nicholls,
Derek Clarke, Nazmul Haq, Zoe Matthews, John Dearing (Southampton)
Helen Adams, Neil Adger (Exeter)
Abdur Razzaque Akanda (BARI)
Abul Fazal M. Saleh (BUET)
Dilruba Begum (ICDDRB)
2
Presentation overview
• ESPA Deltas : aim of integrating ecosystems support
• Challenges of modelling the agricultural systems
• Preliminary results
Bay of
Bengal
3
Scales and project elements
Exogenous drivers (upstream flow diversion, climate change, macro-economics, …)
off-shore fisheries
fisheries
Sundarbans
agriculture
aquaculture
char land
Endogenous governance (BD policies, laws, subsidies, flood protection, education system, …)
Soci
o-e
con
om
ics
demography
migration
security (financial,
environmental)
markets
livelihood & poverty
4
Ecosystems support for the rural poor consist of
wide range of components e.g.
– agriculture
– fisheries
– etc.
The Aim of this work is to quantify ecosystem provisions with an
integrated model (ΔDIEM)
The model will be used to explore the impacts of changes in
– climate and sea level rise
– environmental change (e.g. salinization)
– land use changes (e.g. rice to shrimp farming)
– external influences (e.g. water and nutrient changes in rivers)
– etc.
The outputs will enable decision makers to identify the likely
key drivers of change and the impacts of policy decisions
Aim of integration work
Bay Bengal Model GCOMS
GCM/ RCM
Catchment Models: GWAVA / INCA MODFLOW HydroTrend
Delta Model FVCOM, Delft3D
Crop Model: CROPWAT
Coastal Fisheries Model Size- & Species-based models
Temp, rainfall
Sea
leve
l, SL
P, S
ST, w
ind
s
Water, sediment, nutrients
Water flow, level, salinity, temp, sediment, nutrients
Primary productivity, T,S,O2, currents
Mangrove Model
Quantitative Physical/Ecological Models
Inland Fisheries Model
Morphology &
Land Cover Aquaculture Model
Surg
e le
vel
Lan
d U
se
Demography Cohort Comp
Macro-economics
Governance
Loan types
Mig
rati
on
Household Livelihood
Poverty & Health
Demography, economics & poverty
storm/cyclone/flood events
The ΔDIEM framework and integration progress
6
Main challenges of agriculture
• shifting monsoon
• unpredictability of weather
• flooding, cyclones, storm surges
• saline water intrusion (agriculture loss
and changing land use)
• land elevation and fertility (due to
polderization)
• water logging (due to channel siltation)
• water shortages (in dry season due to
upstream flow diversion)
• fragmentation of land ownership (due to population increase)
• conflicting interests
- large land owners - small land owners - sharecroppers - landless labourers
- commercial - subsistence
up to 10 crops
- house - livestock - vehicle - other
- financial - env. hazards
- low interest rate - high interest rate
- 17 age groups
CROPWAT model
Welfare
MC
loop - sea level rise, - increased salinity, - reduced sediment supply, - temperature rise, - CO2 changes
7
Integrated simulations
8
The next slides
One scenario run:
• Simulation from 1980-2050
• 5dS/m gradual increase in soil salinity levels from 2010 to 2050
• One cropping pattern: Aman rice and Boro rice
Preliminary simulation results for:
• Ecosystem Services (crop yield)
• Socio-Economics (Demography, Household earning/livelihood)
• Human well-being (Headcount)
% population change
between 1980 and 2050
-20
-19 - -15
-14 - -5
-4 - 38
39 - 78
-20%
-15%
-10 - -5%
4 - 38%
78%
Simulated demographic changes
The model suggests decreasing population over time in many districts as
the land is not able to support the population.
Probable outcome – migration away from marginal areas.
% population change
between 1980 and 2050
-20
-19 - -15
-14 - -5
-4 - 38
39 - 78
-20%
-15%
-10 - -5%
4 - 38%
78%
10
Simulated demographic changes
Khulna (growth)
Barisal (decrease)
Bhola (decrease)
Barguna (decrease)
11
Very suitable Suitable Moderately suitable Marginally suitable Not suitable Sundarban
Source: Bangladesh Agriculture Research Council (2012) Land Suitability Assessment and Crop Zoning of Bangladesh
Aman rice – yield (t/ha)
Traditional Aman rice will likely not to be suitable due to salinity increase
Simulation results (salinity increases scenario)
Crop yield ton/ha
12
Very suitable Suitable Moderately suitable Marginally suitable Not suitable Sundarban
Boro rice – yield (t/ha)
Traditional Boro rice will likely not to be suitable due to salinity increase
Crop yield ton/ha
Simulation results (salinity increases scenario) Source: Bangladesh Agriculture Research Council (2012) Land Suitability Assessment and Crop Zoning of Bangladesh
Results are based on the increasing salinity scenario
Simulated Profit Margin (fraction)
1980-2050
13
the fraction of revenue that remains in the pocket of the households after all the costs paid
Bagerhat
Khulna
Shatkira
Pirojpur
1.0
0.8
0.6
0.4
0.2
0
1.0
0.8
0.6
0.4
0.2
0
1.0
0.8
0.6
0.4
0.2
0
1.0
0.8
0.6
0.4
0.2
0
Large Land Owners Small Land Owners Sharecroppers Landless Labourers
• When fraction is around 0, loan is necessary or multiple jobs
• Farming is difficult post 2005
• Situation of Landless seems ok, but in poverty
14
Large Land Owners Small Land Owners Sharecroppers Landless Labourers
• Farming is better, but difficulties after 2030
• Loans are likely for Small Land Owners, Sharecroppers and Landless
Borgona
Barisal
Bhola
Jalakhati
Patuakhali
1.0
0.8
0.6
0.4
0.2
0
1.0
0.8
0.6
0.4
0.2
0
1.0
0.8
0.6
0.4
0.2
0
1.0
0.8
0.6
0.4
0.2
0
1.0
0.8
0.6
0.4
0.2
0
Simulated Profit Margin
1980-2050
15
Headcount
% of farmers living under the $1.25 (PPP) Poverty line
• Poverty levels are high.
• Simulated future poverty levels are currently uncertain.
1980 2009
2050
16
Other crops – yield (t/ha) in 2050 (Salinity increases by 5dS/m)
Chillies (rabi)
Garlic
Groundnut
Jute
Lentil Maize
Mustard
Onion Wheat
Changes are necessary (under the scenario):
• Crop diversification + value addition
• Integrated agriculture (?)
• Better management
• OR multiple jobs
17
Preliminary conclusions
Crop yields: • good fit to published results • some crops require parameter adjustments to BD varieties
Soil salinity:
• a major threat for many crops in the simulations • future food security is likely an issue • importance of proper salinity data in simulations
Poverty:
• most farmers are very poor • all farmers are expected to be poorer unless they adapt
Validation:
• preliminary model results are on-going
