Potential winners and losers in the agriculture sector of coastal Bangladesh: preliminary insights from an integrated modelling approach

Transcription

1 2013 ESPA Annual Science Conference November 2013 London, UK Potential winners and losers in the agriculture sector of coastal Bangladesh: preliminary insights from an integrated modelling approach 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 2

3 Socio-economics Scales and project elements Endogenous governance (BD policies, laws, subsidies, flood protection, education system, ) demography char land migration aquaculture agriculture Sundarbans fisheries markets security (financial, environmental) Bay of Bengal off-shore fisheries livelihood & poverty Exogenous drivers (upstream flow diversion, climate change, macro-economics, ) 3

4 Aim of integration work 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 4

5 Sea level, SLP, SST, winds Surge level Quantitative Physical/Ecological Models Land Use Migration Demography, economics & poverty The ΔDIEM framework and integration progress Temp, rainfall GCM/ RCM storm/cyclone/flood events Catchment Models: GWAVA / INCA MODFLOW HydroTrend Demography Cohort Comp Macroeconomics Water, sediment, nutrients Delta Model FVCOM, Delft3D Morphology & Land Cover Water flow, level, salinity, temp, sediment, nutrients Crop Model: CROPWAT Aquaculture Model Mangrove Model Household Livelihood Governance Loan types Bay Bengal Model GCOMS Primary productivity, T,S,O 2, currents Coastal Fisheries Model Size- & Speciesbased models Poverty & Health Inland Fisheries Model

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 6

7 Integrated simulations - 17 age groups - house - livestock - vehicle - other - financial - env. hazards Welfare - large land owners - small land owners - sharecroppers - landless labourers - commercial - subsistence - low interest rate - high interest rate up to 10 crops - sea level rise, - increased salinity, - reduced sediment supply, - temperature rise, - CO changes MC loop CROPWAT model 7

8 The next slides One scenario run: Simulation from dS/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) 8

9 Simulated demographic changes % population change between 1980 and % % % % 39 78% - 78 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.

10 Simulated demographic changes Khulna (growth) Barisal (decrease) % population change between 1980 and % -15% % % 78% Barguna (decrease) Bhola (decrease) 10

11 Aman rice yield (t/ha) Source: Bangladesh Agriculture Research Council (2012) Land Suitability Assessment and Crop Zoning of Bangladesh Simulation results (salinity increases scenario) Very suitable Suitable Moderately suitable Marginally suitable Not suitable Sundarban Traditional Aman rice will likely not to be suitable due to salinity increase Crop yield ton/ha 11

12 Boro rice yield (t/ha) Source: Bangladesh Agriculture Research Council (2012) Land Suitability Assessment and Crop Zoning of Bangladesh Simulation results (salinity increases scenario) Very suitable Suitable Moderately suitable Marginally suitable Not suitable Sundarban Traditional Boro rice will likely not to be suitable due to salinity increase Crop yield ton/ha 12

13 Simulated Profit Margin (fraction) 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 Khulna the fraction of revenue that remains in the pocket of the households after all the costs paid Results are based on the increasing salinity scenario Shatkira Bagerhat Pirojpur 13

14 Simulated Profit Margin Large Land Owners Small Land Owners Sharecroppers Landless Labourers Jalakhati Barisal Farming is better, but difficulties after 2030 Loans are likely for Small Land Owners, Sharecroppers and Landless Borgona Bhola Patuakhali 14

15 Headcount % of farmers living under the $1.25 (PPP) Poverty line Poverty levels are high. Simulated future poverty levels are currently uncertain. 15

16 Other crops yield (t/ha) in 2050 (Salinity increases by 5dS/m) Wheat Groundnut Onion Changes are necessary (under the scenario): Maize Mustard Crop diversification Garlic + value addition Integrated agriculture (?) Better management OR multiple jobs Chillies (rabi) Lentil Jute 16

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 17

18 Thank you for your attention! 18