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Research Detail

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Attila N. Lázár*
University of Southampton, University Road, Southampton, Hampshire SO17 1BJ, UK.

Derek Clarke
University of Southampton, University Road, Southampton, Hampshire SO17 1BJ, UK.

Helen Adams
College of Life and Environmental Sciences, University of Exeter, Prince of Wales Road, Exeter, Devon EX4 4SB, UK

Abdur Razzaque Akanda
Bangladesh Agriculture Research Institute, Joydebpur, Gazipur-1701, Bangladesh

Sylvia Szabo
University of Southampton, University Road, Southampton, Hampshire SO17 1BJ, UK.

Robert J. Nicholls
University of Southampton, University Road, Southampton, Hampshire SO17 1BJ, UK.

Zoe Matthews
University of Southampton, University Road, Southampton, Hampshire SO17 1BJ, UK.

Dilruba Begum
International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka-1000, Bangladesh

Abul Fazal M. Saleh
Bangladesh University of Engineering & Technology, Dhaka-1000, Bangladesh

Md. Anwarul Abedin
Bangladesh Agriculture University, Mymensingh, Bangladesh

Andres Payo
University of Southampton, University Road, Southampton, Hampshire SO17 1BJ, UK.

Peter Kim Streatfield
International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka-1000, Bangladesh

Craig Hutton
University of Southampton, University Road, Southampton, Hampshire SO17 1BJ, UK.

M. Shahjahan Mondal
Bangladesh University of Engineering & Technology, Dhaka-1000, Bangladesh

Abu Zofar Md. Moslehuddin
Bangladesh Agriculture University, Mymensingh, Bangladesh

Coastal Bangladesh experiences significant poverty and hazards today and is highly vulnerable to climate and environmental change over the coming decades. Coastal stakeholders are demanding information to assist in the decision making processes, including simulation models to explore how different interventions, under different plausible future socio-economic and environmental scenarios, could alleviate environmental risks and promote development. Many existing simulation models neglect the complex interdependencies between the socio-economic and environmental system of coastal Bangladesh. Here an integrated approach had been proposed to develop a simulation model to support agriculture and poverty-based analysis and decision-making in coastal Bangladesh. An extended version of the FAO's CROPWAT agriculture model has been integrated with a down scaled regional demography model to simulate net agriculture profit. This is used together with a household income–expenses balance and a loans logical tree to simulate the evolution of food security indicators and poverty levels. Modelling identifies salinity and temperature stress as limiting factors to crop productivity and fertilization due to atmospheric carbon dioxide concentrations as a reinforcing factor. The crop simulation results compare well with expected outcomes but also reveal some unexpected behaviours. The agriculture-based livelihood and poverty simulations highlight the critical significance of debt through informal and formal loans set at such levels as to persistently undermine the well-being of agriculture-dependent households. The livelihood and poverty results highlight the importance of the holistic consideration of the human–nature system and the careful selection of poverty indicators. Although the simulation model at this stage contains the minimum elements required to simulate the complexity of farmer livelihood interactions in coastal Bangladesh, the crop and socio-economic findings compare well with expected behaviours. The presented integrated model is the first step to develop a holistic, transferable analytic method and tool for coastal Bangladesh.

  Agricultural livelihoods, Coastal area, Bangladesh, Climate and environmental change, Model framework
  Six districts of the Barisal Division of Bangladesh.
  
  
  Socio-economic and Policy
  Income generation, Weather/Climate

The aim of this paper was to develop a medium-complexity model framework and to carry out a preliminary investigation of

  1. the effect of climate and environmental change on crop productivity,
  2. the cumulative consequences of crop productivity, demographical changes and market conditions on the well-being and poverty levels of coastal Bangladesh, and
  3. the uncertainties associated with the integrated framework.

A model has been developed to simulate the livelihood and poverty changes of farmers in coastal Bangladesh under climate and environmental change. To do this, crop productivity is linked with demographic changes, market price changes and other socio-economic indicators (e.g. household expenditure). This was needed to balance out the spatial and temporal scale of observations, meaningful scientific methods, computational requirement and yet useful results for decision making.

Crop productivity was estimated using the extended CROPWAT model calculated separately for all 70 upazilas (sub-districts). This spatial scale is a compromise between data limitation (observed yields, cropping patterns and soil characteristics), computational time and the ability to show spatial variation in results. The net profit of the produce obtained from agriculture is estimated from market price time series. Demographic projections were carried out at the district level and at a five-year calculation time step. The annual population size was obtained from a combination of the annual (linear) interpolation of the district level results and from Census data that describes the population distribution within each district. Population change and the total agricultural land are important determinants of the available land for each household of the simulated farmer agent types (large land owners, small land owners, sharecroppers and landless labourers) within each union, because population increase can lead to land fragmentation through inheritance. The household economy is modelled by comparing the totals of farmers' revenue and savings (cash or assets) with observed monthly expenditure levels and estimates the affordable expenditure level of the simulated agent type for each month. If a household cannot meet its minimum requirement, they are assumed to obtain a loan to cover shortfalls. Household economic calculations were done at the union-level each month and for each farmer type. Total expenditure is an indicator of wealth and here it is also used as indication for the typical diet of the household. This link was used to calculate food security indicators such as the calorie intake and hunger periods.

The union scale (28 km2 on average) was decided to be the most appropriate spatial scale for decision makers and thus for presenting the results, because (i) unions are the smallest planning units in Bangladesh, (ii) unions allow fine spatial variations of environmental factors and land use changes to be captured, and (iii) well-being results are still useful without becoming computationally very expensive. The results are presented at a monthly time step to capture the seasonality of the environment-based livelihoods.

  Environ. Sci.: Processes Impacts, 2015, 17, 1018-1031
  http://pubs.rsc.org/en/content/articlehtml/2015/EM/C4EM00600C
Funding Source:
1.   Budget:  
  

This paper has provided insights into the livelihood changes of farmers that may occur as a result of climate and environmental change using an innovative prototype model. In addition, by exploring plausible scenarios, the model development and the analysis of results promote multi-disciplinary co-operation and discussions within the research community and stakeholders. Even though the model elements presented in this paper are simplified representations of both agricultural and population changes, the model produces realistic portrayals and provides a unique platform to explore the links between demographical, climate and environmental changes and their cumulative effect on farming livelihoods and poverty levels in coastal Bangladesh. The model is going to be further developed and extended as more modelled and field data become available from the ESPA Deltas project. This will include incorporating a soil salinity model (based on river and groundwater salinity and farm management), including fishing, livestock and resource collection livelihoods, and further development of the household livelihood model with feedback on land cover/land use and migration. Despite its limitations, the model provides a unique platform to explore the links between demographical and climate changes on agriculture and their cumulative effect on farming livelihoods and poverty levels in not only coastal Bangladesh, but also in other coastal deltas.

  Journal
  


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