Agricultural livelihoods in coastal Bangladesh under climate and environmental change - A model framework

We describe a novel integrated modelling system aiming to approximate the impact of environmental change on farmers' livelihoods in Bangladesh.</p

Integrative Analysis Applying the Delta Dynamic Integrated Emulator Model in South-West Coastal Bangladesh

A flexible meta-model, the Delta Dynamic Integrated Emulator Model (ΔDIEM), is developed to capture the socio-biophysical system of coastal Bangladesh as simply and efficiently as possible. Operating at the local scale, calculations occur efficiently using a variety of methods, including linear statistical emulators, which capture the behaviour of more complex models, internal process-based models and statistical associations. All components are tightly coupled, tested and validated, and their behaviour is explored with sensitivity tests. Using input data, the integrated model approximates the spatial and temporal change in ecosystem services and a number of livelihood, well-being, poverty and health indicators of archetypal households. Through the use of climate, socio-economic and governance scenarios plausible trajectories and futures of coastal Bangladesh can be explored

Prospects for agriculture under climate change and soil salinisation

Agriculture is the largest and most important provisioning ecosystem in the Ganges-Brahmaputra-Meghna delta and is significantly affected by levels of soil and water salinity. Model-based assessment using both soil moisture and salt balance models indicate that whilst monsoon rains supply adequate water to grow a main season rice crop, agricultural diversity is currently constrained by the limited availability of good quality irrigation water in the dry season. There is a tipping point of water salinity around four parts per thousand beyond which soil salinity accumulates. Although the development of soil salinity is an environmental process, soil salinisation is closely linked to farmers’ behaviour and land use practices. It is also closely associated with the decline in other ecosystem services associated with water regulation

Simulating yield response of rice to salinity stress with the AquaCrop model

The FAO AquaCrop model has been widely applied throughout the world to simulate crop responses to deficit water applications. However, its application to saline conditions is not yet reported, though saline soils are common in coastal areas. In this study, we parameterized and tested AquaCrop to simulate rice yield under different salinity regimes. The data and information required in the model were collected through a field experiment at the Bangladesh Agricultural Research Institute, Gazipur. The experiment was conducted with the BRRI Dhan28, a popular boro rice variety in Bangladesh, with five levels of saline water irrigation, three replicates for each level. In addition, field monitoring was carried out at Satkhira in the southwest coastal region of Bangladesh to collect data and information based on farmers' practices and to further validate the model. The results indicated that the AquaCrop model with most of its default parameters could replicate the variation of rice yield with the variation of salinity reasonably well. The root mean square error and mean absolute error of the model yield were only 0.12 t per ha and 0.03 t per ha, respectively. The crop response versus soil salinity stress curve was found to be convex in shape with a lower threshold of 2 dS m?1, an upper threshold of 10 dS m?1 and a shape factor of 2.4. As the crop production system in the coastal belt of Bangladesh has become vulnerable to climate induced sea-level rise and the consequent increase in water and soil salinity, the AquaCrop would be a useful tool in assessing the potential impact of these future changes as well as other climatic parameters on rice yield in the coastal region