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 has been proposed to develop a simulation model to support agriculture and poverty-based analysis and decision-making in coastal Bangladesh. In particular, we show how a simulation model of farmer's livelihoods at the household level can be achieved. An extended version of the FAO's CROPWAT agriculture model has been integrated with a downscaled 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 fertilisation 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. For example, under current model assumptions, temperature is more important than salinity for crop production. 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. Simulations also indicate that progressive approaches to agriculture (i.e. diversification) might not provide the clear economic benefit from the perspective of pricing due to greater susceptibility to climate vagaries. 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.

In this study, we propose a new baseline and transect method, the open-source digital shoreline analysis system (ODSAS), which is specifically designed to deal with very irregular coastlines. We have compared the ODSAS results with those obtained using the digital shoreline analysis system (DSAS). Like DSAS, our proposed method uses a single baseline parallel to the shoreline and offers the user different smoothing and spacing options to generate the transects. Our method differs from DSAS in the way that the transects’ starting points and orientation are delineated by combining raster and vector objects. ODSAS uses SAGA GIS and R, which are both free open-source software programs. In this paper, we delineate the ODSAS workflow, apply it to ten study sites along the very irregular Galician coastline (NW Iberian Peninsula), and compare it with the one obtained using DSAS. We show how ODSAS produces similar values of coastline changes in terms of the most common indicators at the aggregated level (i.e., using all transects), but the values differ when compared at the transect-by-transect level. We argue herein that explicitly requesting the user to define a minimum resolution is important to reduce the subjectivity of the transect and baseline method.

The prediction of berm and dune erosion during a storm is essential for storm damage assessment. Simple and transparent formulas for the cross-shore and longshore transport rates of suspended sediment and bed load on beaches are proposed and incorporated into a combined wave and current model to predict the berm and dune erosion under normally and obliquely incident irregular waves. Two small-scale experiments for two different berm profiles were conducted for the calibration of the developed numerical model. The calibrated numerical model is shown to predict the measured berm and dune erosion in these experiments as well as dune erosion measured in three large-scale tests with errors less than a factor of two. The numerical model is used to examine the effects of the wave period and incident wave angle on the berm and dune erosion. These effects are computed to be within a factor of two.

Understanding the dynamics of salt movement in the soil is a prerequisite for devising appropriate management strategies for land productivity of coastal regions, especially low‐lying delta regions, which support many millions of farmers around the world. At present, there are no numerical models able to resolve soil salinity at regional scale and at daily time steps. In this research, we develop a novel holistic approach to simulate soil salinization comprising an emulator‐based soil salt and water balance calculated at daily time steps. The method is demonstrated for the agriculture areas of coastal Bangladesh (∼20,000 km²). This shows that we can reproduce the dynamics of soil salinity under multiple land uses, including rice crops, combined shrimp and rice farming, as well as non‐rice crops. The model also reproduced well the observed spatial soil salinity for the year 2009. Using this approach, we have projected the soil salinity for three different climate ensembles, including relative sea‐level rise for the year 2050. Projected soil salinity changes are significantly smaller than other reported projections. The results suggest that inter‐season weather variability is a key driver of salinization of agriculture soils at coastal Bangladesh.