Assessing impact of salinity and climate scenarios on dry season field crops in the coastal region of Bangladesh

Soil salinity is the main environmental limiting factor for current agricultural farming systems in Bangladesh coastal zone. Targeting crop selection to ameliorate its impact food production a priority ensure security, diversifying outputs and reducing smallholders' vulnerabilities. In this context, growth modelling emerges as useful tool exploring different scenarios selection. Studying spatial -temporal heterogeneity productivity under climate scenarios. A dataset from Polder 30 located southwest zone, including (rice-maize, rice-mungbean, rice-sunflower) comprising two years (2017–2019), was utilized, together with polder-level contiguous layers of factors (i.e., salinity, elevation, precipitation), create clusters representing yield-limiting conditions. Two were defined included long term in-silico assessment explore dry-season field options (maize, sunflower, mungbean). APSIM models maize, sunflower mungbean, selected perform all simulations. Based on yield, most stable choice maize best non-saline Lastly, yield stability accounted conditions, showing large reduction when combining low precipitation high temperature, whereas mungbean presented less sensitivity climates. Right right environment, considering both restrictions uncertainties, critical long-term stability. The present study provides novel framework better match suitable challenging uncertainties affecting smallholders zone Bangladesh.