Quantifying the relative contributions of climate change and ENSO to flood occurrence in Bangladesh

Abstract Bangladesh is highly vulnerable to flood hazards, and its risk projected increase with global warming. In addition climate change, internal variation, such as the El Niño–Southern Oscillation (ENSO), influences flooding in many rivers worldwide. However, impact of variability on remains unclear due limited observations. Here, we assess impacts ENSO change occurrence using a large-ensemble simulation dataset river model (CaMa-Flood). After separating 6000 years (100-member ensemble simulations for 1950–2010) into Niño, La Niña, neutral years, calculated extent which each stage increased probability relative state fraction attributable method. addition, estimated historical past through comparison without Under no-global-warming climate, Niña 10 year return period at Hardinge Bridge Ganges River by 38% compared years. The influence or Niño Brahmaputra Bahadurabad station negligible. Historical warming River, their confluence 59%, 44%, 55%, respectively. decreased simulation, likely conflation signals, no significant correlation between was detected when only small-ensemble were used. These findings suggest that use datasets essential precise attribution Bangladesh.