A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Water Engineering and Management, School of Engineering and Technology

Thesis (M. Sc.) - Asian Institute of Technology, 2024

In recent times, floods have garnered global attention because of its destructive power as well as propensity to cause enormous financial and human losses. Bangladesh, in particular, faces recurring challenges amplified by its geographical setting and the influence of climate change on its populous deltaic landscape. However, the absence of an extensive database that correlates flood features with geographical and geomorphologic data has hampered research on flood characterization of Bangladesh. This study addresses this gap by employing a large-event dataset that relies on BWDB classifications of floods, introducing a protocol for flood characterization using the Flood Intensity Index (FII). This classification will open doors for better risk management and hydrologic predictions. Examining flooding characteristics reveals variations in spatial and temporal scales across different climatic regimes and geomorphological features. The Meghna Basin emerges as a focal point, dominating in maximum flood years and hosting the highest number of flood-vulnerable stations. It records the highest number of flooding events and annual precipitation, falling under the Tropical monsoon climate (Am), indicating the highest rainfall zone. Analysis of envelop curve indicates distinctive trends in unit peak discharge values with catchment area among basins, reflecting their geomorphological attributes. To validate findings, a flood-susceptible map is prepared using a multi-criteria decision technique integrating GIS and AHP. Seven parameters that can cause flooding are taken into account are elevation, drainage density, rainfall, topographic moisture index, slope, flood depth, and discharge. Analysis spanning from 1987 to 2021 highlights a significant decreasing trend in floods across Bangladesh, as evidenced by the Mann-Kendall Trend Test (MK). While pinpointing exact drivers remains challenging, potential explanations include variations in precipitation due to climate change, global warming effects, and water management strategies both within and beyond Bangladesh's borders.