Flood Exposure and Governance Insights for the Dongting Lake Region under Climate Change and Urbanization

Abstract Under the dual pressures of climate change and rapid urbanization, flood risk in the Dongting Lake region, a key grain-producing area in China, has intensified over the past two decades. However, the spatiotemporal change and driving mechanisms of flood exposure in this region remain unclear, constraining effective flood risk reduction and management. Using multi-source remote sensing imagery and population data, this study quantified population exposure during five typical floods (August 2002, July 2010, July 2016, July 2017, and July 2020) in the Dongting Lake region between 2000 and 2020, and selected comparable floods to analyze exposure dynamics. An XGBoost-SHAP framework was further applied to examine the nonlinear effects of environmental and socioeconomic factors on flood exposure. The findings show that: (1) Of the Dongting Lake floodplain areas, 93.2% are at low flood exposure, with moderate to high exposure concentrated near urban areas and tributaries. (2) The proportion of flood-exposed population around East Dongting Lake showed a persistent upward trend, with decomposition analysis indicating that changes in inundation expansion contributed more strongly to this trend than population redistribution. (3) Population density, building density, annual average temperature, terrain wetness index, and vegetation cover were important drivers shaping flood exposure patterns. This study offers insights for flood resilience planning in lakeside urban areas along the Yangtze River and supports adaptive flood management under climate change.