Spatiotemporal coupling mechanism between land use and water disaster risk in lake-dominated basins: a multimodel assessment of the Dongting Lake Basin

The increasing frequency of extreme hydrological events has underscored the significant challenges involved in systematically assessing and managing compound water disasters for sustainable development. This study examined the Dongting Lake Basin, presenting an integrated risk assessment framework that incorporates drought and flood disasters across four dimensions and 13 indicators. Employing the entropy weight method and obstacle degree model, key risk factors were identified and spatial coupling mechanisms between land use and disaster risks were quantitatively deciphered using the spatial Durbin model. From 2000 to 2020, considerable spatiotemporal variation in water disaster risks was observed, with high-risk zones consistently concentrated in eastern and central-southern regions and extending into central-northern areas during extreme years. Additionally, five principal driving factors were recognised through obstacle degree diagnostics: population density, GDP per unit area of primary and secondary industries, extreme precipitation index (flood-oriented), terrain drought sensitivity, and vegetation cover (NDVI). Land use exhibited a threshold effect, with forest land exceeding 70 % in low-risk areas (decreasing as risk level increased), while construction land accounted for more than 50 % in high-risk areas. Spatial econometric analysis demonstrated that each additional square kilometre of forest land or water bodies reduced local risk by 2.73 × 10 −4 and 9.93 × 10 −4 , respectively, whereas increases in grassland and arable land increased risk by 3.84 × 10 −4 and 2.14 × 10 −3 , respectively. Collectively, these results indicate that the spatial distribution of water-related disaster risk within the basin is shaped by population density, industrial distribution, land use structure, and natural conditions. It is recommended that land use optimisation and ecological restoration be prioritised in high-risk zones, specifically by expanding woodland and water body coverage while restricting high-vulnerability land uses. Additionally, improving disaster prevention infrastructure and enhancing response capability to extreme weather should be pursued, particularly in densely populated and economically significant areas. This study ultimately provides a dynamic spatiotemporal framework for optimising land use within lake basins, emphasising targeted exposure regulation and strengthening landscape resilience.