Levees are critical infrastructure to mitigate flood hazards worldwide. Despite their importance, current global flood models inadequately account for levees due to the complexity of flow mechanisms involving levees and the lack of comprehensive levee data. This research aims to address these gaps by developing a levee module suitable for global flood modeling and proposing a reach-level parameterization approach to estimate the necessary levee parameters on a global scale. Specifically, we developed a simplified levee module based on the CaMa-Flood global flood model, requiring only two levee parameters: levee unprotected fraction and equivalent levee height. We then identified river reaches globally that are protected by levees and estimated the levee parameters for these reaches using open-access land use and levee standard data respectively. Finally, we evaluated the model’s performance by comparing changes in river hydrodynamics and flood hazard maps, with and without levees, against observed data or official flood records from representative case studies. The results showed that (1) the proposed approach successfully identified globally protected reaches with a high hit rate of 91.3%; (2) the levee unprotected fraction can be accurately estimated based on open-access land-use data, and equivalent levee height can be derived from flood defense data using the global flood model; and (3) The enhanced CaMa-Flood model, incorporating the levee module, accurately simulated both river hydrodynamics and flood hazard mapping, improving the mean Nash-Sutcliffe efficiency of water levels from 0.68 to 0.84 and increasing the mean accuracy of flood hazard mapping from 76% to 87%.

Some recent land surface models can explicitly represent land surface process and focus more on sub-grid terrestrial features. Many studies have involved the analysis of how hillslope water dynamics determine vegetation patterns and shape ecologically and hydrologically important landscapes, such as desert riparian and waterlogged areas. However, the global locations and abundance of hillslope-dominated landscapes remain unclear. To address this knowledge gap, we propose a globally applicable method that employs high-resolution elevation, hydrography, and land cover data to neatly resolve explicit land cover heterogeneity for the mapping of hillslope-dominated landscapes. First, we aggregate pixels into unit catchments to represent topography-based hydrological units, and then vertically discretize them into height bands to approximate the hillslope profile. The dominant land cover type in each height band is determined, and the uphill land cover transition is analyzed to identify hillslope-dominated landscapes. The results indicate that hillslope-dominated landscapes are distributed extensively worldwide in diverse climate zones. Notably, some landscapes, including gallery forests in northeastern Russia and desert riparian in the Horn of Africa, are newly revealed. Furthermore, the proposed strategy enables more accurate representation of explicit land cover heterogeneity than does the simple downscaling of a rectangular grid from larger to smaller units, revealing its capability to neatly resolve land cover heterogeneity in land surface modeling with relatively high accuracy. Overall, we present the extensive global distribution of landscapes shaped by hillslope water dynamics, underscoring the importance of the explicit resolution of heterogeneity in land surface modeling.