SHIFT: A DEM-Based Spatial Heterogeneity Improved Mapping of Global Geomorphic Floodplains

Abstract

Abstract. Floodplain is a vital part of the global riverine system. Among all the global floodplain delineation strategies empowered by remote sensing, DEM-based delineation is considered computationally efficient with relatively low uncertainties, but the parsimonious model struggles with incorporating spatial heterogeneity into the floodplain map. In this study, we propose a globally applicable thresholding scheme for DEM-based floodplain delineation to improve the representation of spatial heterogeneity. Specifically, we develop a stepwise approach to estimate the Floodplain Hydraulic Geometry (FHG) scaling parameters for 269 river basins worldwide to best respect the scaling law while approximating the spatial extent of two publicly available global flood maps derived from hydrodynamic modeling. Based on the spatially-varying FHG parameters, a ~90-m resolution global floodplain map named Spatial Heterogeneity Improved Floodplain by Terrain analysis (SHIFT) is delineated, which takes the hydrologically corrected MERIT-Hydro dataset as the DEM inputs and the Height Above Nearest Drainage (HAND) as the terrain attribute. Our results demonstrate that SHIFT validates well with reference maps with the overall accuracy exceeding 0.85. At the same time, it shows superior consistencies with several other datasets sourced from independent hydrodynamic modeling and DEM-based approaches. SHIFT effectively captures the global patterns of the geomorphic floodplains, with better regional details than existing data. The estimated FHG exponent exhibits a significant positive relation with the basins’ climatic aridity conditions, particularly for 34 world’s major river basins, suggesting the ability of the scaling exponents in capturing more spatial heterogeneity. SHIFT estimates global floodplain area to be 8.2 million km2, representing 5.5 % of the world's total land area, and we anticipate SHIFT available at https://zenodo.org/records/10440609 (Zheng et al., 2023) to be used to support a range of applications requiring boundary delineations of the global geomorphic floodplains.