Digital Elevation Model and Drainage Network Data Sets for Global Flood and Drought Modeling

Monitoring of hydrological hazards (e. g drought, flooding, etc) is largely limited by the lack of appropriate modeling systems and high-quality input data, especially in less developed countries and data-scarce regions. The fundamental data set for global drought monitoring and flood modeling is the digital elevation model (DEM), and hydrographic variables that are usually derived from DEMs. This chapter summarizes the currently available global DEMs and hydrographic data sets for drought monitoring and flood modeling, describes the recently released high-quality data sets, and discusses key challenges in producing a high-quality baseline DEM as well as the upscaling of various hydrographic layers. Specifically, the newly developed MultiError-Removed Improved-Terrain DEM provides globally consistent high-accuracy terrain elevation data, although with several minor caveats. The TanDEM-X data opens a new era of timely monitoring dynamic topographic changes of the Earth’s surface with high accuracy. We further introduced a few commonly used algorithms for hydrological processing of DEMs and upscaling drainage networks, and discussed their advantages and limitations. The hierarchically dominant river tracing algorithm, with proved high capability in preserving river network information defined in a high-resolution DEM, is suggested for application to a recently updated high-quality DEM for the derivation of upscaled hydrographic data sets for hydrological modeling at various spatial resolutions. We end the chapter by discussing the necessity of next-generation hydrologically consistent full-hydrography data sets for development of a better monitoring system for hazards warning, guidance, and risk assessment at the global scale.