A national topographic dataset for hydrological modeling over the contiguous United States

Jun Zhang, Laura E. Condon, Hoang Tran, Reed M. Maxwell

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Topography is a fundamental input to hydrologic models critical for generating realistic streamflow networks as well as infiltration and groundwater flow. Although there exist several national topographic datasets for the United States, they may not be compatible with gridded models that require hydrologically consistent digital elevation models (DEMs). Here, we present a national topographic dataset developed to support gridded hydrologic simulations at 1km and 250m spatial resolution over the contiguous United States. The workflow is described step by step in two parts: (a) DEM processing using a Priority Flood algorithm to ensure hydrologically consistent drainage networks and (b) slope calculation and smoothing to improve drainage performance. The accuracy of the derived stream network is evaluated by comparing the derived drainage area to drainage areas reported by the national stream gage network. The slope smoothing steps are evaluated using the runoff simulations with an integrated hydrologic model. Our DEM product started from the National Water Model DEM to ensure our final datasets will be as consistent as possible with this existing national framework. Our analysis shows that the additional processing we provide improves the consistency of simulated drainage areas and the runoff simulations that simulate gridded overland flow (as opposed to a network routing scheme). The workflow uses an open-source R package, and all output datasets and processing scripts are available and fully documented. All of the output datasets and scripts for processing are published through CyVerse at 250m and 1km resolution. The DOI link for the dataset is 10.25739/e1ps-qy48 (Zhang and Condon, 2020).

Original languageEnglish (US)
Pages (from-to)3263-3279
Number of pages17
JournalEarth System Science Data
Issue number7
StatePublished - Jul 8 2021

All Science Journal Classification (ASJC) codes

  • General Earth and Planetary Sciences


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