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GIS Features of the Geospatial Fabric for the National Hydrologic Model, Hawaii Domain

Published by U.S. Geological Survey | Department of the Interior | Metadata Last Checked: January 27, 2026 | Last Modified: 2024-06-03T00:00:00Z
The Geospatial Fabric is a dataset of spatial modeling units for use within the National Hydrologic Model that covers the conterminous United States (CONUS), Alaska, and most major river basins that flow in from Canada. This U.S. Geological Survey (USGS) data release consists of the geospatial fabric features and other related datasets created to expand the National Hydrologic Model to Hawaii. This page contains data and information related to the GIS features of the Geospaital Fabric for National Hydrologic Model, Hawaii domain. An Open Geospatial Consortium geopackage (GF_20.gpkg) contains 4 feature layers (layer names in parentheses): points of interest (poi), a stream network (nsegment), aggregated catchments (catchment), and hydrologic repsonse units (nhru). Features were derived from NHDPlus, version 2.0, and several hydroclimatic datasets representing domain-specific processes and key drainage basins within the Hawaii. All data cover the National Hydrologic Model's (NHM) Hawaiin domain. The NHM is a modeling infrastructure consisting of three main parts: 1) an underlying geospatial fabric of modeling units (hydrologic response units and stream segments) with an associated parameter database, 2) a model input data archive, and 3) a repository of the physical model simulation code bases (Regan and others, 2014). The pois represent hydro locations and points on the network. Segments are connected by the pois and are used to route streamflow and characterize upstream watershed conditions. The HRUs represent the spatial modeling units at which most of the physical processes (such as precipitation, runoff, evapotranspiration, and infiltration) are simulated. Some HRUs are connected to a corresponding segment, and may represent left and right-bank areas of each stream segment. See Regan and others (2018) and entities and attributes for more information.

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