Map used to develop the Minnesota machine learning (ML) models for fluvial sediment estimates in StreamStats
By Upper Midwest Water Science Center
January 2025 (approx.)
Detailed Description
U.S. Geological Survey (USGS) sediment-monitoring sites, rivers and streams, and five sediment regions used to develop the Minnesota machine learning (ML) models for Fluvial Sediment Estimates in StreamStats. A selected basin delineation of High Island Creek near Henderson, Minnesota (USGS streamgage 05327000) used to run the ML learning models in StreamStats.
Sources/Usage
Public Domain.
Related
Fluvial Sediment Estimates in StreamStats
Fluvial sediment samples are valuable for addressing key environmental concerns such as aquatic habitat degradation and excess nutrients, but their collection is often impractical across all rivers and timeframes of interest. In addition, previously used analytical and numerical methods (Gray and Simões, 2008; Ellison and others, 2016) have not allowed for the transfer of knowledge from sites that...
Related
Fluvial Sediment Estimates in StreamStats
Fluvial sediment samples are valuable for addressing key environmental concerns such as aquatic habitat degradation and excess nutrients, but their collection is often impractical across all rivers and timeframes of interest. In addition, previously used analytical and numerical methods (Gray and Simões, 2008; Ellison and others, 2016) have not allowed for the transfer of knowledge from sites that...