|Created:||Dec 06, 2016 at 5:13 p.m.|
|Last updated:||Dec 14, 2016 at 12:06 a.m. by Irene Garousi-Nejad|
In hydrology, water data and specifically streamflow, has been an interesting issue, and historical observations of streamflow are collected by the United States Geological Survey (USGS). Additionally, several hydrologic models are used to produce forecasts of streamflow conditions in the future. Among efforts to forecast streamflow, the most recent endeavors to predict streamflow have led to the development, launch, and unveiling of America’s first National Water Model (NWM) on August 16, 2016. This model forecasts more precise, detailed, frequent, and expanded water information that can be utilized by various communities to improve water-related decisions. However, researchers who aim to use NWM forecast data may face some problems due to the retrieval, management, and analysis of these data. To cope with these challenges, a retrieval code (NWM_USGS_retrieval) that facilitates and automates the process of querying and retrieving data was generated in this project using the Python scripting language and demonstrated in a Jupyter IPython Notebook.
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This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/
|Irene Garousi-Nejad||Utah State University|
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