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Basic Model Interface (BMI) for streamflow prediction using Long Short-Term Memory (LSTM) networks
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Created: Nov 06, 2025 at 5:37 p.m. (UTC)
Last updated: Nov 09, 2025 at 3:05 a.m. (UTC)
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Abstract

This Long Short-Term Memory (LSTM) network was developed for use in the Next Generation Water Resources Modeling Framework (NextGen). LSTMs are able to provide relatively accurate streamflow predictions when compared to other model types. This module is available through a Basic Model Interface (BMI)

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Name Value
docs_url https://docs.ciroh.org/docs/products/ngiab/community-nextgen-repos/lstm
page_url https://github.com/CIROH-UA/lstm

Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
National Oceanic and Atmospheric Administration (NOAA), University of Alabama CIROH: Enabling collaboration through data and model sharing with CUAHSI HydroShare NA22NWS4320003 to University of Alabama, subaward A23-0266-S001 to Utah State University

How to Cite

Patel, A. (2025). Basic Model Interface (BMI) for streamflow prediction using Long Short-Term Memory (LSTM) networks, HydroShare, http://www.hydroshare.org/resource/881959bd0602490494f29dd1f674ebce

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
CC-BY

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