Time series forecasting of chlorophyll-a concentrations in the Chesapeake Bay

Time series forecasting of chlorophyll-a concentrations in the Chesapeake Bay

Abstract Declining water quality poses serious environmental and public health risks, with chlorophyll-a serving as a key biological indicator of harmful algal blooms. This study evaluates the use of a Long Short-Term Memory (LSTM) neural network to forecast chlorophyll-a concentrations in the Chesa...

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Bibliographic Details
Main Authors: Sahil Gupta, Sagar Gupta
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Chesapeake bay
Time series forecasting
Water quality management
Chlorophyll-a
Machine learning
Long short term memory (LSTM)
Online Access:https://doi.org/10.1038/s41598-025-16352-3
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https://doi.org/10.1038/s41598-025-16352-3

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