Diel temperature patterns unveiled: High-frequency monitoring and deep learning in Lake Kasumigaura

Diel temperature patterns unveiled: High-frequency monitoring and deep learning in Lake Kasumigaura

The diel variation of water temperatures is crucial information for lakes. This study investigated such variation in Lake Kasumigaura, the second largest lake in Japan, situated 60 km from the Tokyo metropolitan area, utilizing high-frequency monitoring and deep learning techniques. Data from high-f...

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Bibliographic Details
Main Authors: Senlin Zhu, Ryuichiro Shinohara, Shin–Ichiro S. Matsuzaki, Ayato Kohzu, Mirai Watanabe, Megumi Nakagawa, Fabio Di Nunno, Jiang Sun, Quan Zhou, Francesco Granata
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Ecological Indicators
Subjects:
Thermal dynamics
Diel variation
High-frequency monitoring
Deep modeling
Climate change
Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X24014158
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