Deep Learning-Based Predictive Framework for Groundwater Level Forecast in Arid Irrigated Areas

Deep Learning-Based Predictive Framework for Groundwater Level Forecast in Arid Irrigated Areas

An accurate groundwater level (GWL) forecast at multi timescales is vital for agricultural management and water resource scheduling in arid irrigated areas such as the Hexi Corridor, China. However, the forecast of GWL in these areas remains a challenging task owing to the deficient hydrogeological...

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Bibliographic Details
Main Authors: Wei Liu, Haijiao Yu, Linshan Yang, Zhenliang Yin, Meng Zhu, Xiaohu Wen
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Water
Subjects:
groundwater level forecasting
complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)
genetic algorithm (GA)
feature selection (FS)
deep belief network (DBN)
quantile regression (QR)
Online Access:https://www.mdpi.com/2073-4441/13/18/2558

Internet

https://www.mdpi.com/2073-4441/13/18/2558

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