Explaining the Mechanism of Multiscale Groundwater Drought Events: A New Perspective From Interpretable Deep Learning Model

Explaining the Mechanism of Multiscale Groundwater Drought Events: A New Perspective From Interpretable Deep Learning Model

Abstract This study presents a new approach to understand the causes of groundwater drought events with interpretable deep learning (DL) models. As prerequisites, accurate long short‐term memory (LSTM) models for simulating groundwater are built for 16 regions representing three types of spatial sca...

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Bibliographic Details
Main Authors: Hejiang Cai, Haiyun Shi, Zhaoqiang Zhou, Suning Liu, Vladan Babovic
Format: Article
Language:English
Published: Wiley 2024-07-01
Series:Water Resources Research
Subjects:
groundwater drought
explainable AI
LSTM network
temporal analysis
model interpretation
Online Access:https://doi.org/10.1029/2023WR035139
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https://doi.org/10.1029/2023WR035139

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