High Resolution Water Table Modeling of the Shallow Groundwater Using a Knowledge-Guided Gradient Boosting Decision Tree Model

High Resolution Water Table Modeling of the Shallow Groundwater Using a Knowledge-Guided Gradient Boosting Decision Tree Model

Detailed knowledge of the uppermost water table representing the shallow groundwater system is critical in order to address societal challenges that relate to the mitigation and adaptation to climate change and enhancing climate resilience in general. Machine learning (ML) allows for high resolution...

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Bibliographic Details
Main Authors: Julian Koch, Jane Gotfredsen, Raphael Schneider, Lars Troldborg, Simon Stisen, Hans Jørgen Henriksen
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Water
Subjects:
water table depth
machine learning
high resolution
CatBoost
quantile regression
Online Access:https://www.frontiersin.org/articles/10.3389/frwa.2021.701726/full

Internet

https://www.frontiersin.org/articles/10.3389/frwa.2021.701726/full

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