A surrogate approach to model groundwater level in time and space based on tree regressors

A surrogate approach to model groundwater level in time and space based on tree regressors

Abstract Groundwater is a crucial resource for humans and the environment. Protection of groundwater supplies requires tools to explore and understand the behavior of aquifers. This research presents a machine learning approach to predict groundwater levels in time and space based on tree regressors...

Full description

Saved in:
Bibliographic Details
Main Authors: Pedro Martínez-Santos, Víctor Gómez-Escalonilla, Silvia Díaz-Alcaide, Manuel Rodríguez del Rosario, Héctor Aguilera
Format: Article
Language:English
Published: SpringerOpen 2025-07-01
Series:Applied Water Science
Subjects:
Regression
Machine learning
Groundwater modeling
Tree algorithms
Surrogate models
Black box
Online Access:https://doi.org/10.1007/s13201-025-02572-5
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1007/s13201-025-02572-5

Similar Items