A parsimonious methodological framework for short-term forecasting of groundwater levels-Reference-Cited by-同舟云学术

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A parsimonious methodological framework for short-term forecasting of groundwater levels

Published:2023-07 Issue: Volume:881 Page:163328
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Collados-Lara A.J.,Pulido-Velazquez D.,Ruiz L.G.B.,Pegalajar M.C.,Pardo-Igúzquiza E.,Baena-Ruiz L.

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference59 articles.

1. A wavelet neural network conjunction model for groundwater level forecasting;Adamowski;J. Hydrol.,2011

2. Towards flexible groundwater-level prediction for adaptive water management: using Facebook’s prophet forecasting approach;Aguilera;Hydrol. Sci. J.,2019

3. Soil properties prediction for precision agriculture using visible and near-infrared spectroscopy: a systematic review and meta-analysis;Ahmadi;Agronomy,2021

4. Global assessment of seawater intrusion problems (Status and Vulnerability);Baena-Ruiz;Water Resour. Manag.,2018

5. Geostatistics-based groundwater-level monitoring network design and its application to the Upper Floridan aquifer, USA;Bhat;Environ. Monit. Assess.,2015

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1. A machine learning framework for multi-step-ahead prediction of groundwater levels in agricultural regions with high reliance on groundwater irrigation;Environmental Modelling & Software;2024-09

2. Long-term effects of subsurface structures on groundwater level in a typical urban area of Shanghai, China;Hydrogeology Journal;2024-05-25

3. Short-Term Prediction of Groundwater Level Based on Spatiotemporal Correlation;Water Resources;2024-05-23

4. Groundwater level forecasting with machine learning models: A review;Water Research;2024-03

5. Reconstructing high-resolution groundwater level data using a hybrid random forest model to quantify distributed groundwater changes in the Indus Basin;Journal of Hydrology;2024-01

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