Application of machine learning in groundwater quality modeling-A comprehensive review

R Haggerty, J Sun, H Yu, Y Li - Water Research, 2023 - Elsevier
Groundwater is a crucial resource across agricultural, civil, and industrial sectors. The
prediction of groundwater pollution due to various chemical components is vital for planning …

Integrating artificial intelligence, machine learning, and deep learning approaches into remediation of contaminated sites: A review

JK Janga, KR Reddy, K Raviteja - Chemosphere, 2023 - Elsevier
The growing number of contaminated sites across the world pose a considerable threat to
the environment and human health. Remediating such sites is a cumbersome process with …

Environmental source tracking of per-and polyfluoroalkyl substances within a forensic context: current and future techniques

JA Charbonnet, AE Rodowa, NT Joseph… - … science & technology, 2021 - ACS Publications
The source tracking of per-and polyfluoroalkyl substances (PFASs) is a new and
increasingly necessary subfield within environmental forensics. We define PFAS source …

Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?

C Varadharajan, AP Appling, B Arora… - Hydrological …, 2022 - Wiley Online Library
The global decline of water quality in rivers and streams has resulted in a pressing need to
design new watershed management strategies. Water quality can be affected by multiple …

Microbial dark matter: from discovery to applications

Y Zha, H Chong, P Yang, K Ning - Genomics, Proteomics and …, 2022 - academic.oup.com
With the rapid increase of the microbiome samples and sequencing data, more and more
knowledge about microbial communities has been gained. However, there is still much more …

Unsupervised phase map** of X-ray diffraction data by nonnegative matrix factorization integrated with custom clustering

V Stanev, VV Vesselinov, AG Kusne… - npj Computational …, 2018 - nature.com
Analyzing large X-ray diffraction (XRD) datasets is a key step in high-throughput map** of
the compositional phase diagrams of combinatorial materials libraries. Optimizing and …

Contaminant source identification in aquifers: A critical view

JJ Gómez-Hernández, T Xu - Mathematical Geosciences, 2022 - Springer
Forty years and 157 papers later, research on contaminant source identification has grown
exponentially in number but seems to be stalled concerning advancement towards the …

Distribution, source identification and health risk assessment of PFASs in groundwater from Jiangxi Province, China

Q Wang, X Song, C Wei, D Ding, Z Tang, X Tu, X Chen… - Chemosphere, 2022 - Elsevier
There is an urgent need to investigate on the distribution and fate of short-chain analogues
and emerging per-and polyfluoroalkyl substances (PFASs) in groundwater, and little …

Machine-learning predictions of the shale wells' performance

M Mehana, E Guiltinan, V Vesselinov… - Journal of Natural Gas …, 2021 - Elsevier
The ultra-low permeability nature of shale reservoirs leads to an extended linear flow and
necessitates horizontal wells with multi-stage engineered fractures to efficiently extract …

A novel hybrid random forest linear model approach for forecasting groundwater fluoride contamination

MB Nafouanti, J Li, EE Nyakilla… - … Science and Pollution …, 2023 - Springer
Groundwater quality in the Datong basin is threatened by high fluoride contamination.
Laboratory analysis is a standard method for estimating groundwater quality parameters …