Applications of XGBoost in water resources engineering: A systematic literature review (Dec 2018–May 2023)

M Niazkar, A Menapace, B Brentan, R Piraei… - … Modelling & Software, 2024 - Elsevier
Abstract Applications of Machine Learning methods make a paradigm shift in the domain of
water resources engineering. This study not only presents the story of emerging eXtreme …

A review on snowmelt models: progress and prospect

G Zhou, M Cui, J Wan, S Zhang - Sustainability, 2021 - mdpi.com
The frequency and intensity of flood events have been increasing recently under the
warming climate, with snowmelt floods being a significant part. As an effective manner of …

Impact of climate change on river water temperature and dissolved oxygen: Indian riverine thermal regimes

M Rajesh, S Rehana - Scientific Reports, 2022 - nature.com
The impact of climate change on the oxygen saturation content of the world's surface waters
is a significant topic for future water quality in a warming environment. While increasing river …

Forecasting weekly reference evapotranspiration using Auto Encoder Decoder Bidirectional LSTM model hybridized with a Boruta-CatBoost input optimizer

M Karbasi, M Jamei, M Ali, A Malik… - Computers and Electronics …, 2022 - Elsevier
Reference evapotranspiration (ET o) is one of the most important and influential components
in optimizing agricultural water consumption and water resources management. In the …

Application of a modern multi-level ensemble approach for the estimation of critical shear stress in cohesive sediment mixture

UK Singh, M Jamei, M Karbasi, A Malik, M Pandey - Journal of Hydrology, 2022 - Elsevier
Exploration of incipient motion study is significantly important for the river hydraulics
community. The present study, along with experimental investigation, considered a new …

Application of machine learning and process-based models for rainfall-runoff simulation in Dupage River basin, Illinois

A Bhusal, U Parajuli, S Regmi, A Kalra - Hydrology, 2022 - mdpi.com
Rainfall-runoff simulation is vital for planning and controlling flood control events. Hydrology
modeling using Hydrological Engineering Center—Hydrologic Modeling System (HEC …

Air quality monitoring based on chemical and meteorological drivers: Application of a novel data filtering-based hybridized deep learning model

M Jamei, M Ali, A Malik, M Karbasi, E Sharma… - Journal of Cleaner …, 2022 - Elsevier
Particulate matter (PM) or particle pollution include the tiny particles of dust and fly ash
particles are expelled from coal-burning power plants. Coal combustion is an extremely …

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 …

A random forest approach to improve estimates of tributary nutrient loading

PDF Isles - Water Research, 2024 - Elsevier
Estimating constituent loads from discrete water quality samples coupled with stream
discharge measurements is critical for management of freshwater resources. Nutrient loads …

Data driven insights for parabolic trough solar collectors: Artificial intelligence-based energy and exergy performance analysis

H Tao, OA Alawi, RZ Homod, MKA Mohammed… - Journal of Cleaner …, 2024 - Elsevier
Artificial intelligence (AI) algorithms can potentially contribute to optimizing energy and
exergy outputs in renewable resources to increase efficiencies and reduce environmental …