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Aug 2026
Ensemble Machine-Learning-Based Horizontal Permeability Prediction and Hydraulic Flow Unit Characterization of the Hugin Sandstone
Understanding permeability is essential for evaluating reservoir quality and field development planning. Reliable permeability estimation can reduce the uncertainty in reservoir characterization, particularly in intervals where core data are limited. As the industry relies on log-based interpretations and empirical cor...
Vikram Kumar, Sayantan Ghosh, S. Maiti
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Open access
Sep 2026
COMPARATIVE EVALUATION OF MACHINE LEARNING-BASED MODELS FOR RAINFALL–RUNOFF PREDICTION
Accurate rainfall–runoff prediction is important in hydrological modeling. However, watershed processes are nonlinear and dynamic. This study examined the effect of different input configurations on daily streamflow prediction using data-driven methods. A total of 1,826 daily observations covering the period 01/01/2020...
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Evaluation of Machine-Learning Models for Reliable Prediction of Gabion Weir Aeration Efficiency for Water Quality Enhancement
Aeration efficiency is a key indicator of the environmental performance of weirs, particularly for enhancing dissolved oxygen levels in natural water bodies. This study focuses on predicting gabion weir aeration efficiency ( E 20 ) and presents a comparative evaluation of empirical equations alongsid...
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Refined simulation of groundwater level dynamics based on a machine learning stacking framework
Accurate and rapid prediction of groundwater levels (GWL) is essential for effective groundwater management. Machine learning models are efficient tools for GWL prediction, but individual models often suffer from limited generalization due to inherent randomness. This study proposed a stacking-based GWL prediction fr...
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Conference
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Aug 2026
Comparative Analysis of Five Machine Learning Regression Models for Salinity Prediction in the California Current System
Salinity significantly influences ocean water movement, climate change, marine ecosystems and heat transfer, impacting processes such as ocean circulation patterns, density-driven currents, sea ice production, nutrient distribution, and the global climate system. Various physics-based equations and oceanographic theori...
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Machine Learning-Based Groundwater Level Forecasting in a Semi-Arid Agricultural Area: Insights from SHAP, PELT, and Mann–Kendall Analyses in the Saïss Basin, Morocco
This study proposes an innovative framework that combines hydroclimatic and agro-environmental predictors, including nitrate concentration and NDVI, with climatic factors such as Rainfall, temperature, and evapotranspiration to forecast piezometric level variations in the Saïss Basin, Morocco. Eight Machine Learning (M...
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