A Comprehensive Review of Methods for Hydrological Forecasting Based on Deep Learning

X Zhao, H Wang, M Bai, Y Xu, S Dong, H Rao, W Ming - Water, 2024 - mdpi.com
Artificial intelligence has undergone rapid development in the last thirty years and has been
widely used in the fields of materials, new energy, medicine, and engineering. Similarly, a …

Imaging of moho topography with conditional generative adversarial network from observed gravity anomalies

A Roy, RK Sharma, D Jash, BP Rao, JA Dev… - Journal of Asian Earth …, 2024 - Elsevier
Accurate estimation of Moho topography plays a crucial role in understanding Earth's
structure, geodynamic processes, and resource exploration. This study presents a novel …

Groundwater quality assessment using machine learning models: a comprehensive study on the industrial corridor of a semi-arid region

L Krishnamoorthy, VR Lakshmanan - Environmental Science and …, 2024 - Springer
Water plays a significant role in sustaining the lives of humans and other living organisms.
Groundwater quality analysis has become inevitable, because of increased contamination of …

A Novel Stochastic Tree Model for Daily Streamflow Prediction Based on A Noise Suppression Hybridization Algorithm and Efficient Uncertainty Quantification

NF Attar, MT Sattari, H Apaydin - Water Resources Management, 2024 - Springer
Streamflow prediction is one of the critical components of hydrological interactions and a
vital step for integrated water resources management for different water-related sectors …

Boosting algorithms for projecting streamflow in the Lower Godavari Basin for different climate change scenarios

BR Mishra, RK Vogeti, R Jauhari, KS Raju… - Water Science & …, 2024 - iwaponline.com
The present study investigates the ability of five boosting algorithms, namely Adaptive
Boosting (AdaBoost), Categorical Boosting (CatBoost), Light Gradient Boosting (LGBoost) …

Do non-linearity and non-Gaussianity truly matter in streamflow forecasting? A comparative study between PAR (p) and vine copula for Brazilian streamflow time …

GA de Almeida Pereira… - Environmental Monitoring …, 2024 - Springer
This study evaluates the joint impact of non-linearity and non-Gaussianity on predictive
performance in 23 Brazilian monthly streamflow time series from 1931 to 2022. We consider …

[PDF][PDF] A Comprehensive Review of Methods for Hydrological Forecasting Based on Deep Learning. Water 2024, 16, 1407

X Zhao, H Wang, M Bai, Y Xu, S Dong, H Rao, W Ming - 2024 - researchgate.net
Artificial intelligence has undergone rapid development in the last thirty years and has been
widely used in the fields of materials, new energy, medicine, and engineering. Similarly, a …

Extraction of Surface Water Extent: Automated Thresholding Approaches

M Sathish Kumar - Environmental Sciences Proceedings, 2023 - mdpi.com
Inland water bodies play a crucial role in both ecological and sociological contexts. The
distribution of these water bodies can change over time due to natural or human-induced …

Apa Barajı havzasındaki hidrolojik parametrelerin makine öğrenmesi ile tahmini

T Tuğrul - 2024 - acikerisim.aksaray.edu.tr
Son yıllarda, özellikle de sanayi devriminden sonra insanoğlunun suya olan ihtiyacı
artmıştır. Canlılar için yaşamsal önemi tartışılmaz olan bu suyun, gelecekteki ve mevcut …

[PDF][PDF] Extraction of Surface Water Extent: Automated Thresholding Approaches

MS Kumar - Presented at the 5th International electronic …, 2023 - sciforum.net
Inland water bodies play a crucial role in both ecological and sociological contexts. The
distribution of these water bodies can change over time due to natural or human-induced …