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Issues

Volume 27, Issue 2
1 February 2025
Issue Cover
ISSN 1464-7141
EISSN 1465-1734
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Special Issue Paper

Using applications of machine learning models for predicting and analyzing scour depth at the submerged weir
Abdulnoor Ghanim; Talha Ahmed; Mahmood Ahmad; Abubakr Taha Bakheit Taha; Muhammad Babur ...
View articletitled, Using applications of machine learning models for predicting and analyzing scour depth at the submerged weir
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Leveraging level data for accurate downstream flow prediction in the Narmada River Basin with advanced machine learning models
Vijendra Kumar; Namal Rathnayake; S. Hariprasad Reddy; Naresh Kedam; Upaka Rathnayake ...
View articletitled, Leveraging level data for accurate downstream flow prediction in the Narmada River Basin with advanced machine learning models
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Technical Paper

Entropy-based groundwater quality monitoring network design using a simulation–optimization approach by coupling genetic algorithm, MODFLOW and MT3DMS
Hasan Farshad; Mojtaba Shourian; Maryam Javan Salehi
View articletitled, Entropy-based groundwater quality monitoring network design using a simulation–optimization approach by coupling genetic algorithm, MODFLOW and MT3DMS
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Special Issue Paper

Assessing the Riparian Squeeze in the Greater Bay Area based on multisource data
Jiazhi Zhong; Zhuhao Chen
View articletitled, Assessing the Riparian Squeeze in the Greater Bay Area based on multisource data
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Technical Paper

A comparative study of machine learning models for river topography prediction under different data abundance
Yang Liu; Zhonghua Yang; Wenhai Li; Ming Li
View articletitled, A comparative study of machine learning models for river topography prediction under different data abundance
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Special Issue Paper

Influence of land use activities on predicted soil loss in a semi-arid river basin
Vikram Gaurav Singh; Nirmal Kumar; Siham Acharki; Sudhir Kumar Singh; Luc Cimusa Kulimushi ...
View articletitled, Influence of land use activities on predicted soil loss in a semi-arid river basin
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Enhancing river discharge inversion for the midstream Jialing River (China) using the Google Earth Engine platform
Dejing Chen; Yi He
View articletitled, Enhancing river discharge inversion for the midstream Jialing River (China) using the Google Earth Engine platform
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Technical Paper

Enhanced flood prediction using LSTM and climate parameters: multi-station analysis of snowmelt-induced flooding in the Red River of the North
Vida Atashi; Hamed Taheri Gorji
View articletitled, Enhanced flood prediction using LSTM and climate parameters: multi-station analysis of snowmelt-induced flooding in the Red River of the North
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Stormwater hydrographs from the highly urbanized catchment for synthetic rainfalls with linear patterns
Lesya Vovk; Volodymyr Zhuk
View articletitled, Stormwater hydrographs from the highly urbanized catchment for synthetic rainfalls with linear patterns
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Streamflow prediction using Long Short-Term Memory networks: a case study at the Kratie Hydrological Station, Mekong River Basin
Nhu Y Nguyen; Dang Dinh Kha; Luu Van Ninh; Vu Tuan Anh; Tran Ngoc Anh
View articletitled, Streamflow prediction using Long Short-Term Memory networks: a case study at the Kratie Hydrological Station, Mekong River Basin
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Special Issue Paper

Advanced machine learning models for robust prediction of water quality index and classification
Abdessamad Elmotawakkil; Nourddine Enneya; Suraj Kumar Bhagat; Mohamed Mohamed Ouda; Vikram Kumar
View articletitled, Advanced machine learning models for robust prediction of water quality index and classification
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Technical Paper

Integrating wavelet transform and support vector machine for improved drought forecasting based on standardized precipitation index
Reza Rezaiy; Ani Shabri
View articletitled, Integrating wavelet transform and support vector machine for improved drought forecasting based on standardized precipitation index
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Practice Paper

Enhancing groundwater predictions by incorporating response lag effects in machine learning models
Fan Yang; Xinan Zhang; Jiabao Yang; Jun Zhang; Qiang Dai ...
View articletitled, Enhancing groundwater predictions by incorporating response lag effects in machine learning models
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