OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Identifying major drivers of daily streamflow from large-scale atmospheric circulation with machine learning
Jenny Sjåstad Hagen, Étienne Leblois, Deborah Lawrence, et al.
Journal of Hydrology (2021) Vol. 596, pp. 126086-126086
Open Access | Times Cited: 51

Showing 26-50 of 51 citing articles:

Futuristic Streamflow Prediction Based on Cmip6 Scenarios Using Machine Learning Models
Basir Ullah, Muhammad Fawad, Afed Ullah Khan, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 4

Downscaling of the flood discharge in a probabilistic framework
Sanaz Moghim, Mohammad Ahmadi Gharehtoragh
Journal of Hydro-environment Research (2022) Vol. 43, pp. 10-21
Closed Access | Times Cited: 3

Machine Learning and Committee Models for Improving ECMWF Subseasonal to Seasonal (S2S) Precipitation Forecast
Mohamed Elneel Elshaikh Eltayeb Elbasheer, Gerald Corzo, Dimitri Solomatine, et al.
(2022)
Open Access | Times Cited: 3

Flow prediction in Kabul River: An artificial intelligence based technique
Salah Ud Din
International Journal of Multidisciplinary Research and Growth Evaluation (2024) Vol. 5, Iss. 2, pp. 854-857
Open Access

What drives the distinct evolution of the Aral Sea and Lake Balkhash? Insights from a novel CD-RF-FA method
Shuang Liu, Aihua Long, Geping Luo, et al.
Journal of Hydrology Regional Studies (2024) Vol. 56, pp. 102014-102014
Open Access

Enhancing streamflow prediction in a mountainous watershed using a convolutional neural network with gridded data
Zahra Hajibagheri, Mohammad Mahdi Rajabi, Ebrahim Asadi Oskouei, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 55, pp. 63959-63976
Closed Access

Exploring climate-change impacts on streamflow and hydropower potential: insights from CMIP6 multi-GCM analysis
Nikki Chanda, Madhusudana Rao Chintalacheruvu, A. K. Choudhary
Journal of Water and Climate Change (2024) Vol. 15, Iss. 9, pp. 4476-4498
Closed Access

A new method for monthly streamflow prediction using multi-source data: Range-dependent multivariate adaptive regression splines-genetic algorithm
Mariam Idowu, Christoph Külls, Özgür Kişi
Hydrological Sciences Journal (2024) Vol. 69, Iss. 13, pp. 1860-1880
Closed Access

Machine learning strategies for multiannual rainfall prediction and drought early warning: insights from Ceará, Brazil
Larissa Zaira Rafael Rolim, Francisco de Assis de Souza Filho
Natural Hazards (2024)
Closed Access

A Comparison of Stepwise Cluster Analysis and Multiple Linear Regression for Hydrological Simulation
Chunxiao Wang, Jie Sun, Yongping Li, et al.
Journal of Physics Conference Series (2022) Vol. 2224, Iss. 1, pp. 012026-012026
Open Access | Times Cited: 1

Comment on hess-2022-348
Mohamed Elneel Elshaikh Eltayeb Elbasheer, Gerald Corzo, Dimitri Solomatine, et al.
(2023)
Open Access

Reply to RC1
Louise Slater
(2023)
Open Access

Reply to RC2
Louise Slater
(2023)
Open Access

Reply on RC2
Mohamed Elneel Elshaikh Eltayeb Elbasheer
(2023)
Open Access

Reply on RC1
Mohamed Elneel Elshaikh Eltayeb Elbasheer
(2023)
Open Access

Machine Learning and Committee Models for Improving ECMWF Subseasonal to Seasonal (S2S) Precipitation Forecast
Mohamed Elneel Elshaikh Eltayeb Elbasheer, Gerald Corzo, Dimitri Solomatine, et al.
(2023)
Open Access

Reference evapotranspiration estimation using machine learning approaches for arid and semi-arid regions of India
Pangam Heramb, K. V. Ramana Rao, A. Subeesh, et al.
Climate Research (2023) Vol. 91, pp. 97-120
Closed Access

Comment on hess-2023-98
Mohamed Elneel Elshaikh Eltayeb Elbasheer, Gerald Corzo, Dimitri Solomatine, et al.
(2023)
Open Access

Comment on hess-2023-98
Mohamed Elneel Elshaikh Eltayeb Elbasheer, Gerald Corzo, Dimitri Solomatine, et al.
(2023)
Open Access

Comment on hess-2023-98
Mohamed Elneel Elshaikh Eltayeb Elbasheer, Gerald Corzo, Dimitri Solomatine, et al.
(2023)
Open Access

Reply on RC3
Mohamed Elneel Elshaikh Eltayeb Elbasheer
(2023)
Open Access

Reply on RC2
Mohamed Elneel Elshaikh Eltayeb Elbasheer
(2023)
Open Access

Reply on RC1
Mohamed Elneel Elshaikh Eltayeb Elbasheer
(2023)
Open Access

Scroll to top