Leaderboards/Hydrological Forecasting Using AI

Hydrological Forecasting Using AI

Last updated July 7, 2026

Rising Stars

New and hot

Rising Stars Researchers

1
Hafiza Nida
University of Faisalabad
2
Dulakshi Santhusitha Kumari Karunasingha
University of Peradeniya
3
Ahmedbahaaaldin Ibrahem Ahmed Osman
Universiti Tenaga Nasional
4
Saber Kouadri
University of Ouargla
5
Sudhakar Singha
Dr. Reddy's Laboratories (India)
6
Nida Nasir
University of Sharjah
7
Abhirup Dikshit
UNSW Sydney
8
Kyeungwoo Cho
Georgia Institute of Technology
9
Marwah Sattar Hanoon
Iraqi University
10
Kumar Puran Tripathy
Texas A&M University

Rising Stars Papers

1
Artificial Intelligence: A new era for spatial modelling and interpreting climate-induced hazard assessment
Geoscience Frontiers|2024
22 cit.
2
Advanced machine learning algorithm to predict the implication of climate change on groundwater level for protecting aquifer from depletion
Groundwater for Sustainable Development|2024
16 cit.
3
Calibration of the SMAP Soil Moisture Retrieval Algorithm to Reduce Bias Over the Amazon Rainforest
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing|2024
11 cit.
4
Lagged Soil Moisture Controls on the Persistence of Drought and Heatwaves in the United States
Geophysical Research Letters|2025
9 cit.
5
A novel composite machine learning model for the prediction of compressive strength of blended concrete
Journal of Building Pathology and Rehabilitation|2024
5 cit.
6
Impacts of climate change on Pakistan’s weather patterns: a comprehensive study of temperature and precipitation trends
Environmental Monitoring and Assessment|2025
4 cit.
7
Wide Band, High Gain Substrate Integrated Waveguide Dielectric Resonator Antenna for 5G Applications
Unknown Journal|2024
2 cit.
8
Quantifying vegetation recovery after fire considering post-fire rainfall
Environmental Research Communications|2024
2 cit.
9
Design and Analysis of a linearly polarized substrate integrated waveguide fed DRA for enhanced 5G performance
Unknown Journal|2024
1 cit.
10
Remote Sensing of Live Fuel Moisture for Wildfires Using SMAP Satellite Observations
Geophysical Research Letters|2025
1 cit.

Emerging Leaders

Gaining momentum

Emerging Leaders Researchers

1
Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬
King Fahd University of Petroleum and Minerals
2
Daniel Klotz
BOKU University
3
Claire Brenner
BOKU University
4
Quoc Bao Pham
University of Silesia in Katowice
5
Zhaocai Wang
Shanghai Ocean University
6
Ahmed Elbeltagi
Mansoura University
7
Sungho Jung
Electronics and Telecommunications Research Institute
8
Sani I. Abba
Prince Mohammad bin Fahd University
9
Duong Tran Anh
Van Lang University
10
Martin Gauch
Johannes Kepler University of Linz

Emerging Leaders Papers

1
Uncertainty estimation with deep learning for rainfall–runoff modeling
Hydrology and earth system sciences|2022
220 cit.
2
A Hybrid Model for Water Quality Prediction Based on an Artificial Neural Network, Wavelet Transform, and Long Short-Term Memory
Water|2022
202 cit.
3
Groundwater level prediction using machine learning algorithms in a drought-prone area
Neural Computing and Applications|2022
199 cit.
4
An interpretable machine learning approach based on DNN, SVR, Extra Tree, and XGBoost models for predicting daily pan evaporation
Journal of Environmental Management|2022
191 cit.
5
NeuralHydrology — A Python library for Deep Learningresearch in hydrology
The Journal of Open Source Software|2022
183 cit.
6
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions
Engineering Applications of Artificial Intelligence|2023
135 cit.
7
A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM
Frontiers of Environmental Science & Engineering|2023
132 cit.
8
A deep learning interpretable model for river dissolved oxygen multi-step and interval prediction based on multi-source data fusion
Journal of Hydrology|2024
129 cit.
9
Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR) models
Environmental Science and Pollution Research|2023
127 cit.
10
A pH-Sensitive Surface of Chitosan/Sepiolite Clay/Algae Biocomposite for the Removal of Malachite Green and Remazol Brilliant Blue R Dyes: Optimization and Adsorption Mechanism Study
Journal of Polymers and the Environment|2022
108 cit.

Current Senior Leaders

Established & currently active

Current Senior Leaders Researchers

1
J. V. Sutcliffe
HR Wallingford
2
Daniel L. Clarke‐Pearson
University of North Carolina at Chapel Hill
3
Kwok‐wing Chau
Japan Real Estate Institute
4
Özgür Kişi
Korea University
5
Ahmed El‐Shafie
United Arab Emirates University
6
Soroosh Sorooshian
Irvine University
7
Jan Adamowski
McGill University
8
Gregory J. McCabe
United States Geological Survey
9
Andrew Binley
Lancaster University
10
Hoshin V. Gupta
University of Arizona

Current Senior Leaders Papers

1
River flow forecasting through conceptual models part I — A discussion of principles
Journal of Hydrology|1970
24k cit.
2
Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach
Biometrics|1988
22.3k cit.
3
Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling
Journal of Hydrology|2009
6.7k cit.
4
The future of distributed models: Model calibration and uncertainty prediction
Hydrological Processes|1992
4.6k cit.
5
Evaluating the use of “goodness‐of‐fit” Measures in hydrologic and hydroclimatic model validation
Water Resources Research|1999
4.6k cit.
6
A modified soil adjusted vegetation index
Remote Sensing of Environment|1994
3.3k cit.
7
Status of Automatic Calibration for Hydrologic Models: Comparison with Multilevel Expert Calibration
Journal of Hydrologic Engineering|1999
2.2k cit.
8
Shuffled complex evolution approach for effective and efficient global minimization
Journal of Optimization Theory and Applications|1993
1.7k cit.
9
Artificial Neural Network Modeling of the Rainfall‐Runoff Process
Water Resources Research|1995
1.5k cit.
10
Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information
Water Resources Research|1998
1.5k cit.

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