Journal of Hydrologic Engineering

Papers
(The H4-Index of Journal of Hydrologic Engineering is 15. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-05-01 to 2026-05-01.)
ArticleCitations
Discussion of “Application of a Hybrid Model Based on Secondary Decomposition and ELM Neural Network in Water Level Prediction”143
Dual-Phase Calibration for Surface–Subsurface Hydrologic Models with Diverse Hydrologic Conditions52
Impact of Progressive Reservoir Construction on Nonstationary Sediment Load Response to Streamflow in the Upper Yangtze River, China29
Inversion-Based Assessment of the Clogging Characteristics of Injection Wells Using Analytical Calculations25
Analyzing the Impact of Reservoir Incorporation, Changing Land Cover, and Future Climate Change on Basin Response Using a SWAT Model24
Reducing Latency in Satellite-Based Precipitation Estimates Using GOES-16 and Machine Learning22
Discussion of “Nonoverlapping Block Stratified Random Sampling Approach for Assessment of Stationarity” by Ramesh S. V. Teegavarapu and Priyank J. Sharma21
Improving Rainfall Fields in Data-Scarce Basins: Influence of the Kernel Bandwidth Value of Merging on Hydrometeorological Modeling21
Developing Interpretable Pan Evaporation Forecasting Models for Wafra Agricultural Basin Based on Optimized Decision Tree Ensembles18
Long-Term Streamflow Prediction Using Hybrid SVR-ANN Based on Bayesian Model Averaging17
Forestation and Hydrology: Lessons Learned from China17
Geographic Dependency of the Curve Number Method’s Initial Abstraction Ratio16
Regional Trends and Spatiotemporal Analysis of Rainfall and Groundwater in the West Coast Basins of India16
Analysis of Extreme Precipitation under Nonstationary Conditions in the Yangtze River Basin16
Discussion of “Runoff Predictions in a Semiarid Watershed by Convolutional Neural Networks Improved with Metaheuristic Algorithms and Forced with Reanalysis and Climate Data”15
NRCS Curve Number Method: Comparison of Methods for Estimating the Curve Number from Rainfall-Runoff Data15
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