Water Resources Management

Papers
(The H4-Index of Water Resources Management is 32. 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 2020-11-01 to 2024-11-01.)
ArticleCitations
Ensemble Boosting and Bagging Based Machine Learning Models for Groundwater Potential Prediction158
Performance Comparison of an LSTM-based Deep Learning Model versus Conventional Machine Learning Algorithms for Streamflow Forecasting114
Evaluation of Soil Moisture Climatology and Anomaly Components Derived From ERA5-Land and GLDAS-2.1 in China87
Uncertainty Analysis of Climate Change Impacts on Flood Frequency by Using Hybrid Machine Learning Methods78
Streamflow Variations in Monthly, Seasonal, Annual and Extreme Values Using Mann-Kendall, Spearmen’s Rho and Innovative Trend Analysis63
Optimal Design and Feature Selection by Genetic Algorithm for Emotional Artificial Neural Network (EANN) in Rainfall-Runoff Modeling58
Incorporating Social System into Water-Food-Energy Nexus58
An Ensemble Hybrid Forecasting Model for Annual Runoff Based on Sample Entropy, Secondary Decomposition, and Long Short-Term Memory Neural Network58
Using Optimized Deep Learning to Predict Daily Streamflow: A Comparison to Common Machine Learning Algorithms52
Advancing the Water Footprint into an Instrument to Support Achieving the SDGs – Recommendations from the “Water as a Global Resources” Research Initiative (GRoW)51
Runoff Forecasting using Convolutional Neural Networks and optimized Bi-directional Long Short-term Memory51
Water Conflict Management between Agriculture and Wetland under Climate Change: Application of Economic-Hydrological-Behavioral Modelling51
Forecasting Groundwater Levels using a Hybrid of Support Vector Regression and Particle Swarm Optimization48
Development of Bio-Inspired- and Wavelet-Based Hybrid Models for Reconnaissance Drought Index Modeling47
Monthly Streamflow Forecasting Using Convolutional Neural Network44
Catchment-Scale and Local-Scale Based Evaluation of LID Effectiveness on Urban Drainage System Performance44
An Ensemble Modeling Approach to Forecast Daily Reservoir Inflow Using Bidirectional Long- and Short-Term Memory (Bi-LSTM), Variational Mode Decomposition (VMD), and Energy Entropy Method43
Separation of the Impact of Landuse/Landcover Change and Climate Change on Runoff in the Upstream Area of the Yangtze River, China43
A Hybrid VMD-SVM Model for Practical Streamflow Prediction Using an Innovative Input Selection Framework41
A Novel LSSVM Model Integrated with GBO Algorithm to Assessment of Water Quality Parameters41
Clarifying Regional Water Scarcity in Agriculture based on the Theory of Blue, Green and Grey Water Footprints39
Simulating Future Groundwater Recharge in Coastal and Inland Catchments38
Sustainable Water Supply and Demand Management in Semi-arid Regions: Optimizing Water Resources Allocation Based on RCPs Scenarios38
Monthly Runoff Forecasting Using Variational Mode Decomposition Coupled with Gray Wolf Optimizer-Based Long Short-term Memory Neural Networks38
A Comparative Study of Artificial Intelligence Models and A Statistical Method for Groundwater Level Prediction38
Short to Long-Term Forecasting of River Flows by Heuristic Optimization Algorithms Hybridized with ANFIS37
Identification of the Groundwater Potential Recharge Zones Using MCDM Models: Full Consistency Method (FUCOM), Best Worst Method (BWM) and Analytic Hierarchy Process (AHP)37
Temporal and Spatial Assessment of Supply and Demand of the Water-yield Ecosystem Service for Water Scarcity Management in Arid to Semi-arid Ecosystems36
Prediction of Water Quality Index in Drinking Water Distribution System Using Activation Functions Based Ann33
A Novel Framework for Urban Flood damage Assessment33
Climate Change in the Mediterranean Basin (Part I): Induced Alterations on Climate Forcings and Hydrological Processes32
Coupling Singular Spectrum Analysis with Least Square Support Vector Machine to Improve Accuracy of SPI Drought Forecasting32
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