OOIR: Observatory of International Research

Papers

(The H4-Index of Journal of Hydrology is 67. 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 2020-12-01 to 2024-12-01.)

Article	Citations
Ensemble machine learning paradigms in hydrology: A review	315
Evaluation of the ERA5 reanalysis precipitation dataset over Chinese Mainland	236
Cotransport of heavy metals and SiO2 particles at different temperatures by seepage	207
XGBoost-based method for flash flood risk assessment	193
Research on particle swarm optimization in LSTM neural networks for rainfall-runoff simulation	171
Estimating daily reference evapotranspiration based on limited meteorological data using deep learning and classical machine learning methods	157
Predicting flood susceptibility using LSTM neural networks	152
Global data assessment and analysis of drought characteristics based on CMIP6	131
Flood hazard mapping methods: A review	129
Improving streamflow prediction in the WRF-Hydro model with LSTM networks	129
Causes and implications of groundwater depletion in India: A review	128
Root zone soil moisture estimation with Random Forest	126
Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam	123
Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting	117
Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran	116
Do ERA5 and ERA5-land precipitation estimates outperform satellite-based precipitation products? A comprehensive comparison between state-of-the-art model-based and satellite-based precipitation produ	115
A novel attention-based LSTM cell post-processor coupled with bayesian optimization for streamflow prediction	111
A comparative analysis of statistical and machine learning techniques for mapping the spatial distribution of groundwater salinity in a coastal aquifer	111
Runoff changes in the major river basins of China and their responses to potential driving forces	108
The key drivers for the changes in global water scarcity: Water withdrawal versus water availability	106
Coupling analysis of the heat-water dynamics and frozen depth in a seasonally frozen zone	106
Impact of land uses, drought, flood, wildfire, and cascading events on water quality and microbial communities: A review and analysis	104
Climate change impacts on water resources in the Upper Blue Nile (Abay) River Basin, Ethiopia	102
Radial basis function artificial neural network (RBF ANN) as well as the hybrid method of RBF ANN and grey relational analysis able to well predict trihalomethanes levels in tap water	99
Using machine learning models, remote sensing, and GIS to investigate the effects of changing climates and land uses on flood probability	99

Intensification of extreme precipitation in arid Central Asia	98
Study on optimization and combination strategy of multiple daily runoff prediction models coupled with physical mechanism and LSTM	97
Evidence of shorter more extreme rainfalls and increased flood variability under climate change	96
Merging multiple satellite-based precipitation products and gauge observations using a novel double machine learning approach	96
Regional hydrological frequency analysis at ungauged sites with random forest regression	91
Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hy	91
Modelling the impacts of climate and land use change on water security in a semi-arid forested watershed using InVEST	90
Sub-regional groundwater storage recovery in North China Plain after the South-to-North water diversion project	88
Extreme value analysis dilemma for climate change impact assessment on global flood and extreme precipitation	88
Artificial intelligence modelling integrated with Singular Spectral analysis and Seasonal-Trend decomposition using Loess approaches for streamflow predictions	87
Prediction of estuarine water quality using interpretable machine learning approach	86
Urban flood modeling using deep-learning approaches in Seoul, South Korea	85
Understanding the effects of Digital Elevation Model resolution in urban fluvial flood modelling	85
Can deep learning algorithms outperform benchmark machine learning algorithms in flood susceptibility modeling?	85
Physics-guided deep learning for rainfall-runoff modeling by considering extreme events and monotonic relationships	84
A hybrid deep learning algorithm and its application to streamflow prediction	83
Improved daily SMAP satellite soil moisture prediction over China using deep learning model with transfer learning	82
Investigation about the correlation and propagation among meteorological, agricultural and groundwater droughts over humid and arid/semi-arid basins in China	81
Global rainfall erosivity projections for 2050 and 2070	81
Stacked machine learning algorithms and bidirectional long short-term memory networks for multi-step ahead streamflow forecasting: A comparative study	81
Characterization of agricultural drought propagation over China based on bivariate probabilistic quantification	80
A transfer Learning-Based LSTM strategy for imputing Large-Scale consecutive missing data and its application in a water quality prediction system	79
Blending multi-satellite, atmospheric reanalysis and gauge precipitation products to facilitate hydrological modelling	78
Reconstruction of missing groundwater level data by using Long Short-Term Memory (LSTM) deep neural network	77
Modeling projected impacts of climate and land use/land cover changes on hydrological responses in the Lake Tana Basin, upper Blue Nile River Basin, Ethiopia	75
A social-ecological coupling model for evaluating the human-water relationship in basins within the Budyko framework	75
Effects of vegetation restoration on groundwater drought in the Loess Plateau, China	75
Exploring the utility of radar and satellite-sensed precipitation and their dynamic bias correction for integrated prediction of flood and landslide hazards	75
Crop evapotranspiration prediction by considering dynamic change of crop coefficient and the precipitation effect in back-propagation neural network model	75
Daily runoff forecasting by deep recursive neural network	73
Rainfall-runoff modeling using LSTM-based multi-state-vector sequence-to-sequence model	73
Water infiltration in a cracked soil considering effect of drying-wetting cycles	73
U-FLOOD – Topographic deep learning for predicting urban pluvial flood water depth	73
Spatial and temporal patterns of propagation from meteorological to hydrological droughts in Brazil	72
A critical review of real-time modelling of flood forecasting in urban drainage systems	72
Past, present, and future of global seawater intrusion research: A bibliometric analysis	72
A comprehensive evaluation of GPM-IMERG V06 and MRMS with hourly ground-based precipitation observations across Canada	71
A new artificial intelligence strategy for predicting the groundwater level over the Rafsanjan aquifer in Iran	70
Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity	69
An integrated experimental design framework for optimizing solute transport monitoring locations in heterogeneous sedimentary media	69
Identification of sensitivity indicators of urban rainstorm flood disasters: A case study in China	69
A global perspective on the probability of propagation of drought: From meteorological to soil moisture	68
Soil water erosion susceptibility assessment using deep learning algorithms	67