OOIR: Observatory of International Research

Papers

(The H4-Index of Hydrology and Earth System Sciences is 42. 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.)

Article	Citations
Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors	168
The International Soil Moisture Network: serving Earth system science for over a decade	155
Groundwater level forecasting with artificial neural networks: a comparison of long short-term memory (LSTM), convolutional neural networks (CNNs), and non-linear autoregressive networks with exoge	137
Rainfall–runoff prediction at multiple timescales with a single Long Short-Term Memory network	134
Nonstationary weather and water extremes: a review of methods for their detection, attribution, and management	129
Deep learning methods for flood mapping: a review of existing applications and future research directions	115
Urban surface water flood modelling – a comprehensive review of current models and future challenges	106
A standardized index for assessing sub-monthly compound dry and hot conditions with application in China	101
Benchmarking data-driven rainfall–runoff models in Great Britain: a comparison of long short-term memory (LSTM)-based models with four lumped conceptual models	89
Deep learning rainfall–runoff predictions of extreme events	87
Progressive water deficits during multiyear droughts in basins with long hydrological memory in Chile	78
Flood forecasting with machine learning models in an operational framework	73
Rapid reduction in ecosystem productivity caused by flash droughts based on decade-long FLUXNET observations	70
Hydrologically informed machine learning for rainfall–runoff modelling: towards distributed modelling	70
Uncertainty of simulated groundwater recharge at different global warming levels: a global-scale multi-model ensemble study	70
The 2018 northern European hydrological drought and its drivers in a historical perspective	68
Machine-learning methods for stream water temperature prediction	68
A history of TOPMODEL	62
Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa	61
Quantifying the impacts of compound extremes on agriculture	58
Evaporation, infiltration and storage of soil water in different vegetation zones in the Qilian Mountains: a stable isotope perspective	58
Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought	57
Technical Note: Improved partial wavelet coherency for understanding scale-specific and localized bivariate relationships in geosciences	57
Uncertainty estimation with deep learning for rainfall–runoff modeling	56
Flash drought onset over the contiguous United States: sensitivity of inventories and trends to quantitative definitions	56

Comparative analysis of kernel-based versus ANN and deep learning methods in monthly reference evapotranspiration estimation	55
Global cotton production under climate change – Implications for yield and water consumption	54
Lake thermal structure drives interannual variability in summer anoxia dynamics in a eutrophic lake over 37 years	53
Sentinel-3 radar altimetry for river monitoring – a catchment-scale evaluation of satellite water surface elevation from Sentinel-3A and Sentinel-3B	52
Compound flood potential from storm surge and heavy precipitation in coastal China: dependence, drivers, and impacts	52
Using a long short-term memory (LSTM) neural network to boost river streamflow forecasts over the western United States	51
Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models	51
Two-stage variational mode decomposition and support vector regression for streamflow forecasting	51
Towards hybrid modeling of the global hydrological cycle	51
Evaluation of random forests for short-term daily streamflow forecasting in rainfall- and snowmelt-driven watersheds	49
Do small and large floods have the same drivers of change? A regional attribution analysis in Europe	48
A note on leveraging synergy in multiple meteorological data sets with deep learning for rainfall–runoff modeling	48
Quantifying the effects of land use and model scale on water partitioning and water ages using tracer-aided ecohydrological models	48
Ensemble streamflow forecasting over a cascade reservoir catchment with integrated hydrometeorological modeling and machine learning	46
Hydrological concept formation inside long short-term memory (LSTM) networks	45
Hybrid forecasting: blending climate predictions with AI models	42
Easy-to-use spatial random-forest-based downscaling-calibration method for producing precipitation data with high resolution and high accuracy	42