72 citations as recorded by crossref.

1. Simbi: historical hydro-meteorological time series and signatures for 24 catchments in Haiti R. Bathelemy et al.
2. Disentangling coastal groundwater level dynamics in a global dataset A. Nolte et al.
3. A framework on utilizing of publicly availability stream gauges datasets and deep learning in estimating monthly basin-scale runoff in ungauged regions M. Le et al.
4. A GNN routing module is all you need for LSTM Rainfall–Runoff models H. Mosaffa et al.
5. A Global Benchmark of the Vector-Based Routing Model MizuRoute: Similarities and Divergent Patterns in Simulated River Discharge S. Xu et al.
6. On the Evaluation of Both Spatial and Temporal Performance of Distributed Hydrological Models Using Remote Sensing Products T. Nguyen et al.
7. Vorhersage von hydrologischen Abflusskennwerten in unbeobachteten Einzugsgebieten mit Machine Learning C. Klingler et al.
8. A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting G. Papacharalampous & H. Tyralis
9. AquaFetch: A Unified Python Interface for Water Resource Dataset Acquisition and Harmonization A. Abbas et al.
10. Spatially resolved rainfall streamflow modeling in central Europe M. Vischer et al.
11. Suspended sediment concentrations in Alpine rivers: from annual regimes to sub-daily extreme events A. van Hamel et al.
12. Using century-long reanalysis and a rainfall-runoff model to explore multi-decadal variability in catchment hydrology at the European scale P. Brigode & L. Oudin
13. Evaluating E-OBS forcing data for large-sample hydrology using model performance diagnostics F. Clerc-Schwarzenbach & T. do Nascimento
14. AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods A. Abbas et al.
15. Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale G. Papacharalampous et al.
16. FOCA: a new quality-controlled database of floods and catchment descriptors in Italy P. Claps et al.
17. Large Scale Evaluation of Relationships Between Hydrologic Signatures and Processes H. McMillan et al.
18. Quantifying the Geomorphic Effect of Floods Using Satellite Observations of River Mobility A. Leenman et al.
19. Temporal hydrological drought clustering varies with climate and land-surface processes M. Brunner & K. Stahl
20. CAMELS-DK: hydrometeorological time series and landscape attributes for 3330 Danish catchments with streamflow observations from 304 gauged stations J. Liu et al.
21. GRDC-Caravan: extending Caravan with data from the Global Runoff Data Centre C. Färber et al.
22. Influence of irrigation on root zone storage capacity estimation F. van Oorschot et al.
23. Fine-tuning long short-term memory models for seamless transition in hydrological modelling: From pre-training to post-application X. Chen et al.
24. CAMELS-IND: hydrometeorological time series and catchment attributes for 228 catchments in Peninsular India N. Mangukiya et al.
25. Evaluation of satellite precipitation products for water allocation studies in the Sio-Malaba-Malakisi river basin of East Africa P. Omonge et al.
26. Lateral terrestrial water fluxes in the LSM of WRF‐Hydro: Benefits of a 2D groundwater representation T. Rummler et al.
27. What makes a robust calibration period? Insights into the effects of data properties O. Jaffar et al.
28. Res-CN (Reservoir dataset in China): hydrometeorological time series and landscape attributes across 3254 Chinese reservoirs Y. Shen et al.
29. CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland M. Höge et al.
30. Deep learning foundation and pattern models: Challenges in hydrological time series J. He et al.
31. Caravan - A global community dataset for large-sample hydrology F. Kratzert et al.
32. Widespread deoxygenation in warming rivers W. Zhi et al.
33. Global patterns in vegetation accessible subsurface water storage emerge from spatially varying importance of individual drivers F. van Oorschot et al.
34. BCUB – a large-sample ungauged basin attribute dataset for British Columbia, Canada D. Kovacek & S. Weijs
35. Catchment characterization: Current descriptors, knowledge gaps and future opportunities L. Tarasova et al.
36. Technical note: High Nash–Sutcliffe Efficiencies conceal poor simulations of interannual variance in seasonal regimes S. Ruzzante et al.
37. A Weak-Coupling Flow-Power Forecasting Method for Small Hydropower Station Group B. Chen et al.
38. Swiss data quality: augmenting CAMELS-CH with isotopes, water quality, agricultural and atmospheric data T. do Nascimento et al.
39. Temporal Fusion Transformers for streamflow Prediction: Value of combining attention with recurrence S. Rasiya Koya & T. Roy
40. Impacts of observational uncertainty on analysis and modelling of hydrological processes: Preface H. McMillan et al.
41. CAMELS-DE: hydro-meteorological time series and attributes for 1582 catchments in Germany R. Loritz et al.
42. A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022) X. Chen et al.
43. EStreams: An integrated dataset and catalogue of streamflow, hydro-climatic and landscape variables for Europe T. do Nascimento et al.
44. A dataset of lake-catchment characteristics for the Tibetan Plateau J. Liu et al.
45. Snow drought propagation and its impacts on streamflow drought in the Alps C. Chartier-Rescan et al.
46. Where should hydrology go? An early-career perspective on the next IAHS Scientific Decade: 2023–2032 T. van Hateren et al.
47. BULL Database – Spanish Basin attributes for Unravelling Learning in Large-sample hydrology J. Senent-Aparicio et al.
48. Multi-model hydrological reference dataset over continental Europe and an African basin B. Droppers et al.
49. A novel statistical-dynamical method for a seasonal forecast of particular matter in South Korea J. Jeong et al.
50. A synthesis of Global Streamflow Characteristics, Hydrometeorology, and Catchment Attributes (GSHA) for large sample river-centric studies Z. Yin et al.
51. How do geological map details influence the identification of geology-streamflow relationships in large-sample hydrology studies? T. do Nascimento et al.
52. Regional-scale assessment of groundwater recharge and the water balance for Austria H. Zeitfogel et al.
53. LamaH-Ice: LArge-SaMple DAta for Hydrology and Environmental Sciences for Iceland H. Helgason & B. Nijssen
54. Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters L. Bouaziz et al.
55. What is the near-natural catchment? An application of hydrological signatures assessment H. Xu et al.
56. AI-Empowered Latent Four-dimensional Variational Data Assimilation for River Discharge Forecasting K. Wang et al.
57. River temperature response to atmospheric heatwaves is modulated by discharge and meltwater A. van Hamel et al.
58. Deep learning for cross-region streamflow and flood forecasting at a global scale B. Zhang et al.
59. Investigate the rainfall-runoff relationship and hydrological concepts inside LSTM Y. Hu et al.
60. Catchment Attributes and MEteorology for Large-Sample SPATially distributed analysis (CAMELS-SPAT): streamflow observations, forcing data and geospatial data for hydrologic studies across North America W. Knoben et al.
61. A heterogeneous multi-graph spatio-temporal network for runoff forecasting X. Zhou et al.
62. Building Cross-Site and Cross-Network collaborations in critical zone science B. Arora et al.
63. Comparative analysis of machine learning based dissolved oxygen predictions in the Yellow River Basin: The role of diverse environmental predictors L. Liu et al.
64. How to out-perform default random forest regression: choosing hyperparameters for applications in large-sample hydrology D. Bilolikar et al.
65. Setting expectations for hydrologic model performance with an ensemble of simple benchmarks W. Knoben
66. Functional data analysis to investigate controls on and changes in the seasonality of UK baseflow K. Leeming et al.
67. CAMELS-FR dataset: a large-sample hydroclimatic dataset for France to explore hydrological diversity and support model benchmarking O. Delaigue et al.
68. Changes in the water retention of mountainous landscapes since the 1820s in the Austrian Alps G. Stecher et al.
69. Uncertainty in Environmental Micropollutant Modeling H. Ahkola et al.
70. Potenzial von Machine Learning bei der kurzfristigen Leistungsprognose innerhalb einer Laufkraftwerkskette C. Klingler et al.
71. QUADICA: water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany P. Ebeling et al.
72. Large-sample hydrology – a few camels or a whole caravan? F. Clerc-Schwarzenbach et al.