66 citations as recorded by crossref.

1. The physics and the biology of the water balance: A personal journey through the critical zone into the water balance A. Hunt 10.1002/hyp.15209
2. Hillslope sediment transport across climates and vegetative influences C. Guzman 10.1130/focus052019.1
3. Spatio‐temporal discretization uncertainty of distributed hydrological models S. Markhali et al. 10.1002/hyp.14635
4. Pattern recognition describing spatio-temporal drivers of catchment classification for water quality C. O’Sullivan et al. 10.1016/j.scitotenv.2022.160240
5. Embedding scale: new thinking of scale in machine learning and geographic representation M. Yuan & A. McKee 10.1007/s10109-022-00378-6
6. Performance Evaluation of a National Seven-Day Ensemble Streamflow Forecast Service for Australia M. Bari et al. 10.3390/w16101438
7. Estimation of watershed width function: a statistical approach using LiDAR data P. Bajracharya & S. Jain 10.1007/s00477-020-01846-5
8. 100 Years of Progress in Hydrology C. Peters-Lidard et al. 10.1175/AMSMONOGRAPHS-D-18-0019.1
9. Remote sensing and big data: Google Earth Engine data to assist calibration processes in hydro-sediment modeling on large scales R. Rossoni et al. 10.1016/j.rsase.2024.101352
10. Origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood events L. Rahimi et al. 10.1038/s41598-021-84664-1
11. Global streamflow modelling using process-informed machine learning M. Magni et al. 10.2166/hydro.2023.217
12. Comprehensive Analysis of the NOAA National Water Model: A Call for Heterogeneous Formulations and Diagnostic Model Selection J. Johnson et al. 10.1029/2023JD038534
13. Reporting negative results to stimulate experimental hydrology: discussion of “The role of experimental work in hydrological sciences – insights from a community survey” T. van Emmerik et al. 10.1080/02626667.2018.1493203
14. Characterizing Catchment‐Scale Nitrogen Legacies and Constraining Their Uncertainties F. Sarrazin et al. 10.1029/2021WR031587
15. Variability in flow and tracer-based performance metric sensitivities reveal regional differences in dominant hydrological processes across the Athabasca River basin T. Holmes et al. 10.1016/j.ejrh.2022.101088
16. Improving the Predictive Skill of a Distributed Hydrological Model by Calibration on Spatial Patterns With Multiple Satellite Data Sets M. Dembélé et al. 10.1029/2019WR026085
17. Global-scale characterization of streamflow extremes S. Kuntla et al. 10.1016/j.jhydrol.2022.128668
18. Explore Spatio‐Temporal Learning of Large Sample Hydrology Using Graph Neural Networks A. Sun et al. 10.1029/2021WR030394
19. How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions A. Sun & B. Scanlon 10.1088/1748-9326/ab1b7d
20. Opportunities and challenges in using catchment-scale storage estimates from cosmic ray neutron sensors for rainfall-runoff modelling K. Dimitrova-Petrova et al. 10.1016/j.jhydrol.2020.124878
21. Advancing river monitoring using image-based techniques: challenges and opportunities S. Manfreda et al. 10.1080/02626667.2024.2333846
22. Real time forecasting in the coastal zone: Stream power in the lower Mississippi River L. Manuel et al. 10.1016/j.ejrh.2024.102088
23. Combining static and portable Cosmic ray neutron sensor data to assess catchment scale heterogeneity in soil water storage and their integrated role in catchment runoff response K. Dimitrova-Petrova et al. 10.1016/j.jhydrol.2021.126659
24. Long-term Hydrometeorological Time-series Analysis over the Central Highland of West Papua S. Herho et al. 10.18517/ijods.4.2.84-96.2023
25. Hydrological Spaces of Long‐Term Catchment Water Balance E. Daly et al. 10.1029/2019WR025952
26. Emergent Scaling of Dissolved Oxygen (DO) in Freshwater Streams Across Contiguous USA O. Abdul‐Aziz & A. Gebreslase 10.1029/2022WR032114
27. First-Principles Study Combined with Interpretable Machine-Learning Models of Bayesian Optimization for the Design of Ultrawide Bandgap Double Perovskites H. Shen et al. 10.1021/acs.jpcc.3c05255
28. Temporal Scaling of Streamflow Elasticity to Precipitation: A Global Analysis Y. Zhang et al. 10.1029/2021WR030601
29. Emerging technologies and radical collaboration to advance predictive understanding of watershed hydrobiogeochemistry S. Hubbard et al. 10.1002/hyp.13807
30. Evaluating seasonal hydrological extremes in mesoscale (pre-)Alpine basins at coarse 0.5° and fine hyperresolution J. Buitink et al. 10.5194/hess-23-1593-2019
31. Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets F. Kratzert et al. 10.5194/hess-23-5089-2019
32. What Role Does Hydrological Science Play in the Age of Machine Learning? G. Nearing et al. 10.1029/2020WR028091
33. Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions H. Wainwright et al. 10.5194/hess-26-429-2022
34. From engineering hydrology to Earth system science: milestones in the transformation of hydrologic science M. Sivapalan 10.5194/hess-22-1665-2018
35. Interplays between State and Flux Hydrological Variables across Vadose Zones: A Numerical Investigation Z. Wang et al. 10.3390/w11061295
36. A combined optimization prediction model for earth-rock dam seepage pressure using multi-machine learning fusion with decomposition data-driven B. Liu et al. 10.1016/j.eswa.2023.122798
37. Accuracy assessment of late winter snow depth mapping for tundra environments using Structure-from-Motion photogrammetry B. Walker et al. 10.1139/as-2020-0006
38. Comprehensive assessment of the water environment carrying capacity based on machine learning H. Zhang et al. 10.1016/j.jclepro.2024.143465
39. Toward seamless hydrologic predictions across spatial scales L. Samaniego et al. 10.5194/hess-21-4323-2017
40. Fully distributed versus semi-distributed process simulation of a highly managed watershed with mixed land use and irrigation return flow A. Veettil et al. 10.1016/j.envsoft.2021.105000
41. Norms and values in sociohydrological models M. Roobavannan et al. 10.5194/hess-22-1337-2018
42. Hydrologic similarity based on width function and hypsometry: An unsupervised learning approach P. Bajracharya & S. Jain 10.1016/j.cageo.2022.105097
43. Arc Hydro Hillslope and Critical Duration: New tools for hillslope-scale runoff analysis D. Lapides et al. 10.1016/j.envsoft.2022.105408
44. Initiatives to clarify mechanisms of hydrological evolution in human-influenced Yellow River Basin L. Ren et al. 10.1016/j.wse.2023.01.001
45. Assimilation of NASA's Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF‐Hydro System T. Lahmers et al. 10.1029/2021WR029867
46. The role of topography, soil, and remotely sensed vegetation condition towards predicting crop yield T. Franz et al. 10.1016/j.fcr.2020.107788
47. HydroCAL: A novel integrated surface–subsurface hydrological model based on the Cellular Automata paradigm L. Furnari et al. 10.1016/j.advwatres.2024.104623
48. Cosmic‐ray Neutron Rover Surveys of Field Soil Moisture and the Influence of Roads M. Schrön et al. 10.1029/2017WR021719
49. Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa M. Dembélé et al. 10.5194/hess-24-5379-2020
50. An Information Theory Approach to Identifying a Representative Subset of Hydro‐Climatic Simulations for Impact Modeling Studies I. Pechlivanidis et al. 10.1029/2017WR022035
51. Big data and the fourth paradigm S. Granshaw 10.1111/phor.12255
52. Multi-Spatial Resolution Rainfall-Runoff Modelling—A Case Study of Sabari River Basin, India V. Sharma & S. Regonda 10.3390/w13091224
53. The future of Earth observation in hydrology M. McCabe et al. 10.5194/hess-21-3879-2017
54. Preface: Linking landscape organisation and hydrological functioning: from hypotheses and observations to concepts, models and understanding C. Jackisch et al. 10.5194/hess-25-5277-2021
55. Investigating snowpack across scale in the northern Great Lakes–St. Lawrence forest region of Central Ontario, Canada A. Beaton et al. 10.1002/hyp.13558
56. Is ET often oversimplified in hydrologic models? Using long records to elucidate unaccounted for controls on ET C. Kelleher & S. Shaw 10.1016/j.jhydrol.2017.12.018
57. Discretization approach for large-scale sediment modeling: calibration strategies based on hydro-sediment variability at a range of spatial scales R. Rossoni & F. Fan 10.1590/2318-0331.282320220088
58. Saltwater intrusion into coastal aquifers in the contiguous United States — A systematic review of investigation approaches and monitoring networks J. Panthi et al. 10.1016/j.scitotenv.2022.155641
59. Asynchronous cellular automata subsurface flow simulations in two- and three-dimensional heterogeneous soils L. Furnari et al. 10.1016/j.advwatres.2021.103952
60. Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies M. Dembélé et al. 10.1016/j.advwatres.2020.103667
61. Quantifying dual recharge mechanisms in deep unsaturated zone of Chinese Loess Plateau using stable isotopes W. Xiang et al. 10.1016/j.geoderma.2018.10.006
62. Coupled effects of observation and parameter uncertainty on urban groundwater infrastructure decisions M. Mautner et al. 10.5194/hess-26-1319-2022
63. Clustering of causal graphs to explore drivers of river discharge W. Günther et al. 10.1017/eds.2023.17
64. An Alternative Approach for Improving Prediction of Integrated Hydrologic‐Hydraulic Models by Assessing the Impact of Intrinsic Spatial Scales S. Saksena et al. 10.1029/2020WR027702
65. Continental Hydrologic Intercomparison Project, Phase 1: A Large‐Scale Hydrologic Model Comparison Over the Continental United States D. Tijerina‐Kreuzer et al. 10.1029/2020WR028931
66. The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism M. Clark et al. 10.5194/hess-21-3427-2017