98 citations as recorded by crossref.

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5. Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C A. Marx et al. https://doi.org/10.5194/hess-22-1017-2018
6. QUADICA: water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany P. Ebeling et al. https://doi.org/10.5194/essd-14-3715-2022
7. Testing the mHM-MPR Reliability for Parameter Transferability across Locations in North–Central Nigeria K. Ogbu et al. https://doi.org/10.3390/hydrology9090158
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10. Reconstructed soil moisture droughts in Belgium reveal 2011–2020 was the driest decade since 1970 K. Lekarkar et al. https://doi.org/10.5194/hess-30-2817-2026
11. Parameter's Controls of Distributed Catchment Models—How Much Information is in Conventional Catchment Descriptors? R. Merz et al. https://doi.org/10.1029/2019WR026008
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18. QUADICA v2: extending the large-sample data set for water QUAlity, DIscharge and Catchment Attributes in Germany P. Ebeling et al. https://doi.org/10.5194/essd-18-691-2026
19. The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model A. Borriero et al. https://doi.org/10.1002/hyp.15154
20. From Dynamic Groundwater Level Measurements to Regional Aquifer Parameters— Assessing the Power of Spectral Analysis T. Houben et al. https://doi.org/10.1029/2021WR031289
21. Spatial Patterns of Water Age: Using Young Water Fractions to Improve the Characterization of Transit Times in Contrasting Catchments S. Lutz et al. https://doi.org/10.1029/2017WR022216
22. Improved regional-scale groundwater representation by the coupling of the mesoscale Hydrologic Model (mHM v5.7) to the groundwater model OpenGeoSys (OGS) M. Jing et al. https://doi.org/10.5194/gmd-11-1989-2018
23. Global Fully Distributed Parameter Regionalization Based on Observed Streamflow From 4,229 Headwater Catchments H. Beck et al. https://doi.org/10.1029/2019JD031485
24. Machine-learning methods to assess the effects of a non-linear damage spectrum taking into account soil moisture on winter wheat yields in Germany M. Peichl et al. https://doi.org/10.5194/hess-25-6523-2021
25. Disentangling scatter in long-term concentration–discharge relationships: the role of event types F. Saavedra et al. https://doi.org/10.5194/hess-26-6227-2022
26. Scalability and Computational Performance of an Ecohydrological Model Using Machine Learning-Based Prediction N. Cortés-Torres et al. https://doi.org/10.3390/w18040466
27. A New Fully Distributed Model of Nitrate Transport and Removal at Catchment Scale X. Yang et al. https://doi.org/10.1029/2017WR022380
28. Hortonian Scaling of Coupled Hydrological and Biogeochemical Responses Across an Intensively Managed River Basin S. Yang et al. https://doi.org/10.3389/frwa.2021.693056
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35. Event and Catchment Controls of Heavy Tail Behavior of Floods E. Macdonald et al. https://doi.org/10.1029/2021WR031260
36. Uncertainty in water transit time estimation with StorAge Selection functions and tracer data interpolation A. Borriero et al. https://doi.org/10.5194/hess-27-2989-2023
37. Multi-model hydrological reference dataset over continental Europe and an African basin B. Droppers et al. https://doi.org/10.1038/s41597-024-03825-9
38. The impact of soil initialization on regional decadal climate predictions in Europe M. Breil et al. https://doi.org/10.3354/cr01548
39. Potential of Pan-European Seasonal Hydrometeorological Drought Forecasts Obtained from a Multihazard Early Warning System S. Sutanto et al. https://doi.org/10.1175/BAMS-D-18-0196.1
40. Conditioning a Hydrologic Model Using Patterns of Remotely Sensed Land Surface Temperature M. Zink et al. https://doi.org/10.1002/2017WR021346
41. Re-designing organic grain legume cropping systems using systems agronomy M. Reckling et al. https://doi.org/10.1016/j.eja.2019.125951
42. Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges N. Addor et al. https://doi.org/10.1080/02626667.2019.1683182
43. Damped groundwater response to recharge: From spectral analysis to regional modeling M. Tsypin et al. https://doi.org/10.1016/j.jhydrol.2025.133193
44. MPR 1.0: a stand-alone multiscale parameter regionalization tool for improved parameter estimation of land surface models R. Schweppe et al. https://doi.org/10.5194/gmd-15-859-2022
45. Increased high flows in Germany under 1.5 K, 2.0 K and 3.0 K warming based on a large regional climate model ensemble A. Chandrasekar et al. https://doi.org/10.1007/s10584-026-04165-w
46. Disentangling the Impact of Catchment Heterogeneity on Nitrate Export Dynamics From Event to Long‐Term Time Scales C. Winter et al. https://doi.org/10.1029/2020WR027992
47. A drought monitoring tool for South Asia T. Saha et al. https://doi.org/10.1088/1748-9326/abf525
48. The multiscale routing model mRM v1.0: simple river routing at resolutions from 1 to 50 km S. Thober et al. https://doi.org/10.5194/gmd-12-2501-2019
49. Seasonal forecasting of local-scale soil moisture droughts with Global BROOK90: a case study of the European drought of 2018 I. Vorobevskii et al. https://doi.org/10.5194/nhess-24-681-2024
50. Explaining the Variability in High‐Frequency Nitrate Export Patterns Using Long‐Term Hydrological Event Classification C. Winter et al. https://doi.org/10.1029/2021WR030938
51. Pseudo-Spatially-Distributed Modeling of Water Balance Components in the Free State of Saxony T. Luong et al. https://doi.org/10.3390/hydrology7040084
52. Construction of a daily streamflow dataset for Peru using a similarity-based regionalization approach and a hybrid hydrological modeling framework H. Llauca et al. https://doi.org/10.1016/j.ejrh.2023.101381
53. Reducing hydrological disturbances in absolute gravity observations by combining global hydrological models with a regional run-off model B. Bramanto et al. https://doi.org/10.1093/gji/ggac054
54. Drought Reduces Release of Plant Matter Into Dissolved Organic Matter Potentially Restraining Ecosystem Recovery A. Orme et al. https://doi.org/10.3389/fsoil.2022.904259
55. Characterizing Catchment‐Scale Nitrogen Legacies and Constraining Their Uncertainties F. Sarrazin et al. https://doi.org/10.1029/2021WR031587
56. Towards the construction of representative regional hydro(geo)logical numerical models: Modelling the upper Danube basin as a starting point E. Pujades et al. https://doi.org/10.3389/feart.2023.1061420
57. Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model E. Fatima et al. https://doi.org/10.5194/hess-28-5419-2024
58. Assessing the contribution of groundwater to catchment travel time distributions through integrating conceptual flux tracking with explicit Lagrangian particle tracking M. Jing et al. https://doi.org/10.1016/j.advwatres.2021.103849
59. Transformation of Generation Processes From Small Runoff Events to Large Floods L. Tarasova et al. https://doi.org/10.1029/2020GL090547
60. Exploring Controls on Rainfall‐Runoff Events: 2. Regional Patterns and Spatial Controls of Event Characteristics in Germany L. Tarasova et al. https://doi.org/10.1029/2018WR022588
61. Influence of input and parameter uncertainty on the prediction of catchment-scale groundwater travel time distributions M. Jing et al. https://doi.org/10.5194/hess-23-171-2019
62. Drought propagation and ecosystem resilience in a peri-urban catchment of Berlin-Brandenburg P. Franke et al. https://doi.org/10.5194/nhess-26-3617-2026
63. A Process‐Based Framework to Characterize and Classify Runoff Events: The Event Typology of Germany L. Tarasova et al. https://doi.org/10.1029/2019WR026951
64. Developing a digital mapping of soil organic carbon on a national scale using Sentinel-2 and hybrid models at varying spatial resolutions X. Ji et al. https://doi.org/10.1016/j.ecolind.2024.112654
65. High-resolution drought simulations and comparison to soil moisture observations in Germany F. Boeing et al. https://doi.org/10.5194/hess-26-5137-2022
66. Can the young water fraction reduce predictive uncertainty in water transit time estimations? A. Borriero et al. https://doi.org/10.1016/j.jhydrol.2024.132238
67. Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing I. Vorobevskii et al. https://doi.org/10.5194/hess-26-3177-2022
68. Extreme flooding controlled by stream network organization and flow regime S. Basso et al. https://doi.org/10.1038/s41561-023-01155-w
69. Spectral analysis of groundwater level time series for robust estimation of aquifer response times T. Houben et al. https://doi.org/10.5194/hess-30-5685-2026
70. Towards seamless large‐domain parameter estimation for hydrologic models N. Mizukami et al. https://doi.org/10.1002/2017WR020401
71. Revisiting parameter sensitivities in the variable infiltration capacity model across a hydroclimatic gradient U. Sepúlveda et al. https://doi.org/10.5194/hess-26-3419-2022
72. Spatial patterns of water quality impairments from point source nutrient loads in Germany's largest national River Basin (Weser River) S. Yang et al. https://doi.org/10.1016/j.scitotenv.2019.134145
73. Multiple stressor effects on biological quality elements in the Ebro River: Present diagnosis and predicted responses A. Herrero et al. https://doi.org/10.1016/j.scitotenv.2018.02.032
74. Droughts can reduce the nitrogen retention capacity of catchments C. Winter et al. https://doi.org/10.5194/hess-27-303-2023
75. Modelling temporal variability of in situ soil water and vegetation isotopes reveals ecohydrological couplings in a riparian willow plot A. Smith et al. https://doi.org/10.5194/bg-19-2465-2022
76. Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales G. Baroni et al. https://doi.org/10.5194/hess-21-2301-2017
77. Groundwater head responses to droughts across Germany P. Ebeling et al. https://doi.org/10.5194/hess-29-2925-2025
78. Projecting impacts of extreme weather events on crop yields using LASSO regression J. Heilemann et al. https://doi.org/10.1016/j.wace.2024.100738
79. Elevation-dependent compensation effects in snowmelt in the Rhine River Basin upstream gauge Basel E. Rottler et al. https://doi.org/10.2166/nh.2021.092
80. Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest B. Bahrami et al. https://doi.org/10.5194/gmd-15-6957-2022
81. Regionalisierung hydrologischer Modelle mit Function Space Optimization M. Feigl et al. https://doi.org/10.1007/s00506-021-00766-0
82. Nutrient loading and stream order shape benthic and pelagic spring algal biomass in a large, temperate river basin (Elbe River) N. Heinemann et al. https://doi.org/10.1016/j.jenvman.2025.125440
83. Climate impacts on long-term silage maize yield in Germany M. Peichl et al. https://doi.org/10.1038/s41598-019-44126-1
84. Disparate Seasonal Nitrate Export From Nested Heterogeneous Subcatchments Revealed With StorAge Selection Functions T. Nguyen et al. https://doi.org/10.1029/2021WR030797
85. Assessing the response of groundwater quantity and travel time distribution to 1.5, 2, and 3 °C global warming in a mesoscale central German basin M. Jing et al. https://doi.org/10.5194/hess-24-1511-2020
86. Comparing recent and buried Chernozems/Phaeozems in Central Germany: Soil transformation and human impact since 3.8 ka H. von Suchodoletz et al. https://doi.org/10.1016/j.catena.2025.109270
87. Computationally Efficient Multivariate Calibration and Validation of a Grid-Based Hydrologic Model in Sparsely Gauged West African River Basins T. Poméon et al. https://doi.org/10.3390/w10101418
88. Emergent spatial patterns of competing benthic and pelagic algae in a river network: A parsimonious basin-scale modeling analysis S. Yang et al. https://doi.org/10.1016/j.watres.2021.116887
89. Automatic Regionalization of Model Parameters for Hydrological Models M. Feigl et al. https://doi.org/10.1029/2022WR031966
90. The development and persistence of soil moisture stress during drought across southwestern Germany E. Tijdeman & L. Menzel https://doi.org/10.5194/hess-25-2009-2021
91. Emergence of heavy tails in streamflow distributions: the role of spatial rainfall variability H. Wang et al. https://doi.org/10.1016/j.advwatres.2022.104359
92. Challenges in Applying Machine Learning Models for Hydrological Inference: A Case Study for Flooding Events Across Germany L. Schmidt et al. https://doi.org/10.1029/2019WR025924
93. How well do process-based and data-driven hydrological models learn from limited discharge data? M. Staudinger et al. https://doi.org/10.5194/hess-29-5005-2025
94. Inferring Grassland Drought Stress with Unsupervised Learning from Airborne Hyperspectral VNIR Imagery F. Hermanns et al. https://doi.org/10.3390/rs13101885
95. High-resolution impact-based early warning system for riverine flooding H. Najafi et al. https://doi.org/10.1038/s41467-024-48065-y
96. Spatial Organization of Human Population and Wastewater Treatment Plants in Urbanized River Basins S. Yang et al. https://doi.org/10.1029/2018WR024614
97. Assessment of groundwater recharge for a coarse-gravel porous aquifer in Slovenia V. Zupanc et al. https://doi.org/10.1007/s10040-020-02152-8
98. The effect of soil moisture anomalies on maize yield in Germany M. Peichl et al. https://doi.org/10.5194/nhess-18-889-2018