79 citations as recorded by crossref.

1. Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparameter Tuning, SHAP Analysis, Partial Dependency, and LIME M. Islam et al. https://doi.org/10.1002/eng2.13080
2. A review on statistical postprocessing methods for hydrometeorological ensemble forecasting W. Li et al. https://doi.org/10.1002/wat2.1246
3. Joint modeling of precipitation and temperature under influences of El Niño Southern Oscillation for compound event evaluation and prediction Z. Hao et al. https://doi.org/10.1016/j.atmosres.2020.105090
4. Postprocessing of Medium Range Hydrological Ensemble Forecasts Making Use of Reforecasts J. Van den Bergh & E. Roulin https://doi.org/10.3390/hydrology3020021
5. A latent space method with maximum entropy deep reinforcement learning for data assimilation J. Zhang et al. https://doi.org/10.1016/j.geoen.2024.213275
6. Deep hierarchical distillation proxy-oil modeling for heterogeneous carbonate reservoirs G. Cirac et al. https://doi.org/10.1016/j.engappai.2023.107076
7. Homogenisation of a gridded snow water equivalent climatology for Alpine terrain: methodology and applications S. Jörg-Hess et al. https://doi.org/10.5194/tc-8-471-2014
8. Characterization of drought propagation over the Tibetan Plateau D. Wu & Z. Hu https://doi.org/10.1016/j.ejrh.2024.102035
9. Error-correction across gauged and ungauged locations: A data assimilation-inspired approach to post-processing river discharge forecasts G. Matthews et al. https://doi.org/10.5194/hess-29-6157-2025
10. Hypoxia weakens mussel attachment by interrupting DOPA cross-linking during adhesive plaque curing M. George et al. https://doi.org/10.1098/rsif.2018.0489
11. Upper and Lower Bound Interval Forecasting Methodology Based on Ideal Boundary and Multiple Linear Regression Models W. Li et al. https://doi.org/10.1007/s11269-018-2177-0
12. Increasing impact of compound agricultural drought and hot events on maize yield in China X. Wu et al. https://doi.org/10.3354/cr01715
13. The benefit of climatological and calibrated reforecast data for simulating hydrological droughts in Switzerland S. Jörg-Hess et al. https://doi.org/10.1002/met.1474
14. Understanding the Propagation of Meteorological Drought to Groundwater Drought: A Case Study of the North China Plain Y. Chen et al. https://doi.org/10.3390/w16030501
15. Data-driven lumped plasticity hysteresis model for predicting the cyclic response of rectangular reinforced concrete columns M. Phoeuk & M. Kwon https://doi.org/10.1016/j.istruc.2026.112452
16. Spatiotemporal variation and propagation process of snow drought over the Tibetan Plateau D. Wu & Z. Hu https://doi.org/10.1016/j.atmosres.2025.108623
17. On the implementation of post-processing of runoff forecast ensembles J. Skøien et al. https://doi.org/10.1175/JHM-D-21-0008.1
18. A five-parameter Gamma-Gaussian model to calibrate monthly and seasonal GCM precipitation forecasts Z. Huang et al. https://doi.org/10.1016/j.jhydrol.2021.126893
19. An ensemble approach of data transformation for bug prediction based on uncertainty K. Rani et al. https://doi.org/10.1007/s13198-025-03106-7
20. Alternative configurations of quantile regression for estimating predictive uncertainty in water level forecasts for the upper Severn River: a comparison P. López López et al. https://doi.org/10.5194/hess-18-3411-2014
21. Differences in effects of varying compound extreme temperature and precipitation events on summer maize yield in North China Z. Liu et al. https://doi.org/10.1016/j.agwat.2024.109237
22. Hydrological uncertainty processor based on a copula function Z. Liu et al. https://doi.org/10.1080/02626667.2017.1410278
23. The monetary benefit of early flood warnings in Europe F. Pappenberger et al. https://doi.org/10.1016/j.envsci.2015.04.016
24. Probabilistic Assessment of the Impact of Compound Dry and Hot Events on Vegetation Drought Over Northwestern China J. Lu et al. https://doi.org/10.1002/eco.70008
25. Quantifying likelihoods of extreme occurrences causing maize yield reduction at the global scale S. Feng & Z. Hao https://doi.org/10.1016/j.scitotenv.2019.135250
26. Review of dependence modeling in hydrology and water resources Z. Hao & V. Singh https://doi.org/10.1177/0309133316632460
27. Probabilistic evaluation of the impact of compound dry-hot events on global maize yields S. Feng et al. https://doi.org/10.1016/j.scitotenv.2019.06.373
28. Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system S. Sharma et al. https://doi.org/10.5194/hess-22-1831-2018
29. Quantile-Based Hydrological Modelling H. Tyralis & G. Papacharalampous https://doi.org/10.3390/w13233420
30. Short-term ensemble streamflow forecasting using operationally-produced single-valued streamflow forecasts – A Hydrologic Model Output Statistics (HMOS) approach S. Regonda et al. https://doi.org/10.1016/j.jhydrol.2013.05.028
31. Monitoring shrimp growth with control charts in aquaculture I. Sánchez & I. González https://doi.org/10.1016/j.aquaeng.2021.102180
32. Impact of Distribution Type in Bayes Probability Flood Forecasting W. Li et al. https://doi.org/10.1007/s11269-016-1557-6
33. A seven-parameter Bernoulli-Gamma-Gaussian model to calibrate subseasonal to seasonal precipitation forecasts Z. Huang et al. https://doi.org/10.1016/j.jhydrol.2022.127896
34. IMAGE: a multivariate multi-site stochastic weather generator for European weather and climate N. Sparks et al. https://doi.org/10.1007/s00477-017-1433-9
35. Impacts of hot-dry conditions on hydropower production in Switzerland N. Otero et al. https://doi.org/10.1088/1748-9326/acd8d7
36. Generating Coherent Ensemble Forecasts After Hydrological Postprocessing: Adaptations of ECC‐Based Methods J. Bellier et al. https://doi.org/10.1029/2018WR022601
37. Risk of simultaneous food shocks to cities increases with supply chain vulnerability to droughts M. Gomez & A. Mejia https://doi.org/10.1088/2976-601X/adb752
38. Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas M. Rogelis & M. Werner https://doi.org/10.5194/hess-22-853-2018
39. Probabilistic Precipitation Estimation with a Satellite Product N. Krakauer et al. https://doi.org/10.3390/cli3020329
40. Comparing Approaches to Deal With Non‐Gaussianity of Rainfall Data in Kriging‐Based Radar‐Gauge Rainfall Merging F. Cecinati et al. https://doi.org/10.1002/2016WR020330
41. Seasonal Forecasting of the Onset of the Rainy Season in West Africa M. Rauch et al. https://doi.org/10.3390/atmos10090528
42. Reliability of Ensemble Climatological Forecasts Z. Huang et al. https://doi.org/10.1029/2023WR034942
43. Evaluating the impact of post-processing medium-range ensemble streamflow forecasts from the European Flood Awareness System G. Matthews et al. https://doi.org/10.5194/hess-26-2939-2022
44. Hydrological post-processing using stacked generalization of quantile regression algorithms: Large-scale application over CONUS H. Tyralis et al. https://doi.org/10.1016/j.jhydrol.2019.123957
45. Subgrouping with Chain Graphical VAR Models J. Park et al. https://doi.org/10.1080/00273171.2023.2289058
46. Ensemble-based forecasting of wildfire potentials using relative index in Gangwon Province, South Korea S. Kim et al. https://doi.org/10.1016/j.ecoinf.2025.103021
47. Intraday probabilistic forecasts of surface solar radiation with cloud scale-dependent autoregressive advection A. Carpentieri et al. https://doi.org/10.1016/j.apenergy.2023.121775
48. Statistical Modeling and Prediction for Tourism Economy Using Dendritic Neural Network Y. Yu et al. https://doi.org/10.1155/2017/7436948
49. Assessment of NO3−, As, and F− background levels in groundwater bodies: A methodological review and case study utilizing sequential Gaussian simulation (SGS) G. Busico et al. https://doi.org/10.1016/j.gsd.2024.101211
50. An investigation of emotion dynamics in major depressive disorder patients and healthy persons using sparse longitudinal networks S. de Vos et al. https://doi.org/10.1371/journal.pone.0178586
51. Increasing compound drought and hot event over the Tibetan Plateau and its effects on soil water D. Wu & Z. Hu https://doi.org/10.1016/j.ecolind.2023.110413
52. Post-Processing of Stream Flows in Switzerland with an Emphasis on Low Flows and Floods K. Bogner et al. https://doi.org/10.3390/w8040115
53. Evaluation and attribution of trends in compound dry-hot events for major river basins in China S. Xiong et al. https://doi.org/10.1007/s11430-022-1174-7
54. A Novel Quantile‐Transformed Exponential Distribution With Applications in Reliability and Survival Analyses T. Abebe & S. Sen https://doi.org/10.1155/jpas/7423778
55. Altman Z-Score Modeling and Financial Risk analysis: An Empirical Study on Companies Listed on the Bucharest Stock Exchange C. Spulbar et al. https://doi.org/10.2478/sbe-2025-0037
56. Emulator-enabled approximate Bayesian computation (ABC) and uncertainty analysis for computationally expensive groundwater models T. Cui et al. https://doi.org/10.1016/j.jhydrol.2018.07.005
57. From HUP to MCP: Analogies and extended performances E. Todini https://doi.org/10.1016/j.jhydrol.2012.10.037
58. Two Majority Voting Classifiers Applied to Heart Disease Prediction T. Karadeniz et al. https://doi.org/10.3390/app13063767
59. HESS Opinions "Forecaster priorities for improving probabilistic flood forecasts" F. Wetterhall et al. https://doi.org/10.5194/hess-17-4389-2013
60. Changes in climate-crop yield relationships affect risks of crop yield reduction S. Feng et al. https://doi.org/10.1016/j.agrformet.2021.108401
61. Predictive Uncertainty Estimation of Hydrological Multi-Model Ensembles Using Pair-Copula Construction B. Klein et al. https://doi.org/10.3390/w8040125
62. Comparative Study of Three Updating Procedures for Real-Time Flood Forecasting Z. Liu et al. https://doi.org/10.1007/s11269-016-1275-0
63. An agricultural drought early warning threshold model with considering copula combined with diminishing marginal benefit theory: A case study in the Yellow River basin T. Qian et al. https://doi.org/10.1016/j.agwat.2025.109582
64. Comparison of Different Configurations of Quantile Regression in Estimating Predictive Hydrological Uncertainty M. Muthusamy et al. https://doi.org/10.1016/j.proeng.2016.07.546
65. Water clarity affects collective behavior in two cyprinid fishes S. Michael et al. https://doi.org/10.1007/s00265-021-03060-x
66. Performance and robustness of probabilistic river forecasts computed with quantile regression based on multiple independent variables F. Hoss & P. Fischbeck https://doi.org/10.5194/hess-19-3969-2015
67. Effect of slope gradient on drought propagation in different climate zones and under different climate-change backgrounds D. Wu & Z. Hu https://doi.org/10.1080/19475705.2025.2579749
68. A crash-testing framework for predictive uncertainty assessment when forecasting high flows in an extrapolation context L. Berthet et al. https://doi.org/10.5194/hess-24-2017-2020
69. Compound dry and hot events over major river basins of the world from 1921 to 2020 T. Zhao et al. https://doi.org/10.1016/j.wace.2024.100679
70. Long term prediction of flood occurrence C. Aguilar et al. https://doi.org/10.5194/piahs-373-189-2016
71. Real-time updating of the flood frequency distribution through data assimilation C. Aguilar et al. https://doi.org/10.5194/hess-21-3687-2017
72. Toward a seasonal precipitation prediction system for West Africa: Performance of CFSv2 and high‐resolution dynamical downscaling J. Siegmund et al. https://doi.org/10.1002/2014JD022692
73. Severity-Aware Drift Adaptation for Cost-Efficient Model Maintenance K. Shakhovska & P. Pukach https://doi.org/10.3390/ai6110279
74. A theoretical drought classification method for the multivariate drought index based on distribution properties of standardized drought indices Z. Hao et al. https://doi.org/10.1016/j.advwatres.2016.04.010
75. Geostatistical upscaling of rain gauge data to support uncertainty analysis of lumped urban hydrological models M. Muthusamy et al. https://doi.org/10.5194/hess-21-1077-2017
76. Geostatistical analysis and hydrofacies simulation for estimating the spatial variability of hydraulic conductivity in the Jianghan Plain, central China P. Xue et al. https://doi.org/10.1007/s10040-022-02495-4
77. Technical note: comparison of methods for threshold selection for extreme sea levels C. Caballero‐Megido et al. https://doi.org/10.1111/jfr3.12296
78. Can Machine Learning classifiers be used to regulate nutrients using small training datasets for aquaponic irrigation?: A comparative analysis S. Dhal et al. https://doi.org/10.1371/journal.pone.0269401
79. Historical agricultural drought patterns and drought-related factors over western China D. Wu et al. https://doi.org/10.1080/02626667.2023.2197116