158 citations as recorded by crossref.

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49. A retrospective streamflow ensemble forecast for an extreme hydrologic event: a case study of Hurricane Irene and on the Hudson River basin F. Saleh et al. https://doi.org/10.5194/hess-20-2649-2016
50. Monthly‐, medium‐, and short‐range flood warning: testing the limits of predictability J. Thielen et al. https://doi.org/10.1002/met.140
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55. Potentialities of ensemble strategies for flood forecasting over the Milano urban area G. Ravazzani et al. https://doi.org/10.1016/j.jhydrol.2016.05.023
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58. Superposition of three sources of uncertainties in operational flood forecasting chains M. Zappa et al. https://doi.org/10.1016/j.atmosres.2010.12.005
59. The European Flood Alert System and the communication, perception, and use of ensemble predictions for operational flood risk management D. Demeritt et al. https://doi.org/10.1002/hyp.9419
60. Assessing the role of uncertain precipitation estimates on the robustness of hydrological model parameters under highly variable climate conditions B. Bisselink et al. https://doi.org/10.1016/j.ejrh.2016.09.003
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75. Probabilistic flood forecasting on the Rhone River: evaluation with ensemble and analogue-based precipitation forecasts J. Bellier et al. https://doi.org/10.1051/e3sconf/20160718011
76. Potential skill of continental-scale, medium-range ensemble streamflow forecasts for flood prediction in South America V. Siqueira et al. https://doi.org/10.1016/j.jhydrol.2020.125430
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79. Flooding time nomograph for urban river flood prediction: Case study of Dorim stream basin, Seoul H. Moon et al. https://doi.org/10.1111/jfr3.12887
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82. Why hydrological predictions should be evaluated using information theory S. Weijs et al. https://doi.org/10.5194/hess-14-2545-2010
83. Evaluation of quantitative precipitation forecasts by TIGGE ensembles for south China during the presummer rainy season L. Huang & Y. Luo https://doi.org/10.1002/2017JD026512
84. Evaluating uncertainty estimates in hydrologic models: borrowing measures from the forecast verification community K. Franz & T. Hogue https://doi.org/10.5194/hess-15-3367-2011
85. The benefit of seamless forecasts for hydrological predictions over Europe F. Wetterhall & F. Di Giuseppe https://doi.org/10.5194/hess-22-3409-2018
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115. The potential of radar-based ensemble forecasts for flash-flood early warning in the southern Swiss Alps K. Liechti et al. https://doi.org/10.5194/hess-17-3853-2013
116. The reduction continuous rank probability score for evaluating discharge forecasts from hydrological ensemble prediction systems B. Trinh et al. https://doi.org/10.1002/asl2.417
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118. CREST-VEC: a framework towards more accurate and realistic flood simulation across scales Z. Li et al. https://doi.org/10.5194/gmd-15-6181-2022
119. Operational early warning systems for water-related hazards in Europe L. Alfieri et al. https://doi.org/10.1016/j.envsci.2012.01.008
120. Evaluation of two hydrometeorological ensemble strategies for flash-flood forecasting over a catchment of the eastern Pyrenees H. Roux et al. https://doi.org/10.5194/nhess-20-425-2020
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122. Investigations of Multi-Platform Data for Developing an Integrated Flood Information System in the Kalu River Basin, Sri Lanka M. Rasmy et al. https://doi.org/10.3390/w15061199
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125. Dam Flood Control Operation Based on Ensemble Rainfall Forecast H. INOMATA et al. https://doi.org/10.3178/jjshwr.34.24
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127. An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios N. Addor et al. https://doi.org/10.5194/hess-15-2327-2011
128. Evaluating the Forecast Skill of a Hydrometeorological Modelling System in Greece G. Varlas et al. https://doi.org/10.3390/atmos12070902
129. Investigation of Atmospheric Circulation Regimes for Wildfire, Flood and Rainfall Extremes in Greece S. Karozis et al. https://doi.org/10.3390/geohazards7020074
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133. Verification of two hydrological models for real-time flood forecasting in the Hindu Kush Himalaya (HKH) region K. Tsering et al. https://doi.org/10.1007/s11069-021-05014-y
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137. Statistical processing of forecasts for hydrological ensemble prediction: a comparative study of different bias correction strategies I. Zalachori et al. https://doi.org/10.5194/asr-8-135-2012
138. Performance Evaluation of Numerical Weather Prediction Models in Forecasting Rainfall Events in Kerala, India V. Nitha et al. https://doi.org/10.3390/atmos16040372
139. Analog‐Based Postprocessing of Navigation‐Related Hydrological Ensemble Forecasts S. Hemri & B. Klein https://doi.org/10.1002/2017WR020684
140. Technical note: Comparing three different methods for allocating river points to coarse-resolution hydrological modelling grid cells J. Godet et al. https://doi.org/10.5194/hess-28-1403-2024
141. Real-time bias correction of rainfall nowcasts using biward tracking method W. Na & C. Yoo https://doi.org/10.1016/j.jhydrol.2023.129642
142. Skill of a global forecasting system in seasonal ensemble streamflow prediction N. Candogan Yossef et al. https://doi.org/10.5194/hess-21-4103-2017
143. Epistemic uncertainties and natural hazard risk assessment – Part 1: A review of different natural hazard areas K. Beven et al. https://doi.org/10.5194/nhess-18-2741-2018
144. Skill assessment of a seasonal forecast model to predict drought events for water resource systems J. Madrigal et al. https://doi.org/10.1016/j.jhydrol.2018.07.046
145. Importance of Two-way Communication with Users for Effective Utilization of Ensemble Flood Forecast Information M. WATANABE et al. https://doi.org/10.3178/jjshwr.35.104
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147. Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors B. Revilla-Romero et al. https://doi.org/10.5194/hess-18-4467-2014
148. The monetary benefit of early flood warnings in Europe F. Pappenberger et al. https://doi.org/10.1016/j.envsci.2015.04.016
149. Estimating the snowfall limit in alpine and pre-alpine valleys: A local evaluation of operational approaches M. Fehlmann et al. https://doi.org/10.1016/j.atmosres.2018.01.016
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152. Evaluating flood potential with GRACE in the United States T. Molodtsova et al. https://doi.org/10.5194/nhess-16-1011-2016
153. The New York City Operations Support Tool (OST): Managing Water for Millions of People in an Era of Changing Climate and Extreme Hydrological Events J. Porter et al. https://doi.org/10.1142/S2345737615500086
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156. Extreme floods in Europe: going beyond observations using reforecast ensemble pooling M. Brunner & L. Slater https://doi.org/10.5194/hess-26-469-2022
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158. Improving GEOGLOWS streamflow simulations using a hybrid GEOGLOWS–long short-term memory framework: Application to data-scarce catchments in Malawi P. Kumambala et al. https://doi.org/10.1016/j.jafrearsci.2026.106181