Open this publication in new window or tab >>Swiss Fed Inst Forest, Snow & Landscape Res WSL, Birmensdorf, Switzerland.;Swiss Fed Inst Technol, Inst Atmospher & Climate Sci, Zurich, Switzerland..
Univ Grenoble Alpes, CNRS, IRD, Grenoble INP,IGE,INRAE, Grenoble, France..
Rhein Westfal TH Aachen, Inst Hydraul Engn & Water Resources Management, Aachen, Germany.;Monash Univ, Dept Civil Engn, Clayton, Vic, Australia..
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Ctr Nat Hazards & Disaster Sci CNDS, Uppsala, Sweden..
Justus Liebig Univ, Giessen, Germany..
European Ctr Medium Range Weather Forecasts, Reading, England..
Univ Paris Saclay, INRAE, HYCAR, Antony, France..
Univ Oxford, Sch Geog & Environm, Oxford, England..
World Meteorol Org, Geneva, Switzerland..
Univ Paris Saclay, INRAE, HYCAR, Antony, France..
Natl Ctr Atmospher Res, Climate & Global Dynam, Boulder, CO USA..
SENAMHI, Lima, Peru..
Univ Tokyo, Tokyo, Japan..
Deltares, Delft, Netherlands..
George Mason Univ, Fairfax, VA USA..
Swedish Meteorol & Hydrol Inst, Norrköping, Sweden..
Natl Inst Water & Atmospher Res, Christchurch, New Zealand..
Univ Cordoba, Andalusian Inst Earth Syst Res, Fluvial Dynam & Hydrol, Area Ingn Hidraulica, Campus Rabanales Edificio Leonardo Vinci, Cordoba, Spain.;Univ Cordoba, Dept Agron, Unit Excellence Maria de Maeztu DAUCO, Cordoba, Spain..
IHE Delft Inst Water Educ, Dept Water Resources & Ecosyst, Delft, Netherlands..
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2025 (English)In: Bulletin of The American Meteorological Society - (BAMS), ISSN 0003-0007, E-ISSN 1520-0477, Vol. 106, no 5, p. E894-E919Article in journal (Refereed) Published
Abstract [en]
Over the past 20 years, the Hydrological Ensemble Prediction Experiment (HEPEX) international community of practice has advanced the science and practice of hydrological ensemble prediction and its application in impact- and risk-based decision-making, fostering innovations through cutting-edge techniques and data that enhance water-related sectors. Here, we present insights from those 20 years on the key priorities for (co)creating broadly applicable hydrological forecasting systems that add value across spatial scales and time horizons. We highlight the advancement of hydrological forecasting chains through rigorous data management that incorporates diverse, high-quality data sources, data assimilation techniques, and the application of artificial intelligence (AI) to improve predictive accuracy. HEPEX has played a critical role in enhancing the reliability of water resources and water-related risk management globally by standardizing ensemble forecasting. This effort complements HEPEX's broader initiative to strengthen research to operations, making innovative forecasting solutions both practical and accessible. Additionally, efforts have been made toward supporting the United Nations Early Warnings for All initiative through developing robust and reliable early warning systems by means of global training, education and capacity development, and the sharing of technology. Finally, we note that the integration of advanced science, user-centric methods, and global collaboration can provide a solid framework for improving the prediction and management of hydrological extremes, aligning forecasting systems with the dynamic needs of water resource and risk management in a changing climate. To effectively meet future demands, it is crucial to accelerate the integration of innovative science within operational frameworks, fostering adaptable and resilient hydrological forecasting systems globally. SIGNIFICANCE STATEMENT: We present transformative advancements in hydrological forecast- ing that integrate diverse, high-quality data sources , advanced modeling techniques, including artificial intelligence (AI)/machine learning (ML) to enhance predictive accuracy across different time scales and spatial dimensions. Through Hydrological Ensemble Prediction Experiment (HEPEX)'s contributions in standardizing ensemble predictions, we have significantly improved forecast reli- ability and support across various water-related sectors. The efforts of the HEPEX community of practice also underpin robust early warning systems through extensive global capacity develop- ment and technology sharing, in alignment with the United Nations Early Warnings for All initia- tive. By fostering strategic collaborations, we bridge the research-to-operations gap, promoting forecasting solutions that are both practical and accessible. HEPEX body of work enhances global disaster resilience, making substantial contributions toward sophisticated, actionable hydrological forecasting and management worldwide.
Place, publisher, year, edition, pages
American Meteorological Society, 2025
Keywords
Hydrology, Ensembles, Forecasting, Communications/ decision making, Emergency preparedness, Water resources
National Category
Oceanography, Hydrology and Water Resources
Identifiers
urn:nbn:se:uu:diva-558835 (URN)10.1175/BAMS-D-24-0322.1 (DOI)001493691300004 ()2-s2.0-105005493152 (Scopus ID)
Funder
Energy ResearchEU, Horizon 2020, 101121192EU, Horizon 2020, 101084110EU, Horizon 2020, 101037293EU, Horizon 2020
2025-06-102025-06-102025-06-10Bibliographically approved