Articles | Volume 19, issue 1
https://doi.org/10.5194/nhess-19-1-2019
https://doi.org/10.5194/nhess-19-1-2019
Research article
 | 
04 Jan 2019
Research article |  | 04 Jan 2019

A stochastic event-based approach for flood estimation in catchments with mixed rainfall and snowmelt flood regimes

Valeriya Filipova, Deborah Lawrence, and Thomas Skaugen

Related authors

seNorge2 daily precipitation, an observational gridded dataset over Norway from 1957 to the present day
Cristian Lussana, Tuomo Saloranta, Thomas Skaugen, Jan Magnusson, Ole Einar Tveito, and Jess Andersen
Earth Syst. Sci. Data, 10, 235–249, https://doi.org/10.5194/essd-10-235-2018,https://doi.org/10.5194/essd-10-235-2018, 2018
Short summary
Estimating catchment-scale groundwater dynamics from recession analysis – enhanced constraining of hydrological models
Thomas Skaugen and Zelalem Mengistu
Hydrol. Earth Syst. Sci., 20, 4963–4981, https://doi.org/10.5194/hess-20-4963-2016,https://doi.org/10.5194/hess-20-4963-2016, 2016
Short summary
A model for the spatial distribution of snow water equivalent parameterized from the spatial variability of precipitation
Thomas Skaugen and Ingunn H. Weltzien
The Cryosphere, 10, 1947–1963, https://doi.org/10.5194/tc-10-1947-2016,https://doi.org/10.5194/tc-10-1947-2016, 2016
Short summary
Trends in projections of standardized precipitation indices in a future climate in Poland
Marzena Osuch, Renata J. Romanowicz, Deborah Lawrence, and Wai K. Wong
Hydrol. Earth Syst. Sci., 20, 1947–1969, https://doi.org/10.5194/hess-20-1947-2016,https://doi.org/10.5194/hess-20-1947-2016, 2016
Short summary
Evaluation of a compound distribution based on weather pattern subsampling for extreme rainfall in Norway
J. Blanchet, J. Touati, D. Lawrence, F. Garavaglia, and E. Paquet
Nat. Hazards Earth Syst. Sci., 15, 2653–2667, https://doi.org/10.5194/nhess-15-2653-2015,https://doi.org/10.5194/nhess-15-2653-2015, 2015
Short summary

Related subject area

Hydrological Hazards
Precursors and pathways: dynamically informed extreme event forecasting demonstrated on the historic Emilia-Romagna 2023 flood
Joshua Dorrington, Marta Wenta, Federico Grazzini, Linus Magnusson, Frederic Vitart, and Christian M. Grams
Nat. Hazards Earth Syst. Sci., 24, 2995–3012, https://doi.org/10.5194/nhess-24-2995-2024,https://doi.org/10.5194/nhess-24-2995-2024, 2024
Short summary
Demonstrating the use of UNSEEN climate data for hydrological applications: case studies for extreme floods and droughts in England
Alison L. Kay, Nick Dunstone, Gillian Kay, Victoria A. Bell, and Jamie Hannaford
Nat. Hazards Earth Syst. Sci., 24, 2953–2970, https://doi.org/10.5194/nhess-24-2953-2024,https://doi.org/10.5194/nhess-24-2953-2024, 2024
Short summary
Exploring the use of seasonal forecasts to adapt flood insurance premiums
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Botzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 24, 2923–2937, https://doi.org/10.5194/nhess-24-2923-2024,https://doi.org/10.5194/nhess-24-2923-2024, 2024
Short summary
Are 2D shallow-water solvers fast enough for early flood warning? A comparative assessment on the 2021 Ahr valley flood event
Shahin Khosh Bin Ghomash, Heiko Apel, and Daniel Caviedes-Voullième
Nat. Hazards Earth Syst. Sci., 24, 2857–2874, https://doi.org/10.5194/nhess-24-2857-2024,https://doi.org/10.5194/nhess-24-2857-2024, 2024
Short summary
Water depth estimate and flood extent enhancement for satellite-based inundation maps
Andrea Betterle and Peter Salamon
Nat. Hazards Earth Syst. Sci., 24, 2817–2836, https://doi.org/10.5194/nhess-24-2817-2024,https://doi.org/10.5194/nhess-24-2817-2024, 2024
Short summary

Cited articles

Alfieri, L., Laio, F., and Claps, P.: A simulation experiment for optimal design hyetograph selection, Hydrol. Process., 22, 813–820, https://doi.org/10.1002/hyp.6646, 2008. a
Andersen, J., Sælthun, N., Hjukse, T., and Roald, L.: Hydrologisk modell for flomberegning (Hydrological for flood estimation), Tech. rep., NVE, Oslo, 1983. a, b, c
Ball, J. E.: Australian Rainfall and Runoff: A Guide to Flood Estimation – Draft for Industry Comment 151205, Geoscience Australia, 2015. a
Beven, K. and Hall, J.: Applied Uncertainty Analysis for Flood Risk Management, edited by: Beven, K. and Hall, J., 684 pp., https://doi.org/10.1142/p588, 2014. a
Blanchet, J., Touati, J., Lawrence, D., Garavaglia, F., and Paquet, E.: Evaluation of a compound distribution based on weather pattern subsampling for extreme rainfall in Norway, Nat. Hazards Earth Syst. Sci., 15, 2653–2667, https://doi.org/10.5194/nhess-15-2653-2015, 2015. a
Download
Short summary
This paper presents a stochastic event-based method for analysis of extreme floods, which uses a Monte Carlo procedure to sample initial conditions, snowmelt and rainfall. A study of 20 catchments in Norway shows that this method gives flood estimates that are closer to those obtained using statistical flood frequency analysis than a deterministic event-based model based on a single design storm.
Altmetrics
Final-revised paper
Preprint