Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-5237-2021
https://doi.org/10.5194/hess-25-5237-2021
Research article
 | 
27 Sep 2021
Research article |  | 27 Sep 2021

Uncertainties and their interaction in flood hazard assessment with climate change

Hadush Meresa, Conor Murphy, Rowan Fealy, and Saeed Golian

Related authors

Implementation of global soil databases in NOAH-MP model and the effects on simulated mean and extreme soil hydrothermal changes
Kazeem Ishola, Gerald Mills, Ankur Sati, Benjamin Obe, Matthias Demuzere, Deepak Upreti, Gourav Misra, Paul Lewis, Daire Walsh, Tim McCarthy, and Rowan Fealy
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-304,https://doi.org/10.5194/hess-2023-304, 2024
Preprint under review for HESS
Short summary
Hybrid forecasting: blending climate predictions with AI models
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023,https://doi.org/10.5194/hess-27-1865-2023, 2023
Short summary
Reassessing long-standing meteorological records: an example using the national hottest day in Ireland
Katherine Dooley, Ciaran Kelly, Natascha Seifert, Therese Myslinski, Sophie O'Kelly, Rushna Siraj, Ciara Crosby, Jack Kevin Dunne, Kate McCauley, James Donoghue, Eoin Gaddren, Daniel Conway, Jordan Cooney, Niamh McCarthy, Eoin Cullen, Simon Noone, Conor Murphy, and Peter Thorne
Clim. Past, 19, 1–22, https://doi.org/10.5194/cp-19-1-2023,https://doi.org/10.5194/cp-19-1-2023, 2023
Short summary
Insights from 20 years of temperature parallel measurements in Mauritius around the turn of the 20th century
Samuel O. Awe, Martin Mahony, Edley Michaud, Conor Murphy, Simon J. Noone, Victor K. C. Venema, Thomas G. Thorne, and Peter W. Thorne
Clim. Past, 18, 793–820, https://doi.org/10.5194/cp-18-793-2022,https://doi.org/10.5194/cp-18-793-2022, 2022
Short summary
Conditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead times
Seán Donegan, Conor Murphy, Shaun Harrigan, Ciaran Broderick, Dáire Foran Quinn, Saeed Golian, Jeff Knight, Tom Matthews, Christel Prudhomme, Adam A. Scaife, Nicky Stringer, and Robert L. Wilby
Hydrol. Earth Syst. Sci., 25, 4159–4183, https://doi.org/10.5194/hess-25-4159-2021,https://doi.org/10.5194/hess-25-4159-2021, 2021
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Uncertainty analysis
On the visual detection of non-natural records in streamflow time series: challenges and impacts
Laurent Strohmenger, Eric Sauquet, Claire Bernard, Jérémie Bonneau, Flora Branger, Amélie Bresson, Pierre Brigode, Rémy Buzier, Olivier Delaigue, Alexandre Devers, Guillaume Evin, Maïté Fournier, Shu-Chen Hsu, Sandra Lanini, Alban de Lavenne, Thibault Lemaitre-Basset, Claire Magand, Guilherme Mendoza Guimarães, Max Mentha, Simon Munier, Charles Perrin, Tristan Podechard, Léo Rouchy, Malak Sadki, Myriam Soutif-Bellenger, François Tilmant, Yves Tramblay, Anne-Lise Véron, Jean-Philippe Vidal, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 27, 3375–3391, https://doi.org/10.5194/hess-27-3375-2023,https://doi.org/10.5194/hess-27-3375-2023, 2023
Short summary
Historical rainfall data in northern Italy predict larger meteorological drought hazard than climate projections
Rui Guo and Alberto Montanari
Hydrol. Earth Syst. Sci., 27, 2847–2863, https://doi.org/10.5194/hess-27-2847-2023,https://doi.org/10.5194/hess-27-2847-2023, 2023
Short summary
Daytime-only mean data enhance understanding of land–atmosphere coupling
Zun Yin, Kirsten L. Findell, Paul Dirmeyer, Elena Shevliakova, Sergey Malyshev, Khaled Ghannam, Nina Raoult, and Zhihong Tan
Hydrol. Earth Syst. Sci., 27, 861–872, https://doi.org/10.5194/hess-27-861-2023,https://doi.org/10.5194/hess-27-861-2023, 2023
Short summary
Quantifying the uncertainty of precipitation forecasting using probabilistic deep learning
Lei Xu, Nengcheng Chen, Chao Yang, Hongchu Yu, and Zeqiang Chen
Hydrol. Earth Syst. Sci., 26, 2923–2938, https://doi.org/10.5194/hess-26-2923-2022,https://doi.org/10.5194/hess-26-2923-2022, 2022
Short summary
Unraveling the contribution of potential evaporation formulation to uncertainty under climate change
Thibault Lemaitre-Basset, Ludovic Oudin, Guillaume Thirel, and Lila Collet
Hydrol. Earth Syst. Sci., 26, 2147–2159, https://doi.org/10.5194/hess-26-2147-2022,https://doi.org/10.5194/hess-26-2147-2022, 2022
Short summary

Cited articles

Addor, N., Rossler, O., Koplin, N., Huss, M., Weingartner, R., and Seibert, J.: Robust Changes and Sources of Projected, Uncertainty in the Swiss, Hydrological Regimes of Catchments, Water Resour. Res., 50 7541–7562, 2014. 
Bastola, S., Murphy, C., and Sweeney, J.: The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments, Adv. Water Resour., 34, 562–576, https://doi.org/10.1016/j.advwatres.2011.01.008, 2011a. 
Bastola, S., Murphy, C., and Sweeney, J.: The sensitivity of fluvial flood risk in Irish catchments to the range of IPCC AR4 climate change scenarios, Sci. Total Environ., 409, 5403–5415, https://doi.org/10.1016/j.scitotenv.2011.08.042, 2011b. 
Berg, P., Feldmann, H., and Panitz, H.-J.: Bias correction of high resolution regional climate model data, J. Hydrol., 448–449, 80–92, https://doi.org/10.1016/j.jhydrol.2012.04.026, 2012. 
Beven, K. and Binley, A.: The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, https://doi.org/10.1002/hyp.3360060305, 1992. 
Download
Short summary
The assessment of future impacts of climate change is associated with a cascade of uncertainty linked to the modelling chain employed in assessing local-scale changes. Understanding and quantifying this cascade is essential for developing effective adaptation actions. We find that not only do the contributions of different sources of uncertainty vary by catchment, but that the dominant sources of uncertainty can be very different on a catchment-by-catchment basis.