Articles | Volume 22, issue 7
https://doi.org/10.5194/nhess-22-2347-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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https://doi.org/10.5194/nhess-22-2347-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Compound flood impact of water level and rainfall during tropical cyclone periods in a coastal city: the case of Shanghai
Hanqing Xu
Institute of Eco-Chongming (IEC), Key Laboratory of Geographic Information Science (Ministry of Education), and School of Geographic Sciences, East China Normal University, Shanghai, China
School of Environmental Science and Engineering, Southern University
of Science and Technology, Shenzhen, China
Department of Hydraulic Engineering, Faculty of Civil Engineering and
Geosciences, University of Technology, Delft, the Netherlands
Zhan Tian
CORRESPONDING AUTHOR
School of Environmental Science and Engineering, Southern University
of Science and Technology, Shenzhen, China
Peng Cheng Laboratory, Shenzhen, China
Laixiang Sun
School of Finance & Management, SOAS University of London, London, WC1H 0XG, UK
Department of Geographical Sciences, University of Maryland, College Park, USA
Qinghua Ye
Department of Hydraulic Engineering, Faculty of Civil Engineering and
Geosciences, University of Technology, Delft, the Netherlands
Deltares, Delft, the Netherlands
Elisa Ragno
Department of Hydraulic Engineering, Faculty of Civil Engineering and
Geosciences, University of Technology, Delft, the Netherlands
Jeremy Bricker
Department of Hydraulic Engineering, Faculty of Civil Engineering and
Geosciences, University of Technology, Delft, the Netherlands
Department of Civil and Environmental Engineering, University of
Michigan, Ann Arbor, Michigan, USA
Ganquan Mao
School of Environmental Science and Engineering, Southern University
of Science and Technology, Shenzhen, China
Jinkai Tan
School of Atmospheric Sciences and Key Laboratory of Tropical
Atmosphere–Ocean System (Ministry of Education), Sun Yat-sen University,
Zhuhai, China
Jun Wang
CORRESPONDING AUTHOR
Institute of Eco-Chongming (IEC), Key Laboratory of Geographic Information Science (Ministry of Education), and School of Geographic Sciences, East China Normal University, Shanghai, China
Qian Ke
Department of Hydraulic Engineering, Faculty of Civil Engineering and
Geosciences, University of Technology, Delft, the Netherlands
Shuai Wang
Department of Physics, Imperial College London, London, UK
Ralf Toumi
Department of Physics, Imperial College London, London, UK
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Ben Clarke, Sihan Li, Ralf Toumi, and Nathan Sparks
EGUsphere, https://doi.org/10.5194/egusphere-2025-665, https://doi.org/10.5194/egusphere-2025-665, 2025
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In December 2021, Super Typhoon Odette brought high winds and heavy rainfall to the central Philippines. The Philippines is one of the most exposed nations globally to tropical cyclones, so the influence of climate change on such events is of huge societal importance. This study combines several methods in extreme event attribution to investigate this, finding that the likelihood of a disaster like Odette in the Philippines has roughly doubled due to current warming.
Dan Li, Laixiang Sun, Yang Yu, and Peipei Tian
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-260, https://doi.org/10.5194/essd-2025-260, 2025
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We present a standardized, bottom-up framework to estimate slum populations at neighborhood level across 129 Global South countries. Our approach addresses underestimations in prior studies that rely heavily on slum geometry. Our dataset offers the first comprehensive inventory in data-sparse settings. This research offers valuable insights to support sustainable urban development goals, inform humanitarian aid distribution, and enhance the well-being in underserved communities.
Hengzhi Hu, Qian Ke, Wei Wu, Min Zhang, and Jiahong Wen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-391, https://doi.org/10.5194/hess-2024-391, 2025
Revised manuscript under review for HESS
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This study proposes a framework combining robustness and adaptability for long-term flood planning. Applied to Shanghai, it shows that the most cost-effective option may not meet long-term goals, and a combination of green spaces, drainage, and tunnels outperforms individual measures. The findings emphasize the importance of flexibility and adaptability in flood control to avoid regrets and help other cities plan resilient, long-term solutions.
Hanqing Xu, Elisa Ragno, Sebastiaan N. Jonkman, Jun Wang, Jeremy D. Bricker, Zhan Tian, and Laixiang Sun
Hydrol. Earth Syst. Sci., 28, 3919–3930, https://doi.org/10.5194/hess-28-3919-2024, https://doi.org/10.5194/hess-28-3919-2024, 2024
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A coupled statistical–hydrodynamic model framework is employed to quantitatively evaluate the sensitivity of compound flood hazards to the relative timing of peak storm surges and rainfall. The findings reveal that the timing difference between these two factors significantly affects flood inundation depth and extent. The most severe inundation occurs when rainfall precedes the storm surge peak by 2 h.
Patrick Olschewski, Qi Sun, Jianhui Wei, Yu Li, Zhan Tian, Laixiang Sun, Joël Arnault, Tanja C. Schober, Brian Böker, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-95, https://doi.org/10.5194/hess-2024-95, 2024
Preprint under review for HESS
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There are indications that typhoon intensities may increase under global warming. However, further research on these projections and their uncertainties is necessary. We study changes in typhoon intensity under SSP5-8.5 for seven events affecting the Pearl River Delta using Pseudo-Global Warming and a storyline approach based on 16 CMIP6 models. Results show intensified wind speed, sea level pressure drop and precipitation levels for six events with amplified increases for individual storylines.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev., 17, 53–69, https://doi.org/10.5194/gmd-17-53-2024, https://doi.org/10.5194/gmd-17-53-2024, 2024
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This study presents a deep learning architecture, multi-scale feature fusion (MFF), to improve the forecast skills of precipitations especially for heavy precipitations. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors so that heavy precipitations are produced.
Elisa Ragno, Markus Hrachowitz, and Oswaldo Morales-Nápoles
Hydrol. Earth Syst. Sci., 26, 1695–1711, https://doi.org/10.5194/hess-26-1695-2022, https://doi.org/10.5194/hess-26-1695-2022, 2022
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We explore the ability of non-parametric Bayesian networks to reproduce maximum daily discharge in a given month in a catchment when the remaining hydro-meteorological and catchment attributes are known. We show that a saturated network evaluated in an individual catchment can reproduce statistical characteristics of discharge in about ~ 40 % of the cases, while challenges remain when a saturated network considering all the catchments together is evaluated.
Qing Liu, Hanqing Xu, and Jun Wang
Nat. Hazards Earth Syst. Sci., 22, 665–675, https://doi.org/10.5194/nhess-22-665-2022, https://doi.org/10.5194/nhess-22-665-2022, 2022
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The coastal area is a major floodplain in compound flood events in coastal cities, primarily due to storm tide, with the inundation severity positively correlated with the height of the storm tide. Simply accumulating every single-driven flood hazard (rainstorm inundation and storm tide flooding) to define the compound flood hazard may cause underestimation. The assessment of tropical cyclone compound flood risk can provide vital insight for research on coastal flooding prevention.
Manuel Andres Diaz Loaiza, Jeremy D. Bricker, Remi Meynadier, Trang Minh Duong, Rosh Ranasinghe, and Sebastiaan N. Jonkman
Nat. Hazards Earth Syst. Sci., 22, 345–360, https://doi.org/10.5194/nhess-22-345-2022, https://doi.org/10.5194/nhess-22-345-2022, 2022
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Extratropical cyclones are one of the major causes of coastal floods in Europe and the world. Understanding the development process and the flooding of storm Xynthia, together with the damages that occurred during the storm, can help to forecast future losses due to other similar storms. In the present paper, an analysis of shallow water variables (flood depth, velocity, etc.) or coastal variables (significant wave height, energy flux, etc.) is done in order to develop damage curves.
Christopher H. Lashley, Sebastiaan N. Jonkman, Jentsje van der Meer, Jeremy D. Bricker, and Vincent Vuik
Nat. Hazards Earth Syst. Sci., 22, 1–22, https://doi.org/10.5194/nhess-22-1-2022, https://doi.org/10.5194/nhess-22-1-2022, 2022
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Many coastlines around the world have shallow foreshores (e.g. salt marshes and mudflats) that reduce storm waves and the risk of coastal flooding. However, most of the studies that tried to quantify this effect have excluded the influence of very long waves, which often dominate in shallow water. Our newly developed framework addresses this oversight and suggests that safety along these coastlines may be overestimated, since these very long waves are largely neglected in flood risk assessments.
Víctor M. Santos, Mercè Casas-Prat, Benjamin Poschlod, Elisa Ragno, Bart van den Hurk, Zengchao Hao, Tímea Kalmár, Lianhua Zhu, and Husain Najafi
Hydrol. Earth Syst. Sci., 25, 3595–3615, https://doi.org/10.5194/hess-25-3595-2021, https://doi.org/10.5194/hess-25-3595-2021, 2021
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We present an application of multivariate statistical models to assess compound flooding events in a managed reservoir. Data (from a previous study) were obtained from a physical-based hydrological model driven by a regional climate model large ensemble, providing a time series expanding up to 800 years in length that ensures stable statistics. The length of the data set allows for a sensitivity assessment of the proposed statistical framework to natural climate variability.
Camelia-Eliza Telteu, Hannes Müller Schmied, Wim Thiery, Guoyong Leng, Peter Burek, Xingcai Liu, Julien Eric Stanislas Boulange, Lauren Seaby Andersen, Manolis Grillakis, Simon Newland Gosling, Yusuke Satoh, Oldrich Rakovec, Tobias Stacke, Jinfeng Chang, Niko Wanders, Harsh Lovekumar Shah, Tim Trautmann, Ganquan Mao, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Luis Samaniego, Yoshihide Wada, Vimal Mishra, Junguo Liu, Petra Döll, Fang Zhao, Anne Gädeke, Sam S. Rabin, and Florian Herz
Geosci. Model Dev., 14, 3843–3878, https://doi.org/10.5194/gmd-14-3843-2021, https://doi.org/10.5194/gmd-14-3843-2021, 2021
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We analyse water storage compartments, water flows, and human water use sectors included in 16 global water models that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b. We develop a standard writing style for the model equations. We conclude that even though hydrologic processes are often based on similar equations, in the end these equations have been adjusted, or the models have used different values for specific parameters or specific variables.
Matteo U. Parodi, Alessio Giardino, Ap van Dongeren, Stuart G. Pearson, Jeremy D. Bricker, and Ad J. H. M. Reniers
Nat. Hazards Earth Syst. Sci., 20, 2397–2414, https://doi.org/10.5194/nhess-20-2397-2020, https://doi.org/10.5194/nhess-20-2397-2020, 2020
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We investigate sources of uncertainty in coastal flood risk assessment in São Tomé and Príncipe, a small island developing state. We find that, for the present-day scenario, uncertainty from depth damage functions and digital elevation models can be more significant than that related to the estimation of significant wave height or storm surge level. For future scenarios (year 2100), sea level rise prediction becomes the input with the strongest impact on coastal flood damage estimate.
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Short summary
A hydrodynamic model and copula methodology were used to set up a joint distribution of the peak water level and the inland rainfall during tropical cyclone periods, and to calculate the marginal contributions of the individual drivers. The results indicate that the relative sea level rise has significantly amplified the peak water level. The astronomical tide is the leading driver, followed by the contribution from the storm surge.
A hydrodynamic model and copula methodology were used to set up a joint distribution of the peak...
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