Articles | Volume 14, issue 2
https://doi.org/10.5194/nhess-14-219-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-14-219-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
13 Feb 2014
Research article |
| 13 Feb 2014
The challenge of forecasting high streamflows 1–3 months in advance with lagged climate indices in southeast Australia
J. C. Bennett
CSIRO Land and Water, Graham Road, Highett, Victoria 3190, Australia
Q. J. Wang
CSIRO Land and Water, Graham Road, Highett, Victoria 3190, Australia
P. Pokhrel
now at: Entura, 89 Cambridge Park Drive, Cambridge, Tasmania 7170, Australia
CSIRO Land and Water, Graham Road, Highett, Victoria 3190, Australia
D. E. Robertson
CSIRO Land and Water, Graham Road, Highett, Victoria 3190, Australia
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Sean W. D. Turner, James C. Bennett, David E. Robertson, and Stefano Galelli
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Hydrol. Earth Syst. Sci., 17, 1913–1931, https://doi.org/10.5194/hess-17-1913-2013, https://doi.org/10.5194/hess-17-1913-2013, 2013
P. Pokhrel, D. E. Robertson, and Q. J. Wang
Hydrol. Earth Syst. Sci., 17, 795–804, https://doi.org/10.5194/hess-17-795-2013, https://doi.org/10.5194/hess-17-795-2013, 2013
D. E. Robertson, P. Pokhrel, and Q. J. Wang
Hydrol. Earth Syst. Sci., 17, 579–593, https://doi.org/10.5194/hess-17-579-2013, https://doi.org/10.5194/hess-17-579-2013, 2013
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Inland flooding is threatening coastal lowlands. If rainfall and storm surges are coinciding, the risk of inland flooding increases. We examine how such compound events are influenced by climate change. Our model based scenario analysis shows that climate change induces an increasing frequency and intensity of compounding precipitation and storm tide events along the North Sea coast. Overload of inland drainage systems will also increase if no timely adaptation measures are taken.
Lorenzo Alfieri, Andrea Libertino, Lorenzo Campo, Francesco Dottori, Simone Gabellani, Tatiana Ghizzoni, Alessandro Masoero, Lauro Rossi, Roberto Rudari, Nicola Testa, Eva Trasforini, Ahmed Amdihun, Jully Ouma, Luca Rossi, Yves Tramblay, Huan Wu, and Marco Massabò
Nat. Hazards Earth Syst. Sci., 24, 199–224, https://doi.org/10.5194/nhess-24-199-2024, https://doi.org/10.5194/nhess-24-199-2024, 2024
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This work describes Flood-PROOFS East Africa, an impact-based flood forecasting system for the Greater Horn of Africa. It is based on hydrological simulations, inundation mapping, and estimation of population and assets exposed to upcoming river floods. The system supports duty officers in African institutions in the daily monitoring of hydro-meteorological disasters. A first evaluation shows the system performance for the catastrophic floods in the Nile River basin in summer 2020.
Christoph Nathanael von Matt, Regula Mülchi, Lukas Gudmundsson, and Olivia Martius
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-6, https://doi.org/10.5194/nhess-2024-6, 2024
Revised manuscript accepted for NHESS
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The simultaneous occurrence of meteorological (precipitation), agricultural (soil moisture) and hydrological (streamflow) drought can lead to augmented impacts. By analysing drought indices derived from newest climate scenarios for Switzerland (CH2018, Hydro-CH2018), we show that with climate change the concurrence of all drought types will increase in all investigated regions of Switzerland. Our results highlight the benefits and need of both mitigation and adaptation measures at early stages.
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-224, https://doi.org/10.5194/nhess-2023-224, 2024
Revised manuscript accepted for NHESS
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To identify the flash flood potential in Germany, we shifted the most extreme rainfall events from the last 22 years systematically across Germany and simulated the consequent run off reaction.
Our results show, that almost all areas in Germany have not seen the worst-case scenario of flood peaks within the last 22 years. With a slight spatial change of historical rainfall events, flood peaks by the factor 2 or more would be achieved for most areas. The results can aid disaster risk management.
Günter Blöschl, Andreas Buttinger-Kreuzhuber, Daniel Cornel, Julia Eisl, Michael Hofer, Markus Hollaus, Zsolt Horváth, Jürgen Komma, Artem Konev, Juraj Parajka, Norbert Pfeifer, Andreas Reithofer, José Salinasa, Peter Valent, Roman Výleta, Jürgen Waser, Michael H. Wimmer, and Heinz Stiefelmeyer
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-209, https://doi.org/10.5194/nhess-2023-209, 2023
Revised manuscript accepted for NHESS
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A methodology of regional flood hazard mapping is proposed, based on experiences in Austria, which combines automatic methods with manual interventions in order to maximise efficiency and estimation accuracy similar to that of local studies. Flood discharge records from 781 stations are used to estimate flood hazard patterns of a given return period at a resolution of 2 m over a total stream length of 38000 km. The hazard maps are used for civil protection, risk awareness and insurance purposes.
Nejc Bezak, Panos Panagos, Leonidas Liakos, and Matjaž Mikoš
Nat. Hazards Earth Syst. Sci., 23, 3885–3893, https://doi.org/10.5194/nhess-23-3885-2023, https://doi.org/10.5194/nhess-23-3885-2023, 2023
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Extreme flooding occurred in Slovenia in August 2023. This brief communication examines the main causes, mechanisms and effects of this event. The flood disaster of August 2023 can be described as relatively extreme and was probably the most extreme flood event in Slovenia in recent decades. The economic damage was large and could amount to well over 5 % of Slovenia's annual gross domestic product; the event also claimed three lives.
Ana Paez-Trujilo, Jeffer Cañon, Beatriz Hernandez, Gerald Corzo, and Dimitri Solomatine
Nat. Hazards Earth Syst. Sci., 23, 3863–3883, https://doi.org/10.5194/nhess-23-3863-2023, https://doi.org/10.5194/nhess-23-3863-2023, 2023
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This study uses a machine learning technique, the multivariate regression tree approach, to assess the hydroclimatic characteristics that govern agricultural and hydrological drought severity. The results show that the employed technique successfully identified the primary drivers of droughts and their critical thresholds. In addition, it provides relevant information to identify the areas most vulnerable to droughts and design strategies and interventions for drought management.
Bouchra Zellou, Nabil El Moçayd, and El Houcine Bergou
Nat. Hazards Earth Syst. Sci., 23, 3543–3583, https://doi.org/10.5194/nhess-23-3543-2023, https://doi.org/10.5194/nhess-23-3543-2023, 2023
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In this study, we underscore the critical importance of strengthening drought prediction capabilities in the Mediterranean region. We present an in-depth evaluation of current drought forecasting approaches, encompassing statistical, dynamical, and hybrid statistical–dynamical models, and highlight unexplored research opportunities. Additionally, we suggest viable directions to enhance drought prediction and early warning systems within the area.
Francisco Rodrigues do Amaral, Nicolas Gratiot, Thierry Pellarin, and Tran Anh Tu
Nat. Hazards Earth Syst. Sci., 23, 3379–3405, https://doi.org/10.5194/nhess-23-3379-2023, https://doi.org/10.5194/nhess-23-3379-2023, 2023
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We propose an in-depth analysis of typhoon-induced compound flood drivers in the megacity of Ho Chi Minh, Vietnam. We use in situ and satellite measurements throughout the event to form a holistic overview of its impact. No evidence of storm surge was found, and peak precipitation presents a 16 h time lag to peak river discharge, which evacuates only 1.5 % of available water. The astronomical tide controls the river level even during the extreme event, and it is the main urban flood driver.
Juliette Godet, Olivier Payrastre, Pierre Javelle, and François Bouttier
Nat. Hazards Earth Syst. Sci., 23, 3355–3377, https://doi.org/10.5194/nhess-23-3355-2023, https://doi.org/10.5194/nhess-23-3355-2023, 2023
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This article results from a master's research project which was part of a natural hazards programme developed by the French Ministry of Ecological Transition. The objective of this work was to investigate a possible way to improve the operational flash flood warning service by adding rainfall forecasts upstream of the forecasting chain. The results showed that the tested forecast product, which is new and experimental, has a real added value compared to other classical forecast products.
Florian Roth, Bernhard Bauer-Marschallinger, Mark Edwin Tupas, Christoph Reimer, Peter Salamon, and Wolfgang Wagner
Nat. Hazards Earth Syst. Sci., 23, 3305–3317, https://doi.org/10.5194/nhess-23-3305-2023, https://doi.org/10.5194/nhess-23-3305-2023, 2023
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In August and September 2022, millions of people were impacted by a severe flood event in Pakistan. Since many roads and other infrastructure were destroyed, satellite data were the only way of providing large-scale information on the flood's impact. Based on the flood mapping algorithm developed at Technische Universität Wien (TU Wien), we mapped an area of 30 492 km2 that was flooded at least once during the study's time period. This affected area matches about the total area of Belgium.
Clément Houdard, Adrien Poupardin, Philippe Sergent, Abdelkrim Bennabi, and Jena Jeong
Nat. Hazards Earth Syst. Sci., 23, 3111–3124, https://doi.org/10.5194/nhess-23-3111-2023, https://doi.org/10.5194/nhess-23-3111-2023, 2023
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We developed a system able to to predict, knowing the appropriate characteristics of the flood defense structure and sea state, the return periods of potentially dangerous events as well as a ranking of parameters by order of uncertainty.
The model is a combination of statistical and empirical methods that have been applied to a Mediterranean earthen dike. This shows that the most important characteristics of the dyke are its geometrical features, such as its height and slope angles.
Melody Gwyneth Whitehead and Mark Stephen Bebbington
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-160, https://doi.org/10.5194/nhess-2023-160, 2023
Revised manuscript accepted for NHESS
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Precipitation-driven hazards including floods, landslides, and lahars can be catastrophic and difficult to forecast due to high uncertainty around future weather patterns. This work presents SWM, a stochastic weather model that produces catchment-scale stochastically similar (realistic) rainfall over long time periods at minimal computational cost. These data provide much needed inputs for hazard simulations to support long-term, time- and spatially varying, risk assessments.
Lisa Köhler, Torsten Masson, Sabrina Köhler, and Christian Kuhlicke
Nat. Hazards Earth Syst. Sci., 23, 2787–2806, https://doi.org/10.5194/nhess-23-2787-2023, https://doi.org/10.5194/nhess-23-2787-2023, 2023
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We analyzed the impact of flood experience on adaptive behavior and self-reported resilience. The outcomes draw a paradoxical picture: the most experienced people are the most adapted but the least resilient. We find evidence for non-linear relationships between the number of floods experienced and resilience. We contribute to existing knowledge by focusing specifically on the number of floods experienced and extending the rare scientific literature on the influence of experience on resilience.
Helen Hooker, Sarah L. Dance, David C. Mason, John Bevington, and Kay Shelton
Nat. Hazards Earth Syst. Sci., 23, 2769–2785, https://doi.org/10.5194/nhess-23-2769-2023, https://doi.org/10.5194/nhess-23-2769-2023, 2023
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Ensemble forecasts of flood inundation produce maps indicating the probability of flooding. A new approach is presented to evaluate the spatial performance of an ensemble flood map forecast by comparison against remotely observed flooding extents. This is important for understanding forecast uncertainties and improving flood forecasting systems.
Arnau Amengual, Romu Romero, María Carmen Llasat, Alejandro Hermoso, and Montserrat Llasat-Botija
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-130, https://doi.org/10.5194/nhess-2023-130, 2023
Revised manuscript accepted for NHESS
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On 22 October 2019, the Francolí river basin (Catalonia, Spain) experienced a heavy precipitation event, resulting in a catastrophic flash flood. The main hydrometeorological factors are investigated. The social response times are also collected and compared with catchment dynamics in order to examine the adequacy of monitoring and warning issuance. Finally, the study provides recommendations aimed at minimizing losses and improving preparedness for similar natural hazards in the future.
Betina I. Guido, Ioana Popescu, Vidya Samadi, and Biswa Bhattacharya
Nat. Hazards Earth Syst. Sci., 23, 2663–2681, https://doi.org/10.5194/nhess-23-2663-2023, https://doi.org/10.5194/nhess-23-2663-2023, 2023
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We used an integrated model to evaluate the impacts of nature-based solutions (NBSs) on flood mitigation across the Little Pee Dee and Lumber River watershed, the Carolinas, US. This area is strongly affected by climatic disasters, which are expected to increase due to climate change and urbanization, so exploring an NBS approach is crucial for adapting to future alterations. Our research found that NBSs can have visible effects on the reduction in hurricane-driven flooding.
Taylor Glen Johnson, Jorge Leandro, and Divine Kwaku Ahadzie
EGUsphere, https://doi.org/10.5194/egusphere-2023-1511, https://doi.org/10.5194/egusphere-2023-1511, 2023
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Reliance on infrastructure creates vulnerabilities to disruptions caused by natural hazards. To assess the impacts of natural hazards on the performance of infrastructure, we present a framework for quantifying resilience and develop a model of recovery based upon an application of project scheduling under resource constraints. The resilience framework and recovery model were applied in a case study to assess the resilience of buildings infrastructure to flooding hazards in Accra, Ghana.
Maliko Tanguy, Michael Eastman, Eugene Magee, Lucy J. Barker, Thomas Chitson, Chaiwat Ekkawatpanit, Daniel Goodwin, Jamie Hannaford, Ian Holman, Liwa Pardthaisong, Simon Parry, Dolores Rey Vicario, and Supattra Visessri
Nat. Hazards Earth Syst. Sci., 23, 2419–2441, https://doi.org/10.5194/nhess-23-2419-2023, https://doi.org/10.5194/nhess-23-2419-2023, 2023
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Droughts in Thailand are becoming more severe due to climate change. Understanding the link between drought impacts on the ground and drought indicators used in drought monitoring systems can help increase a country's preparedness and resilience to drought. With a focus on agricultural droughts, we derive crop- and region-specific indicator-to-impact links that can form the basis of targeted mitigation actions and an improved drought monitoring and early warning system in Thailand.
Yanxia Shen, Zhenduo Zhu, Qi Zhou, and Chunbo Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2023-1106, https://doi.org/10.5194/egusphere-2023-1106, 2023
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We present an improved Multigrid Dynamical Bidirectional Coupled hydrologic-hydrodynamic Model (M-DBCM) with two major improvements: 1) automated non-uniform mesh generation based on the D∞ algorithm was implemented to identify the flood-prone areas where high-resolution inundation conditions are needed; 2) ghost cells and bilinear interpolation were implemented to improve numerical accuracy in interpolating variables between the coarse and fine grids. The improved model was reliable.
Leon Scheiber, Mazen Hoballah Jalloul, Christian Jordan, Jan Visscher, Hong Quan Nguyen, and Torsten Schlurmann
Nat. Hazards Earth Syst. Sci., 23, 2313–2332, https://doi.org/10.5194/nhess-23-2313-2023, https://doi.org/10.5194/nhess-23-2313-2023, 2023
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Numerical models are increasingly important for assessing urban flooding, yet reliable input data are oftentimes hard to obtain. Taking Ho Chi Minh City as an example, this paper explores the usability and reliability of open-access data to produce preliminary risk maps that provide first insights into potential flooding hotspots. As a key novelty, a normalized flood severity index is presented which combines flood depth and duration to enhance the interpretation of hydro-numerical results.
Claudia Herbert and Petra Döll
Nat. Hazards Earth Syst. Sci., 23, 2111–2131, https://doi.org/10.5194/nhess-23-2111-2023, https://doi.org/10.5194/nhess-23-2111-2023, 2023
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This paper presents a new method for selecting streamflow drought hazard indicators for monitoring drought hazard for human water supply and river ecosystems in large-scale drought early warning systems. Indicators are classified by their inherent assumptions about the habituation of people and ecosystems to the streamflow regime and their level of drought characterization, namely drought magnitude (water deficit at a certain point in time) and severity (cumulated magnitude since drought onset).
Maryse Charpentier-Noyer, Daniela Peredo, Axelle Fleury, Hugo Marchal, François Bouttier, Eric Gaume, Pierre Nicolle, Olivier Payrastre, and Maria-Helena Ramos
Nat. Hazards Earth Syst. Sci., 23, 2001–2029, https://doi.org/10.5194/nhess-23-2001-2023, https://doi.org/10.5194/nhess-23-2001-2023, 2023
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This paper proposes a methodological framework designed for event-based evaluation in the context of an intense flash-flood event. The evaluation adopts the point of view of end users, with a focus on the anticipation of exceedances of discharge thresholds. With a study of rainfall forecasts, a discharge evaluation and a detailed look at the forecast hydrographs, the evaluation framework should help in drawing robust conclusions about the usefulness of new rainfall ensemble forecasts.
Min Li, Mingfeng Zhang, Runxiang Cao, Yidi Sun, and Xiyuan Deng
Nat. Hazards Earth Syst. Sci., 23, 1453–1464, https://doi.org/10.5194/nhess-23-1453-2023, https://doi.org/10.5194/nhess-23-1453-2023, 2023
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It is an important disaster reduction strategy to forecast hydrological drought. In order to analyse the impact of human activities on hydrological drought, we constructed the human activity factor based on the method of restoration. With the increase of human index (HI) value, hydrological droughts tend to transition to more severe droughts. The conditional distribution model involving of human activity factor can further improve the forecasting accuracy of drought in the Luanhe River basin.
Patrick Ludwig, Florian Ehmele, Mário J. Franca, Susanna Mohr, Alberto Caldas-Alvarez, James E. Daniell, Uwe Ehret, Hendrik Feldmann, Marie Hundhausen, Peter Knippertz, Katharina Küpfer, Michael Kunz, Bernhard Mühr, Joaquim G. Pinto, Julian Quinting, Andreas M. Schäfer, Frank Seidel, and Christina Wisotzky
Nat. Hazards Earth Syst. Sci., 23, 1287–1311, https://doi.org/10.5194/nhess-23-1287-2023, https://doi.org/10.5194/nhess-23-1287-2023, 2023
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Heavy precipitation in July 2021 led to widespread floods in western Germany and neighboring countries. The event was among the five heaviest precipitation events of the past 70 years in Germany, and the river discharges exceeded by far the statistical 100-year return values. Simulations of the event under future climate conditions revealed a strong and non-linear effect on flood peaks: for +2 K global warming, an 18 % increase in rainfall led to a 39 % increase of the flood peak in the Ahr river.
Nadav Peleg, Herminia Torelló-Sentelles, Grégoire Mariéthoz, Lionel Benoit, João P. Leitão, and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1233–1240, https://doi.org/10.5194/nhess-23-1233-2023, https://doi.org/10.5194/nhess-23-1233-2023, 2023
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Floods in urban areas are one of the most common natural hazards. Due to climate change enhancing extreme rainfall and cities becoming larger and denser, the impacts of these events are expected to increase. A fast and reliable flood warning system should thus be implemented in flood-prone cities to warn the public of upcoming floods. The purpose of this brief communication is to discuss the potential implementation of low-cost acoustic rainfall sensors in short-term flood warning systems.
Katharina Lengfeld, Paul Voit, Frank Kaspar, and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 1227–1232, https://doi.org/10.5194/nhess-23-1227-2023, https://doi.org/10.5194/nhess-23-1227-2023, 2023
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Estimating the severity of a rainfall event based on the damage caused is easy but highly depends on the affected region. A less biased measure for the extremeness of an event is its rarity combined with its spatial extent. In this brief communication, we investigate the sensitivity of such measures to the underlying dataset and highlight the importance of considering multiple spatial and temporal scales using the devastating rainfall event in July 2021 in central Europe as an example.
Paul D. Bates, James Savage, Oliver Wing, Niall Quinn, Christopher Sampson, Jeffrey Neal, and Andrew Smith
Nat. Hazards Earth Syst. Sci., 23, 891–908, https://doi.org/10.5194/nhess-23-891-2023, https://doi.org/10.5194/nhess-23-891-2023, 2023
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We present and validate a model that simulates current and future flood risk for the UK at high resolution (~ 20–25 m). We show that UK flood losses were ~ 6 % greater in the climate of 2020 compared to recent historical values. The UK can keep any future increase to ~ 8 % if all countries implement their COP26 pledges and net-zero ambitions in full. However, if only the COP26 pledges are fulfilled, then UK flood losses increase by ~ 23 %; and potentially by ~ 37 % in a worst-case scenario.
Dirk Eilander, Anaïs Couasnon, Tim Leijnse, Hiroaki Ikeuchi, Dai Yamazaki, Sanne Muis, Job Dullaart, Arjen Haag, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 23, 823–846, https://doi.org/10.5194/nhess-23-823-2023, https://doi.org/10.5194/nhess-23-823-2023, 2023
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In coastal deltas, flooding can occur from interactions between coastal, riverine, and pluvial drivers, so-called compound flooding. Global models however ignore these interactions. We present a framework for automated and reproducible compound flood modeling anywhere globally and validate it for two historical events in Mozambique with good results. The analysis reveals differences in compound flood dynamics between both events related to the magnitude of and time lag between drivers.
Omar Seleem, Georgy Ayzel, Axel Bronstert, and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 809–822, https://doi.org/10.5194/nhess-23-809-2023, https://doi.org/10.5194/nhess-23-809-2023, 2023
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Data-driven models are becoming more of a surrogate that overcomes the limitations of the computationally expensive 2D hydrodynamic models to map urban flood hazards. However, the model's ability to generalize outside the training domain is still a major challenge. We evaluate the performance of random forest and convolutional neural networks to predict urban floodwater depth and investigate their transferability outside the training domain.
Tahmina Yasmin, Kieran Khamis, Anthony Ross, Subir Sen, Anita Sharma, Debashish Sen, Sumit Sen, Wouter Buytaert, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 23, 667–674, https://doi.org/10.5194/nhess-23-667-2023, https://doi.org/10.5194/nhess-23-667-2023, 2023
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Floods continue to be a wicked problem that require developing early warning systems with plausible assumptions of risk behaviour, with more targeted conversations with the community at risk. Through this paper we advocate the use of a SMART approach to encourage bottom-up initiatives to develop inclusive and purposeful early warning systems that benefit the community at risk by engaging them at every step of the way along with including other stakeholders at multiple scales of operations.
Venkataswamy Sahana and Arpita Mondal
Nat. Hazards Earth Syst. Sci., 23, 623–641, https://doi.org/10.5194/nhess-23-623-2023, https://doi.org/10.5194/nhess-23-623-2023, 2023
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In an agriculture-dependent, densely populated country such as India, drought risk projection is important to assess future water security. This study presents the first comprehensive drought risk assessment over India, integrating hazard and vulnerability information. Future drought risk is found to be more significantly driven by increased vulnerability resulting from societal developments rather than climate-induced changes in hazard. These findings can inform planning for drought resilience.
Susanna Mohr, Uwe Ehret, Michael Kunz, Patrick Ludwig, Alberto Caldas-Alvarez, James E. Daniell, Florian Ehmele, Hendrik Feldmann, Mário J. Franca, Christian Gattke, Marie Hundhausen, Peter Knippertz, Katharina Küpfer, Bernhard Mühr, Joaquim G. Pinto, Julian Quinting, Andreas M. Schäfer, Marc Scheibel, Frank Seidel, and Christina Wisotzky
Nat. Hazards Earth Syst. Sci., 23, 525–551, https://doi.org/10.5194/nhess-23-525-2023, https://doi.org/10.5194/nhess-23-525-2023, 2023
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The flood event in July 2021 was one of the most severe disasters in Europe in the last half century. The objective of this two-part study is a multi-disciplinary assessment that examines the complex process interactions in different compartments, from meteorology to hydrological conditions to hydro-morphological processes to impacts on assets and environment. In addition, we address the question of what measures are possible to generate added value to early response management.
Yinxue Liu, Paul D. Bates, and Jeffery C. Neal
Nat. Hazards Earth Syst. Sci., 23, 375–391, https://doi.org/10.5194/nhess-23-375-2023, https://doi.org/10.5194/nhess-23-375-2023, 2023
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In this paper, we test two approaches for removing buildings and other above-ground objects from a state-of-the-art satellite photogrammetry topography product, ArcticDEM. Our best technique gives a 70 % reduction in vertical error, with an average difference of 1.02 m from a benchmark lidar for the city of Helsinki, Finland. When used in a simulation of rainfall-driven flooding, the bare-earth version of ArcticDEM yields a significant improvement in predicted inundation extent and water depth.
Joseph L. Gutenson, Ahmad A. Tavakoly, Mohammad S. Islam, Oliver E. J. Wing, William P. Lehman, Chase O. Hamilton, Mark D. Wahl, and T. Christopher Massey
Nat. Hazards Earth Syst. Sci., 23, 261–277, https://doi.org/10.5194/nhess-23-261-2023, https://doi.org/10.5194/nhess-23-261-2023, 2023
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Emergency managers use event-based flood inundation maps (FIMs) to plan and coordinate flood emergency response. We perform a case study test of three different FIM frameworks to see if FIM differences lead to substantial differences in the location and magnitude of flood exposure and consequences. We find that the FIMs are very different spatially and that the spatial differences do produce differences in the location and magnitude of exposure and consequences.
Mohamed Saadi, Carina Furusho-Percot, Alexandre Belleflamme, Ju-Yu Chen, Silke Trömel, and Stefan Kollet
Nat. Hazards Earth Syst. Sci., 23, 159–177, https://doi.org/10.5194/nhess-23-159-2023, https://doi.org/10.5194/nhess-23-159-2023, 2023
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On 14 July 2021, heavy rainfall fell over central Europe, causing considerable damage and human fatalities. We analyzed how accurate our estimates of rainfall and peak flow were for these flooding events in western Germany. We found that the rainfall estimates from radar measurements were improved by including polarimetric variables and their vertical gradients. Peak flow estimates were highly uncertain due to uncertainties in hydrological model parameters and rainfall measurements.
Arefeh Safaei-Moghadam, David Tarboton, and Barbara Minsker
Nat. Hazards Earth Syst. Sci., 23, 1–19, https://doi.org/10.5194/nhess-23-1-2023, https://doi.org/10.5194/nhess-23-1-2023, 2023
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Climate change, urbanization, and aging infrastructure contribute to flooding on roadways. This study evaluates the potential for flood reports collected from Waze – a community-based navigation app – to predict these events. Waze reports correlate primarily with low-lying depressions on roads. Therefore, we developed two data-driven models to determine whether roadways will flood. Analysis showed that in the city of Dallas, drainage area and imperviousness are the most significant contributors.
Zongjia Zhang, Jun Liang, Yujue Zhou, Zhejun Huang, Jie Jiang, Junguo Liu, and Lili Yang
Nat. Hazards Earth Syst. Sci., 22, 4139–4165, https://doi.org/10.5194/nhess-22-4139-2022, https://doi.org/10.5194/nhess-22-4139-2022, 2022
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An innovative multi-strategy-mode waterlogging-prediction framework for predicting waterlogging depth is proposed in the paper. The framework selects eight regression algorithms for comparison and tests the prediction accuracy and robustness of the model under different prediction strategies. Ultimately, the accuracy of predicting water depth after 30 min can exceed 86.1 %. This can aid decision-making in terms of issuing early warning information and determining emergency responses in advance.
Cited articles
Ashok, K., Guan, Z., and Yamagata, T.: Influence of the Indian Ocean dipole on the Australian winter rainfall, Geophys. Res. Lett., 30, 1821, https://doi.org/10.1029/2003GL017926, 2003.
Ashok, K., Nakamura, H., and Yamagata, T.: Impacts of ENSO and Indian Ocean dipole events on the southern hemisphere storm-track activity during austral winter, J. Climate, 20, 3147–3163, https://doi.org/10.1175/jcli4155.1, 2007.
Baxter-Tomkins, T. and Wallace, M.: Recruitment and retention of volunteers in emergency services, Australian Journal on Volunteering, 14, 1–11, 2009.
Benedetti, R.: Scoring rules for forecast verification, Mon. Weather Rev., 138, 203–211, https://doi.org/10.1175/2009MWR2945.1, 2010.
Brier, G. W.: Verification of forecasts expressed in terms of probability, Mon. Weather Rev., 78, 1–3, https://doi.org/10.1126/science.27.693.594, 1950.
Brown, J. N., McIntosh, P. C., Pook, M. J., and Risbey, J. S.: An investigation of the links between ENSO flavors and rainfall processes in southeastern Australia, Mon. Weather Rev., 137, 3786–3795, https://doi.org/10.1175/2009MWR3066.1, 2009.
Cai, W. and van Rensch, P.: The 2011 southeast Queensland extreme summer rainfall: a confirmation of a negative Pacific Decadal Oscillation phase?, Geophys. Res. Lett., 39, L08702, https://doi.org/10.1029/2011GL050820, 2012.
Chiew, F. H. S., Zhou, S. L., and McMahon, T. A.: Use of seasonal streamflow forecasts in water resources management, J. Hydrol., 270, 135–144, https://doi.org/10.1016/S0022-1694(02)00292-5, 1998.
Cloke, H. L. and Pappenberger, F.: Evaluating forecasts of extreme events for hydrological applications: an approach for screening unfamiliar performance measures, Meteorol. Appl., 15, 181–197, https://doi.org/10.1002/met.58, 2008.
Cloke, H. L. and Pappenberger, F.: Ensemble flood forecasting: a review, J. Hydrol., 375, 613–626, https://doi.org/10.1016/j.jhydrol.2009.06.005, 2009.
Cuo, L., Pagano, T. C., and Wang, Q. J.: A review of quantitative precipitation forecasts and their use in short-to medium range streamflow forecasting, J. Hydrometeorol., 12, 713–728, https://doi.org/10.1175/2011JHM1347.1, 2011.
Del Giudice, D., Honti, M., Scheidegger, A., Albert, C., Reichert, P., and Rieckermann, J.: Improving uncertainty estimation in urban hydrological modeling by statistically describing bias, Hydrol. Earth Syst. Sci., 17, 4209–4225, https://doi.org/10.5194/hess-17-4209-2013, 2013.
DelSole, T. and Shukla, J.: Artificial skill due to predictor screening, J. Climate, 22, 331–345, https://doi.org/10.1175/2008JCLI2414.1, 2009.
Elliott, J., Catchlove, R., Sooriyakumaran, S., and Thompson, R.: Recent advances in the development of flood forecasting and warning services in Australia, International conference on innovation, advances and implementation of flood forecasting technology, Tromsø, Norway, 2005, 1–10, 2005.
Hawthorne, S., Wang, Q. J., Schepen, A., and Robertson, D. E.: Effective use of GCM outputs for forecasting monthly rainfalls to long lead times, Water Resour. Res., 49, 5427–5436, https://doi.org/10.1002/wrcr.20453, 2013.
Jewson, S.: The problem with the Brier score, arXiv: physics/0401046v1 [physics.ao-ph], available at: http://arxiv.org/abs/physics/0401046v1 (last access: June 2013), 2008.
Jones, D. A., Wang, W., and Fawcett, R.: High-quality spatial climate data-sets for Australia, Australian Meteorological and Oceanographic Journal, 58, 233–248, 2009.
Kalnay, E., Kanamitsua, M., Kistlera, R., Collinsa, W., Deavena, D., Gandina, L., Iredella, M., Sahaa, S., Whitea, G., Woollena, J., Zhua, Y., Leetmaaa, A., Reynoldsa, R., Chelliahb, M., Ebisuzakib, W., Higginsb, W., Janowiakb, J., Mob, K. C., Ropelewskib, C., Wangb, J., Jennec, R., and Joseph, D.: The NCEP/NCAR 40-year reanalysis project, B. Am. Meteorol. Soc., 77, 437–471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
Kiem, A. S., Franks, S. W., and Kuczera, G.: Multi-decadal variability of flood risk, Geophys. Res. Lett., 30, 1035, https://doi.org/10.1029/2002GL015992, 2003.
Koster, R. D. P., Mahanama, S. P., Livneh, B., Lettenmaier, D. P., and Reichle, R. H.: Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow, Nat. Geosci., 3, 613–616, https://doi.org/10.1038/NGEO944, 2010.
Kwon, H.-H., Brown, C., Xu, K., and Lall, U.: Seasonal and annual maximum streamflow forecasting using climate information: application to the Three Gorges Dam in the Yangtze River basin, China, Hydrolog. Sci. J., 54, 582–595, https://doi.org/10.1623/hysj.54.3.582, 2009.
Li, H., Luo, L., Wood, E. F., and Schaake, J.: The role of initial conditions and forcing uncertainties in seasonal hydrologic forecasting, J. Geophys. Res.-Atmos., 114, D04114, https://doi.org/10.1029/2008jd010969, 2009.
Lindström, G. and Olsson, J.: A systematic review of sensitivities in the Swedish flood-forecasting system, Atmos. Res., 100, 275–284, https://doi.org/10.1016/j.atmosres.2010.09.013, 2011.
Mahanama, S., Livneh, B., Koster, R., Lettenmaier, D., and Reichle, R.: Soil moisture, snow, and seasonal streamflow forecasts in the United States, Journal of Hydrometeorology, 13, 189-203, https://doi.org/10.1175/jhm-d-11-046.1, 2012.
Marshall, A. G., Hudson, D., Wheeler, M. C., Hendon, H. H., and Alves, O.: Assessing the simulation and prediction of rainfall associated with the MJO in the POAMA seasonal forecast system, Clim. Dynam., 37, 2129–2141, https://doi.org/10.1007/s00382-010-0948-2, 2011.
Murphy, B. F. and Timbal, B.: A review of recent climate variability and climate change in southeastern Australia, Int. J. Climatol., 28, 859–879, https://doi.org/10.1002/joc.1627, 2008.
Pfister, N.: Community response to flood warnings: the case of an evacuation from Grafton, March 2001, The Australian Journal of Emergency Management, 17, 19-29, 2002.
Piechota, T. C., Chiew, F. H. S., Dracup, J. A., and McMahon, T. A.: Seasonal streamflow forecasting in eastern Australia and the El Niño–Southern Oscillation, Water Resour. Res., 34, 3035–3044, https://doi.org/10.1029/98WR02406, 1998.
Pook, M. J., McIntosh, P. C., and Meyers, G. A.: The synoptic decomposition of cool-season rainfall in the southeastern Australian cropping region, J. Appl. Meteorol. Clim., 45, 1156–1170, https://doi.org/10.1175/JAM2394.1, 2006.
Risbey, J. S., Pook, M. J., McIntosh, P. C., Wheeler, M. C., and Hendon, H. H.: On the remote drivers of rainfall variability in Australia, Mon. Weather Rev., 137, 3233–3253, https://doi.org/10.1175/2009MWR2861.1, 2009.
Roberts, N. M., Cole, S. J., Forbes, R. M., Mooreb, R. J., and Boswell, D.: Use of high-resolution NWP rainfall and river flow forecasts for advance warning of the Carlisle flood, north-west England, Meteorol. Appl., 16, 23–34, https://doi.org/10.1002/met.94, 2008.
Robertson, D. E. and Wang, Q. J.: A Bayesian approach to predictor selection for seasonal streamflow forecasting, J. Hydrometeorol., 13, 155–171, https://doi.org/10.1175/JHM-D-10-05009.1, 2012.
Robertson, D. E. and Wang, Q. J.: Seasonal Forecasts of Unregulated Inflows into the Murray River, Australia, Water Resour. Manage., 27, 2747–2769, https://doi.org/10.1007/s11269-013-0313-4, 2013.
Robertson, D. E., Pokhrel, P., and Wang, Q. J.: Improving statistical forecasts of seasonal streamflows using hydrological model output, Hydrol. Earth Syst. Sci., 17, 579–593, https://doi.org/10.5194/hess-17-579-2013, 2013a.
Robertson, D. E., Shrestha, D. L., and Wang, Q. J.: Post-processing rainfall forecasts from numerical weather prediction models for short-term streamflow forecasting, Hydrol. Earth Syst. Sci., 17, 3587–3603, https://doi.org/10.5194/hess-17-3587-2013, 2013b.
Rosenberg, E. A., Wood, A. W., and Steinemann, A. C.: Statistical applications of physically based hydrologic models to seasonal streamflow forecasts, Water Resour. Res., 47, W00H14, https://doi.org/10.1029/2010WR010101, 2011.
Saji, N. H., Goswami, B. N., Vinayachandran, P. N., and Yamagata, T.: A dipole mode in the tropical Indian Ocean, Nature, 401, 360–363, https://doi.org/10.1038/43854, 1999.
Schepen, A., Wang, Q. J., and Robertson, D.: Evidence for using lagged climate indices to forecast Australian seasonal rainfall, J. Climate, 25, 1230–1246, https://doi.org/10.1175/JCLI-D-11-00156.1, 2012a.
Schepen, A., Wang, Q. J., and Robertson, D. E.: Combining the strengths of statistical and dynamical modeling approaches for forecasting Australian seasonal rainfall, J. Geophys. Res., 117, D20107, https://doi.org/10.1029/2012JD018011, 2012b.
Sharma, A.: Seasonal to interannual rainfall probabilistic forecasts for improved water supply management: part 3 –- a nonparametric probabilistic forecast model, J. Hydrol., 239, 249–258, https://doi.org/10.1016/S0022-1694(00)00348-6, 2000.
Shrestha, D. L., Robertson, D. E., Wang, Q. J., Pagano, T. C., and Hapuarachchi, H. A. P.: Evaluation of numerical weather prediction model precipitation forecasts for short-term streamflow forecasting purpose, Hydrol. Earth Syst. Sci., 17, 1913–1931, https://doi.org/10.5194/hess-17-1913-2013, 2013.
Shukla, S. and Lettenmaier, D. P.: Seasonal hydrologic prediction in the United States: understanding the role of initial hydrologic conditions and seasonal climate forecast skill, Hydrol. Earth Syst. Sci., 15, 3529–3538, https://doi.org/10.5194/hess-15-3529-2011, 2011.
Smith, T. M., Reynolds, R. W., Peterson, T. C., and Lawrimore, J.: Improvements to NOAA's historical merged land–ocean surface temperature analysis (1880–2006), J. Climate, 21, 2283–2296, 2008.
Troup, A. J.: The southern oscillation, Q. J. Roy. Meteorol. Soc., 91, 490–506, https://doi.org/10.1002/qj.49709139009, 1965.
Vaze, J., Perraud, J., Teng, J., Chiew, F., Wang, B., and Yang, Z.: Catchment Water Yield Estimation Tools (CWYET), 34th World Congress of the International Association for Hydro-environment Research and Engineering and 33rd Hydrology and Water Resources Symposium and the 10th Conference on Hydraulics in Water Engineering, Brisbane, 2011, 1554–1561, 2011.
Verdon, D. C. and Franks, S. W.: Indian Ocean sea surface temperature variability and winter rainfall: Eastern Australia, Water Resour. Res., 41, W09413, https://doi.org/10.1029/2004WR003845, 2005.
Verdon, D. C., Wyatt, A. M., Kiem, A. S., and Franks, S. W.: Multidecadal variability of rainfall and streamflow: Eastern Australia, Water Resour. Res., 40, W10201, https://doi.org/10.1029/2004WR003234, 2004.
Wang, Q. J. and Robertson, D. E.: Multisite probabilistic forecasting of seasonal flows for streams with zero value occurrences, Water Resour. Res., 47, W02546, https://doi.org/10.1029/2010WR009333, 2011.
Wang, Q. J., Robertson, D. E., and Chiew, F. H. S.: A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites, Water Resour. Res., 45, W05407, https://doi.org/10.1029/2008WR007355, 2009.
Wang, Q. J., Schepen, A., and Robertson, D. E.: Merging seasonal rainfall forecasts from multiple statistical models through Bayesian model averaging, J. Climate, 25, 5524–5537, https://doi.org/10.1175/JCLI-D-11-00386.1, 2012a.
Wang, Q. J., Shrestha, D. L., Robertson, D. E., and Pokhrel, P.: A log-sinh transformation for data normalization and variance stabilization, Water Resour. Res., 48, W05514, https://doi.org/10.1029/2011WR010973, 2012b.
Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, Elsevier, New York, 648 pp., 1995.
Yeo, I. K. and Johnson, R. A.: A new family of power transformations to improve normality or symmetry, Biometrika, 87, 954–959, https://doi.org/10.1093/biomet/87.4.954, 2000.
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