Progress Toward Hyperresolution Models of Global Flood Hazard

Bates, Paul; Neal, J. C.; Sampson, Chris; Smith, Andy; Trigg, Mark A.

doi:10.1016/b978-0-12-804071-3.00009-4

Cited by 19 publications

(21 citation statements)

References 65 publications

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“…When modeling a sequence of low‐ and high‐flow periods, underestimation of water withdrawal and the well‐known difficulty of accurately predicting low flows (Garcia et al, ) can lead to increasing errors in the prediction of floodplain dynamics and can hamper the accurate evaluation of the duration of flooding. Nevertheless, the duration of flooding has a primary role on determining inundation economic and environmental costs (Bates et al, ) and the results of this study advocate for more research to improve the modeling skill of the drainage phase of large flood events.…”

Section: Discussionmentioning

confidence: 82%

“…In fact, a prediction scenario should contemplate ensemble flood forecasting (Cloke & Pappenberger, ) and a thorough evaluation of all the sources of uncertainty in order to produce probabilistic maps of inundation extents and levels. However, computational constraints still limit the number of model runs that can be made in both an offline and real‐time forecasting scenario (Bates et al, ). In this context, it is worth noting that the simple approach of this study, in which only two flow time series were routed through a hydraulic model, was capable of pinpointing areas critical for improving flood inundation modeling.…”

Section: Discussionmentioning

confidence: 99%

“…Challenges posed to inundation prediction by the low accuracy of the widely used SRTM DEM (or versions derived thereof) were pointed out in several other analyses (e.g., Bates et al, 2018;Sampson et al, 2015;Sampson et al, 2016;Trigg et al, 2016). To tackle this issue, the creation of a new open-access high-accuracy global DEM is being strongly advocated for by the flooding community (e.g., Sampson et al, 2016;Schumann et al, 2014).…”

Section: Hydrological Regime Morphological Features and Simulation mentioning

confidence: 99%

“…However, inclusion of two‐dimensional hydraulic models into large‐scale flood forecast and risk assessment systems has been advocated by a number of studies (e.g., Falter et al, ; Falter et al, ; Huang & Hattermann, ; Schumann et al, ; Vorogushyn et al, ; Zhao et al, ) because it enables more accurate predictions of floodplain inundation dynamics. Moreover, Bates et al () highlighted the need to use hydraulic models to predict the duration of flooding, as this parameter largely affected the impacts of flood events in a number of recent disasters, such as the floods in Queensland (Australia) in 2010–2011, in Thailand in 2011, in England and Wales (UK) in 2014, and, more recently, the 2017 hurricane floods in the United States. Nevertheless, the technical hurdles (mainly, data availability and computational power) that have so far hindered routine implementation of two‐dimensional hydraulic models at the large scale are sensibly diminishing (e.g., Bates et al, ; Moretti & Orlandini, ; Neal et al, ), and recently, large‐scale flood modeling approaches have begun to couple hydrologic and hydraulic models.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, Bates et al () highlighted the need to use hydraulic models to predict the duration of flooding, as this parameter largely affected the impacts of flood events in a number of recent disasters, such as the floods in Queensland (Australia) in 2010–2011, in Thailand in 2011, in England and Wales (UK) in 2014, and, more recently, the 2017 hurricane floods in the United States. Nevertheless, the technical hurdles (mainly, data availability and computational power) that have so far hindered routine implementation of two‐dimensional hydraulic models at the large scale are sensibly diminishing (e.g., Bates et al, ; Moretti & Orlandini, ; Neal et al, ), and recently, large‐scale flood modeling approaches have begun to couple hydrologic and hydraulic models. For instance, Biancamaria et al () optimized the river depth and roughness coefficient of a coupled system for the Ob River in Western Siberia; Yamazaki et al () applied a new river routing model to provide global flood hazard maps, and the same model was used by Hirabayashi et al () to produce global flood risk maps under climate change.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Challenges, Opportunities, and Pitfalls for Global Coupled Hydrologic‐Hydraulic Modeling of Floods

Grimaldi

Schumann

Shokri

et al. 2019

Water Resources Research

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Flood modeling at the regional to global scale is a key requirement for equitable emergency and land management. Coupled hydrological‐hydraulic models are at the core of flood forecasting and risk assessment models. Nevertheless, each model is subject to uncertainties from different sources (e.g., model structure, parameters, and inputs). Understanding how uncertainties propagate through the modeling cascade is essential to invest in data collection, increase flood modeling accuracy, and comprehensively communicate modeling results to end users. This study used a numerical experiment to quantify the propagation of errors when coupling hydrological and hydraulic models for multiyear flood event modeling in a large basin, with large morphological and hydrological variability. A coupled modeling chain consisting of the hydrological model Hydrologiska Byråns Vattenbalansavdelning and the hydraulic model LISFLOOD‐FP was used for the prediction of floodplain inundation in the Murray Darling Basin (Australia), from 2006 to 2012. The impacts of discrepancies between simulated and measured flow hydrographs on the predicted inundation patterns were analyzed by moving from small upstream catchments to large lowland catchments. The numerical experiment was able to identify areas requiring tailored modeling solutions or data collection. Moreover, this study highlighted the high sensitivity of inundation volume and extent prediction to uncertainties in flood peak values and explored challenges in time‐continuous modeling. Accurate flood peak predictions, knowledge of critical morphological features, and an event‐based modeling approach were outlined as pragmatic solutions for more accurate prediction of large‐scale spatiotemporal patterns of flood dynamics, particularly in the presence of low‐accuracy elevation data.

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Section: Discussionmentioning

confidence: 82%

Section: Discussionmentioning

confidence: 99%

Section: Hydrological Regime Morphological Features and Simulation mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Challenges, Opportunities, and Pitfalls for Global Coupled Hydrologic‐Hydraulic Modeling of Floods

Grimaldi

Schumann

Shokri

et al. 2019

Water Resources Research

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Global Flood Models

Trigg

Bernhofen

Maréchal³

et al. 2021

Geophysical Monograph Series

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Flooding is the most damaging natural hazard, both economically and by population affected. Flood models are important tools for evaluating the risks associated with flooding. Historically, the modeling domain has been limited in scale; however, advancements in computing power and global data sets have led to the development of global flood models (GFMs). This global modeling capability has benefited scientific studies of exposure and climate change impact, the insurance industry, and intergovernmental disaster risk reduction efforts. Global flood modeling has now progressed beyond its infancy to a point where coordinated and targeted model development can take place based on collective studies. This chapter provides a detailed summary of the current global flood modeling state-of-affairs. It begins with a summary of the history and challenges of GFM development. This is followed by a review of current GFMs and their structures, applications, and credibility. A section is also dedicated to describing global flood modeling in the context of the insurance catastrophe model, an important GFM category that is less visible due to their proprietary nature. The chapter concludes by looking to the future and highlighting how GFMs need to improve and the new data sets and methods that could con tribute to their continued development.

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Amazon hydrology from space: scientific advances and future challenges

Fassoni‐Andrade

Fleischmann

Papa³

et al. 2021

Preprint

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As the largest river basin on Earth, the Amazon is of major importance to the world's climate and water resources. Over the past decades, advances in satellite-based remote sensing (RS) have brought our understanding of its terrestrial water cycle and the associated hydrological processes to a new era. Here, we review major studies and the various techniques using satellite RS in the Amazon. We show how RS played a major role in supporting new research and key findings regarding the Amazon water cycle, and how the region became a laboratory for groundbreaking investigations of new satellite retrievals and analyses. At the basin-scale, the understanding of several hydrological processes was only possible with the advent of RS observations, such as the characterization of "rainfall hotspots" in the Andes-Amazon transition, evapotranspiration rates, and variations of surface waters and groundwater storage. These results strongly contribute to the recent advances of hydrological models and to our new understanding of the Amazon water budget and aquatic environments. In the context of upcoming hydrology-oriented satellite missions, which will offer the opportunity for new synergies and new observations with finer space-time resolution, this review aims to guide future research agenda toward integrated monitoring and understanding of the Amazon water from space. Integrated multidisciplinary studies, fostered by international collaborations, set up future directions to tackle the great challenges the Amazon is currently facing, from climate change to increased anthropogenic pressure. Plain Language SummaryThe Amazon basin is the largest river basin in the world, characterized by complex hydrological processes that connect high rates of precipitation, extensive floodplains, dense tropical forests, complex topography, and large variations in freshwater storage and discharge. It plays a key role in the water, energy, and carbon cycles and interacts with the global climate system. Earth observations have played a major role in supporting research in Amazon hydrology, and the characterization of several hydrological processes was only possible with the help of remote sensing data. The basin is now facing great risk under current climate change and increased anthropogenic pressure and the resulting environmental alterations require a better understanding of the overall basin's water cycle across scales. We review the strengths and limitations of observations from satellites in the context of the current and upcoming hydrology-oriented satellite missions, and we make recommendations for improving satellite observations of the Amazon basin water cycle, along with an interdisciplinary and stepwise approach to guide research for the next decades.

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Progress Toward Hyperresolution Models of Global Flood Hazard

Cited by 19 publications

References 65 publications

Challenges, Opportunities, and Pitfalls for Global Coupled Hydrologic‐Hydraulic Modeling of Floods

Challenges, Opportunities, and Pitfalls for Global Coupled Hydrologic‐Hydraulic Modeling of Floods

Global Flood Models

Amazon hydrology from space: scientific advances and future challenges

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