Quantifying flood risk of extreme events using density forecasts based on a new digital archive and weather ensemble predictions

McSharry, Patrick E.; Little, Max A.; Rodda, Harvey J. E.; Rodda, John C.

doi:10.1002/qj.2136

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…Floods are the most frequently occurring natural hazard in Canada and around the globe [1][2][3][4]. A number of studies have been performed in different parts of the globe to establish methods for effective quantification of floods and their associated risks [5][6][7][8][9][10][11][12][13][14][15][16][17]. Studies have also investigated methods to quantify compound flooding i.e., that are caused by two or more events contributing to flooding example occurrence of extreme rainfall, variations in astronomical tides, storm surge, and wave action, rise in groundwater levels etc., occurring simultaneously or successively [18,19].…”

Section: Introductionmentioning

confidence: 99%

Future Changes in Flood Hazards across Canada under a Changing Climate

Gaur

Simonović́

2018

Water

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Climate change has induced considerable changes in the dynamics of key hydro-climatic variables across Canada, including floods. In this study, runoff projections made by 21 General Climate Models (GCMs) under four Representative Concentration Pathways (RCPs) are used to generate 25 km resolution streamflow estimates across Canada for historical and future (2061-2100) time-periods. These estimates are used to calculate future projected changes in flood magnitudes and timings across Canada. Results obtained indicate that flood frequencies in the northernmost regions of Canada, and south-western Ontario can be expected to increase in the future. As an example, the historical 100-year return period events in these regions are expected to become 10-60 year return period events. On the other hand, northern prairies and north-central Ontario can be expected to experience decreases in flooding frequencies in future. The historical 100-year return period flood events in these regions are expected to become 160-200 year return period events in future. Furthermore, prairies, parts of Quebec, Ontario, Nunavut, and Yukon territories can be expected to experience earlier snowmelt-driven floods in the future. The results from this study will help decision-makers to effectively manage and design municipal and civil infrastructure in Canada under a changing climate.Basin Network (RHBN) catchments in Canada were examined by [28]. A decreasing trend in annual maximum flows for catchments located in southern Canada, and an increasing trend in catchments located in northern Canada was obtained. In addition, a robust signal of increases in spring snowmelt driven peak flow was obtained in the months of March and April, whereas a decrease in June month peak flow was obtained. These findings highlight that the behavior of extreme floods has changed across Canada as a consequence of climate change. Therefore, as advocated in previous research [29,30], it is important to obtain reliable flood frequency estimates under a non-stationary climate, such that they can be used to design climate resilient civil and municipal infrastructure across Canada.General Climate Models (GCMs) simulate complex bio-geophysical and chemical processes occurring within the earth system and their interactions [20]. Land surface schemes are the interface within the GCMs that host important energy budget and water balance calculations occurring within a GCM grid-cell. GCM simulations are performed at a coarse spatial resolution of~110-550 km, which hinders the accurate representation of some of the important physical processes, such as convection that shapes the earth's climate [22]. As a result, large uncertainties have been obtained in GCM projections, especially for variables linked to precipitation [22]. For making future flows and flooding projections at catchment(s) scales, typically, coarse resolution climate projections from GCMs are downscaled, and they are used to generate streamflow responses using a hydrologic model. This approach has been adopted in ...

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Section: Introductionmentioning

confidence: 99%

Future Changes in Flood Hazards across Canada under a Changing Climate

Gaur

Simonović́

2018

Water

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Ensemble flood forecasting: Current status and future opportunities

et al. 2020

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Ensemble flood forecasting has gained significant momentum over the past decade due to the growth of ensemble numerical weather and climate prediction, expansion in high performance computing, growing interest in shifting from deterministic to risk-based decision-making that accounts for forecast uncertainty, and the efforts of communities such as the international Hydrologic Ensemble Prediction Experiment (HEPEX), which focuses on advancing relevant ensemble forecasting capabilities and fostering its adoption. With this shift, comes the need to understand the current state of ensemble flood forecasting, in order to provide insights into current capabilities and areas for improvement, thus identifying future research opportunities to allow for better allocation of research resources. In this article, we provide an overview of current research activities in ensemble flood forecasting and discuss knowledge gaps and future research opportunities, based on a review of 70 papers focusing on various aspects of ensemble flood forecasting around the globe. Future research directions include opportunities to improve technical aspects of ensemble flood forecasting, such as data assimilation techniques and methods to account for more sources of uncertainty, and developing ensemble forecasts for more variables, for example, flood inundation, by applying techniques such as machine learning. Further to this, we conclude that there is a need to not only improve technical aspects of flood forecasting, but also to bridge the gap between scientific research and hydrometeorological model development, and real-world flood management using probabilistic ensemble forecasts, especially through effective communication.

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The Role of Scientific Modelling and Insurance in Providing Innovative Solutions for Managing the Risk of Natural Disasters

McSharry

2014

Reducing Disaster: Early Warning Systems for Climate Change

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Quantifying flood risk of extreme events using density forecasts based on a new digital archive and weather ensemble predictions

Cited by 4 publications

References 19 publications

Future Changes in Flood Hazards across Canada under a Changing Climate

Future Changes in Flood Hazards across Canada under a Changing Climate

Ensemble flood forecasting: Current status and future opportunities

The Role of Scientific Modelling and Insurance in Providing Innovative Solutions for Managing the Risk of Natural Disasters

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