A method for probabilistic flash flood forecasting

Hardy, Jill; Gourley, Jonathan J.; Kirstetter, Pierre‐Emmanuel; Hong, Yang; Kong, Fanyou; Flamig, Zachary L.

doi:10.1016/j.jhydrol.2016.04.007

Cited by 54 publications

(26 citation statements)

References 34 publications

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“…Flash floods are regarded as one of the most destructive hydrological hazards, resulting in considerable loss of human life and high costs due to infrastructure damage (Roux et al, 2011;Gruntfest and Handmer, 2001). Among all different types of floods, Jonkman (2005) shows that flash floods result in the highest average mortality rate per event (3.62 %), almost 10 times larger than the mortality rate for river floods.…”

Section: Introductionmentioning

confidence: 99%

“…Flash floods are usually described as rapidly rising waterlevel events occurring in steep streams and rivers, associated with short-term, very intense convective precipitation systems or orographically forced rainfall events over highly saturated land surfaces and steep terrains (Šálek et al, 2006;Llasat et al, 2016;Douinot et al, 2016). Convective precipitation episodes often feature high intensity, short duration, and relatively reduced spatial coverage (Houze, 2004).…”

Section: Introductionmentioning

confidence: 99%

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Reconstructing the 2015 Salgar flash flood using radar retrievals and a conceptual modeling framework in an ungauged basin

Velásquez

Hoyos

Vélez

et al. 2020

Hydrol. Earth Syst. Sci.

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Abstract. On 18 May 2015, a severe rainfall event triggered a flash flood in the municipality of Salgar, located in the northwestern Colombian Andes. This work aims to reconstruct the main hydrological features of the flash flood to better understand the processes modulating the occurrence of the event. Radar quantitative precipitation estimates (QPEs), satellite information, and post-event field visits are used to reconstruct the Salgar flash flood, in an ungauged basin, addressing the relationship among rainfall spatiotemporal structure, soil moisture, and runoff generation during successive rainfall events by using a conceptual modeling framework including landslide and hydraulic submodels. The hydrological model includes virtual tracers to explore the role of runoff and subsurface flow and the relative importance of convective and stratiform precipitation in flash flood generation. Despite potential shortcomings due to the lack of data, the modeling results allow an assessment of the impact of the interactions between runoff, subsurface flow, and convective–stratiform rainfall on the short-term hydrological mechanisms leading to the flash flood event. The overall methodology reproduces the magnitude and timing of the La Liboriana flash flood peak discharge considerably well, as well as the areas of landslide occurrence and flood spots, with limitations due to the spatial resolution of the available digital elevation model. Simulation results indicate that the flash flood and regional landslide features were strongly influenced by the antecedent rainfall, which was associated with a northeasterly stratiform event. The latter recharged the gravitational and capillary storages within the model, moistening the entire basin before the occurrence of the flash flood event and impacting the subsurface–runoff partitioning during the flash flood event. Evidence suggests that the spatial structure of the rainfall is at least as important as the geomorphological features of the basin in regulating the occurrence of flash flood events.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reconstructing the 2015 Salgar flash flood using radar retrievals and a conceptual modeling framework in an ungauged basin

Velásquez

Hoyos

Vélez

et al. 2020

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…On the one hand, elucidating flash flood processes may reveal aspects of flood response that either were unexpected on the basis of less intense rainfall input or that highlight anticipated but previously undocumented characteristics. On the other hand, improved understanding of flash floods is required to better forecast these events and manage the relevant risks (Hardy et al, 2016), because knowledge based on the analysis of moderate floods may be questioned when used for forecasting the response to local extreme storms (Collier, 2007;Yatheendradas et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Integrated high-resolution dataset of high-intensity European and Mediterranean flash floods

Amponsah

Ayral

Boudevillain

et al. 2018

Earth Syst. Sci. Data

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This paper describes an integrated, high-resolution dataset of hydro-meteorological variables (rainfall and discharge) concerning a number of high-intensity flash floods that occurred in Europe and in the Mediterranean region from 1991 to 2015. This type of dataset is rare in the scientific literature because flash floods are typically poorly observed hydrological extremes. Valuable features of the dataset (hereinafter referred to as the EuroMedeFF database) include (i) its coverage of varied hydro-climatic regions, ranging from Continental Europe through the Mediterranean to Arid climates, (ii) the high space-time resolution radar rainfall estimates, and (iii) the dense spatial sampling of the flood response, by observed hydrographs and/or flood peak estimates from post-flood surveys. Flash floods included in the database are selected based on the limited upstream catchment areas (up to 3000 km 2 ), the limited storm durations (up to 2 days), and the unit peak flood magnitude. The EuroMedeFF database comprises 49 events that occurred in

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“…Probabilistic forecasts quantify the potential risk of impacts for decision makers [26]. Therefore, probabilistic flood warning models are increasingly sought in the hydrological field [18,[27][28][29][30][31][32][33][34][35][36][37]. In seven of the above studies [18,[27][28][29][30][31][32], the values of the probabilistic information were provided to the flood warning models by hydro-meteorological ensembles.…”

mentioning

confidence: 99%

“…Therefore, probabilistic flood warning models are increasingly sought in the hydrological field [18,[27][28][29][30][31][32][33][34][35][36][37]. In seven of the above studies [18,[27][28][29][30][31][32], the values of the probabilistic information were provided to the flood warning models by hydro-meteorological ensembles. In the other five of the above studies, statistical post-processors are applied to provide probabilistic forecasts, i.e., the predictive uncertainty, from the output of a single (or multiple) deterministic model (either a meteorological or a hydrologic model) [33][34][35][36][37].…”

mentioning

confidence: 99%

A Data-Driven Probabilistic Rainfall-Inundation Model for Flash-Flood Warnings

Pan

Lin

Liao

2019

Water

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Owing to their short duration and high intensity, flash floods are among the most devastating natural disasters in metropolises. The existing warning tools-flood potential maps and two-dimensional numerical models-are disadvantaged by time-consuming computation and complex model calibration. This study develops a data-driven, probabilistic rainfall-inundation model for flash-flood warnings. Applying a modified support vector machine (SVM) to limited flood information, the model provides probabilistic outputs, which are superior to the Boolean functions of the traditional rainfall-flood threshold method. The probabilistic SVM-based model is based on a data preprocessing framework that identifies the expected durations of hazardous rainfalls via rainfall pattern analysis, ensuring satisfactory training data, and optimal rainfall thresholds for validating the input/output data. The proposed model was implemented in 12 flash-flooded districts of the Xindian River. It was found that (1) hydrological rainfall pattern analysis improves the hazardous event identification (used for configuring the input layer of the SVM); (2) brief hazardous events are more critical than longer-lasting events; and (3) the SVM model exports the probability of flash flooding 1 to 3 h in advance. Such a combined model is quick and suitable for fluvial floods, but inapplicable to pluvial flash floods. A similar combined hydrological model, which derives the rainfall thresholds in pluvial flash floods, was considered by Forestieri et al. (2016) [5]. In natural hazards induced by short-term heavy rainfall such as flash floods or landslides, a timely warning is more important than evaluating the disaster impacts on people. Therefore, the empirical rainfall thresholds of flash floods and rainfall-induced landslides have been increasingly sought in recent years [5][6][7][8][9][10][11][12][13][14][15].The local governments in Taiwan also consider the rainfall thresholds in flash floods and landslides [16][17][18]. In the official flash-flood warning system of Taiwan, the rainfall thresholds in all counties and districts are decided from five cumulative rainfalls of durations 1, 3, 6, 12, and 24 h. At least one rain gauge is assigned as the reference rain gauge for each county or district [19]. In 2017, the Water Resources Agency (WRA) used 754 sets of rainfall thresholds based on 500 rain gauges and warned 368 counties and districts of pending flash floods in Taiwan. However, the rainfall thresholds are based on historical flood records, which lack the parameters (start times, areas, and durations of the floods) required in complex flood warning models. Most of the historical flood records in Taiwan are reports of people's phone calls, which are checked by officers several hours later. Therefore, when determining rainfall thresholds, the historical flood records of the WRA are useful only for predicting whether a rainfall event will cause a disaster. Although potential inundation maps improve the information input [18,20,21], the models based on th...

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A method for probabilistic flash flood forecasting

Cited by 54 publications

References 34 publications

Reconstructing the 2015 Salgar flash flood using radar retrievals and a conceptual modeling framework in an ungauged basin

Reconstructing the 2015 Salgar flash flood using radar retrievals and a conceptual modeling framework in an ungauged basin

Integrated high-resolution dataset of high-intensity European and Mediterranean flash floods

A Data-Driven Probabilistic Rainfall-Inundation Model for Flash-Flood Warnings

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