Two-dimensional simulations of extreme floods on a large watershed

England, John F.; Velleux, Mark; Juliën, Pierre Y.

doi:10.1016/j.jhydrol.2007.09.034

Cited by 64 publications

(20 citation statements)

References 41 publications

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“…It is particularly well suited for real‐time forecasting as it requires relatively short computation time, and model outputs can be formulated in accordance with the forecaster's needs. More recently, England et al (2007) investigated the applicability of the TREX (Two‐dimensional, Runoff, Erosion and Export) model to simulate extreme floods in semi‐arid regions in the western US, and concluded that the model could generate good results with limited data. Other recently developed physically based distributed hydrological models with potential in flash flood modelling include LISFLOOD (Roo et al , 2000), tRIBS (Ivanov et al , 2004) and BTOP (Takeuchi et al , 2008).…”

Section: Flow Forecasting Modelsmentioning

confidence: 99%

A review of advances in flash flood forecasting

Hapuarachchi

Wang

Pagano

2011

Hydrological Processes

434

286

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Abstract:Flash flooding is one of the most hazardous natural events, and it is frequently responsible for loss of life and severe damage to infrastructure and the environment. Research into the use of new modelling techniques and data types in flash flood forecasting has increased over the past decade, and this paper presents a review of recent advances that have emerged from this research. In particular, we focus on the use of quantitative precipitation estimates and forecasts, the use of remotely sensed data in hydrological modelling, developments in forecasting models and techniques, and uncertainty estimates. Over the past decade flash flood forecast lead-time has expanded up to six hours due to improved rainfall forecasts. However the largest source of uncertainty of flash flood forecasts remains unknown future precipitation. An increased number of physically based hydrological models have been developed and used for flash flood forecasting and they have been found to give more plausible results when compared with the results of conceptual, statistical, and neural network models. Among the three methods for deciding flash flood occurrence discussed in this review, the rainfall comparison method (flash flood guidance) is most commonly used for flash flood forecasting as it is easily understood by the general public. Unfortunately, no existing model is capable of making reliable flash flood forecasts in urban watersheds even though the incidence of urban flash flooding is increasing due to increasing urbanisation.

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Section: Flow Forecasting Modelsmentioning

confidence: 99%

A review of advances in flash flood forecasting

Hapuarachchi

Wang

Pagano

2011

Hydrological Processes

434

286

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“…The overland flow can occur after exceeding the depression storage threshold, and it is governed by equations ensuring the conservation of mass (continuity) and momentum. This flow depends on the surface properties as well as the elevation, and is computed using the diffusive wave approximation of Saint-Venant equations (England et al, 2007;Velleux et al, 2008). …”

Section: Multi-hydro Modelmentioning

confidence: 99%

Scale effect challenges in urban hydrology highlighted with a distributed hydrological model

Ichiba

Gires

Tchiguirinskaia

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. Hydrological models are extensively used in urban water management, development and evaluation of future scenarios and research activities. There is a growing interest in the development of fully distributed and grid-based models. However, some complex questions related to scale effects are not yet fully understood and still remain open issues in urban hydrology. In this paper we propose a twostep investigation framework to illustrate the extent of scale effects in urban hydrology. First, fractal tools are used to highlight the scale dependence observed within distributed data input into urban hydrological models. Then an intensive multi-scale modelling work is carried out to understand scale effects on hydrological model performance. Investigations are conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model is implemented at 17 spatial resolutions ranging from 100 to 5 m. Results clearly exhibit scale effect challenges in urban hydrology modelling. The applicability of fractal concepts highlights the scale dependence observed within distributed data. Patterns of geophysical data change when the size of the observation pixel changes. The multi-scale modelling investigation confirms scale effects on hydrological model performance. Results are analysed over three ranges of scales identified in the fractal analysis and confirmed through modelling. This work also discusses some remaining issues in urban hydrology modelling related to the availability of high-quality data at high resolutions, and model numerical instabilities as well as the computation time requirements. The main findings of this paper enable a replacement of traditional methods of "model calibration" by innovative methods of "model resolution alteration" based on the spatial data variability and scaling of flows in urban hydrology.

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“…This model was selected because it is a two-dimensional distributed model, compatible with Arc-GIS and able to model continuous rainfall. Moreover, this model has been extensively tested and applied to different sizes of watersheds, ranging from small to large (Ogden and Julien, 2002;Velleux, 2005;England, 2006). In addition, England et al (2007); Velleux (2005) and Velleux et al (2006Velleux et al ( , 2008 have simulated rainfall.…”

Section: Hydrological Modellingmentioning

confidence: 99%

Flood flow simulations and return period calculation for the Kota Tinggi watershed, Malaysia

Abdullah

Muhammad

Juliën

et al. 2016

J Flood Risk Management

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The City of Kota Tinggi in Malaysia was under more than 5 m of water during the floods in December 2006 and January 2007. The watershed received between 280 and 530 mm of rain in 4 days. These extreme events occurred 3 weeks apart and caused extensive damages. The application of the fully distributed two‐dimensional model two‐dimensional runoff, erosion and export (TREX) to simulate these events and the estimation of the return period of such extreme events are the main objectives of this study. The model performance was very good based on the relative percentage different (3.7%), percent BIAS (overestimated the volume by 1.5%) and Nash–Sutcliffe efficiency coefficient (0.8). The TREX model is successful in simulating extreme flood events. The December 2006 rainstorm event at Kota Tinggi is extremely rare, and this multiday rainstorm had an estimated return period greater than 2000 years. The analysis of the return period shows that multiday rainstorms occur more frequently than single‐day events. In addition, we produce a flood threshold graph by integrating both the hydrological modelling process using TREX and the theoretical formulation of return period. The proposed flood threshold graph is useful in the estimation of the amount of accumulated rainfall from multiday rainfall that can cause flooding on a large watershed like Kota Tinggi.

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Two-dimensional simulations of extreme floods on a large watershed

Cited by 64 publications

References 41 publications

A review of advances in flash flood forecasting

A review of advances in flash flood forecasting

Scale effect challenges in urban hydrology highlighted with a distributed hydrological model

Flood flow simulations and return period calculation for the Kota Tinggi watershed, Malaysia

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