Comparison of hydrodynamic models of different complexities to model floods with emergency storage areas

Chatterjee, Chandranath; Förster, Saskia; Bronstert, Axel

doi:10.1002/hyp.7079

Cited by 82 publications

(55 citation statements)

References 18 publications

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“…Savage et al (2015) and Fewtrell et al (2008) describe the effects of spatial scale on inundation modelling. Altarejos-García et al (2012), Chatterjee et al (2008), Bates (2001, 2002), Kvočka et al (2015), and Neal et al (2012b) discuss the effects of the chosen inundation model, its parametrization, and the role of input data on flood modelling results. Other uncertainties in flood modelling outputs are related to uncertainties in levee heights (Sanyal, 2017) or digital elevation models (Saksena and Merwade, 2015).…”

Section: Introductionmentioning

confidence: 99%

Effects of variability in probable maximum precipitation patterns on flood losses

Zischg

Felder

Weingartner

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. The assessment of the impacts of extreme floods is important for dealing with residual risk, particularly for critical infrastructure management and for insurance purposes. Thus, modelling of the probable maximum flood (PMF) from probable maximum precipitation (PMP) by coupling hydrological and hydraulic models has gained interest in recent years. Herein, we examine whether variability in precipitation patterns exceeds or is below selected uncertainty factors in flood loss estimation and if the flood losses within a river basin are related to the probable maximum discharge at the basin outlet. We developed a model experiment with an ensemble of probable maximum precipitation scenarios created by Monte Carlo simulations. For each rainfall pattern, we computed the flood losses with a model chain and benchmarked the effects of variability in rainfall distribution with other model uncertainties. The results show that flood losses vary considerably within the river basin and depend on the timing and superimposition of the flood peaks from the basin's sub-catchments. In addition to the flood hazard component, the other components of flood risk, exposure, and vulnerability contribute remarkably to the overall variability. This leads to the conclusion that the estimation of the probable maximum expectable flood losses in a river basin should not be based exclusively on the PMF. Consequently, the basin-specific sensitivities to different precipitation patterns and the spatial organization of the settlements within the river basin need to be considered in the analyses of probable maximum flood losses.

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Section: Introductionmentioning

confidence: 99%

Effects of variability in probable maximum precipitation patterns on flood losses

Zischg

Felder

Weingartner

et al. 2018

Hydrol. Earth Syst. Sci.

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“…Hydrodynamic modeling can play a significant role in de-termining the values of these parameters. Several numerical models, using different computational algorithms, have been developed in order to solve the Saint Venant equations for river and floodplain flow simulation (Chatterjee et al, 2008). Software tools, such as the MIKE 11 hydraulic model developed at the Danish Hydraulic Institute (DHI, 1997) and the HEC-RAS (HEC River Analysis System) model from the US Army Corps of Engineers (USACE1, 2002), have been used extensively for the dynamic one-dimensional flow simulation in rivers.…”

Section: Introductionmentioning

confidence: 99%

A hydro-sedimentary modeling system for flash flood propagation and hazard estimation under different agricultural practices

Kourgialas

Karatzas

2014

Nat. Hazards Earth Syst. Sci.

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Abstract.A modeling system for the estimation of flash flood flow velocity and sediment transport is developed in this study. The system comprises three components: (a) a modeling framework based on the hydrological model HSPF, (b) the hydrodynamic module of the hydraulic model MIKE 11 (quasi-2-D), and (c) the advection-dispersion module of MIKE 11 as a sediment transport model. An important parameter in hydraulic modeling is the Manning's coefficient, an indicator of the channel resistance which is directly dependent on riparian vegetation changes. Riparian vegetation's effect on flood propagation parameters such as water depth (inundation), discharge, flow velocity, and sediment transport load is investigated in this study. Based on the obtained results, when the weed-cutting percentage is increased, the flood wave depth decreases while flow discharge, velocity and sediment transport load increase. The proposed modeling system is used to evaluate and illustrate the flood hazard for different riparian vegetation cutting scenarios. For the estimation of flood hazard, a combination of the flood propagation characteristics of water depth, flow velocity and sediment load was used. Next, a well-balanced selection of the most appropriate agricultural cutting practices of riparian vegetation was performed. Ultimately, the model results obtained for different agricultural cutting practice scenarios can be employed to create flood protection measures for flood-prone areas. The proposed methodology was applied to the downstream part of a small Mediterranean river basin in Crete, Greece.

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“…This was compared to a simple 1D model, with two storage areas defined by elevation-volume relationships. Chatterjee et al (2008) found that there was very little difference between the two models in the peak flow magnitude, but they differed considerably in terms of timing especially of the emptying of the polders, which took 4 days for the 1D-2D model and 24 days for the 1D model. Forster et al (2008) showed the steepness of the hydrograph determined how effective polders were in terms of reducing peak flow magnitudes downstream.…”

Section: Hydraulic Modelsmentioning

confidence: 94%

“…This means that water is only stored temporarily and can be managed to reduce the rising limb and peak flow and then release water on the falling limb Chatterjee et al, 2008). If the storage area is utilised too early then the detained volume is taken from the rising limb and is full by the time the peak flow arrives.…”

Section: Wetlandsmentioning

confidence: 99%

“…These scenarios either alter channel dimensions or planforms or how the river interacts with its floodplain. further study by Chatterjee et al (2008) and Forster et al (2008) investigated the effects of emergency storage areas further, especially circumstances where the retention and release of water is controlled. The MIKE11 1D model was used to represent the channel, which was linked to the MIKE21 2D model to represent the polders using a 50m resolution DEM.…”

Section: Hydraulic Modelsmentioning

confidence: 99%

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Rural land management impacts on catchment scale flood risk

Pattison¹

2010

Role of Hydrology in Managing Consequences of a Changing Global Environment

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The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source• a link is made to the metadata record in Durham E-Theses• the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full Durham E-Theses policy for further details. Most approaches to this problem aim to upscale from individual grid cells to whole catchments, something that restricts the complexity of possible process representation, produces models that may not be parsimonious with the data needed to calibrate them and, faced with data uncertainties, provides computational limitations on the extent to which model uncertainty can be fully explored. Rather than upscaling to problems of concern, this thesis seeks to downscale from locations of known flood risk, as a means of identifying where land use management changes might be beneficial and then uses numerical modelling to identify the kinds of management changes required in those downscaled locations. Thus, the aim of this thesis is to test an approach to understanding the impacts of rural land management upon flood risk based upon catchment-to-source downscaling.This thesis uses the case study of the River Eden catchment (2400 km 2 ) as a test (1) it was shown to have a significant impact on downstream flood risk; and (2) it had range of data and information needed for modelling land use changes.The second part of this thesis explored the land management scenarios that could be used to reduce flood risk at the catchment scale. The scenarios to be tested were determined through a stakeholder participation approach, whereby workshops were held to brainstorm and prioritise land management options, and then to identify specific locations within the Eamont sub-catchment where they could tested. There were two main types of land management scenarios chosen: (1) landscape-scale changes, including afforestation and compaction; and (2) corresponding to a 5.8% decrease in peak discharge. A key conclusion is that land management practices have been shown to have an effect on catchment scale flooding, even for extreme flood events. However, the effect of land management scenarios are both spatially and temporally dependent i.e. the same land management practice has different effects depending on where it is implemented, and when implemented in the same location has different effects on different flood events.

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Comparison of hydrodynamic models of different complexities to model floods with emergency storage areas

Cited by 82 publications

References 18 publications

Effects of variability in probable maximum precipitation patterns on flood losses

Effects of variability in probable maximum precipitation patterns on flood losses

A hydro-sedimentary modeling system for flash flood propagation and hazard estimation under different agricultural practices

Rural land management impacts on catchment scale flood risk

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