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Berz, Gerhard; Kron, Wolfgang; Loster, Thomas; Rauch, Erik; Schimetschek, J.; Schmieder, Jens; Siebert, Asher; Smolka, Anselm; Wirtz, Andrea L.

doi:10.1023/a:1011193724026

Cited by 136 publications

(27 citation statements)

References 7 publications

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“…Flooding is the most frequent and the most damaging of natural disasters globally [1]. From 1995-2015, floods affected 2.3 billion people, killing 157 000 [2].…”

Section: Introductionmentioning

confidence: 99%

A first collective validation of global fluvial flood models for major floods in Nigeria and Mozambique

Bernhofen

Whyman

Trigg

et al. 2018

Environ. Res. Lett.

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Global flood models (GFMs) are becoming increasingly important for disaster risk management internationally. However, these models have had little validation against observed flood events, making it difficult to compare model performance. In this paper, we introduce the first collective validation of multiple GFMs against the same events and we analyse how different model structures influence performance. We identify three hydraulically diverse regions in Africa with recent large scale flood events: Lokoja, Nigeria; Idah, Nigeria; and Chemba, Mozambique. We then evaluate the flood extent output provided by six GFMs against satellite observations of historical flood extents in these regions. The critical success index of individual models across the three regions ranges from 0.45 to 0.7 and the percentage of flood captured ranges from 52% to 97%. Site specific conditions influence performance as the models score better in the confined floodplain of Lokoja but score poorly in Idah's flat extensive floodplain. 2D hydrodynamic models are shown to perform favourably. The models forced by gauged flow data show a greater level of return period accuracy compared to those forced by climate reanalysis data. Using the results of our analysis, we create and validate a three-model ensemble to investigate the usefulness of ensemble modelling in a flood hazard context. We find the ensemble model performs similarly to the best individual and aggregated models. In the three study regions, we found no correlation between performance and the spatial resolution of the models. The best individual models show an acceptable level of performance for these large rivers.

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“…Flooding is the most frequent and the most damaging of natural disasters globally [1]. From 1995-2015, floods affected 2.3 billion people, killing 157 000 [2].…”

Section: Introductionmentioning

confidence: 99%

A first collective validation of global fluvial flood models for major floods in Nigeria and Mozambique

Bernhofen

Whyman

Trigg

et al. 2018

Environ. Res. Lett.

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“…Floods are becoming increasingly serious natural disasters as more and more people move themselves and their assets into flood-prone areas (Berz et al, 2001;Barredo, 2007;Kundzewicz et al, 2010). Present-day levee breaches along rivers under human control create landforms quite different from and, in some cases, much larger than those created by levee breaches along natural rivers, because of houses and paved streets, which control the distribution of sand lobes by acting as channels for flood flow (Nelson and Leclair, 2006), and because the construction of artificial levees raises the potential energy of the flood waters (Gebica and Sokolowski, 2001).…”

Section: Introductionmentioning

confidence: 99%

Application of UAV-SfM photogrammetry and aerial lidar to a disastrous flood: repeated topographic measurement of a newly formed crevasse splay of the Kinu River, central Japan

Izumida

Uchiyama

Sugai

2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Geomorphic impacts of a disastrous crevasse splay that formed in September 2015 and its post-formation modifications were quantitatively documented by using repeated, high-definition digital surface models (DSMs) of an inhabited and cultivated floodplain of the Kinu River, central Japan. The DSMs were based on pre-flood (resolution: 2 m) and post-flood (resolution: 1 m) aerial light detection and ranging (lidar) data from January 2007 and September 2015, respectively, and on structure-from-motion (SfM) photogrammetry data (resolution: 3.84 cm) derived from aerial photos taken by an unmanned aerial vehicle (UAV) in December 2015. After elimination of systematic errors among the DSMs and down-sampling of the SfM-derived DSM, elevation changes on the order of 10 −1 m -including not only topography but also growth of vegetation, vanishing of flood waters, and restoration and repair works -were detected. Comparison of the DSMs showed that the volume eroded by the flood was more than twice the deposited volume in the area within 300-500 m of the breached artificial levee, where the topography was significantly affected. The results suggest that DSMs based on a combination of UAV-SfM and lidar data can be used to quantify, rapidly and in rich detail, topographic changes on floodplains caused by floods.

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“…Floods and windstorms cause about one third of the total economic losses related to natural hazards worldwide [1]. Globally, no other natural hazard occurs as frequently as floods [2]. An important physical process related to floods is hydraulic bank erosion, i.e., the detachment and entrainment of streambank material due to hydrodynamic forces [3].…”

Section: Introductionmentioning

confidence: 99%

“…It is acknowledged that riparian vegetation, or vegetation growing on and adjacent to streambanks, islands and bars, (1) reduces sediment mobilization due to increases in material strength as well as flow velocity (and thus hydraulic shear stress) [16][17][18], (2) decreases water pollution [19,20], (3) acts as water temperature regulators [21] and (4) in-stream wood provides habitat for microbial decomposers, creating moist microsites and fish-friendly environments by forming pools and riffles that improve biodiversity [22][23][24]. Riparian vegetation is therefore important because of its multifunctionality to the wider ecosystem.…”

Section: Introductionmentioning

confidence: 99%

“…However, hydraulic bank erosion is highly complex and is influenced by numerous factors at different spatiotemporal scales. These include (1) the continuous change of the channel hydrogeomorphology pre, post and during erosion events [9,28], (2) the heterogeneity of geotechnical streambank properties for overall bank stability (i.e., cohesion, friction angle, porosity [29]), (3) weathering processes enhancing streambank erodibility [30,31], (4) the presence of roots (i.e., different root densities dependent on vegetation type [32][33][34]), (5) fluctuating flow properties such as magnitude, duration, event peak and variability [35] and (6) spatiotemporal distribution of precipitation affecting (2) and (5). In theory, all these factors should be considered for bank erosion models at catchment scale, which is why many numerical models require high levels of site-specific parametrization [36].…”

Section: Introductionmentioning

confidence: 99%

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A New Framework to Model Hydraulic Bank Erosion Considering the Effects of Roots

Gasser

Perona

Dorren

et al. 2020

Water

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Floods and subsequent bank erosion are recurring hazards that pose threats to people and can cause damage to buildings and infrastructure. While numerous approaches exist on modeling bank erosion, very few consider the stabilizing effects of vegetation (i.e., roots) for hydraulic bank erosion at catchment scale. Taking root reinforcement into account enables the assessment of the efficiency of vegetation to decrease hydraulic bank erosion rates and thus improve risk management strategies along forested channels. A new framework (BankforNET) was developed to model hydraulic bank erosion that considers the mechanical effects of roots and randomness in the Shields entrainment parameter to calculate probabilistic scenario-based erosion events. The one-dimensional, probabilistic model uses the empirical excess shear stress equation where bank erodibility parameters are randomly updated from an empirical distribution based on data found in the literature. The mechanical effects of roots are implemented by considering the root area ratio (RAR) affecting the material dependent critical shear stress. The framework was validated for the Selwyn/Waikirikiri River catchment in New Zealand, the Thur River catchment and the Sulzigraben catchment, both in Switzerland. Modeled bank erosion deviates from the observed bank erosion between 7% and 19%. A sensitivity analysis based on data of vertically stable river reaches also suggests that the mechanical effects of roots can reduce hydraulic bank erosion up to 100% for channels with widths < 15.00 m, longitudinal slopes < 0.05 m m −1 and a RAR of 1% to 2%. The results show that hydraulic bank erosion can be significantly decreased by the presence of roots under certain conditions and its contribution can be quantified considering different conditions of channel geometry, forest structure and discharge scenarios.

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Untitled

Cited by 136 publications

References 7 publications

A first collective validation of global fluvial flood models for major floods in Nigeria and Mozambique

A first collective validation of global fluvial flood models for major floods in Nigeria and Mozambique

Application of UAV-SfM photogrammetry and aerial lidar to a disastrous flood: repeated topographic measurement of a newly formed crevasse splay of the Kinu River, central Japan

A New Framework to Model Hydraulic Bank Erosion Considering the Effects of Roots

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