Risk assessment as tool for coastal erosion management

Rangel-Buitrago, Nelson; Neal, William J.; Jonge, Victor N. de

doi:10.1016/j.ocecoaman.2020.105099

Cited by 100 publications

(68 citation statements)

References 57 publications

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“…Another type-1 method is based on the "Coastal-Erosion Risk Index", which is given by the combination of the sub-indexes that describes, respectively, coastal hazard and vulnerability. The hazard subindex is, in turn, composed of variables related to both forcing actions and morphological characteristics, while the vulnerability sub-index deals with socio-economic, ecological and cultural aspects [18,42]. Furthermore, more complex models have been recently developed and account for several separate modules and equations, e.g., the index-based method called CERA2.0, which follows a Source-Pathway-Receptor-Consequence approach and links all components of the system to well identify the risk propagation path [43].…”

Section: Susceptibility/vulnerability Characterizationmentioning

confidence: 99%

“…In other words, CVI is the square root of the product among all variables divided by the number of variables themselves. Based on recent applications of the CVI approach all over the world (e.g., Sekovski et al [17] Koroglu et al [36], Díaz-Cuevas et al [38], Rangel-Buitrago et al [42], Narra et al [43], Hoque et al [44], Mohd et al [45]), three different groups are here used to cluster all variables considered in the susceptibility/vulnerability analysis, i.e., forcing-related aspects, coastal characteristics, and socio-economic activities. Such groups and relevant variables are detailed in the following subsections.…”

Section: Susceptibility/vulnerability Characterizationmentioning

confidence: 99%

“…Since the storm surge controls coastal inundation and erosion, intense and sudden beach flooding often leads to destruction and loss of lives in coastal areas. Although many works use class limits based on absolute storm-surge values (typically in mm), some works use absolute values percentages of the maximum value obtained in the considered area with the aim to have a more representative and objective idea of the storm-surge distribution [18,42]. Historical data are commonly analyzed and used for frequency analyses (e.g., exploiting Gumbel distribution) aimed at finding a reference surge height linked to a specific return period (e.g., 50 years).…”

Section: Forcing Characteristicsmentioning

confidence: 99%

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Coastal Sensitivity/Vulnerability Characterization and Adaptation Strategies: A Review

Anfuso

Postacchini

Luccio

et al. 2021

JMSE

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Coastal area constitutes a vulnerable environment and requires special attention to preserve ecosystems and human activities therein. To this aim, many studies have been devoted both in past and recent years to analyzing the main factors affecting coastal vulnerability and susceptibility. Among the most used approaches, the Coastal Vulnerability Index (CVI) accounts for all relevant variables that characterize the coastal environment dealing with: (i) forcing actions (waves, tidal range, sea-level rise, etc.), (ii) morphological characteristics (geomorphology, foreshore slope, dune features, etc.), (iii) socio-economic, ecological and cultural aspects (tourism activities, natural habitats, etc.). Each variable is evaluated at each portion of the investigated coast, and associated with a vulnerability level which usually ranges from 1 (very low vulnerability), to 5 (very high vulnerability). Following a susceptibility/vulnerability analysis of a coastal stretch, specific strategies must be chosen and implemented to favor coastal resilience and adaptation, spanning from hard solutions (e.g., groins, breakwaters, etc.) to soft solutions (e.g., beach and dune nourishment projects), to the relocation option and the establishment of accommodation strategies (e.g., emergency preparedness).

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Section: Susceptibility/vulnerability Characterizationmentioning

confidence: 99%

Section: Susceptibility/vulnerability Characterizationmentioning

confidence: 99%

Section: Forcing Characteristicsmentioning

confidence: 99%

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Coastal Sensitivity/Vulnerability Characterization and Adaptation Strategies: A Review

Anfuso

Postacchini

Luccio

et al. 2021

JMSE

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“…This method determines the changes between different riverbanks by calculating the distance of the riverbanks to the baseline [ 96 ]. The DSAS method uses an arbitrary baseline as a reference to calculate the change in the riverbank [ 97 ]. Therefore, the minimum distance that would ensure the baseline was on the land was determined.…”

Section: Dataset and Methodsmentioning

confidence: 99%

UAV-based evaluation of morphological changes induced by extreme rainfall events in meandering rivers

et al. 2020

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Morphological changes, caused by the erosion and deposition processes due to water discharge and sediment flux occur, in the banks along the river channels and in the estuaries. Flow rate is one of the most important factors that can change river morphology. The geometric shapes of the meanders and the river flow parameters are crucial components in the areas where erosion or deposition occurs in the meandering rivers. Extreme precipitation triggers erosion on the slopes, which causes significant morphological changes in large areas during and after the event. The flow and sediment amount observed in a river basin with extreme precipitation increases and exceeds the long-term average value. Hereby, erosion severity can be determined by performing spatial analyses on remotely sensed imagery acquired before and after an extreme precipitation event. Changes of erosion and deposition along the river channels and overspill channels can be examined by comparing multi-temporal Unmanned Aerial Vehicle (UAV) based Digital Surface Model (DSM) data. In this study, morphological changes in the Büyük Menderes River located in the western Turkey, were monitored with pre-flood (June 2018), during flood (January 2019), and post-flood (September 2019) UAV surveys, and the spatial and volumetric changes of eroded/deposited sediment were quantified. For this purpose, the DSAS (Digital Shoreline Analysis System) method and the DEM of Difference (DoD) method were used to determine the changes on the riverbank and to compare the periodic volumetric morphological changes. Hereby, Structure from Motion (SfM) photogrammetry technique was exploited to a low-cost UAV derived imagery to achieve riverbank, areal and volumetric changes following the extreme rainfall events extracted from the time series of Tropical Rainfall Measuring Mission (TRMM) satellite data. The change analyses were performed to figure out the periodic morphodynamic variations and the impact of the flood on the selected meandering structures. In conclusion, although the river water level increased by 0.4–5.9 meters with the flood occurred in January 2019, the sediment deposition areas reformed after the flood event, as the water level decreased. Two-year monitoring revealed that the sinuosity index (SI) values changed during the flood approached the pre-flood values over time. Moreover, it was observed that the amount of the deposited sediments in September 2019 approached that of June 2018.

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“…There are different assumption and tools used by research specialists to assess shoreline erosion, for example, Rangel-Buitrago et al 6 and Stanchev et al 7 Used DSAS 3.2 extension in ArcGIS developed by USGS to identify and analyse the changes in shorelines. An optimal approach is to evaluate the risk of erosion in order to appropriate land use planning.…”

mentioning

confidence: 99%

Shoreline Erosion Assessment Modelling for Sohar Region: Measurements, Analysis, and Scenario

Abushandi

Abualkishik

2020

Sci Rep

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the extended coastlines of oman have been forced to change in the last few decades because of urbanization development or by natural disasters. Recently, Oman has suffered from a couple of tornados and cyclones, e.g. Cyclone Gonu on June 1, 2007, making the changes even much more dynamic. in order to protect the coastal regions infrastructure, an accurate estimation of shoreline erosion is required. this research paper presents an assessment of shoreline erosion magnitudes using field measurements coupled with Multiple Linear Regressions Models (MLR) to predict future changes. inverse Distance Weighing and Kriging interpolation methods have been applied in order to visualize shoreline variations from gathered data prospective. The field measurements for the shoreline were taken at 19 different points, the space between the points in a range of 500-700 m approximately. The first field measurements were taken on 19 th 20 th 21 st of June, 2016 while the second field measurements were taken on 14 th 15 th 16 th of November 2016. Pearson correlation shows a strong relationship between the first and the second field trips with an average of 0.83. This significant relationship ensures the applicability of MLRs to project future changes on the shorelines. The results of the MLRs showed severe negative volumetric shoreline erosion with an average of 5.2 m/year with some exceptions at the catchment outlets.

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Risk assessment as tool for coastal erosion management

Cited by 100 publications

References 57 publications

Coastal Sensitivity/Vulnerability Characterization and Adaptation Strategies: A Review

Coastal Sensitivity/Vulnerability Characterization and Adaptation Strategies: A Review

UAV-based evaluation of morphological changes induced by extreme rainfall events in meandering rivers

Shoreline Erosion Assessment Modelling for Sohar Region: Measurements, Analysis, and Scenario

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