Remote Sensed and In Situ Data: an integrated approach for Coastal Risk Assessment

Korean coasts are exposed to high risks such as storm surge, storm-induced high waves and wave overtopping. Also, localized heavy rainfall events have occurred frequently due to climate change, too. Especially, since coastal urban areas depend heavily on pump and pipe systems, extreme rainfalls that exceed the design capacity of drainage facility result in increasing inland flood damage. Nevertheless, the population in Korea is concentrated in the coastal areas and the value and density of coastal utilization are increasing. In this study, the risk of hybrid disasters in the coastal areas was assessed for safe utilization and value enhancement of coastal areas. The framework of the coastal risk assessment has been adopted from the concept of climate change vulnerability of the IPCC(2001). Coastal Risk Index(CRI) in this study was defined as a function of Exposure and Sensitivity exclude Adaptive Capacity using GIS-based DBs. Indicators of Exposure consisted of a storm surge, storm-induced high waves, wave overtopping and rainfalls. Indicators of Sensitivity consisted of human(population density), property(buildings and roads), and geography(inundation area). All these indicators were gathered from government agencies, numerical model experiments(ADCIRC, unSWAN, FLOW3D and XP-SWMM model), and field surveys(Drone & Lidar survey). And then spatial analysis was performed by using a GIS program after passing the quality control and analyzed data were standardized and classified 4 grades; Attention(blue color), Caution(yellow color), Warning(orange color) and Danger(red color). This frame of risk assessment was first applied to Marine City, Haeundae in Busan, Korea which was heavily damaged by the typhoon CHABA in 2018. According to the assessment results, it was confirmed that the results were in good agreement with the observation data and damage range. At present, the study area of risk assessment is expanding to other areas. The results of coastal risk assessment are used as reference indicators to identify and prevent the cause of coastal disasters, establish countermeasures, determine the development or management of coastal areas based on GIS, thus will contribute to effective and safe coastal management.

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BARBADOS COASTAL RISK ASSESSMENT AND MANAGEMENT PROGRAMME

Coastal Engineering Proceedings ◽

10.9753/icce.v36.risk.52 ◽

2018 ◽

pp. 52

Author(s):

Kevin MacIntosh ◽

Derek Williamson ◽

Matthew Armstrong ◽

Leo Brewster ◽

Ricardo Arthur

Keyword(s):

Risk Assessment ◽

Coastal Zone ◽

Coastal Zone Management ◽

Coastal Environments ◽

Management Planning ◽

Zone Management ◽

Coastal Risk Assessment ◽

The Government ◽

Coastal Risk ◽

Risk Assessment And Management

Monitoring of coastal environments is critical to understanding the responses of the natural environment to human interventions. The ability to definitively attribute impacts to a development versus those which are part of the natural variation of a dynamic system is a valuable tool to understanding the successes and failures of coastal zone management planning. The Coastal Zone Management Unit of the Government of Barbados (CZMU) undertook the Coastal Risk Assessment and Management (CRMP) project to define the baseline conditions and risks for the entire coastline of Barbados in order to have this comprehensive database upon which to base future decisions and coastal planning. This paper will focus on three of the nine baseline studies and the unique approaches used, and challenges encountered, along the way.

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Post-storm recuperation as a stepping-stone towards long-term integrated modelling in steep beaches

10.5194/egusphere-egu2020-17470 ◽

2020 ◽

Author(s):

Katerina Kombiadou ◽

Susana Costas ◽

Dano Roelvink ◽

Robert McCall

Keyword(s):

Methodological Approach ◽

Integrated Approach ◽

Integrated Modelling ◽

Dune System ◽

Critical System ◽

Event Scale ◽

Nearshore Processes ◽

In Situ Data

Integrated modelling approaches for the evolution of the entire dune-beach system have become increasingly sought-after, not only for management purposes, but also to allow better understanding of the feedbacks between processes and scales and a closer approximation of where critical system thresholds may lie. The effective reproduction of both destructive and constructive processes over a broad spectrum of temporal scales is crucial to any, such, integrated approach. Recent improvements of the XBeach-Duna model regarding approximation of nearshore processes were tested using in-situ data from the Emma storm impacts on a reflective beach (Praia de Faro, in S. Portugal). The model results compare well with measured post-storm and recovered profiles, showing high model skill under both erosive and constructive regimes. Building from this event-scale analysis, a gradual increase of temporal windows in simulated forcing conditions, through wave schematisation, is presented and discussed in terms of optimisation between gains in simulation time and losses in geomorphic change information. This methodological approach and findings are the basis that will allow passing on to dependable, long-term simulations of the beach-dune system evolution.&#160;Acknowledgements: The work was implemented in the framework of the ENLACE project (ref. 28949 FEDER), funded by FCT (Funda&#231;&#227;o para a Ci&#234;ncia e a Tecnologia)

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Error estimation of buoy, altimeter, and model significant wave height from triple collocation technique

10.5194/egusphere-egu21-14753 ◽

2021 ◽

Author(s):

Guillaume Dodet ◽

Jean-Raymond Bidlot ◽

Mickaël Accensi ◽

Mathias Alday ◽

Saleh Abdalla ◽

...

Keyword(s):

Wave Height ◽

Significant Wave Height ◽

Wave Model ◽

Sea State ◽

Significant Wave ◽

In Situ Data ◽

Collocation Technique ◽

Coastal Risk ◽

Marine Engineering

Ocean wave information is of major importance for a number of applications including climate studies, safety at sea, marine engineering (offshore and coastal), and coastal risk management. Depending on the scales and regions of interest, several data sources may be considered (e.g. in situ data, VOS observations, altimeter records, numerical wave model), each one with its pros and cons. In order to optimize the use of multiple source wave information (e.g. through assimilation scheme in NWP), the error characteristics of each measurement system need to be investigated and inter-compared. In this study, we use triple collocation technique to estimate the random error variances of significant wave height from in situ, altimeter and model data. The buoy dataset is a selection of ~100 in-situ measuring stations provided by the CMEMS In-Situ Thematic Assembly Center. The altimeter dataset is composed of the ESA Sea State CCI V1.1 L2P product. The model dataset is the result of WW3 Ifremer hindcast run forced with ERA5 winds using the recently updated T475 parameterization. In comparisons to previous studies using similar techniques, the large triple collocation dataset (~450 000 matchups in total) generated for this study provides some new insights on the error variability within in situ stations, satellite missions and upon sea state conditions.Moreover, the results of the triple collocation technique help developing improved calibration of the altimeter missions included in the ESA Sea State CCI V1.1 dataset.

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