scholarly journals The Shoreline Retreat and Spatial Analysis over the Coastal Water of Belawan

INSIST ◽  
2016 ◽  
Vol 1 (1) ◽  
pp. 65 ◽  
Author(s):  
A. Perwira Mulia Tarigan ◽  
Wiwin Nurzanah

Abstract – An examination of shoreline retreat is conducted over the muddy coast in the vicinities of the port of Belawan. The related sea level rise is estimated using the well-known Bruun Rule based on the characteristics of mud profile prevalent along the eastern coast of North Sumatera Province. The spatial analysis involved is done utilizing the concept and procedure of GIS. The averaged shoreline retreat over the hot spot area of erosion, i.e. 18 m per year, implies that the relative rate of sea level rise is in the range of 14 to 18 mm per year, indicating an extremely severe rate. In addition, three other cases of simple GIS applications related to coastal water of the port are spatially demonstrated.  Keywords –  coastal water, coastal erosion, sea level rise, and GIS

2004 ◽  
Vol 43 (3-4) ◽  
pp. 157-171 ◽  
Author(s):  
J. Andrew G. Cooper ◽  
Orrin H. Pilkey

2017 ◽  
Vol 862 ◽  
pp. 34-40 ◽  
Author(s):  
Marita Ika Joesidawati ◽  
Suntoyo

Changes in the shoreline setback is a major threat of coastal areas dominated by sandy beaches and coastal lowlands. The impacts of sea level rise itself will be greatly felt by coastal regions in the island nations, such as Indonesia. Tuban is one of northern coastal areas in East Java, which includes the areas where the condition of beaches damaged. Thus, it is necessary to investigate the characteristics of beaches in Tuban, and how much the sea level rise occurs in Tuban district as well as the extent of its influence on the shorelines of Tuban. The calculation of sea level rise was predicted using the Least Square Method with tidal data of Semarang city in 1985-2014 which was later adopted as the tidal of Tuban, and the sea level rise at the beaches in Tuban, which was estimated at 0,024 meter annually by implementing the equation of y = 0.002x + 0.751. In the year of 2050 and 2100, the rise of the sea level reaches 2.55 m and 3.54 m respectively. The most appropriate method used is the Hennecke method, with the error value of 0.27%. The error value of Hennecke method is smaller than the error value of Bruun Rule method, which reaches 0.38%. Using Hennecke method, the prediction of the shoreline changes in Tuban with the starting point of the year of 2008 shows that the average shoreline retreat in the year of 2050 is about 94.71 meters and in 2100 is about 234.2 m. However, by using the method of Bruun Rule, the average shoreline retreat in the year of 2050 is about 161.27 m, and in the year of 2100 is about 349.16 m. The adaptation strategies that can be conducted to minimize the impacts are (i) protective pattern, (ii) accommodative pattern, and it is better to have a Strategic Area Construction Plan.


2021 ◽  
Vol 13 (8) ◽  
pp. 1424
Author(s):  
Lucas Terres de Lima ◽  
Sandra Fernández-Fernández ◽  
João Francisco Gonçalves ◽  
Luiz Magalhães Filho ◽  
Cristina Bernardes

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of free and open-source models to estimate the sea-level impact can contribute to improve coastal management. This study aims to develop and validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE)—a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the sea-level rise impact module of TerrSet—Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses the Bruun rule formula implemented in GEE and can determine the coastline retreat of a profile by creatting a simple vector line from topo-bathymetric data. The model shows a very high correlation (0.97) with a classical Bruun rule study performed in the Aveiro coast (NW Portugal). Therefore, the achieved results disclose that the GEE platform is suitable to perform these analysis. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific community.


Author(s):  
Lucas Terres de Lima ◽  
Sandra Fernández-Fernández ◽  
João Francisco Gonçalves ◽  
Luiz Magalhães Filho ◽  
Cristina Bernardes

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence 15 of Free and Open-Source Models to estimate the sea-level impact can contribute to better coastal 16 management. This study aims to develop and to validate two different models to predict the 17 sea-level rise impact supported by Google Earth Engine (GEE) – a cloud-based platform for plan-18 etary-scale environmental data analysis. The first model is a Bathtub Model based on the uncer-19 tainty of projections of the Sea-level Rise Impact Module of TerrSet - Geospatial Monitoring and 20 Modeling System software. The validation process performed in the Rio Grande do Sul coastal 21 plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses Bruun Rule for-22 mula implemented in GEE and is capable to determine the coastline retreat of a profile through the 23 creation of a simple vector line from topo-bathymetric data. The model shows a very high correla-24 tion (0.97) with a classical Bruun Rule study performed in Aveiro coast (NW Portugal). The GEE 25 platform seems to be an important tool for coastal management. The models developed have been 26 openly shared, enabling the continuous improvement of the code by the scientific community.


Author(s):  
Lucas Terres de Lima ◽  
Sandra Fernández-Fernández ◽  
João Francisco Gonçalves ◽  
Luiz Magalhães Filho ◽  
Cristina Bernardes

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of Free and Open-Source Models to estimate the sea-level impact can contribute to better coastal man-agement. This study aims to develop and to validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE) – a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the Sea-level Rise Impact Module of TerrSet - Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses Bruun Rule formula implemented in GEE and is capable to determine the coastline retreat of a profile through the creation of a simple vector line from topo-bathymetric data. The model shows a very high cor-relation (0.97) with a classical Bruun Rule study performed in Aveiro coast (NW Portugal). The GEE platform seems to be an important tool for coastal management. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific commu-nity.


2021 ◽  
Vol 9 (9) ◽  
pp. 974
Author(s):  
Maurizio D’Anna ◽  
Deborah Idier ◽  
Bruno Castelle ◽  
Sean Vitousek ◽  
Goneri Le Cozannet

Long-term (>decades) coastal recession due to sea-level rise (SLR) has been estimated using the Bruun Rule for nearly six decades. Equilibrium-based shoreline models have been shown to skillfully predict short-term wave-driven shoreline change on time scales of hours to decades. Both the Bruun Rule and equilibrium shoreline models rely on the equilibrium beach theory, which states that the beach profile shape equilibrates with its local wave and sea-level conditions. Integrating these two models into a unified framework can improve our understanding and predictive skill of future shoreline behavior. However, given that both models account for wave action, but over different time scales, a critical re-examination of the SLR-driven recession process is needed. We present a novel physical interpretation of the beach response to sea-level rise, identifying two main contributing processes: passive flooding and increased wave-driven erosion efficiency. Using this new concept, we analyze the integration of SLR-driven recession into equilibrium shoreline models and, with an idealized test case, show that the physical mechanisms underpinning the Bruun Rule are explicitly described within our integrated model. Finally, we discuss the possible advantages of integrating SLR-driven recession models within equilibrium-based models with dynamic feedbacks and the broader implications for coupling with hybrid shoreline models.


2020 ◽  
Vol 89 (sp1) ◽  
pp. 145
Author(s):  
Silamban Dhanalakshmi ◽  
Roop Singh Kankara

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