Assessment on Shoreline Retreat in Response to Sea Level Rise – Chennai Coast

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


Author(s):  
Sinta FLORENTINA ◽  
Tomoaki NAKAMURA ◽  
Yonghwan CHO ◽  
Norimi MIZUTANI ◽  
Masayuki TAKEUCHI

2011 ◽  
Vol 67 (2) ◽  
pp. I_1196-I_1200 ◽  
Author(s):  
Taichi SUGAWA ◽  
Keiko UDO ◽  
Nobuo MIMURA ◽  
Akira MANO

2021 ◽  
Vol 8 ◽  
Author(s):  
Pau Luque ◽  
Lluís Gómez-Pujol ◽  
Marta Marcos ◽  
Alejandro Orfila

Sea-level rise induces a permanent loss of land with widespread ecological and economic impacts, most evident in urban and densely populated areas. Potential coastline retreat combined with waves and storm surges will result in more severe damages for coastal zones, especially over insular systems. In this paper, we quantify the effects of sea-level rise in terms of potential coastal flooding and potential beach erosion, along the coasts of the Balearic Islands (Western Mediterranean Sea), during the twenty-first century. We map projected flooded areas under two climate-change-driven mean sea-level rise scenarios (RCP4.5 and RCP8.5), together with the impact of an extreme event defined by the 100-year return level of joint storm surges and waves. We quantify shoreline retreat of sandy beaches forced by the sea-level rise (scenarios RCP4.5 and RCP8.5) and the continuous action of storm surges and waves (modeled by synthetic time series). We estimate touristic recreational services decrease of sandy beaches caused by the obtained shoreline retreat, in monetary terms. According to our calculations, permanent flooding by the end of our century will extend 7.8–27.7 km2 under the RCP4.5 scenario (mean sea-level rise between 32 and 80 cm by 2100), and up to 10.9–36.5 km2 under RCP8.5 (mean sea-level rise between 46 and 103 cm by 2100). Some beaches will lose more than 50% of their surface by the end of the century: 20–50% of them under RCP4.5 scenario and 25–60% under RCP8.5 one. Loss of touristic recreational services could represent a gross domestic product (GDP) loss up to 7.2% with respect to the 2019 GDP.


2021 ◽  
Author(s):  
Mitchell Harley ◽  
Gerd Masselink ◽  
Amaia Ruiz de Alegría-Arzaburu ◽  
Nieves Valiente ◽  
Tim Scott

Abstract Extreme storms cause extensive beach-dune erosion and are universally considered to enhance coastal erosion due to sea-level rise (SLR). However, extreme storms can also have a positive contribution to the nearshore sediment budget by exchanging sediment between the lower and upper shoreface and/or between adjacent headlands, potentially mitigating adverse SLR impacts. Here we use three high-resolution morphological datasets of extreme storm-recovery sequences from Australia, the UK and Mexico to quantify the nearshore sediment budget and relate these episodic volume changes to long-term coastal forecasts. We show that sediment gains over the upper shoreface and beach were very significant (58-140 m3/m) and sufficient to offset decades of predicted shoreline retreat due to SLR, even for an upper SSP5-8.5 scenario. It is evident that increased confidence in shoreline predictions due to SLR relies fundamentally on robust quantitative understanding of the sediment budget, in particular any long-term contribution of sediment transport from outside the nearshore region.


2013 ◽  
Vol 16 (1) ◽  
pp. 104-113 ◽  

<p>The present study investigates recent and future evolution of the beach zone of Almiros Bay, one of the most touristic developed beaches of north Crete, in relation to its morphodynamic setting and the anticipated sea level rise. The beach zone is exposed to northerly winds, with maximum wave heights and periods of 4.3 m and 9 s, respectively. The comparison of the aerial photographs (1982-1996) and a satellite image of 2007 have revealed an extended retreat of the beach zone, with its highest retreating rates (i.e. 0.6-0.8 m y-1 for the last 25 years) found at its central part. Moreover, an estimation of the future shoreline retreat, due to the anticipated sea level rise (i.e. 0.38 or 1 m for the year 2100), has shown that there is a potential coastal zone loss from 48% up to 100%, respectively. A gross evaluation of the economical impact due to the aforementioned beach loss accounts to approximately from $ 270,000 up to $ 720.000, annually.</p>


2022 ◽  
Author(s):  
Oula Amrouni ◽  
Essam Heggy ◽  
Abderraouf Hzami

Abstract The alarming vulnerability of low-lying sandy beaches to the acceleration of global sea level rise has been confirmed in the recent IPCC AR6 report. The situation is worsened by increasing coastal erosion, resulting in additional shoreline retreat of sandy beaches along several semi-arid urban coastal areas around the globe. The additional shoreline retreats from erosion are indicative of the rising imbalance in coastal sedimentary processes, which are a direct consequence of changes in precipitation patterns, urban growth, and change in land use. To quantify the magnitude and timescale of both coastal erosion and sea-level rise (SLR) in generating shoreline retreat of sandy beaches in semi-arid urban areas, we combine photogrammetric and statistical methods to measure and forecast the decadal evolution of these coastlines using two well-characterized sites that are hypothesized herein to be globally representative of these types of coasts undergoing rapid urban growth. We use multi-decadal shoreline positioning and land use classification surveys of the Southern California (SC, USA) and the Hammamet-North (HAM, Tunisia) beaches from aerial and orbital photogrammetric images, combined with the Digital Shoreline Analysis System, for the period from 1985 to 2018. Our results suggest that the current average shoreline retreat rates of sandy beaches range from -0.75 to -1.24 m/yr in SC and from -0.21 to -4.49 m/yr in HAM under similar aridity, land coverage and precipitation patterns. The observed decadal changes in shoreline positions along these semi-arid urban coastal areas are found to be accentuated by anthropogenic drivers associated with extensive urbanization, causing sediment imbalance at the coastline, adding up to the effect of the accelerating SLR. We assess that ~81% and 57% of the observed shoreline retreat was due to SLR, and 19% to 43% due to coastal erosion from urban growth along SC and HAM beaches, respectively. Using these measured rates, we establish a semi-empirical numerical model that combines urban growth and the observed shoreline retreat rate to forecast retreat rates through 2100 for both of our study areas, inferred herein to be representative of other global semi-arid urban coasts. Our model suggests that future average total shoreline retreat rates, accounting for both urban growth and SLR, range from -2 to -4 m/yr for SC and HAM sandy beaches, respectively, through 2100. The above suggests that if no mitigation is made, by 2100 the cumulative shoreline retreat in these urban areas could significantly exceed the Global Scale Assessment Model’s [46] cumulative projected average retreat of -30 m, confirming the alarming vulnerability of the semi-arid coastal urban areas that would need intensive and costly beach nourishment to control increasing shoreline erosion.


2020 ◽  
Author(s):  
Panagiotis Athanasiou ◽  
Ap van Dongeren ◽  
Alessio Giardino ◽  
Michalis Vousdoukas ◽  
Roshanka Ranasinghe ◽  
...  

&lt;p&gt;Climate change driven sea level rise (SLR) is expected to rise with even higher rates during the second half of the present century. This will exacerbate shoreline retreat of sandy coasts, which comprise one third of the global coastline. Sandy coasts have high touristic and ecological value while they are the first level of defense against storms, protecting valuable infrastructures and buildings. Therefore, in recent years, large scale risk assessments are considered useful tools for the guidance of policy makers to identify high risk hotspots.&amp;#160; Reliable input data at this scale are required in order to make useful estimations. Among others, crucial data to assess the impact of SLR on shoreline retreat are the detection of different coastal types and, in particular, of sandy erodible beaches, and the nearshore slope, which is usually assumed to be uniform.&lt;/p&gt;&lt;p&gt;The important issue of input data uncertainty and spatial variation and consequent impact on predictions has been so far ignored in most large-scale studies. Estimates of shoreline retreat are however very sensitive to the variation in these inputs. Here we quantify SLR driven potential shoreline retreat and consequent land loss in Europe during the 21st century by employing different combinations of geophysical datasets for (a) the location of sandy beaches and (b) their nearshore slopes. For the estimation of the shoreline retreat, the Bruun Rule is used, which offers a suitable approach for a first approximation of erosion impacts at large scales. Sea level rise projections associated with the moderate-emission- mitigation-policy (RCP4.5) and the high-end, business-as-usual scenario (RCP8.5) are used as boundary conditions. The location of sandy beaches is determined from two different datasets. One is based on manual visual estimation from satellite images and the other on automatic detection from satellite images using machine learning techniques. For nearshore slopes we apply the commonly used constant slope assumption of 1:100 and a newly produced global dataset which captures the spatial variation of coastal slopes.&lt;/p&gt;&lt;p&gt;With this approach, we create four different combinations for each SLR scenario, for which we estimate and compare land loss at EU, country and NUTS3 regional level. We find that the land loss estimations for each combination can differ significantly, especially at the regional and local level. At the European or country level, even though differences in total land loss projections can be significant, they can be concealed by the spatial aggregation of the results. Using data-based spatially-varying nearshore slope data, a European averaged median shoreline retreat of 97 m (54 m) is projected under RCP 8.5 (4.5) by year 2100, relative to the baseline year 2010. This retreat would translate to 2,500 km2 (1,400 km2) of land loss. A variance-based global sensitivity analysis indicates that the uncertainty associated with the choice of geophysical datasets can contribute up to 45% (26%) of the variance in land loss projections for Europe by 2050 (2100).&lt;/p&gt;


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