Sea-level rise and coastal vulnerability: an assessment of Andhra Pradesh coast, India through remote sensing and GIS

Rao, K. Nageswara; Subraelu, P.; Rao, T. V.; Malini, B. Hema; Ratheesh, R.; Bhattacharya, S.; Rajawat, A. S.; Ajai,

doi:10.1007/s11852-009-0042-2

Cited by 195 publications

(65 citation statements)

References 32 publications

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“…Geomorphology also considers the relative resistance of various geological formations occurring at the shoreline to marine erosion processes. Thus, geomorphology is ranked qualitatively according to the relative strength of the coastal landforms and rocks [22] outcropping along the northern coast of the Peloponnese. The predominant coastal landforms in the study area (ranging from very high to very low vulnerability) identified during the field coastal geomorphological mapping were coarse sandy to gravelly beaches, which developed mainly at the aprons of coastal alluvial cones and fan deltas, and marine cliffs composed of various rock types, such as marls, conglomerates, and limestones (Fig.…”

Section: Geological -Structural Variablesmentioning

confidence: 99%

“…Thus, an index that is based on physical variables, such as coastal landforms, geology, relief, shoreline displacement, relative sea-level change, tide range and wave height, has been used to assess the sensitivity of coasts in the USA, Europe, Brazil, India and Argentina [16,[19][20][21][22]. A similar formula, referred to as a sensitivity index, was used by Shaw et al [23] along the Canadian coast while Catto, in an attempt to study the coastal erosion of the island of Newfoundland, proposed two separate indices: a newly developed Coastal Erosion Index (CEI) for the assessment of the sensitivity to short-term erosion and a Coastal Sensitivity Index for the assessment of longer term coastal erosion and susceptibility to sea-level rise [24].…”

Section: Introductionmentioning

confidence: 99%

“…A similar formula, referred to as a sensitivity index, was used by Shaw et al [23] along the Canadian coast while Catto, in an attempt to study the coastal erosion of the island of Newfoundland, proposed two separate indices: a newly developed Coastal Erosion Index (CEI) for the assessment of the sensitivity to short-term erosion and a Coastal Sensitivity Index for the assessment of longer term coastal erosion and susceptibility to sea-level rise [24]. Nageswara Rao et al [22] proposed a coastal index by integrating the differentially weighted rank values for five of the abovementioned variables, including geomorphology, coastal slope, shoreline change, spring-tide range and significant wave height. Several studies considered additional parameters for estimating coastal sensitivity.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of the sensitivity of the southern coast of the Gulf of Corinth (Peloponnese, Greece) to sea-level rise

Karymbalis

Chalkias

et al. 2012

Open Geosciences

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Abstract:The eustatic sea-level rise due to global warming is predicted to reach approximately 18 -59 cm by the year 2100, which necessitates the identification and protection of sensitive sections of coastline. In this study, the classification of the southern coast of the Gulf of Corinth according to the sensitivity to the anticipated future sealevel rise is attempted by applying the Coastal Sensitivity Index (CSI), with variable ranges specifically modified for the coastal environment of Greece, utilizing GIS technology. The studied coastline has a length of 148 km and is oriented along the WNW-ESE direction. CSI calculation involves the relation of the following physical variables, associated with the sensitivity to long-term sea-level rise, in a quantifiable manner: geomorphology, coastal slope, relative sea-level rise rate, shoreline erosion or accretion rate, mean tidal range and mean wave height. For each variable, a relative risk value is assigned according to the potential magnitude of its contribution to physical changes on the coast as the sea-level rises. Every section of the coastline is assigned a risk ranking based on each variable, and the CSI is calculated as the square root of the product of the ranked variables divided by the total number of variables. Subsequently, a CSI map is produced for the studied coastline. This map showed that an extensive length of the coast (57.0 km, corresponding to 38.7% of the entire coastline) is characterized as highly and very highly sensitive primarily due to the low topography, the presence of erosionsusceptible geological formations and landforms and fast relative sea-level rise rates. Areas of high and very high CSI values host socio-economically important land uses and activities.

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Section: Geological -Structural Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessment of the sensitivity of the southern coast of the Gulf of Corinth (Peloponnese, Greece) to sea-level rise

Karymbalis

Chalkias

et al. 2012

Open Geosciences

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“…There is a considerable amount of subjectivity involved in the case of categorical classes; however, they can be used as indicators in the case of vulnerability assessment. The quantitative classes have been decided based on the expert judgments, literature information (Rao et al, 2008;Kumar et al, 2010;Kumar and Kunte, 2012) and the spectrum of values of the data set considered specific to the region. All these methodologies of classification depict site-specific relative vulnerability thresholds and thus are appropriate for regions with similar environmental conditions.…”

Section: Methods and Proceduresmentioning

confidence: 99%

“…However, Vittal Hegde and Radhakrishnan Reju (2007) used the sum of the value of each variable divided by the number of variables. Later, Nageswara Rao et al (2008) calculated CVI by taking the summation of the variables considered with the ranks of each multiplied by their corresponding weights on the Andhra Pradesh coast.…”

Section: Coastal Vulnerabilitymentioning

confidence: 99%

Coastal vulnerability assessment of Puducherry coast, India, using the analytical hierarchical process

Murali

Ankita

Amrita

et al. 2013

Nat. Hazards Earth Syst. Sci.

182

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Abstract. As a consequence of change in global climate, an increased frequency of natural hazards such as storm surges, tsunamis and cyclones, is predicted to have dramatic affects on the coastal communities and ecosystems by virtue of the devastation they cause during and after their occurrence. The tsunami of December 2004 and the Thane cyclone of 2011 caused extensive human and economic losses along the coastline of Puducherry and Tamil Nadu. The devastation caused by these events highlighted the need for vulnerability assessment to ensure better understanding of the elements causing different hazards and to consequently minimize the after-effects of the future events. This paper demonstrates an analytical hierarchical process (AHP)-based approach to coastal vulnerability studies as an improvement to the existing methodologies for vulnerability assessment. The paper also encourages the inclusion of socio-economic parameters along with the physical parameters to calculate the coastal vulnerability index using AHP-derived weights. Seven physical-geological parameters (slope, geomorphology, elevation, shoreline change, sea level rise, significant wave height and tidal range) and four socio-economic factors (population, land use/land cover (LU/LC), roads and location of tourist areas) are considered to measure the physical vulnerability index (PVI) as well as the socio-economic vulnerability index (SVI) of the Puducherry coast. Based on the weights and scores derived using AHP, vulnerability maps are prepared to demarcate areas with very low, medium and high vulnerability. A combination of PVI and SVI values are further utilized to compute the coastal vulnerability index (CVI). Finally, the various coastal segments are grouped into the 3 vulnerability classes to obtain the coastal vulnerability map. The entire coastal extent between Muthiapet and Kirumampakkam as well as the northern part of Kalapet is designated as the high vulnerability zone, which constitutes 50 % of the coastline. The region between the southern coastal extent of Kalapet and Lawspet is the medium vulnerability zone and the remaining 25 % is the low vulnerability zone. The results obtained enable the identification and prioritization of the more vulnerable areas of the region in order to further assist the government and the residing coastal communities in better coastal management and conservation.

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Tropical Cyclone–Induced Storm Surges and Wind Waves in the Bay of Bengal

Bhaskaran¹,

Rao²,

Murty³

2020

Techniques for Disaster Risk Management and Mitigation

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Sea-level rise and coastal vulnerability: an assessment of Andhra Pradesh coast, India through remote sensing and GIS

Cited by 195 publications

References 32 publications

Assessment of the sensitivity of the southern coast of the Gulf of Corinth (Peloponnese, Greece) to sea-level rise

Assessment of the sensitivity of the southern coast of the Gulf of Corinth (Peloponnese, Greece) to sea-level rise

Coastal vulnerability assessment of Puducherry coast, India, using the analytical hierarchical process

Tropical Cyclone–Induced Storm Surges and Wind Waves in the Bay of Bengal

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