Coastal erosion risk assessment in the dynamic estuary: The Meghna estuary case of Bangladesh coast

Roy, Subhash Kanti; Pandit, Santa; Papia, Mossammat; Rahman, Masudur; Ocampo, Jan Christian Otto Rehder; Razi, Mohammad Arfar; Jurado, Pedro Real; Ahmed, Naser; Hoque, Muhammad Al-Amin; Hasan, Mehedi; Yeasmin, Jakeya; Hossain, Sakhawat

doi:10.1016/j.ijdrr.2021.102364

Cited by 19 publications

(10 citation statements)

References 93 publications

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“…Sobre la cuestión de la ausencia de modelado de fenómenos de erosión costera, por lo general común en este tipo de estudios (Roy et al, 2021) cabe resaltar que en algunos sectores del área de estudio pueden llegar a tener una gran importancia. Tal es el caso del área situada frente a la actual costa de Huelva en el tramo Matalascañas -Mazagón, donde además de una intensa erosión costera se ha identificado un aparente fenómeno de elevación tectónica (Salvany et al, 2010).…”

Section: Discussionunclassified

Método para el cálculo, análisis y representación espacial de la variable "tiempo sumergido bajo el nivel del mar durante la última glaciación" en la plataforma continental del Golfo de Cádiz (España y Portugal)

Jurado¹,

Mejías-García²

2022

Rev. geogr. Norte Gd.

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Section: Discussionunclassified

Método para el cálculo, análisis y representación espacial de la variable "tiempo sumergido bajo el nivel del mar durante la última glaciación" en la plataforma continental del Golfo de Cádiz (España y Portugal)

Jurado¹,

Mejías-García²

2022

Rev. geogr. Norte Gd.

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“…By calculating the true positive rate (TPR) and the false positive rate (FPR) as the y axis to draw the characteristic curve, the size of the AUC can be calculated as the probability of verification. where TP (true positives): the number of observed erosion locations accurately identified; FP (false positives): the number of erroneously identified erosion locations in non-eroded regions; TN (true negatives): correctly identified non-erosion locations number of; FN (false negatives): the number of misidentified non-eroded locations in eroded regions (Roy et al, 2021).…”

Section: Vulnerability Verificationmentioning

confidence: 99%

“…Yoo et al (2014) proposed the environmental vulnerability index (EVI) to evaluate the coastal vulnerability of Jakarta, Indonesia, based on historical disasters and socioeconomic statistics, which were more affected by the vulnerability caused by land-based factors than was the CVI. In addition, some scholars have combined vulnerability, exposure, adaptability and hazard to assess coastal erosion risk (Merlotto et al, 2016;Narra et al, 2017;Roy et al, 2021;Swami and Parthasarathy, 2021). Based on vulnerability research, Swami and Parthasarathy proposed that system vulnerability includes three main factors: exposure, sensitivity and adaptability, which can comprehensively explain and evaluate the inherent characteristics of various coasts.…”

Section: Introductionmentioning

confidence: 99%

“…Based on vulnerability research, Swami and Parthasarathy proposed that system vulnerability includes three main factors: exposure, sensitivity and adaptability, which can comprehensively explain and evaluate the inherent characteristics of various coasts. Roy et al, (2021) and others selected 19 indicators, such as physical, environmental and socioeconomic geography, in the Mekhna River estuary area in Bangladesh and used the analytic hierarchy process (AHP) to evaluate the hazard, vulnerability and exposure indices. The area under the curve (AUC) has been used to verify the reliability of evaluating the degree of erosion risk.…”

Section: Introductionmentioning

confidence: 99%

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Characteristics and evaluation of coastal erosion vulnerability of typical coast on Hainan Island

Cao

et al. 2022

Front. Mar. Sci.

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Coastal erosion vulnerability assessment is widely used to assess the loss degree of coastal zone caused by erosion, and plays an important role in coastal natural resources protection, planning, management and decision-making. Based on the natural and social characteristics of the east coast of Qiongdong and the coastal erosion vulnerability index (CVI) method, this study selected 8 assessment indicators, such as shoreline change rate (U1). The Delphi method and the entropy weight method were used to calculate the comprehensive index weight, combined with CVI method and geographic information system (GIS) technology, to quantitatively evaluate the temporal and spatial distribution characteristics of typical coastal erosion vulnerability such as coral reefs in the east of Hainan Island. The study area was divided into 5 grades: very low (31%), low (10%), moderate (28%), high (24%) and high vulnerability (7%), and the overall performance was moderate erosion vulnerability. The research showed that the interannual downward rate erosion of beach (U3) and the rate of change of the isobath (U2) of the beach were the main controlling factors affecting the vulnerability of coastal erosion in the study area, and the coastal dynamic factor had a greater impact than the other two factors. As a natural barrier, the coral reefs in the study area had good wave absorption and energy reduction, and the coral reef coasts showed low coastal erosion vulnerability, due to the complex hydrodynamic characteristics, estuary coasts is the most vulnerable areas. The verification results of the ROC-AUC method showed that the accuracy of erosion vulnerability was 68.9%, which provided an important reference for the ecological restoration of tropical coral reef biological coasts and the development and management of the Hainan Qiongdong coastal zone.

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“…Some studies (Bendoni et al, 2014;Mel et al, 2022;Carniello et al, 2009;Marani et al, 2011;D'Alpaos et al, 2007) have explored marsh retreat behaviours in microtidal settings (e.g. Venice Lagoon, Italy), while others (Shimozono et al, 2019;Roy et al, 2021) have investigated the factors controlling erosion in large tidal-dominated estuaries, typically emphasising hydrodynamic processes or focusing on soil creep in mesotidal environments based on seasonality-related modifications (Mariotti et al, 2019). In contrast, studies that consider the problem of bank collapse geomechanically, and with a particular focus on hypertidal environments, are lacking.…”

mentioning

confidence: 99%

Water level fluctuations drive bank instability in a hypertidal estuary

Gasparotto

Darby²,

Leyland³

et al. 2022

Preprint

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Abstract. Hypertidal estuaries are very dynamic environments characterised by high tidal ranges (>6 m) that can experience rapid rates of bank retreat. Whilst a large body of work on the processes, rates, patterns and factors driving bank erosion has been undertaken in fluvial environments, the process mechanics affecting the stability of the banks with respect to mass failure in hypertidal settings are not well documented. In this study, the processes and trends leading to bank failure and consequent retreat in hypertidal estuaries are treated within the context of the Severn Estuary (UK) by employing a combination of numerical models and field-based observations. Our results highlight that the periodic fluctuations in water level associated with the hypertidal environment drive regular fluctuations in the hydrostatic pressure exerted on the incipient failure surfaces that range from a confinement pressure of 0 kPa (at low tide) to ~100 kPa (at high tide). However, the relatively low transmissivity of the fine-grained banks (that are typical of estuarine environments) results in low seepage inflow/outflow velocities (~3x10-10 m s-1), such that variations in positive pore water pressures within the saturated bank are smaller, ranging between about 10 kPa (at low tide) to ~43 kPa (at high tides). This imbalance in the resisting (hydrostatic confinement) versus driving (positive pore water pressures) forces thereby drives a frequent oscillation of bank stability between stable (at high tide) and unstable states (at low tide). This transition between stability and instability is found not only on a semidiurnal basis, but also on a longer timeframe. In the spring to neaps transitional period, banks experience the coexistence of high degrees of saturation due to the high spring tides and decreasing confinement pressures favoured by the still moderately high channel water levels. This transitional period creates conditions when failures are more likely to occur.

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Coastal erosion risk assessment in the dynamic estuary: The Meghna estuary case of Bangladesh coast

Cited by 19 publications

References 93 publications

Método para el cálculo, análisis y representación espacial de la variable "tiempo sumergido bajo el nivel del mar durante la última glaciación" en la plataforma continental del Golfo de Cádiz (España y Portugal)

Método para el cálculo, análisis y representación espacial de la variable "tiempo sumergido bajo el nivel del mar durante la última glaciación" en la plataforma continental del Golfo de Cádiz (España y Portugal)

Characteristics and evaluation of coastal erosion vulnerability of typical coast on Hainan Island

Water level fluctuations drive bank instability in a hypertidal estuary

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