Spatial variations of sea level along the coast of Thailand: Impacts of extreme land subsidence, earthquakes and the seasonal monsoon

Saramul, Suriyan; Ezer, Tal

doi:10.1016/j.gloplacha.2014.08.012

Cited by 37 publications

(31 citation statements)

References 41 publications

(100 reference statements)

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“…In the continental shelves of the SCS and the Gulf of Thailand, the SSLC is generally dominated by the forcing of wind, associated with the Monsoon wind. Using a simple barotropic model (Sandstrom, 1980), the maximum annual and semiannual amplitude of sea level induced by local wind is 27 cm and 6 cm. The wind phases generally lag the tide gauge records (IB corrected) by less than 30 days and 20 days for the annual and semiannual phase, respectively.…”

Section: Discussionmentioning

confidence: 99%

“…The contribution of local wind to the coastal mean SSLC was quantified using a simple barotropic model formulated by Sandstrom [1980]. This model estimates the setup of sea level ðg W Þ from the maximum expected along-shore currents induced by 3% of the local long-shore wind (p) on the shelf by:…”

Section: Methodsmentioning

confidence: 99%

“…Tsimplis and Woodworth [] noted different annual phases between the east and the west coast of the Malaysian Peninsular. Saramul and Ezer [] reported that the seasonal sea level along the coast of the Gulf of Thailand is primarily driven by the wind associated with the seasonal monsoon. Based on satellite altimetry and an ocean model, Qinyu et al .…”

Section: Introductionmentioning

confidence: 99%

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The seasonal cycle and variability of sea level in the South China Sea

et al. 2015

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The spatial and temporal characteristics of the seasonal sea level cycle in the South China Sea (SCS) and its forcing mechanisms are investigated using tide gauge records and satellite altimetry observations along with steric and meteorological data. The coastal mean annual amplitude of the seasonal cycle varies between zero and 24 cm, reaching a maximum between July and January. The maximum mean semiannual amplitude is 7 cm, peaking between March and June. Along the coast, the seasonal cycle accounts for up to 92% of the mean monthly sea level variability. Atmospheric pressure explains a significant portion of the seasonal cycle with dominant annual signals in the northern SCS, the Gulf of Thailand and the north‐western Philippines Sea. The wind forcing is dominant on the shelf areas of the SCS and the Gulf of Thailand where a simple barotropic model forced by the local wind shows annual amplitudes of up to 27 cm. In the deep basin of the SCS, the Philippines Sea and the shallow Malacca Strait, the steric component is the major contributor with the maximum annual amplitudes reaching 15 cm. Significant variability in the seasonal cycle is found on a year‐to‐year basis. The annual and semiannual amplitudes vary by up to 63% and 45% of the maximum values, 15 cm and 11 cm, respectively. On average, stepwise regression analysis of contribution of different forcing factors accounts for 66% of the temporal variability of the annual cycle. The zonal wind was found to exert considerable influence in the Malacca Strait.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The seasonal cycle and variability of sea level in the South China Sea

et al. 2015

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“…This area is locally affected by land subsidence, mainly due to ground water depletion in some megacities. As a consequence, sinking rates have been found to be in excess of 10 mm/year in Jakarta (Abidin et al 2001) and Bangkok (Saramul and Ezer 2014). GPS-controlled tide gauges exist in Thailand (Trisirisatayawong et al 2011), Indonesia (Schöne et al 2011), and Malaysia (Simons et al 2007).…”

Section: Anthropogenic Signal In Local Vertical Land Motionmentioning

confidence: 99%

Internal Variability Versus Anthropogenic Forcing on Sea Level and Its Components

et al. 2016

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In this paper we review and update detection and attribution studies in sea level and its major contributors during the past decades. Tide gauge records reveal that the observed twentieth-century global and regional sea level rise is out of the bounds of its natural variability, evidencing thus a human fingerprint in the reported trends. The signal varies regionally, and it partly depends on the magnitude of the background variability. The human fingerprint is also manifested in the contributors of sea level for which observations are available, namely ocean thermal expansion and glaciers' mass loss, which dominated the global sea level rise over the twentieth century. Attribution studies provide evidence that the trends in both components are clearly dominated by anthropogenic forcing over the second half of the twentieth century. In the earlier decades, there is a lack of observations hampering an improved attribution of causes to the observed sea level rise. At certain locations along the coast, the human influence is exacerbated by local coastal activities that induce land subsidence and increase the risk of sea level-related hazards.

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“…Sand loss and forced people migration values were about 0.01 square kilometers per year and 2 people per year, respectively. During the validation process, the two main outputs of the SimCLIM/CoastCLIM model (relative sea-level change and retreat of coastline) were applied with evidence-base/observation data from various organizations and studies; Sojisuporn et al (2013), Saramul and Ezer, (2014) including data of the Marine Department and the National Oceanic and Atmospheric Administration (2014). RMSE and MAE represent the difference between actual observed values and estimated values, as well as describing the accuracy of the model's predictions.…”

Section: Results and Discussion 31 Historical Trendsmentioning

confidence: 99%

Modelling Assessment of Sandy Beaches Erosion in Thailand

Thepsiriamnuay¹,

Pumijumnong²

2018

Environ. Nat. Resour. J.

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This paper focuses on the spatial and temporal aspects of rising sea levels and sandy beach erosion in Thailand. The major scientific challenge tackled in this paper was to distinguish the relevance and contribution of sea level rise (including storms) to beach erosion. The Simulator of Climate Change Risks and Adaptation Initiatives (SimCLIM) and its' impact model (CoastCLIM) with two representative concentration pathway (RCP) scenarios (RCP2.6 and RCP8.5) was utilized to forecast changes in sea level and shoreline between the years 1940-2100. Input parameters underlying the modified Brunn Rule were applied (e.g., coastal and storm characteristics). Moreover, sand loss and forced people migration were estimated using fundamental equations. The sea level is predicted to rise by 147.90 cm and the coastline will be eroded around 517.09 m by 2100, compared to levels in 1995. This level of erosion could lead to a decrease of the coastal sandy area by about 2.69 km 2 and a population of 873 people, over the same period. In scientific terms, this paper quantifies the contribution and relevance of sea-level rise (SLR) to sandy beach erosion compared to other factors, including ad-hoc short-term impacts from stochastic storminess. The results also showed that 8.02 and 23.26 percent of erosion was attributed to storms and sea-level rise, respectively. Nevertheless, limited multi-century data of residual movement in Thailand could create uncertainties in distinguishing relative contributions. These results could be beneficial to national-scale data and the adaptation planning processes in Thailand.

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Spatial variations of sea level along the coast of Thailand: Impacts of extreme land subsidence, earthquakes and the seasonal monsoon

Cited by 37 publications

References 41 publications

The seasonal cycle and variability of sea level in the South China Sea

The seasonal cycle and variability of sea level in the South China Sea

Internal Variability Versus Anthropogenic Forcing on Sea Level and Its Components

Modelling Assessment of Sandy Beaches Erosion in Thailand

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