Bayesian statistical analysis reveals spatial heterogeneity in Cyclone Thane deposits from Southeast India

Modern and geological records of storm sedimentary deposits preserved on siliciclastic coastlines are important archives to evaluate the past and current magnitude and impacts of storms. Examination of modern storm deposits also offers the opportunity to evaluate the similarities and differences between storm and other coastal overwash processes and hazards. We examined the stratigraphy and sedimentary characteristics of the 31st December 2011 Cyclone Thane and underlying coastal units from 14 pits from six sites from the coastal zone of Tamil Nadu Province, southeast India. We analysed the grain size parameters, grain shape, and heavy mineral proportions of each deposit in high resolution and examined the sedimentary structures of each unit. For the first time, we use Bayesian factors to quantitatively evaluate the similarities and differences between the storm sedimentary deposits and other co-located coastal sedimentary deposits. At several sites, the storm deposits differ in several parameters from the underlying coastal deposits, but at some locations, distinguishing between different depositional units cannot be achieved. In comparing the storm deposits from the different sites, mean grain size results in the most coherent pattern with closely located sites having similar mean grain size, and more southerly sites being finer grained. The other measured parameters show a far less coherent pattern with adjacent sites often preserving larger differences than more distal sites attesting to very local hydrodynamic variations during sediment deposition. As with the sedimentary parameters, the sedimentary structures formed during sediment deposition preserved at each site are highly variable. To date, the presence of terminal foresets at the landward edge of washover fans remains the only diagnostic feature of storm deposition, but that this feature is not ubiquitous across all storm deposits. Our findings demonstrate the spatially heterogeneous nature of storm sediment deposition and the challenges of identifying storm deposits in coastal siliciclastic sequences. The use of Bayesian statistical approaches also offers a robust method for evaluating and discriminating between coastal sediment deposits that has many advantages over traditional frequentist approaches. This method can easily be applied to other sedimentary depositional environments. • Storm deposits are difficult to discriminate in sandy, coastal environments. • Storm deposit from the same event show extensive spatial variation. • Bayes factors quantify the sedimentary variability in coastal systems.

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Publication Details

Journal
Marine Geology
Published
2024-10-22
DOI
https://doi.org/10.1016/j.margeo.2024.107418
Citations
2
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
1.42

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article

Bayesian statistical analysis reveals spatial heterogeneity in Cyclone Thane deposits from Southeast India

Chris Gouramanis, S. Srinivasalu, Adam D. Switzer, Andasabari Karthik et al.
2 citations
Marine Geology
Landslides and related hazards
1.42
article

Bayesian statistical analysis reveals spatial heterogeneity in Cyclone Thane deposits from Southeast India

Chris Gouramanis, S. Srinivasalu, Adam D. Switzer, Andasabari Karthik, S. Carson
article en
2 citations

Abstract

Modern and geological records of storm sedimentary deposits preserved on siliciclastic coastlines are important archives to evaluate the past and current magnitude and impacts of storms. Examination of modern storm deposits also offers the opportunity to evaluate the similarities and differences between storm and other coastal overwash processes and hazards. We examined the stratigraphy and sedimentary characteristics of the 31st December 2011 Cyclone Thane and underlying coastal units from 14 pits from six sites from the coastal zone of Tamil Nadu Province, southeast India. We analysed the grain size parameters, grain shape, and heavy mineral proportions of each deposit in high resolution and examined the sedimentary structures of each unit. For the first time, we use Bayesian factors to quantitatively evaluate the similarities and differences between the storm sedimentary deposits and other co-located coastal sedimentary deposits. At several sites, the storm deposits differ in several parameters from the underlying coastal deposits, but at some locations, distinguishing between different depositional units cannot be achieved. In comparing the storm deposits from the different sites, mean grain size results in the most coherent pattern with closely located sites having similar mean grain size, and more southerly sites being finer grained. The other measured parameters show a far less coherent pattern with adjacent sites often preserving larger differences than more distal sites attesting to very local hydrodynamic variations during sediment deposition. As with the sedimentary parameters, the sedimentary structures formed during sediment deposition preserved at each site are highly variable. To date, the presence of terminal foresets at the landward edge of washover fans remains the only diagnostic feature of storm deposition, but that this feature is not ubiquitous across all storm deposits. Our findings demonstrate the spatially heterogeneous nature of storm sediment deposition and the challenges of identifying storm deposits in coastal siliciclastic sequences. The use of Bayesian statistical approaches also offers a robust method for evaluating and discriminating between coastal sediment deposits that has many advantages over traditional frequentist approaches. This method can easily be applied to other sedimentary depositional environments. • Storm deposits are difficult to discriminate in sandy, coastal environments. • Storm deposit from the same event show extensive spatial variation. • Bayes factors quantify the sedimentary variability in coastal systems.

Marine GeologyVol. 478
Australian National University (AU), Nanyang Technological University (SG), National Institute of Ocean Technology (IN), Corbett Hospital (GB), Anna University, Chennai (IN), Ministry of Earth Sciences (IN), Earth Observatory of Singapore (SG)
National Research Foundation Singapore, Ministry of Education - Singapore
Climate action
Openalex Percentile: Top 14%
Landslides and related hazards
1.42
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