Browsing by Author "Indika, K.W."

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    Threat of Sea Level Rise to the Coastal Community in Sri Lanka: Use of Satellite Information in Disaster Management
    (3rd International Conference on Library and Information Management, Department of Library and Information Science, Faculty of Social Sciences, University of Kelaniya, Sri Lanka, 2019) Indika, K.W.; Priyadasa, R.U.K.; Wijerathne, E.M.S.
    Sea level rise is a profound indicator for circumstance of human activities relatively growing population and their requirements of the development during last three decades. The coastal area around the country consisted of most dense population, economically active land areas and interconnected infrastructures such as ports, fisheries harbours, industries, express roads and port cities. One of leading impacts of global warming is a progressive rise of mean sea level by the causing of thermal expansion of oceanic water and melting of glaciers. Sea level records were collected from Sri Lankan tide gauge network and 10 sampling stations from gridded satellite sea level observations during last 25 years around the country. The satellite data was provided by the Achieving Validating, Interpretation of Satellite Oceanography (AVISO). The high frequency tide gauge time series data were averaged to obtained monthly mean and was superimposed on the same axis of satellite time series mean sea level to compare the precision of expected sea level trend. The vulnerable coastal area was calculated under three ranking based on elevation factor from the mean sea level zero to 3m elevation in 1m contour using the Shuttle Radar Topographic Mission (SRTM) 90 m Digital Elevation Map (DEM) originally produced by the NASA with horizontal datum WGS84 and Vertical datum EGM96 using Arc Map 10.1. Satellite derived annual average mean sea level trend 2.585mm around the country while tide gauge estimated trend 2.904mm were showed with a difference of 0.319mm positive deviation from satellite observations. The sea level trend in northern coast little lower than southern coast around of the country. The tide gauge observations showed root mean square differences (RMSDs) approximately 80% of the variance of the MSL signal estimated from satellite altimetry data. Annual variation was 20 to 30 cm according to the average monthly mean sea level signals during the last 25 years. The enumerated vulnerable land area were classified as highly vulnerable, moderately vulnerable and low vulnerable with the elevation gradient of 0-10 cm, 10-20 cm, 20-30 cm. The maximum vulnerable land area was recorded in the Northern part of the country within 100 Sq.km of land area below 1m elevation exposing to the ocean based hazards induced by sea level rise.
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    Tide Gauge Data Management for the Analysis of Ocean-based Disasters, their Mitigation and Management: A Standard Procedure.
    (Department of Library and Information Science, Faculty of Social Sciences, University of Kelaniya,Sri Lanka., 2017) Indika, K.W.; Weerakoon, W.R.W.M.A.P.
    Observation of sea-level variation is an essential long-term global process, and is difficult to manage anthropogenic effects at in-situ data recording. Besides, the unremitting collection of data with desired frequencies and research quality is a challenge. Notably, obtaining accurate and firstly data, i.e. real-time and near-real time are important for analysing, prevention, mitigation and management of ocean-based disasters. This paper discloses a model procedure for tide-gauge data management pertaining to ocean-based disasters and recognition of special events while highlighting the usability and prospects. The hydrostatics pressure sensors were installed at known depths below the surface in serene environments without anthropogenic effects whereas tide-wells equipped wave absorbers. Surface wave height radar sensors were installed at known heights above the surface referring to an eternal bench-mark. The data collected [f; frequency = 1 minute] were transmitted via satellite communiqué where the resulted time series was obtained via the global sea level monitoring facility provided by the Intergovernmental Oceanographic Commission (IOC). The data were primarily processed by rectifying noises, null-data fields and outliers according to the IOC quality control standards. Afterwards, the tidal impact was examined while confiscating the residual variation. The process included assessing the astronomical forces of the Moon and the Sun using a Harmonic analysis of a time series, and quantifying the contribution of those tidal constituents. The pattern was appraised quantitatively, pertaining to the Luni-solar declinational diurnal constituent, the Principal Lunar declinational diurnal constituent, whereas the effects produced by the Moon (semidiurnal lunar), and the Sun (semidiurnal solar), whilst the spring and neap tide variations were determined. Ensemble empirical mode decomposition method was used to determine the inter-annual variability and related events. Data (f=1) were re-computed to diverse frequencies where event analyses, i.e., both short-term and long-term variations were performed Accordingly, meteo-tsunami, tidal and seasonal variations, El-Nino Southern Oscillation (ENSO), whereas sea level rise were revealed and were identified as potential research areas.