High Water Mark Determination Based on the Principle of Spatial Continuity of the Swash Probability
This study presents a model that determines the position of the high water mark (HWM) based on the spatial continuityof inundation probability due to swash for a range of HWM indicators. These indicators include mean high water (MHW),high water line (HWL), and a number of shoreline features, such as...
| Main Authors: | , , , , |
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| Format: | Journal Article |
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Coastal Education and Research Foundation
2014
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/15512 |
| _version_ | 1848748913008312320 |
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| author | Liu, Xin Xia, Jianhong (Cecilia) Blenkinsopp, C. Arnold, L. Wright, Graeme |
| author_facet | Liu, Xin Xia, Jianhong (Cecilia) Blenkinsopp, C. Arnold, L. Wright, Graeme |
| author_sort | Liu, Xin |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This study presents a model that determines the position of the high water mark (HWM) based on the spatial continuityof inundation probability due to swash for a range of HWM indicators. These indicators include mean high water (MHW),high water line (HWL), and a number of shoreline features, such as the vegetation line. HWM identifies the landwardextent of the ocean and is required for cadastral boundary definition, land-use and infrastructure development along theforeshore ,and for planning associated with climate change adaptation. In this paper, shoreline indicators are extractedusing an object-oriented image analysis (OOIA) approach. Ten-year hourly swash heights (shoreline excursion length)are fitted into a cumulative distribution function. The probability that swash will reach the various HWM indicators overa 10 y period is then estimated. The spatial continuity distances of the swash probability of HWM indicators arecalculated using semivariogram models that measure similarity of swash probability. The spatial continuity distance isdefined as the distance between the lower bound of sampling position (the most seaward HWM indicator) and theposition where autocorrelation, or the similarity of swash probability of the various HWM indictors, approaches zero. Thelatter is considered as the HWM position in this study. This HWM determination method is evaluated at two study sitesat different latitudes and with distinct coastal features. |
| first_indexed | 2025-11-14T07:12:35Z |
| format | Journal Article |
| id | curtin-20.500.11937-15512 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:12:35Z |
| publishDate | 2014 |
| publisher | Coastal Education and Research Foundation |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-155122017-09-13T15:41:22Z High Water Mark Determination Based on the Principle of Spatial Continuity of the Swash Probability Liu, Xin Xia, Jianhong (Cecilia) Blenkinsopp, C. Arnold, L. Wright, Graeme swash probability distribution semivariogram High water mark This study presents a model that determines the position of the high water mark (HWM) based on the spatial continuityof inundation probability due to swash for a range of HWM indicators. These indicators include mean high water (MHW),high water line (HWL), and a number of shoreline features, such as the vegetation line. HWM identifies the landwardextent of the ocean and is required for cadastral boundary definition, land-use and infrastructure development along theforeshore ,and for planning associated with climate change adaptation. In this paper, shoreline indicators are extractedusing an object-oriented image analysis (OOIA) approach. Ten-year hourly swash heights (shoreline excursion length)are fitted into a cumulative distribution function. The probability that swash will reach the various HWM indicators overa 10 y period is then estimated. The spatial continuity distances of the swash probability of HWM indicators arecalculated using semivariogram models that measure similarity of swash probability. The spatial continuity distance isdefined as the distance between the lower bound of sampling position (the most seaward HWM indicator) and theposition where autocorrelation, or the similarity of swash probability of the various HWM indictors, approaches zero. Thelatter is considered as the HWM position in this study. This HWM determination method is evaluated at two study sitesat different latitudes and with distinct coastal features. 2014 Journal Article http://hdl.handle.net/20.500.11937/15512 10.2112/JCOASTRES-D-12-00061.1 Coastal Education and Research Foundation restricted |
| spellingShingle | swash probability distribution semivariogram High water mark Liu, Xin Xia, Jianhong (Cecilia) Blenkinsopp, C. Arnold, L. Wright, Graeme High Water Mark Determination Based on the Principle of Spatial Continuity of the Swash Probability |
| title | High Water Mark Determination Based on the Principle of Spatial Continuity of the Swash Probability |
| title_full | High Water Mark Determination Based on the Principle of Spatial Continuity of the Swash Probability |
| title_fullStr | High Water Mark Determination Based on the Principle of Spatial Continuity of the Swash Probability |
| title_full_unstemmed | High Water Mark Determination Based on the Principle of Spatial Continuity of the Swash Probability |
| title_short | High Water Mark Determination Based on the Principle of Spatial Continuity of the Swash Probability |
| title_sort | high water mark determination based on the principle of spatial continuity of the swash probability |
| topic | swash probability distribution semivariogram High water mark |
| url | http://hdl.handle.net/20.500.11937/15512 |