TY - JOUR
T1 - High water mark determination based on spatial continuity of swash probability
AU - Liu, Xin
AU - Xia, Jianhong
AU - Blenkinsopp, Chris
AU - Arnold, Lesley
AU - Wright, Graeme
PY - 2014/5
Y1 - 2014/5
N2 - This study presents a model that determines the position of the high water mark (HWM) based on the spatial continuity of 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 landward extent of the ocean and is required for cadastral boundary definition, land-use and infrastructure development along the foreshore ,and for planning associated with climate change adaptation. In this paper, shoreline indicators are extracted using 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 over a 10 y period is then estimated. The spatial continuity distances of the swash probability of HWM indicators are calculated using semivariogram models that measure similarity of swash probability. The spatial continuity distance is defined as the distance between the lower bound of sampling position (the most seaward HWM indicator) and the position where autocorrelation, or the similarity of swash probability of the various HWM indictors, approaches zero. The latter is considered as the HWM position in this study. This HWM determination method is evaluated at two study sites at different latitudes and with distinct coastal features.
AB - This study presents a model that determines the position of the high water mark (HWM) based on the spatial continuity of 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 landward extent of the ocean and is required for cadastral boundary definition, land-use and infrastructure development along the foreshore ,and for planning associated with climate change adaptation. In this paper, shoreline indicators are extracted using 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 over a 10 y period is then estimated. The spatial continuity distances of the swash probability of HWM indicators are calculated using semivariogram models that measure similarity of swash probability. The spatial continuity distance is defined as the distance between the lower bound of sampling position (the most seaward HWM indicator) and the position where autocorrelation, or the similarity of swash probability of the various HWM indictors, approaches zero. The latter is considered as the HWM position in this study. This HWM determination method is evaluated at two study sites at different latitudes and with distinct coastal features.
KW - High water mark
KW - semivariogram
KW - swash probability distribution
UR - http://www.scopus.com/inward/record.url?scp=84900435825&partnerID=8YFLogxK
UR - http://dx.doi.org/10.2112/JCOASTRES-D-12-00061.1
U2 - 10.2112/JCOASTRES-D-12-00061.1
DO - 10.2112/JCOASTRES-D-12-00061.1
M3 - Article
SN - 1551-5036
VL - 30
SP - 487
EP - 499
JO - Journal of Coastal Research
JF - Journal of Coastal Research
IS - 3
M1 - 00061.1
ER -