High water mark determination based on the wave runup height distribution and spatial continuity

Abstract

Determination of High Water Mark (HWM) is important for identifying the landward extent of the ocean. The delineation of HWM is required for cadastral boundary definition, land use and infrastructure development along the foreshore and for planning associated with climate change adaptation. Currently, apart from medium to long term traditional tidal observation methods and subjective interpretation, only limited scientific methods have been developed to determine HWM accurately. The aim of this paper is to develop a systematic method to determine HWM based on the HWM indicators, wave runup distribution and the spatial continuity theory (See Figure 1). A range of HWM indicators are used to determine HWM in this paper including the Mean Higher High Water (MHHW); suggested heights determined by Landgate experienced surveyors in the field (Landgate) and the engineer in Department of Transport (DoT); Highest Tide Records (HTR) derived from tidal records, and natural features on the beach such as sudden change of beach slope (SCoS) and the High Water Line (HWL, boundary between wet sand and dry sand). In order to extract these feature indicator lines, Object-Oriented Image Analysis (OOIA) is used in this research. The heights of HWM indicators are then derived from Digital Elevation Model (DEM) to determine HWM indicator line.To determine HWM based on these indicators for cadastral boundary definition purpose, we develop a method derived from a semivariogram model of wave runup probability. The wave runup probability is defined as the probability that sea water will reach the indicator line in 8 years. Generally the higher the wave runup probability, the more likely sea water reaches the indicator. Cross sections are set up at every 50 meters in the study area and intersect with calculated indicator lines. The wave runup probability was calculated for each intersection point. A semivariogram model of these wave runup probabilities is used to understand spatial continuity of the wave runup on the shore. The semivariogram describe the spatial autocorrelation of wave runup probability of indicator points. Our assumption is that a semivariogram model can define HWM based on the probability of indicator points due to wave runup. The intersection points that are closer will usually have a smaller difference of wave runup probability than distant ones. We aim to identify the maximum distance between pairs of points, which defines the maximum neighbourhood over which wave runup probability should be continue on the shore. This study showed that the height, reached by wave runup equal as 2.5% of the time over 8 years, was the most proper level that could be considered as the HWM height, as the distance between upper (97.5%) and lower (2.5%) bound of this level, when levelling on the ground, was the closest to the autocorrelation range on the shore.