Accurate interpolation when compiling bathymetric maps is essential in any water depth study. In the case of Saldanha Bay, continuous dredging operations are constantly altering the ocean floor, which has a detrimental effect on sedimentation and coastal hydrodynamics. If the integrity of the coastline is to be secured, accurate bathymetry predictions would be invaluable in determining the effect of dredging operations on coastal erosion. Inverse distance weighting (IDW) and ordinary kriging (OK) are two well-known and commonly used interpolation methods to produce surfaces through spatial autocorrelation for numerous applications, inter alia, to estimate bathymetry. This study aims to analyse and compare the efficiency of the IDW and OK interpolation methods to predict the bathymetry of Saldanha Bay. Three comparative interpolation tests, which vary according to the decrease in the quantity of sounding points, are conducted. SPSS statistical software was used to assess the performance of the interpolation methods. Firstly, 2D scatterplots were used to show the correlation between predicted and measured sounding values for each interpolation method. Secondly, analysis of variance was employed to investigate whether the difference between the IDW and OK interpolation methods was statistically significant, and to determine which method was best suited for determining the bathymetry of Saldanha Bay. Findings revealed a strong linear relationship between predicted and measured sounding values for both IDW and OK when 100% of the sounding points are used. Conversely, for medium and small quantities of sounding points, a weak correlation exists. Clear similarities exist in the way that IDW and OK estimate and generate the continuous surface of bathymetry. However, IDW consistently performed better than OK across all interpolation tests. The findings of this study will assist in selecting the most suitable interpolation method for future bathymetry surveys of Saldanha Bay
