A Comparative Accuracy of Regularized and Tension Spline Methods to Estimate and Model the Surface Water pH of Pulau Tuba, Langkawi, Kedah

Abstract

This research is conducted to assess the accuracy of spline interpolation methods to predict and model the surface water pH of Pulau Tuba, Langkawi, Kedah, Malaysia. In-situ sampling activities using pH-meter and Geographic Positioning Systems (GPS) were carried out during high tides and at noon in November 2018. The development of spatial models was constructed using Regularized and Tension spline methods. Then, validation of models was carried out to compare the observed and predicted values of pH using correlation analysis, regression analysis, and error analysis. The accuracy of the developed map was calculated using the overall accuracy equation. This research found that the regularized spline method had more accuracy in estimating surface water pH variability than the tension spline method. Pearson correlation coefficient (r), Coefficient of determination (R2), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were reported at 0.896, 0.803, 0.0265 and 0.0344 for the regularized spline method,respectively. The developed spatial model was then transformed into a map by adding map elements such as legend, title, north arrow, and scales for effective visualization. The developed map has an accuracy of 87.50%. The surface water pH was found at the range of 7-8. Low reading of pH is expected due to the addition of rainwater to the coastal water of Pulau Tuba, Langkawi, Kedah. The research outcomes would benefit government and non-government agencies to monitor the coastal and ocean acidification and the development of strategic policies and rules to reduce the impact of anthropogenic activities and climate changes for this area.

Spatial Assessment and Mapping of Water Quality in Lake Sentani (Indonesia) Using In-Situ Data and Satellite Imagery

“…In this study, the interpolation method used is Spline with barriers. The Spline algorithm is an accurate interpolation that passes through every surface data point (Hofierka et al, 2002), and in several studies obtained low root mean square error values in interpolating water quality data (North and Livingstone, 2013; Kamaruddin et al, 2021;Jaffar et al, 2022). These barriers aim to process data interpolation only in the study area (Lake Sentani).…”

Sustainable Management of the Coastal Water pH of Pulau Tuba Using the Inverse Distance Weighted (IDW) Method

“…Spatial interpolation has become a tool for predicting unknown values from unknown locations in the study area using known values (Kamaruddin et al, 2021). The technique has several advantages such as high accuracy, being low cost, and being able to save time for sampling activities (Kamaruddin et al, 2018).…”

“…Sea surface pH can be predicted using many tools or modelling techniques for a sustainable approach toward healthy coastal and estuarine ecosystems (Kamaruddin et al, 2021). However, in the coastal area and mangrove ecosystem, modelling pH can be difficult as many factors could contribute to the fluctuation of pH readings.…”