Time-series forecasting of particulate organic carbon on the Sunda Shelf: Comparative performance of the SARIMA and SARIMAX models

Abstract

Conducting in-depth studies of carbon dynamics in the Southeast Asia’s Sunda Shelf waters is challenging. Particulate organic carbon (POC) is a key component that can be monitored in the region, but ocean assessment requires advanced research and POC monitoring, especially in relation to ocean dynamics and forecasts. Accurate forecasting of POC in marine environments is difficult due to the complexity of oceanic processes and the influence of various environmental factors. Statistical forecasting models such as Seasonal Autoregressive Integrated Moving Average (SARIMA) or SARIMA with Exogenous Factors (SARIMAX) are useful for this purpose. This study compares these two time-series forecasting models to assess the role of exogenous factors in predicting POC variability in Indonesian seas. The models were specified as SARIMA (3, 1, 3)x(2, 0, 0, 60) and SARIMAX (3, 1, 3)x(2, 0, 0, 60). We obtained Akaike Information Criterion (AIC) values of 1237.767 for the SARIMA model and 1207.341 for SARIMAX[exog=SST]. The SARIMA model's validation metrics were 6.94 % for MAPE, 10.80 for RMSE, and 0.65 for the correlation coefficient, outperforming the SARIMAX model. While SARIMAX incorporates additional environmental variables, SARIMA outperforms it based on MAPE, RMSE, and correlation coefficients. Our findings reveal that only sea surface temperature can significantly influence POC forecasts, thus providing a new perspective on oceanic carbon dynamics. From 2022–2030, POC levels are expected to range between 108.3 and 135.9 mg/m³, with a mean value of 120.9±5.4 mg/m³, lower than that observed from 2002 to 2022, which was 118.8±11.9 mg/m³. The highest peak in POC is predicted for the end of 2026 and 2027. The annual trend shows that the highest POC values correspond to the northwest monsoon season, with the lowest during the intermonsoon period.