The technique combines Variational Mode Decomposition (VMD) with AutoRegressive Moving Average (ARMA) modeling, creating the VMD-ARMA (VARMA) model to predict ionospheric delay values one hour ahead.To evaluate the performance of the proposed VARMA model, the algorithm was tested during geomagnetic storms that occurred in June 2013. GNSS data from April 1, 2013, to June 30, 2013, was collected using a GNSS Ionospheric Scintillation and TEC Monitor (GISTM) receiver located at Koneru Lakshamaiah Education Foundation, Guntur station, India (geographic: 16.37°N, 80.44°E).The results demonstrate that the VARMA model outperforms the ARMA model by 2-3% in terms of forecasting accuracy during storm conditions. This suggests that the VARMA version can be a valuable tool for predicting ionospheric Total Electron Content (TEC) variations in low-latitude regions, even during disturbed ionospheric space weather conditions.