Aquatic plants are key contributors to oxygen production and ecosystem stability. This study quantifies oxygen generation capacity of Hydrilla, Vallisneria, and Potamogeton under varying concentrations of potassium bicarbonate (KHCO3) using a dual-limb apparatus to measure oxygen output via water displacement. The experiment was complemented by gas chromatography-thermal conductivity detector (GC-TCD) analysis and numerical simulations to validate the results. An in silico diffusion model was developed to simulate oxygen release dynamics assuming uniform oxygen generation across plant surfaces and steady-state mass transport through the surrounding medium. The findings indicate that KHCO3 significantly enhances photosynthetic activity and oxygen production, with Hydrilla exhibiting the highest oxygen generation rate, followed by Potamogeton and Vallisneria. The optimal concentration of KHCO3 was determined to be 5 mg/mL, beyond which oxygen production declined due to osmotic stress and ionic imbalances. GC-TCD analysis confirmed oxygen (∼90%) as the primary gas produced, while simulated results closely aligned with the experimental data, reinforcing the robustness of the in silico analysis. This study highlights the role of bicarbonate ions in enhancing carbon availability for aquatic photosynthesis, thereby optimizing oxygen generation rate. The experimental methodology coupled with a numerical framework based on spatial diffusion model, as discussed in this endeavor, is novel in estimating oxygen generation rate from whole-plant in a closed system, enabling reproducible scaling for state-of-the-art environmental technologies. The insights gained from this in silico endeavor are expected to have broad implications for wastewater treatment (enhancing aerobic biodegradation), aquaculture (maintaining high dissolved oxygen), and carbon capture (biomass-based CO2 sequestration). Future research could focus on the exploration of long-term physiological effects of KHCO3 supplementation on oxygen generation and improvisation of modeling framework to incorporate biological feedback mechanisms into the underlying analysis.