To address the global challenge of understanding freshwater bodies, our study introduces a comprehensive approach to model the depth-area-storage (D-A-S) relationships of over 1.4 million global waterbodies. Utilizing the Hydrolakes and GLOBathy databases, we applied six equations, ranging from first to fifth-order polynomial equations and power functions, to accurately simulate depth-volume and depth-area relationships for each waterbody, categorized by volume into small, medium, and large sizes using tertiles. Our approach enhances the precision of modeling D-A-S relationships, achieving an accuracy of 0.1 meters for all waterbodies. A comparative analysis of our simulation results with the existing GLOBathy database reveals good performance of our D-A-S relationships. For D-S relationships, the power functions exhibit the highest number of outlier errors(0.25 \le\ R2 \le0.99), their overall performance surpasses that of the first-order equations but they are less effective compared to second to fifth-order equations. Notably, for large water bodies, the fifth-order equations demonstrate superior performance, with R2 values ≥ 0.99, highlighting their effectiveness in capturing the complex nature of D-S relationships. For depth-area relationships, the power functions perform the worst, having the most outlies with R2 < 0.5. Again, the fifth-order functions have the best performance, with all R2 > 0.8. Overall, the integration of polynomial and power functions has proven to be effective, offering more accurate predictions across all sizes of waterbodies. Furthermore, we have compiled a comprehensive database of D-A-S relationships and equations, accompanied each equation’s error, to serve as a user-friendly resource for furthering water resource and ecological research globally.