Abstract: Microtopography in low-relief plain regions exerts a significant regulatory influence on rainfall-runoff processes through dynamic ponding-detention effects. However, quantitatively describing these effects and integrating them into hydrological models remain challenging. Based on field hydrological monitoring in the Taihu Basin, an elementary microtopographic unit method was developed to provide an organized characterization of microtopographic structures. A dynamic depression-filling algorithm was then established to efficiently simulate ponding-detention processes. Furthermore, a microtopographic detention curve was formulated to quantify these dynamic effects, and a hydrological model incorporating microtopographic effects was proposed. The algorithm and model were applied and validated using high-resolution topographic data from seven typical microtopographic regions, along with field monitoring data from experimental stations. The results demonstrate that while maintaining physical consistency, the algorithm reduces the number of units involved in computations by 1—2 orders of magnitude. The microtopographic detention curve achieves a high goodness-of-fit to the ponding–detention process, with an average correlation coefficient of 0.99. The model effectively captures early-stage rainfall detention and late-stage delayed-release processes, reducing runoff simulation errors by 19%. Overall, the proposed approach provides an effective pathway for quantifying dynamic ponding–detention effects and advances the process-based framework of hydrological modeling in plain regions.