Abstract: To improve the accuracy of 0–2 h precipitation nowcasting over complex terrain, a kilometer- and minute-scale optical-flow fusion framework (Fused) driven by both physics and data principles is proposed. This method fuses the Recurrent All-Pairs Field Transforms (RAFT) optical flow with the classical Farneback dense optical flow. It was trained on the 5-km multi-source merged precipitation analysis product over China from May to September during 2022–2024 and independently validated against 45 precipitation events in 2025 over the Dabie Mountain region. Verification results for complex terrain demonstrate that, within the 120-min forecast lead time, the Fused method achieves an RMSE of 0.55 mm, representing reductions of 19% and 34% compared with the RAFT and Farneback methods, respectively. The rain area correlation coefficient is 0.51. The object-based diagnostic evaluation results show an object similarity of 0.73, area expansion of below 10%, and centroid displacement of less than 5 km. The critical success index (CSI) for 1-h rain areas reaches 0.42, while the 2-h forecast remains operationally usable. The mean absolute divergence of the fused optical flow field is 2.8×10⁻⁵ s⁻¹, with a relative error below 5%, satisfying the mass conservation approximation requirement.