Abstract: The 1D hydrodynamic model is a nonlinear complex system.Long-term simulation often consumes a lot of computing resources and time,bringing challenges to flood control forecasting and early warning.To improve the computational efficiency,the POD model and POD-DEIM model were constructed based on the Proper Orthogonal Decomposition (POD) and the Discrete Empirical Interpolation Method (DEIM) to reduce the order of the 1D hydrodynamic full-order model through projection and interpolation.The model is applied to the numerical experiment of a rectangular open channel.The results show that the first three modes of the POD model and the POD-DEIM model capture more than 99% of the energy of the full-order model.The approximate water depth error is less than 0.1m and the flow per unit width error is less than 0.6m²/s.The speedups of the POD model and POD-DEIM model are 51 times and 111 times,respectively.The results indicate that the reduced order model has high accuracy and efficiency performance and is suitable for the accelerated computation of 1D hydrodynamic models.