To address the problem that the parameters of the LSTM model do not transpose well in nested watersheds with inadequate records of hydrological observations, a runoff modulus-based LSTM(RM-LSTM) was developed using the Tunxi Watershed as the study watershed and its nested sub-basins as the reference watersheds, with the consideration of the influence of area factor on the parameter transfer method. The flood simulations in the reference watersheds were carried out using the parameter transfer method. The results showed that the RM-LSTM model was well applied in the study watershed, with a determination coefficient of 0.87 for the simulation results, and a qualification rate of 85.0% or more for flood peak, flood volume and peak present time. In the reference watersheds, the RM-LSTM model showed a marked improvement in terms of the determination coefficient, qualification rate of flood peak, qualification rate of flood volume, and qualification rate of peak time after the parameter transplantation, compared to the results obtained from the LSTM model. The RM-LSTM model can better take into account the influence of watershed area changes on the parameter transfer method.