Development of a One-Parameter New Exponential (ONE) Model for Simulating Rainfall-Runoff and Comparison with Data-Driven LSTM Model

Abstract

Runoff information can be used for establishing watershed water management plans. However, hydrological models with complex parameters make it difficult to quickly estimate runoff. This study developed a one-parameter new exponential (ONE) model for simulating rainfall-runoff using a single parameter, which was designed based on a nonlinear exponential function and watershed water balance that varies according to the soil water storage. The single parameter was included in the runoff function and implemented to continuously track the state of the soil water storage based on the watershed water balance. Furthermore, to validate the model’s effectiveness, it was applied to two multipurpose dams in Korea and the results showed that the daily results of the ONE model were better than those of a learning-based long short-term memory model in terms of the quantitative evaluation indices, monthly heatmap and annual runoff rate. This study demonstrated that rainfall-runoff can be simulated using only one parameter and that minimizing the number of parameters could enhance the practical utility of a hydrological model. The use of a single parameter is expected to maximize user convenience for simulating runoff, which is essential in the operation of water resource facilities.