PARAMETER ESTIMATION OF A DISTRIBUTED HYDROLOGICAL MODEL FOR THE IBO RIVER BASIN WITH POLYNOMIAL CHAOS EXPANSION

Abstract

 In this study, polynomial chaos expansion (PCE) was utilized to choose the optimal model parameters of a distributed hydrological model (DHM) for the Ibo River watershed in Hyogo, Japan. Because of many model parameters, only parameters with high sensitivity in the simulation results were estimated by the PCE emulator. PCE provided straightforward orthogonal polynomials that effectively captured the behavior of the DHM with greatly reduced computational complexity. The parameter estimation with PCE reduced the misfit between observed and simulated discharges at three observation stations by 25.2%–39.8%. Based on the good agreement in this case study, PCE is recommended for application in other hydrological models.