Iber-PEST: Automatic calibration in fully distributed hydrological models based on the 2D shallow water equations

Abstract

Calibrating physically based hydrological models manually is time-consuming and challenging. Automatic calibration tools have become prevalent in these models; however, its effective use requires not only a deep knowledge of the calibration procedure itself, but also understanding the structure of the model input and output files. In this study, we introduce Iber-PEST, a novel framework combining the parameter estimation and uncertainty analysis package, PEST, with Iber, a 2D model based on the shallow water equations. We demonstrate its capabilities by successfully calibrating eight storm events in northwestern Spain's basins, achieving promising results (mean NSE equal to 0.84). Furthermore, by applying the iterative ensemble smoother included in PEST, we demonstrate the feasibility to use the calibration data generated by Iber-PEST with alternative PEST algorithms not directly integrated in the Iber-PEST framework. This work successfully addresses the significant implementation barrier associated with the automatic calibration of Iber hydrological models with PEST.