Multivariable Integrated Evaluation of Hydrodynamic Modeling: A Comparison of Performance Considering Different Baseline Topography Data

Abstract

AbstractContinental‐scale river hydrodynamic modeling helps to understand the global hydrological cycle, and model evaluation is essential for calibration and performance assessment. Although many models have been evaluated using several variables separately, methods for the integrated multivariable assessment have yet to be established. We proposed an integrated multivariable evaluation method and an overall basin skill score (OSK) metric, which integrates the sub‐basin skill score, calculated by combining multiple variables' normalized Nash‐Sutcliffe efficiency values. The sub‐basin approach and OSK assess the model performance at the sub‐basin and basin scales and overcome the observation‐related limitations of different spatial dimensions. Evaluation of the CaMa‐Flood global river model for the Amazon Basin considering three variables (discharge, water surface elevation, and flooded area) and two baseline topography data (Shuttle Radar Topography Mission (SRTM) and Multi‐Error‐Removed Improved‐Terrain (MERIT) digital elevation models (DEMs)), shows that the proposed methodology can overcome the limitation of single‐variable evaluation in identifying multiple best parameter sets due to low sensitivity. CaMa‐Flood considering MERIT DEM achieves a single optimal parameter set with a maximum OSK of 0.57 compared with 0.52 for the SRTM DEM, and it shows the importance of accuracy of topography data for improvement in the performance of river hydrodynamic modeling. The proposed multivariable integrated evaluation with better topography data proved to help reduce equifinality and estimate the best parameter by maintaining the physical relationships among variables.