HPC MSU

Publication Abstract

Visualizing Uncertainty of River Model Ensembles

van der zwaag, J., Zhang, S., Moorhead, R. J., Welch, D., & Dyer, J. (2015). Visualizing Uncertainty of River Model Ensembles. Conference on Visualization and Data Analysis 2015. San Francisco, CA: IS&T/SPIE.

Abstract

Ensembles are an important tool for researchers to provide accurate forecasts and proper validation of their models. To accurately analyze and understand the ensemble data, it is important that researchers clearly and efficiently visualize the uncertainty of their model output. In this paper, we present several methods for visualizing uncertainty in 1D river model ensembles. 2D and 3D inundation maps are generated by combining the 1D river model output with high-resolution digital elevation model data. We use the strengths of commonly used techniques for analyzing statistical data, and we apply them to the 2D and 3D visualizations of inundation maps. The resulting visualizations give researchers an easy method to quickly identify the areas of highest probability of inundation while also seeing the entire range of the ensemble output. It also allows forecasters to generate inundation maps to clearly show the general public the areas that are more likely to be in danger of flooding.