Using visualization science to inform redesigning environmental decision support tools: a case study of the USGS WaterWatch

This dataset includes the results of evaluating 1,067 survey participants' understanding and efficiency at identifying hydrologic anomalies in map-based display. Users were tasked with identifying maps with two colormaps: rainbow and divergent brown-blue. In addition, users' preference of the two colormaps were evaluated. The surveys were administered in November and December of 2020. The two surveys administered to collect the data included in this dataset are included as an appendix to the dataset. Purpose: These data were collected to answer the following research questions: RQ1: Do users have preconceived beliefs about how colors map to streamflow levels? RQ2: Does switching from the rainbow to brown-blue colormap affect the understandability of WaterWatch maps? RQ3: Is understandability enhanced by introducing users to the colormap legend? RQ4: Does switching from the rainbow to brown-blue colormap affect the efficiency of WaterWatch maps? RQ5: Is efficiency enhanced by introducing users to the colormap legend? RQ6: Do user preferences for the rainbow or brown-blue colormap align with objective measures of performance?