Visualizing Large Data Sets: Spatial and Temporal Soil Moisture Regime Dynamics

Core Ideas • A novel technique is developed for displaying large soil moisture data sets • Spatial and temporal soil moisture regime characteristics are captured • System dynamics are conveyed without plotting subjective profiles or histories Despite constituting a small portion of global water, soil moisture controls regional to continental precipitation patterns, soil biogeochemistry, C and nutrient cycling, watershed rainfall–runoff response, and vegetation patterning. While advanced, spatially and temporally distributed soil moisture measurement and prediction techniques are necessary for improving understanding of vadose zone processes, they generate a wealth of data that are difficult to visualize in a manner that conveys salient features of system dynamics. Specifically, visualizations using soil moisture profiles or time series require subjective selection of times or locations, respectively, and inevitably fail to capture the majority of the data. We developed a method for visualizing the complete soil moisture regime using time series data measured or simulated along a one‐dimensional spatial domain, which maintains the spatial relationship of measurement locations and conveys a sense of the variability of soil moisture at each location ordinate without the subjectivity of selecting representative soil moisture profiles for plotting. This technique is capable of conveying relevant features of soil moisture dynamics, such as the influence of soil texture, precipitation, plant water use, and groundwater interactions, by using (i) simulated soil moisture data from an ecohydrological model and (ii) field data collected using an advanced, spatially distributed measurement technique. Visualization techniques such as this one will be useful for developing insight into vadose zone processes and validating sophisticated vadose zone models with field data.