Exploring large scale variability of a national network of soil moisture stations: magnitudes and distributions

Abstract:

Error budgets for estimating soil moisture are often designed to optimize results for models or decision support tools. For remote sensing validation for example, a mission criteria of unbiased root mean squared error was set at 0.04 m3/m3 volumetric soil moisture. However, soil moisture is a bounded variable, varying between 0.0 m3/m3 and saturated water content of the soil in question. After saturation, the physics related to soil moisture modeling fundamentally changes to a surface water state. The distribution of this variable can vary by climate, season, and location. It is valuable to explore the magnitudes of these different variables on the overall distributions and explore how more simple estimates impact possible error budgets. This study will impact assumptions that are made in remote sensing and modeling of this critical land surface variable.