We estimate the soil moisture variability for basin and SMAP sub-grid using radar rainfall and soil properties.
We drive the statistical information for dry-down and wetting of soils and we use this information to estimate the spatial and temporal variability of soil moisture at the basin and satellite sub-grid. Our methods and results is useful where higher resolution soil moisture data is needed. On the other hand, we show that the variance (and standard deviation) of a bounded variable should be bounded. However, our methodology leads to an estimation of variability and skewness of soil moisture.
As there is precipitation event over the basin, the soil moisture tends to increase and the mean value increases. At the same time, standard deviation of soil moisture decreases for wetter conditions. This phase is more rapid than dry-downs and changes the state of the soils faster. I have created these a video for a demonstration of how the soil moisture distribution changes over time as the wetting and dry-down events occur.
For example, in here I am showing an animation of the soil moisture distribution over time for Turkey River basin, located in North East of State of Iowa, USA.
While satellite-based soil moisture estimations are coarse in spatial resolution, our methods could be used for estimating variability of soil moisture at a given pixel or watershed.
For more details, you can download our paper in the attachment.