Soil moisture exhibited considerable spatial heterogeneity with different magnitudes of spatial dependence at different times.
Due to its complex interactions with various processes and factors, soil moisture exhibits significant spatial variability across different spatial scales.
Therefore, even though the heterogeneity of the land use increases the spatial variability (as expected), soil moisture exhibits a significant temporal stability and its large scale monitoring from few observations is still feasible.
The problem is challenging due to its multiscale nature (temperature usually propagates orders of magnitude faster than moisture), different characters of the two fields (moisture exhibits boundary layers which are not present in the temperature field), extremely long integration times (30 years or more), and lack of viable error control mechanisms.
Areas of the Mongolian steppe that had particular vegetation types and a higher level of spring soil moisture exhibited an overall trend of earlier green-up and an overall temperature increase was observed across much of the region as well as a warming trend at the beginning of the growing season.
In Indianapolis, Syracuse, and New Orleans, BPb concentration and soil moisture exhibited inverse correlations of –0.41, –0.75, –0.47, respectively.
Samples with higher moisture contents exhibit larger left shifts in the extreme T2 values and greater changes in fractal dimension.
The results show that the soil moisture fields exhibit multiscaling and multifractal behavior varying with the scales of observation and hydrometeorological forcing.
Type I GFRP bars, with the lower moisture uptake, exhibited insignificant strength reductions in the range of 2 15% whereas Type II, with the higher moisture uptake, exhibited substantial strength reductions in the range of 19 50%.
The results revealed that the CFD model developed for predicting moisture content exhibited good correlation with a coefficient of determination R2 = 0.96.
