Modeling and prediction of soil hydrologic processes require the identification of soil moisture spatial-temporal patterns and effective methods allowing the data observations to be used across different spatial and temporal scales. This work presents a methodology for the combination of spatially- and temporally-extensive soil moisture data obtained in the Shale Hills Critical Zone Observatory (CZO) from 2004 to 2010. The soil moisture data sets were decomposed into spatial Empirical Orthogonal Function (EOF) patterns, and their relationship with various geophysical parameters was examined to determine the dominant factors contributing to the profiled soil moisture variability. The EOF analyses indicated that one or two EOFs of soil moisture could explain 76-89% of data variation. The primary EOF pattern had high values clustered in the valley region, and conversely low values located in the sloped hills. We suggest a novel approach to integrate the spatially-extensive manually measured datasets with the temporally-extensive automated monitored datasets based on the EOF analyses. Given the data accessibility, the current data merging framework has provided the methodology for the coupling of the mapped and monitored soil moisture datasets, as well as the conceptual coupling of slow and fast pedologic and hydrologic functions. This successful coupling implies that a combination of different extensive moisture data has provided interesting insights into our understanding of hydrological processes at multiple scales.

Excessive salts in soil inhibit enzyme activity, decrease microbial growth and constrain biochemical functioning, which could be alleviated by soil management and fertilization. However, the effect of consecutive chemical fertilizer on soil bacterial community structure under saline environment is poorly understood. Here, a field randomized block design under four nitrogen fertilization rates (0, 150, 300, and 450 kg N hm-2 y-1) was conducted on coastal salt-affected Fluvo-aquic soil. Effect of nitrogen fertilization rates on soil properties and bacterial community was characterized using Illumina Miseq sequencing for 16S rRNA gene. Results indicated that consecutive chemical N fertilization accelerated the improvement of soil chemical and microbial properties under the paddy rice - winter wheat rotation. Soil bacterial community well responded to the nitrogen fertilization and community richness and diversity increased with the nitrogen rates. Predominant bacterial phyla belonged to Proteobacteria, Chloroflexi, Acidobacteria, Actinobacteria and Planctomycetes, whereas Deltaproteobacteria, Anaerolineae, Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, Actinobacteria and Planctomycetia were dominant bacterial classes. Increasing nitrogen fertilization resulted in an elevation in the relative abundance of classes Alphaproteobacteria, Gammaproteobacteria, Planctomycetia and Nitrospira, and a decline in Anaerolineae, Acidobacteria_Gp6, Cytophagia, Bacilli and Acidobacteria_Gp10. Clear separations in the bacterial communities at class level were observed under different nitrogen fertilization rates. Community structure of classes Alphaproteobacteria, Planctomycetia and Nitrospira was significantly influenced by potential nitrification rate (PNR), and community structure of class Actinobacteria was significantly influenced by carbon mineralization rate (CMR). The results demonstrated that nitrogen fertilization improved nutrients and metabolic activities to more suitable bacterial microhabitats for saline soil.