Abstract. Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture. Nevertheless, its spatio-temporal patterns in agriculturally used landscapes affected by multiple natural (rainfall, soil, topography etc.) and agronomic (fertilisation, soil management etc.) factors are often not well known. The aim of this study is to determine the dominant factors governing the spatio-temporal patterns of surface soil moisture in a grassland and an arable land test site within the Rur catchment in Western Germany. Surface soil moisture (0–6 cm) has been measured in an approx. 50×50 m grid at 14 and 17 dates (May 2007 to November 2008) in both test sites. To analyse spatio-temporal patterns of surface soil moisture, an Empirical Orthogonal Function (EOF) analysis was applied and the results were correlated with parameters derived from topography, soil, vegetation and land management to connect the pattern to related factors and processes. For the grassland test site, the analysis results in one significant spatial structure (first EOF), which explains about 57.5% of the spatial variability connected to soil properties and topography. The weight of the first spatial EOF is stronger on wet days. The highest temporal variability can be found in locations with a high percentage of soil organic carbon (SOC). For the arable land test site, the analysis yields two significant spatial structures, the first EOF, explaining 38.4% of the spatial variability, shows a highly significant correlation to soil properties, namely soil texture. The second EOF, explaining 28.3% of the spatial variability, is connected to differences in land management. The soil moisture in the arable land test site varies more during dry and wet periods on locations with low porosity.
Multiscale Data Fusion for Surface Soil Moisture Estimation: A Spatial Hierarchical Approach
