Soil moisture is a key variable for water resources management, weather and climate predictions as well as hazard analysis. It is highly variable in space and time across scales, and thus difficult to assess. The European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) satellite with a passive L-band microwave radiometer on board is the first mission dedicated to surface soil moisture monitoring from space with global coverage every three days. By means of a complex retrieval algorithm, soil moisture is derived from the acquired brightness temperatures. Currently, data validation is performed across a range of climatic regions. In this context, the overall objective of this dissertation is SMOS validation in the Skjern River Catchment in Denmark, including the acquisition of the required in situ data, and its comparison with the SMOS products. Data collection included a short-term airborne campaign with the L-band radiometer EMIRAD-2 and in situ measurements, as well as the establishment of a soil moisture and temperature network. To a priori increase the probability of a representative network average at SMOS scale (∼40-50 km), a method based on analysis of the prevailing environmental conditions was developed and successfully applied. In addition to retrieved soil moisture, validation also involved SMOS brightness temperature data and the most sensitive parameters of the retrieval algorithm. Using two complementary data sets allowed for comprehensive analysis over spatial and temporal scales. While the campaign data set of high spatial coverage and density proved of value for site-specific determination of important algorithm parameters, the long-term network record enables the assessment of temporal trends. Consistent with worldwide findings, results show that SMOS well captures the temporal soil moisture dynamics in the Skjern River Catchment. However, the retrieved soil moisture shows a constant dry-bias and exhibits a stronger precipitation response compared to the in situ measurements. In addition to the broadly discussed Radio Frequency Interferences (RFI) and a mismatch in sampling depth between in situ sensors and L-band emission depth, several inaccuracies in the algorithm could be located as most likely error sources at the Danish site. This includes the vegetation optical depth and surface roughness parameters, soil properties and the Dobson dielectric mixing model. This dissertation is not only a valuable contribution to SMOS validation, but can also be supportive for upcoming space missions such as NASA’s Soil Moisture Active and Passive, SMAP. Knowing the current caveats the use of SMOS data in regional and global modeling of water resources and climate can be initiated. Future work in the Skjern River Catchment will focus on the disclosed error sources, as well as the influence of organic layers by means of not yet explored campaign data.