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Land Surface Models (LSM) have become indispensable tools to quantify water and nutrient fluxes in support of land management strategies or the prediction of climate change impacts. However, the utilization of LSM requires soil and vegetation parameters, which are seldom available in high spatial distribution or in an appropriate temporal frequency. As shown in recent studies, the quality of these model input parameters, especially the spatial heterogeneity and temporal variability of soildoi:10.3390/rs12162660 fatcat:alckjeduxnerxcmf64bvoyabha