Crossing properties of soil saturation, defined as the duration and excursion of soil saturation below and above certain thresholds, are key variables to ecosystem functioning and evolution by primarily influencing the plant and soil microbes physiological dynamics. Under climate change, the variability in the precipitation patterns is expected to be more ubiquitous and directly translate to a shift in soil saturation levels. This, in turn, will influence crossing properties of soil saturation and thus be expected to leave a mark on ecosystems. However, the lack of a deep understanding of the links between biological processes and the change in soil saturation patterns hinders foretelling the impact of climate variability on ecohydrological systems even at the smallest scale, that is, the level of a single plant. To that end, this thesis presents experimental results from laboratory soil column experiments and extensive computational studies on the interactions between soil saturation and biological activities, that is, plants and microbes. To this aim, the depth-time soil saturation patterns are mapped by means of modeling the transport processes of relevance and experimental tools at a minimal hydrological control volume in search for upscaling methods. In this context, two modeling approaches can be employed. Physically based models that explicitly represent transport processes with high costs of application at larger scales. Age-based models that rely on generic functions with a focus on time past since arrival, that is, the age of event water in the storage. This thesis work combines models (HYDRUS-1D as physically based and tran-SAS as age-based) with soil column experimental data and Bayesian inference methods to explore the links between age characteristics and transport processes. In this thesis, data from four different experimental designs on monthly to yearly timescale under varied environmental conditions are examined in terms of tracer type, precipitation pattern, vegetation, soil type, resolution and type of collected data. Of the modeled data, two sets of results from specific experiments were carried out within the framework of this thesis. This thesis addresses also the role of the balance between dispersive and convective forces, known as Péclet number, in controlling the shape of age functions in drainage. While sole reliance on drainage flow and tracer data (reflective of Péclet number) suffice to capture age dynamics in drainage, un- certainties may arise for predictions on (evapo)transpiration. This thesis deals also with the role of root distributions as controls in determining the age to root uptake and shows plants with similar uniform-equivalent root distribution render very similar age dynamics. It was shown in this thesis that nitrate consumption by microbes can be linked to age characteristics of a conservative tracer and that the relation between microbial respiration and soil saturation may bear more complexity than is currently integrated in most models. Overall, this thesis lays steps to the development of modeling tools with high predictive power for soil saturation by originating upscaling methods and bridging the gaps between physically based and age-based models with a view on the consequences of (possi- bly changing) variable soil saturation on adaptations of microbial communities and their metabolic product.