Upscaling Phenotypic Plasticity under Complex Infiltration: From the Lab to the Landscape

Understanding complex processes that control water and rooting interactions in the vadose zone can help change the way we approach urban development, agriculture, and all forms of land use management alike.  Complexities in areas such as soil properties and infiltration patterns can control not only the hydrologic cycle, but the ecologic and biogeochemical cycles as well.  It is important to study and understand the processes that control these complexities to help make more accurate predictions at larger scales, particularly in the face of a steadily changing climate.  The vadose zone is full of uncertainty and heterogeneity on the scale of a few meters.  Taking a careful look at the effects the small scale heterogeneities have on important environmental cycles will certainly lend assistance to a larger scale of understanding.  Laboratory based experiments provide the perfect context to isolate and manipulate the soil properties that control root growth patterns, infiltration patterns, and the relationship between the two.  Monitoring soil moisture, nutrient profiles, and root profiles in a physical 2D tank experiment will yield data that sheds light on how these three cycles interact and react to changes in one another.  In addition to laboratory data collection, finding patterns and relationships that allow for modeling of these relationships is another important step in expanding the relevance of the research from a controlled laboratory scale to a larger watershed scale. This can be done by relating soil properties and vegetation types to precipitation, in order to partition precipitation effectively based on the properties of the watershed in large models, rather than simply averaging precipitation out. The research project has two main parts.  First, a controlled, lab based infiltration study covering complexities created by soil and vegetation, and, second, using the results of the first part as sub-grid parameterization for large scale watershed modeling.

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