Dr. Aoesta K. Rudick

The central theme of my research is identifying relationships between soil structure and climate. Soil structure influences biological, physical, and chemical soil processes, such as water retention, infiltration, erosion, root penetration, and aquifer recharge. Soil structure also influences climate by affecting soil water evaporation, respiration, and the exchange of gases with the atmosphere. For example, changes in soil respiration could exceed or maintain the annual input of atmospheric CO2 due to alterations of soil structure or increases of atmospheric CO2 with consequent climate feedbacks. Degradation of soil structure and reduction in aggregation can lead to anaerobic conditions, which result in depletion of soil organic C pools and increase CO2 flux to the atmosphere.

To understand the relationships between climate, morphology, and soil structure, I had been compiling, organizing and analyzing data from over 600,000 samples on which more than 2000 variables were measured as part of the NRCS Soil Characterization Database, which contains a large variety of both qualitative and quantitative variables including soil taxonomic, morphologic, physical, chemical, climatic, geomorphic, and geographical information across the US. The structures of these data files are complex, which requires cleaning and filtering to transform them into an easily accessible format for further analyses. The data were merged with the PSDM database, the USFS Ecoregions of the US and the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) to add climatological and ecological information. Initial results show that precipitation and temperature are important variables in increasing ped roundness in surface horizons regardless of parent materials. This may open the door to a new understanding of the genesis of soil structure.

The second theme of my research is overcoming the limitation of qualitative descriptions of soil structure. In order to set the context for understanding the evolution of soil structure, I developed a tool to quantify soil structure using morphometric indices for ped shape by digitally analyzing previously published photographs of soil profiles and structure specimens and creating a ped shape digital morphometrics (PSDM) database (Mohammed et al, 2016). Digital shape metrics from this study can be used to convert morphological descriptions of soil structure (e.g., from soil survey descriptions) into numeric shape indices. This method transformed typical categorical descriptions of soil structure into continuous quantitative data.

The third theme of my research is Predicting Flood Vulnerability in a Developing Urbanized Environment. Existing flood vulnerability models typically require datasets containing soil, land use, hydrology, and climate information, all of which are generally available only in developed countries. In contrast, developing countries lack the spatial and temporal information required as inputs to predict potential flood inundation, thereby making those countries particularly vulnerable, especially under evolving global climatic regimes. At present, reliable flood vulnerability models depend on stream flow rate, discharge, and inundation depth data from previous flood events—data which are lacking in many parts of the world.

Currently, I am interested on geographical distribution of soil health in relation with environmental factors in the USA, using many multivariate approaches to model these relationships such as Structural Equation modeling (SEM).