Landscape position and depth in the soil column influence the movement of microbial substrate throughout a catchment, from upslope areas to downslope areas, thereby impacting nutrient cycling rates and capabilities of the microbial communities in those areas. Wildfire also shapes the biogeochemistry of the landscape, creating a mosaic with variations in substrate type and concentration that also influence microbial communities and biogeochemical cycling. Nitrogen (N) in particular is altered by wildfire, as it is easily volatilized and the removal of organic matter (OM) reduces N inputs. We aimed to understand how landscape position and soil depth, first and foremost, influence microbial communities and their N-cycling, but also how this may differ from wildfires and their relative impacts on the soil microbial communities. Landscape position proved to influence few soil and microbial characteristics, while movement from soil surface to deep in the column and the incidence of wildfire caused many variations in soil physical and biogeochemical cycling properties. The interaction of landscape position and soil depth also showed little variation in any measurements, while wildfire and soil depth interactions showed drastic changes that indicate high order controls over the soil microbial community. It can be surmised that while landscape position is important for many soil properties, it is soil depth and wildfire that truly control the soil microbial communities and their N-cycling capabilities.

Soil hydraulic properties, such as saturated hydraulic conductivity (Ks), have high spatial variation, but little is known about how to vary a few measurements of Ks over an area to model hydrology in a watershed with complex topography and multiple land uses. Variations in soil structure, macropores (especially in soil that shrink and swell), land use, and soil development can cause large variations in Ks within one soil type. Characterizing the impacts of soil properties that might vary systematically with land use and terrain attributes on Ks rates would provide insight on how management and human activity affect local and regional hydrology. The overall objective of this research was to develop a strategy for using published infiltration and Ks measurements by the Natural Resources Conservation Service for watershed hydrology applications in a Vertisol, and to extend this knowledge toward developing recommendations for future infiltration measurements. To achieve this goal, soil infiltration measurements were collected across three catenas of Houston Black and Heiden clays (fine, smectitic, thermic Udic Haplusterts) under three land uses (improved pasture, native prairie, and conventional tillage row crop). Measurement locations were selected to account for variation in terrain attributes. Overall, Ks values were not significantly different across different landscape positions; however, in fields under similar land uses, Ks values were found to be lower in the footslope positions and higher in the backslope positions. The pedotransfer function, ROSETTA, provided estimates of 64 percent of the overall variability in Ks while also providing accurate estimates of the mean of Ks when particle size distribution and bulk density are used as inputs in the model. Through the use of multiple regression analysis, soil antecedent water content, bulk density, clay content, and soil organic carbon along with two indicator variables for the catenas were highly correlated (r2 = 0.59) with Ks. The indicator variables explained 17 percent of the variation in Ks that could not be explained by measured soil properties. It is recommended that when NRCS measures Ks on benchmark soils, especially high clay soils, that they collect particle size distribution, bulk density, organic carbon, and antecedent water content data.

The National Wetlands Inventory (NWI) is the definitive source for wetland resources in the United States. The NWI production unit in Hadley, MA has begun to upgrade their digital map database, integrating descriptors for assessment of wetland functions. Updating is conducted manually and some automation is needed to increase production and efficiency. This study assigned landscape position descriptor codes to NWI wetland polygons and correlated polygon environmental properties with public domain terrain, soils, hydrology, and vegetation data within the Coastal Plain of Virginia. Environmental properties were applied to a non-metric multidimensional scaling technique to identify similarities within individual landscape positions based on wetland plant indicators, primary and secondary hydrology indicators, and field indicators of hydric soils. Individual NWI landscape position classes were linked to field-validated environmental properties. Measures provided by this analysis indicated that wetland plant occurrence and wetland plant status obtained a stress value of 0.136 (Kruskal's stress measure = poor), which is a poor indicator when determining correlation among wetland environmental properties. This is due principally to the highly-variable plant distribution and wetland plant status found among the field-validated sites. Primary and secondary hydrology indicators obtained a stress rating of 0.097 (Kruskal's stress measure = good) for correlation. The hydrology indicators measured in this analysis had a high level of correlation with all NWI landscape position classes due the common occurrence of at least one primary hydrology indicator in all field validated wetlands. The secondary indicators had an increased accuracy in landscape position discrimination over the primary indicators because they were less ubiquitous. Hydric soil characteristics listed in the 1987 Manual and NTCHS field indicators of hydric soils proved to be a relatively poor indicator, based on Kruskal's stress measure of 0.117, for contrasting landscape position classes because the same values occurred across all classes. The six NWI field–validated landscape position classes used in this study were then further applied in a public domain digital data analysis. Mean pixel attribute values extracted from the 180 field-validated wetlands were analyzed using cluster analysis. The percent hydric soil component displayed the greatest variance when compared to elevation and slope curvature, streamflow and waterbody, Cowardin classification, and wetland vegetation type. Limitations of the soil survey data included: variable date of acquisition, small scale compared to wetland size, and variable quality. Flow had limitations related to its linear attributes, therefore is often found insignificant when evaluating pixel values that are mean of selected pixels across of wetland landscape position polygons. NLCD data limitations included poor quality resolution (large pixel size) and variable classification of cover types. The three sources of information that would improve wetland mapping and modeling the subtle changes in elevation and slope curvature that characterize wetland landscapes are: recent high resolution leaf-off aerial photography, high-quality soil survey data, and high-resolution elevation data. Due to the data limitations and the choice of variables used in this study, development of models and rules that clearly separate the six different landscape positions was not possible, and thus automation of coding could not be attempted. / Master of Science