Integrating Sub-Centimeter Resolution Photogrammetry with a Surface Roughness Correction Factor Applied to PI-SWERL Measurements

This thesis consists of two chapters that summarize the development and application of a new technique used to quantify surface roughness for dust emission measurements. Chapter 1 begins with a literature review that documents the significance of research pertaining to dust emission. It then presents a summary of the development of the Portable In-situ Wind Erosion Laboratory (i.e., PI-SWERL) along with existing limitations for adjusting dust emission measurements for microtopographic surface roughness. A new method for characterizing the surface roughness correction factor, alpha (α), is introduced to address these limitations. This thesis describes the development of new reference material to assign α and is presented as a new lookup table that relates landform class and surface characteristics. The second chapter presents and discusses results from a case study application of the new approach from Chapter 1. Surface roughness correction factors were computed for landforms within White Sands National Park to study the effects of surface roughness determinations using the new semi-quantitative lookup table approach on resulting dust emission estimates. These results were compared with published literature values using older methodology. As such, the results from Chapter 2 were evaluated to assess the overall uncertainties involved with current techniques. Resulting dust flux measurements from the original dataset were compared with an adjusted version of that dataset, and a statistical analysis was conducted. The statistical analysis indicated that, of each landform evaluated, surface roughness was overestimated only for the sand sheets. As a result, dust flux was significantly underestimated in the previous study compared with this study. This thesis then examines how the recalculated fluxes project into annual dust flux budges, with estimates of annual average fluxes for sand sheets at White Sands increasing from ~277 tons/km2/year to ~329 tons/km2/year based solely on the methodology of assigning α. The new methodology documented in this thesis will help improve reproducibility of PI-SWERL measurements across studies from different researchers. Findings from this thesis will also improve the quality of in-situ field data collected with PI-SWERL that is used to validate larger global or regional scale models.

Level thesis:degree_level

Master's Degree

Year dc:date.issued

2023

Author dc:creator

• Hartshorn, Evan James

Advisor dc:contributor.advisor

• Sion, Brad

Committee members dc:contributor.committeemember

• Sweeney, Mark
• Verburg, Paul

• Dust
• Photogrammetry
• PI-SWERL
• Roughness
• White Sands
• wind tunnel

Statement dc:rights

• Creative Commons Attribution 4.0 United States

Handle dc:identifier.uri

http://hdl.handle.net/11714/10845

OAI identifier oai:identifier

oai:scholarwolf.unr.edu:11714/10845