Location

Nessmith-Lane Atrium

Session Format

Poster Presentation

Research Area Topic:

Natural & Physical Sciences - Geology, Geography and GIS Systems

Co-Presenters, Co- Authors, Co-Researchers, Mentors, or Faculty Advisors

Gustavo Maldonado (Georgia Southern University)

Jan Friesen (Helmholtz Centre for Environmental Research)

John T. Van Stan (Georgia Southern University)

Abstract

Forest canopy can reduce precipitation reaching the ground by up to 50% through interception, storage, and evaporation of droplets from leaf and bark surfaces. This process, called "interception loss," impacts runoff, recharge, flood flashiness, erosion, etc., and cost of stormwater management. It is not well understood how canopy structure affects interception loss, particularly in urban forests. This research addresses this issue by monitoring interception loss variables for a common south eastern US tree species (slash pine) across a natural-to-urban gradient in forest structure. This study considers three different sites to obtain the natural-to-urban gradient. Two of those sites are at the Georgia Southern University campus in Statesboro, GA, and one near the small city of Oliver in Screven County, GA, close to the Ogeechee River. High resolution laser-based scanners (LiDAR) are employed to generate 3D point-cloud models of the forest canopies at each site. Several individual trees from each site are separated into single-tree point clouds. The isolated tree models are then imported into a state-of-the-art computer software, Computree, for further processing. The branch structures of the trees are studied to find correlations with the amount of rain intercepted. In conjunction with the LiDAR data, automatic gauges are deployed under each forest canopy to tie canopy structures to areas where rain water flux to soils. The more automated gauges we deploy, the finer resolution we attain. This improves needed interpolations and produce more accurate results. The importance of this study is related to the fact that many soil and surface hydrological processes (e.g infiltration and recharge vs. stormwater runoff) depend on these throughfall patterns. Currently, the few publications on interception loss have completed studies on a large scale and assumed results to be the same on the small scale. However, from data previously collected, it is inferred that interception loss is actually much more sporadic rather than linear, as it is on the larger scale. This work should provide practical results to better approach runoff and stormwater management in urban environments.

Keywords

Forest, Precipitation, Flash flood, Stromwater, Ogeechee river, Statesboro

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Presentation Type and Release Option

Presentation (Open Access)

Start Date

4-16-2016 10:45 AM

End Date

4-16-2016 12:00 PM

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Apr 16th, 10:45 AM Apr 16th, 12:00 PM

Relationship between LiDAR-derived canopy layering and rainfall redistribution in forests varies with scale

Nessmith-Lane Atrium

Forest canopy can reduce precipitation reaching the ground by up to 50% through interception, storage, and evaporation of droplets from leaf and bark surfaces. This process, called "interception loss," impacts runoff, recharge, flood flashiness, erosion, etc., and cost of stormwater management. It is not well understood how canopy structure affects interception loss, particularly in urban forests. This research addresses this issue by monitoring interception loss variables for a common south eastern US tree species (slash pine) across a natural-to-urban gradient in forest structure. This study considers three different sites to obtain the natural-to-urban gradient. Two of those sites are at the Georgia Southern University campus in Statesboro, GA, and one near the small city of Oliver in Screven County, GA, close to the Ogeechee River. High resolution laser-based scanners (LiDAR) are employed to generate 3D point-cloud models of the forest canopies at each site. Several individual trees from each site are separated into single-tree point clouds. The isolated tree models are then imported into a state-of-the-art computer software, Computree, for further processing. The branch structures of the trees are studied to find correlations with the amount of rain intercepted. In conjunction with the LiDAR data, automatic gauges are deployed under each forest canopy to tie canopy structures to areas where rain water flux to soils. The more automated gauges we deploy, the finer resolution we attain. This improves needed interpolations and produce more accurate results. The importance of this study is related to the fact that many soil and surface hydrological processes (e.g infiltration and recharge vs. stormwater runoff) depend on these throughfall patterns. Currently, the few publications on interception loss have completed studies on a large scale and assumed results to be the same on the small scale. However, from data previously collected, it is inferred that interception loss is actually much more sporadic rather than linear, as it is on the larger scale. This work should provide practical results to better approach runoff and stormwater management in urban environments.