Gully-erosion estimation and terrain reconstruction using analyses of microtopographic roughness and LiDAR

dc.contributor.author

Brecheisen, ZS

dc.contributor.author

Richter, DDB

dc.date.accessioned

2021-04-14T18:57:48Z

dc.date.available

2021-04-14T18:57:48Z

dc.date.issued

2021-07-01

dc.date.updated

2021-04-14T18:57:44Z

dc.description.abstract

Gully mapping techniques successfully identify gullies over a large range of breadths and depths in complex landscapes but practices for estimating gully volumes need further development. Gully gap-interpolation for estimation of gully volume does not often factor in landscape microtopography in the generation of the new surface. These approaches can thus overestimate large classical gully volumes, averaging over depressions, or underestimate volumes by creating overly-smooth highly curved surfaces. Microtopographic methodology was developed to estimate the pre-gully surface and gully volume across the Calhoun Critical Zone Observatory (CCZO) in South Carolina, USA. The CCZO is a Southern Piedmont landscape severely gullied by historic agriculture with upland Ultisols many meters deep. Our gully-mapping and gully-filling approaches used 1 m LiDAR elevation data and is based on the premise that gullies are local depressions on uplands which are deeply incised with high microtopographic roughness. Our smoothing-via-filling-rough-depressions (SvFRD) algorithm iteratively fills gullies until landscape microtopographic roughness is reduced and unchanging after a subsequent iteration. Results were evaluated in the context of prior landscape bulk erosion estimates ranging from 1483 to 3708 m /ha as well as field surveys of gullies. Minimally eroded reference and highly-eroded post-agricultural terrain were compared to test gully-mapping and volume accuracy. Comparing gully-volume estimation techniques, inverse-distance-weighting (IDW) yielded the highest volume (1072 m /ha) followed by ANUDEM (638 m /ha) while spline-interpolation yielded the lowest estimate (555 m /ha). SvFRD landscape gully volume estimates (615.5 m /ha) were most similar to ANUDEM interpolation with roughness and gully extent results most similar to spline interpolation. Spline interpolation is effective and easily implemented but if microtopographic accuracy and mapping of fine-scale erosions features is desired to hindcast pre-gully terrain conditions, our depression-filling approach, implemented using free GIS and statistical software, is an effective method to estimate reasonable erosion volumes. 2 3 3 3 3 3

dc.identifier.issn

0341-8162

dc.identifier.uri

https://hdl.handle.net/10161/22565

dc.language

en

dc.publisher

Elsevier BV

dc.relation.ispartof

Catena

dc.relation.isversionof

10.1016/j.catena.2021.105264

dc.title

Gully-erosion estimation and terrain reconstruction using analyses of microtopographic roughness and LiDAR

dc.type

Journal article

duke.contributor.orcid

Brecheisen, ZS|0000-0002-3712-1725

pubs.begin-page

105264

pubs.end-page

105264

pubs.organisational-group

Nicholas School of the Environment

pubs.organisational-group

Environmental Sciences and Policy

pubs.organisational-group

Duke

pubs.publication-status

Accepted

pubs.volume

202

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
CATENA_proof_105264.pdf
Size:
3.62 MB
Format:
Adobe Portable Document Format
Description:
Accepted version