<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Corrosion of external cast-iron pipe surfaces, a major contributor to pipe failure, has been attributed to the free water in the soil surrounding the pipe. Because observation at pipe depth is difficult, a potential proxy is the soil surface moisture. Herein highly accurate elevation data derived from airborne light detection and ranging is used to model the distribution of soil water in urban catchments containing pipe infrastructure. The results are compared with local soil moisture Theta Probe measurements along the pipe. The results show potential to identify wetter spots above underground infrastructure, which may inform its corrosion potential, without digging up the asset.</p>
</abstract>

Corrosion of external cast-iron pipe surfaces, a major contributor to pipe failure, has been attributed to the free water in the soil surrounding the pipe. Because observation at pipe depth is difficult, a potential proxy is the soil surface moisture. Herein highly accurate elevation data derived from airborne light detection and ranging is used to model the distribution of soil water in urban catchments containing pipe infrastructure. The results are compared with local soil moisture Theta Probe measurements along the pipe. The results show potential to identify wetter spots above underground infrastructure, which may inform its corrosion potential, without digging up the asset.

LiDAR derived terrain wetness indices to infer soil moisture above underground pipelines

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

running-head

Corrosion of external cast-iron pipe surfaces, a major contributor to pipe failure, has been attributed to the free water in the soil surrounding the pipe....

LiDAR derived terrain wetness indices to infer soil moisture above underground pipelines

Article Category: Research-Article

Online veröffentlicht: 15. Feb. 2020

Seitenbereich: 1 - 7

Eingereicht: 20. Dez. 2019

DOI: https://doi.org/10.21307/ijssis-2020-005

Schlüsselwörter
Pipe corrosion, Pipe breaks, Topographic wetness index, SAGA wetness index, Infrastructure assessment

© 2020 David Bretreger et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

LiDAR derived terrain wetness indices to infer soil moisture above underground pipelines

Article Category: Research-Article

Online veröffentlicht: 15. Feb. 2020

Seitenbereich: 1 - 7

Eingereicht: 20. Dez. 2019

DOI: https://doi.org/10.21307/ijssis-2020-005

SchlüsselwörterPipe corrosion, Pipe breaks, Topographic wetness index, SAGA wetness index, Infrastructure assessment

© 2020 David Bretreger et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Pipe corrosion, Pipe breaks, Topographic wetness index, SAGA wetness index, Infrastructure assessment