Delineation of Small Flat Watershed with High-Resolution DEM from Terrestrial Laser Scanning
Publication: Journal of Hydrologic Engineering
Volume 26, Issue 7
Abstract
The digital elevation model (DEM) has been widely used in hydrological analysis and flood assessment. While DEMs, derived from airborne light detection and ranging (lidar) technology, have sufficient accuracy for large-scale floodplain management practices, their utility in supporting high-resolution hydrologic simulations is disputable due to their limitations in resolution. In contrast, terrestrial laser scanning (TLS) is capable of conducting very dense point measurements, especially in close distance, generating high-resolution point clouds that may support high-fidelity hydrologic modeling for small areas. The study takes a case study approach in which we delineate boundaries of a catchment area for a small-scale () stormwater management measure (porous parking lot) under different DEM resolutions generated from TLS with the end goal of understanding the utility of TLS for high-fidelity hydrologic modeling. Results showed that the 0.03-m resolution provided an accurate representation of terrain surface. Larger raster cell–size DEMs generated greater uncertainties on boundaries and streamlines. DEMs with resolutions below have small differences of 1%, while larger cell–size DEMs () could have as high as 13%. Excluding the depressed parking lot of a constrained area, the remaining drainage area could be overestimated by 43% at a 0.96-m resolution. These findings indicate that a fine resolution DEM is necessary for quantifying the drainage area of small flat watersheds.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request, including but not limited to:
1.
Point cloud data set obtained from TLS, and
2.
Point cloud data set obtained from USGS 3D Elevation Program (USGS Lidar Point Cloud NJ SdL5 2014 18TWK640955 LAS 2015, https://www.sciencebase.gov/catalog/item/5fdf00afd34e30b9123e5ff4).
Acknowledgments
This research was conducted as a part of the community resiliency project sponsored by the National Fish and Wildlife Foundation. The graduate study of the first author (Zikai Zhou) was also financially supported by Rutgers University.
References
Argüelles-Fraga, R., C. Ordóñez, S. García-Cortés, and J. Roca-Pardiñas. 2013. “Measurement planning for circular cross-section tunnels using terrestrial laser scanning.” Autom. Constr. 31 (May): 1–9. https://doi.org/10.1016/j.autcon.2012.11.023.
Armesto, J., J. Roca-Pardiñas, H. Lorenzo, and P. Arias. 2010. “Modelling masonry arches shape using terrestrial laser scanning data and nonparametric methods.” Eng. Struct. 32 (2): 607–615. https://doi.org/10.1016/j.engstruct.2009.11.007.
Bater, C. W., and N. C. Coops. 2009. “Evaluating error associated with lidar-derived DEM interpolation.” Comput. Geosci. 35 (2): 289–300. https://doi.org/10.1016/j.cageo.2008.09.001.
Chow, T. E., and M. E. Hodgson. 2009. “Effects of lidar post-spacing and DEM resolution to mean slope estimation.” Int. J. Geog. Inf. Sci. 23 (10): 1277–1295. https://doi.org/10.1080/13658810802344127.
Crutchley, S. 2006. “Light detection and ranging (lidar) in the Witham Valley, Lincolnshire: An assessment of new remote sensing techniques.” Archaeol. Prospect. 13 (4): 251–257. https://doi.org/10.1002/arp.294.
Dixon, B., and J. Earls. 2009. “Resample or not?! Effects of resolution of DEMs in watershed modeling.” Hydrol. Processes 23 (12): 1714–1724. https://doi.org/10.1002/hyp.7306.
Fanti, R., G. Gigli, L. Lombardi, D. Tapete, and P. Canuti. 2013. “Terrestrial laser scanning for rockfall stability analysis in the cultural heritage site of Pitigliano (Italy).” Landslides 10 (4): 409–420. https://doi.org/10.1007/s10346-012-0329-5.
Gong, G., S. Mattevada, and S. E. O’Bryant. 2014. “Comparison of the accuracy of kriging and IDW interpolations in estimating groundwater arsenic concentrations in Texas.” Environ. Res. 130 (Apr): 59–69. https://doi.org/10.1016/j.envres.2013.12.005.
Gong, J., and A. Maher. 2014. “Use of mobile lidar data to assess hurricane damage and visualize community vulnerability.” Transp. Res. Rec. 2459 (1): 119–126. https://doi.org/10.3141/2459-14.
Gueudet, P., G. Wells, D. Maidment, and A. Neuenschwander. 2004. “Influence of the postspacing density of the LiDAR-derived DEM on flood modeling.” In Proc., Geographic Information Systems and Water Resources III—AWRA Spring Specialty Conf. Middleburg, VA: American Water Resources Association.
Habtezion, N., M. Tahmasebi Nasab, and X. Chu. 2016. “How does DEM resolution affect microtopographic characteristics, hydrologic connectivity, and modelling of hydrologic processes?” Hydrol. Processes 30 (25): 4870–4892. https://doi.org/10.1002/hyp.10967.
Hodgson, M. E., and P. Bresnahan. 2004. “Accuracy of airborne lidar-derived elevation.” Photogramm. Eng. Remote Sens. 70 (3): 331–339. https://doi.org/10.14358/PERS.70.3.331.
Kashani, A. G., P. S. Crawford, S. K. Biswas, A. J. Graettinger, and D. Grau. 2015. “Automated tornado damage assessment and wind speed estimation based on terrestrial laser scanning.” J. Comput. Civ. Eng. 29 (3): 04014051. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000389.
Kienzle, S. 2004. “The effect of DEM raster resolution on first order, second order and compound terrain derivatives.” Trans. GIS 8 (1): 83–111. https://doi.org/10.1111/j.1467-9671.2004.00169.x.
Large, A. R. G., and G. L. Heritage. 2007. “Terrestrial laser scanner based instream habitat quantification using a random field approach.” In Proc., of the RSPSpc Conf. 2007. Nottingham, UK: Remote Sensing and Photogrammetry Society.
Liang, X., et al. 2016. “Terrestrial laser scanning in forest inventories.” ISPRS J. Photogramm. Remote Sens. 115 (May): 63–77. https://doi.org/10.1016/j.isprsjprs.2016.01.006.
Mahal, V., and A. Arie. 1996. “Distance measurements using two frequency-stabilized Nd: YAG lasers.” Appl. Opt. 35 (16): 3010–3015. https://doi.org/10.1364/AO.35.003010.
Meneses, D. M. 2020. “Hydrologic monitoring and analysis of porous parking lot in Linden, New Jersey.” Master’s thesis, Rutgers Univ., https://rucore.libraries.rutgers.edu/rutgers-lib/64090/PDF/1/play/.
Moore, I. D., R. B. Grayson, and A. R. Ladson. 1991. “Digital terrain modelling: A review of hydrological, geomorphological, and biological applications.” Hydrol. Processes 5 (1): 3–30. https://doi.org/10.1002/hyp.3360050103.
Novacheva, A. 2008. “Building roof reconstruction from LiDAR data and aerial images through plane extraction and colour edge detection.” In Vol. XXXVII of Proc., Int. Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Part B6b. Beijing: International Society of Photogrammetry and Remote Sensing. https://www.isprs.org/publications/archives.aspx.
Oke, J. B., et al. 1995. “The Keck low-resolution imaging spectrometer.” Publ. Astron. Soc. Pac. 107 (710): 375. https://doi.org/10.1086/133562.
Pavlova, A. I. 2017. “Analysis of elevation interpolation methods for creating digital elevation models.” Optoelectron. Instrum. Data Process. 53 (2): 171–177. https://doi.org/10.3103/S8756699017020108.
Polat, N., and M. Uysal. 2018. “An experimental analysis of digital elevation models generated with lidar data and UAV photogrammetry.” J. Indian Soc. Remote Sens. 46 (7): 1135–1142. https://doi.org/10.1007/s12524-018-0760-8.
Qiu, D. W., and J. G. Wu. 2008. “Terrestrial laser scanning for deformation monitoring of the thermal pipeline traversed subway tunnel engineering.” In Vol. XXXVII of Proc., Int. Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Part B5. Beijing: International Society of Photogrammetry and Remote Sensing. https://www.isprs.org/publications/archives.aspx.
Rengers, F. K., and G. E. Tucker. 2015. “The evolution of gully headcut morphology: A case study using terrestrial laser scanning and hydrological monitoring.” Earth Surf. Processes Landforms 40 (10): 1304–1317. https://doi.org/10.1002/esp.3721.
Resop, J. P., and W. C. Hession. 2010. “Terrestrial laser scanning for monitoring streambank retreat: Comparison with traditional surveying techniques.” J. Hydraul. Eng. 136 (10): 794–798. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000233.
Resop, J. P., J. L. Kozarek, and W. C. Hession. 2012. “Terrestrial laser scanning for delineating in-stream boulders and quantifying habitat complexity measures.” Photogramm. Eng. Remote Sens. 78 (4): 363–371. https://doi.org/10.14358/PERS.78.4.363.
Rishikeshan, C. A., S. K. Katiyar, and V. N. V. Mahesh. 2014. “Detailed evaluation of DEM interpolation methods in GIS using DGPS data.” In Proc., 2014 Int. Conf. on Computational Intelligence and Communication Networks, 666–671. New York: IEEE.
Roostaee, M., and Z. Deng. 2019. “HSPF-based watershed-scale water quality modeling and uncertainty analysis.” Environ. Sci. Pollut. Res. 26 (9): 8971–8991. https://doi.org/10.1007/s11356-019-04390-0.
Roostaee, M., and Z. Deng. 2020. “Effects of digital elevation model resolution on watershed-based hydrologic simulation.” Water Resour. Manage. 34 (8): 2433–2447. https://doi.org/10.1007/s11269-020-02561-0.
Uysal, M., A. S. Toprak, and N. Polat. 2015. “DEM generation with UAV photogrammetry and accuracy analysis in Sahitler hill.” Measurement 73 (Sep): 539–543. https://doi.org/10.1016/j.measurement.2015.06.010.
van den Berg, S. A., S. T. Persijn, G. J. P. Kok, M. G. Zeitouny, and N. Bhattacharya. 2012. “Many-wavelength interferometry with thousands of lasers for absolute distance measurement.” Phys. Rev. Lett. 108 (18): 183901. https://doi.org/10.1103/PhysRevLett.108.183901.
Wang, H., Z. Wu, and C. Hu. 2015. “A comprehensive study of the effect of input data on hydrology and non-point source pollution modeling.” Water Resour. Manage. 29 (5): 1505–1521. https://doi.org/10.1007/s11269-014-0890-x.
Wartenberg, D., C. Uchrin, and P. Coogan. 1991. “Estimating exposure using kriging: A simulation study.” Environ. Health Perspect. 94 (Sep): 75–82. https://doi.org/10.2307/3431296.
Yang, P., D. P. Ames, A. Fonseca, D. Anderson, R. Shrestha, N. F. Glenn, and Y. Cao. 2014. “What is the effect of LiDAR-derived DEM resolution on large-scale watershed model results?” Environ. Modell. Software 58 (Aug): 48–57. https://doi.org/10.1016/j.envsoft.2014.04.005.
Zhang, W., J. Qi, P. Wan, H. Wang, D. Xie, X. Wang, and G. Yan. 2016. “An easy-to-use airborne LiDAR data filtering method based on cloth simulation.” Remote Sens. 8 (6): 501. https://doi.org/10.3390/rs8060501.
Information & Authors
Information
Published In
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Aug 26, 2020
Accepted: Feb 9, 2021
Published online: Apr 20, 2021
Published in print: Jul 1, 2021
Discussion open until: Sep 20, 2021
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Diego M. Meneses, Lin Zheng, Qizhong Guo, Stormwater-Retaining Ground Surface Depressions of Solar Photovoltaic Farms, Journal of Sustainable Water in the Built Environment, 10.1061/JSWBAY.SWENG-525, 10, 1, (2024).
- Diego M. Meneses, Lin Zheng, Qizhong Guo, Identification and Quantification of Surface Depressions on Grassy Land Surfaces of Different Topographic Attributes Using High-Resolution Terrestrial Laser Scanning Point Cloud and Triangulated Irregular Network, Journal of Hydrologic Engineering, 10.1061/JHYEFF.HEENG-5823, 28, 4, (2023).