Abstract
To overcome the difficulty of collecting fine-grained terrain data that is important for flood modelling, this work presents a method for the application of UAV-based LiDAR techniques to drive high-resolution flood propagation and inundation modelling. This paper comprehensively introduces the UAV platform, LiDAR sensor and data processing techniques required and proposes the approach for obtaining refined DEM for flood management using which the DEM accuracy can reach ±3 cm. Accordingly, two kinds of terrains, a small mountain area and a large urban area, have been measured and the time requirements for the method are 5 h and 2 days respectively. Based on the collected data, a full hydrodynamic numerical flood model is applied to simulate a flash flood in the mountain catchment and an urban flood at high-resolution. The results show that the water depth and velocity affected by key micro terrain features, such as tiny channels and roads, can be captured and considered, indicating that LiDAR UAV techniques are an efficient and reliable method for surveying terrain making them highly important for creating high accurate flood simulation.









Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.Data Availability
The data and code that support the study are available from the corresponding author upon reasonable request.
References
Azizian A (2019) The effects of topographic map scale and costs of land surveying on geometric model and flood inundation mapping. Water ResourManag 33(4):1–19. https://doi.org/10.1007/s11269-020-02670-w
Brede B, Calders K, Lau A, Raumonen P, Bartholomeus H, Herold M, Kooistra L (2019) Non-destructive tree volume estimation through quantitative structure modelling: Comparing UAV laser scanning with terrestrial LIDAR. Remote Sens Environ 233:111355. https://doi.org/10.1016/j.rse.2019.111355
Duan W, Hanasaki N, Shiogama H, Chen Y, Zou S, Nover D, Wang Y (2019) Evaluation and future projection of Chinese precipitation extremes using large ensemble high-resolution climate simulations. J Clim 32(8):2169–2183. https://doi.org/10.1175/jcli-d-18-0465.1
Duan W, He B, Nover D, Fan J, Yang G, Chen W, Meng H, Liu C (2016) Floods and associated socioeconomic damages in china over the last century. Nat Hazards 82(1):401–413. https://doi.org/10.1007/s11069-016-2207-2
Haala N, Rothermel M (2012) Dense multi-stereo matching for high quality digital elevation models. PhotogrammFernerkundungGeoinformation 4:331–343. https://doi.org/10.1127/1432-8364/2012/0121
Hammond MJ, Chen AS, Djordjevic S, Butler D, Mark O (2015) Urban flood impact assessment: a state-of-the-art review. Urban Water J 12:14–29. https://doi.org/10.1080/1573062X.2013.857421
Hou J, Li B, Tong Y, Ma L, James B, Luo H, Liang Q, Xia J (2020) Cause analysis for a new type of devastating flash flood. Hydrol Res 51:1–16. https://doi.org/10.2166/nh.2019.091
Hou J, Liang Q, Zhang H, Hinkelmann R (2015) An efficient unstructured MUSCL scheme for solving the 2D shallow water equations. Environ Model Softw 66:131–152. https://doi.org/10.1016/j.envsoft.2014.12.007
Hou J, Simons F, Mahgoub M, Hinkelmann R (2013) A robust well-balanced model on unstructured grids for shallow water flows with wetting and drying over complex topography. Comput Methods ApplMechEng 257(15):126–149. https://doi.org/10.1016/j.cma.2013.01.015
Krolik-Root C, Stansbury DL, Burnside NG (2015) Effective LiDAR-based modelling and visualization of managed retreat scenarios for coastal planning: An example from the southern UK. Ocean Coast Manag 114:164–174. https://doi.org/10.1016/j.ocecoaman.2015.06.013
Langhammer J, Jansky B, Kocum J, Minarik R (2018) 3-D reconstruction of an abandoned montane reservoir using UAV photogrammetry, aerial LiDAR and field survey. ApplGeogr 98:9–21. https://doi.org/10.1016/j.apgeog.2018.07.001
Liang Q, Marche F (2009) Numerical resolution of well-balanced shallow water equations with complex source terms. Adv Water Resour 32(6):873–884. https://doi.org/10.1016/j.advwatres.2009.02.010
Marques G, de Souza V, Moraes N (2017) The economic value of the flow regulation environmental service in a Brazilian urban watershed. J Hydrol 554:406–419. https://doi.org/10.1016/j.jhydrol.2017.08.055
Meinen B, Robinson D (2020) Mapping erosion and deposition in an agricultural landscape: Optimization of UAV image acquisition schemes for SfM-MVS. Remote Sens Environ 239:111666. https://doi.org/10.1016/j.rse.2020.111666
Price RK, Vojinovic Z (2008) Urban flood disaster management. Urban Water J 5(3):259–276. https://doi.org/10.1080/15730620802099721
Ransom OT, Younis BA (2016) Explicit GPU based second-order finite-difference modeling on a high resolution surface, Feather River, California. Water ResourManag 30:261–277. https://doi.org/10.1007/s11269-015-1160-2
Remondino F, Barazzetti L, Nex F, Scaioni M, Sarazzi D (2011) UAV photogrammetry for mapping and 3D modeling-current status and future perspectives. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII-1/C22: 25–31
Solazzo D, Sankey JB, Sankey TT, Munson SM (2018) Mapping and measuring aeolian sand dunes with photogrammetry and lidar from Unmanned Aerial Vehicles (UAV) and multispectral satellite imagery on the Praia Plateau, AZ, USA. Geomorphology 319(15):174–185. https://doi.org/10.1016/j.geomorph.2018.07.023
Soriano E, Mediero L, Garijo C (2020) Quantification of expected changes in peak flow quantiles in climate change by combining continuous hydrological modelling with the modified curve number method. Water ResourManag 34:4381–4397. https://doi.org/10.1007/s11269-020-02670-w
Tamminga AD, Eaton BC, Hugenholtz CH (2015) UAS-based remote sensing of fluvial change following an extreme flood event. Earth Surf Process Landf 40(11):1464–1476. https://doi.org/10.1002/esp.3728
Teng J, Jakeman A, Vaze J, Croke B, Dutta D, Kim S (2017) Flood inundation modelling: A review of methods, recent advances and uncertainty analysis. Environ Model Softw 90:201–216. https://doi.org/10.1016/j.envsoft.2017.01.006
Testa G, Zuccala D, Alcrudo F, Mulet J, Soares-Frazao S (2007) Flash flood flow experiment in a simplified urban district. J Hydraul Res 45(Suppl. 1):37–44. https://doi.org/10.1080/00221686.2007.9521831
Wang Y, Chen AS, Fu G, Djordjevicb S, Zhang C, Savic DA (2018) An integrated framework for high-resolution urban flood modelling considering multiple information sources and urban features. Environ Model Softw 107:85–95. https://doi.org/10.1016/j.envsoft.2018.06.010
Whitfield PH (2012) Floods in future climates: a review. J Flood Risk Manag 5(4):336–365. https://doi.org/10.1111/j.1753-318X.2012.01150.x
Zeybek M, Sanlioglu I (2019) Point cloud filtering on UAV based point cloud. Measurement 133:99–111. https://doi.org/10.1016/j.measurement.2018.10.013
Funding
This work is partly supported by the National Natural Science Foundation of China (No. 52079106), National Key Research and Development Program of China (No. 2016YFC0402704) and Visiting Researcher Fund Program of State Key Laboratory of Water Resources and Hydropower Engineering Science (No. 2016HLG01).
Author information
Authors and Affiliations
Contributions
Conceptualization and Methodology: J. Hou, B. Li; Writing-original draft preparation: B. Li; Material preparation, collection and analysis: B. Li, D. Li, D. Yang, H. Han, X. Bi, X. Wang; Supervision: R. Hinkelmann, J. Xia; Funding acquisition: J. Hou.
Corresponding author
Ethics declarations
Ethical Approval
Informed consent.
Consent to Participate
Not applicable.
Consent to Publish
The authors are indeed informed and agree to publish.
Competing Interests
None.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Li, B., Hou, J., Li, D. et al. Application of LiDAR UAV for High-Resolution Flood Modelling. Water Resour Manage 35, 1433–1447 (2021). https://doi.org/10.1007/s11269-021-02783-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-021-02783-w

