Assessment of loess terraced slope erosion using unmanned aerial vehicle photogrammetry: Topographic and hydrological effects
Pinglang Kou
Chongqing Engineering Research Center of Spatial Big Data Intelligent Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism (TMDPD, MCT), Chongqing University of Posts and Telecommunications, Chongqing, China
Search for more papers by this authorCorresponding Author
Qiang Xu
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China
Correspondence
Qiang Xu, State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, Sichuan 610059, China.
Email: [email protected]
Search for more papers by this authorZhao Jin
State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
Institute of Global Environmental Change, Xi'an Jiaotong University, Xi'an, China
Search for more papers by this authorAli P. Yunus
Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Mohali, Mohali, India
Search for more papers by this authorYuxiang Tao
Chongqing Engineering Research Center of Spatial Big Data Intelligent Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
Search for more papers by this authorYing Xia
Chongqing Engineering Research Center of Spatial Big Data Intelligent Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism (TMDPD, MCT), Chongqing University of Posts and Telecommunications, Chongqing, China
Search for more papers by this authorChuanhao Pu
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China
Search for more papers by this authorShuang Yuan
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China
Search for more papers by this authorGuofan Cao
Urban Ecology and Sustainable Development Department, Xi'an Institute for Innovative Earth Environment Research, Xi'an, China
Search for more papers by this authorPinglang Kou
Chongqing Engineering Research Center of Spatial Big Data Intelligent Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism (TMDPD, MCT), Chongqing University of Posts and Telecommunications, Chongqing, China
Search for more papers by this authorCorresponding Author
Qiang Xu
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China
Correspondence
Qiang Xu, State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, Sichuan 610059, China.
Email: [email protected]
Search for more papers by this authorZhao Jin
State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
Institute of Global Environmental Change, Xi'an Jiaotong University, Xi'an, China
Search for more papers by this authorAli P. Yunus
Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Mohali, Mohali, India
Search for more papers by this authorYuxiang Tao
Chongqing Engineering Research Center of Spatial Big Data Intelligent Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
Search for more papers by this authorYing Xia
Chongqing Engineering Research Center of Spatial Big Data Intelligent Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism (TMDPD, MCT), Chongqing University of Posts and Telecommunications, Chongqing, China
Search for more papers by this authorChuanhao Pu
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China
Search for more papers by this authorShuang Yuan
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China
Search for more papers by this authorGuofan Cao
Urban Ecology and Sustainable Development Department, Xi'an Institute for Innovative Earth Environment Research, Xi'an, China
Search for more papers by this authorAbstract
Terraced slopes are widely used in the Loess Plateau to control gully erosion, yet their potential to induce new erosion patterns remains overlooked. Here we used unmanned aerial vehicle (UAV) photogrammetry to obtain centimeter-resolution digital surface models (DSMs) and derived hydrological networks, slopes, aspects, and curvatures of the terraced slopes. Our analysis reveals terraces disrupted natural water pathways, spurring new rill formations during each rainy season—a process neglected by models. Intriguingly, despite gentler gradients, terraced slopes exhibited higher erosion rates than steeper gullies, with widespread rills on terrace ridges. Vegetation-induced deposition surpassed erosion by 1.52 times, but moisture evaporation on sunny slopes limited plant growth and enhanced erosion. We propose targeted strategies tailored to these erosion mechanisms, including terrace redesign, runoff diversion, slope strengthening, and suitable vegetation, advancing sustainable land management. However, this study faces limitations due to the reliance on drone photogrammetry, which may be influenced by environmental factors like varying solar angles and vegetation growth, and the lack of extensive field validation to support the UAV-derived data. Our study spotlights drone photogrammetry's potential for elucidating complex erosion dynamics on terraced slopes.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflict of interest.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Supporting Information
| Filename | Description |
|---|---|
| ldr5073-sup-0001-Figures.docxWord 2007 document , 13.5 MB | Supplementary Figure 1. Relationship between slope gradient, topographic changes and curvature in the gully. (a–c) Slope gradient, topographic changes and curvature, respectively, in a gully with a concave topography at the bottom of the upstream gully that still had potential for erosion. (d–f) Slope gradient, topographic changes and curvature, respectively, in another gully with a similar concave topography at the bottom of the upstream gully that still had potential for erosion. (g, h) Orthoimages at the location in (f) with sparse vegetation cover on 27 March 2019 and 19 August 2019, respectively. (i) Topographic changes at the location in (h), showing significant vegetation cover of shrubs and trees on the gully head. Supplementary Figure 2. Comparison of vegetation on shaded and sunny slopes using orthoimages from unmanned aerial vehicles. (a) Orthoimage of a gully with a predominantly sunny slope. (b) Comparison of vegetation on northeast and southwest aspects of a gully. (c) Zoomed-in view of (a). (d) Zoomed-in view of (b). (e) Vegetation growth on the terraced slope ridges. (f) Zoomed-in view of (e). (g) Differential result of the digital surface model (DSM) at the location in (f). (h) Orthoimage of the location in (f) with sparse vegetation cover in March 27, 2019. Supplementary Figure 3. Topographic changes and curvature. (a) Curvature at selected locations on March 27, 2019. (b, c) Curvature and topographic changes from digital surface model (DSM) calculations in a gully area. (d) The curvature of a terraced slope. (e) and (f) The differential results of the curvature-degraded DSM for a gully. (g) The DSM difference at the location of (d). (h, i) Curvature and topographic changes in a zoomed-in view of (g). (j, k) Curvature corresponding to erosion and uplift in (b). (l, m) Curvature corresponding to erosion and uplift in (d). (n, o) Curvature corresponding to erosion and uplift in (f). The yellow oval dashed line is a significant uplift of the concave terrain where the topographic changes are most pronounced. Dots are mean values and error bars are 95% confidence intervals. Supplementary Figure 4. Topographic changes and their correspondence with the WEPP erosion model in the study area. (a) Topographic changes derived from DSM differencing and (b) soil erosion modulus calculated by the WEPP erosion model in the study area. (c) Comparison of WEPP soil erosion modulus with relief and (d) slope gradient, the inset in (c) shows the uplift due to vegetation growth corresponding to the high erosion modulus calculated. (e) Comparison of WEPP erosion modulus with erosion and uplift. (f) Comparison of WEPP erosion modulus with slope of erosion and uplift. Error bars represent 95% confidence intervals. (g) and (h) Comparison of topographic changes and WEPP erosion modulus on both sides of a gully. (i) and (j) Comparison of topographic changes and WEPP erosion modulus on both sides of another gully. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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