Volume Estimation of Landslide Affected Soil Moisture Using TRIGRS: A Case Study of Longxi River Small Watershed in Wenchuan Earthquake Zone, China

Sun, Tong; Deng, Zhiyuan; Zhou, Xiqiang; Wang, Xiekang

doi:10.3390/w13010071

Cited by 3 publications

(2 citation statements)

References 40 publications

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“…Complex rainfall processes can be effectively solved using the analytical solution for vertical penetration in the Richards Equation [64]. In addition, this model can be extended to the infiltration into the unsaturated layer above the water table [65,66]. When the infiltration seeping down into the water table exceeds the maximum amount that gravity can discharge, the excess water is compared with the water table or the available pore space on the edge of the capillaries for slope-stability analysis.…”

Section: Trigrs Modelmentioning

confidence: 99%

Accelerating Effect of Vegetation on the Instability of Rainfall-Induced Shallow Landslides

et al. 2022

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Rainfall-induced shallow landslides are widespread throughout the world, and vegetation is frequently utilized to control them. However, in recent years, shallow landslides have continued to frequently occur during the rainy season on the vegetated slopes of the Loess Plateau in China. To better probe this phenomenon, we considered vegetation cover in the sensitivity analysis of landslide hazards and used the transient rainfall infiltration and grid-based regional slope stability (TRIGRS) model to quantitatively describe the impacts of different types of vegetation cover on slope stability. Based on the rainfall information for landslide events, the spatiotemporal distributions of the pore water pressure and the factor of safety of the vegetated slopes were inverted under the driving changes in the soil properties under different vegetation types, and the average prediction accuracy reached 79.88%. It was found that there was a strong positive correlation between the cumulative precipitation and the proportion of landslide-prone areas in woodland covered by tall trees, grassland covered by shrubs and grasses, and cultivated land. The highest landslide susceptibility, which has the greatest potential to hasten the occurrence of rainfall-induced landslides, is found in woodland with tall trees. Therefore, this paper proposes the promoting relationship between vegetation and landslide erosion, which provides a new scientific perspective on watershed management to prevent shallow landslide disasters and manage and develop watershed vegetation.

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Section: Trigrs Modelmentioning

confidence: 99%

Accelerating Effect of Vegetation on the Instability of Rainfall-Induced Shallow Landslides

et al. 2022

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“…water resources monitoring [15,16], monitoring mining hazards [17,18], landslide and natural hazard monitoring [19,20], soil moisture estimation [21], flood risk monitoring [22,23], geomorphic change detection [24,25], and morphometric analysis [26,27]. However, highquality data acquisition and processing protocols for geomorphic research and development are still poorly documented.…”

Section: Introductionmentioning

confidence: 99%

Towards a Guideline for UAV-Based Data Acquisition for Geomorphic Applications

2023

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Recent years have seen a rapid rise in the generation of high-resolution topographic data using custom-built or commercial-grade Unmanned Aerial Vehicles (UAVs). Though several studies have demonstrated the application potential of UAV data, significant knowledge gaps still exist in terms of proper documentation of protocols for data acquisition, post-flight data processing, error assessments, and their mitigation. This work documents and provides guidelines for UAV data acquisition and processing from several years of field experience in diverse geomorphic settings across India, including undulating topography (~17 km2), alluvial plains (~142 km2), lowland-river basin (~66 km2), and a highly urbanized area (~5 km2). A total of 37,065 images with 16 and 20 Megapixels and 604 ground control points (GCPs) were captured with multiple UAV systems and processed to generate point clouds for a total area of ~230 km2. The Root Mean Square Error (RMSE) for each GCP for all sites ranged from 6.41 cm to 36.54 cm. This manuscript documents a comprehensive guideline for (a) pre-field flight planning and data acquisition, (b) generation and removal of noise and errors of the point cloud, and (c) generation of orthoimages and digital elevation models. We demonstrate that a well-distributed and not necessarily uniformly distributed GCP placement can significantly reduce doming error and other artifacts. We emphasize the need for using separate camera calibration parameters for each flight and demonstrate that errors in camera calibration can significantly impact the accuracy of the point cloud. Accordingly, we have evaluated the stability of lens calibration parameters between consumer-grade and professional cameras and have suggested measures for noise removal in the point cloud data. We have also identified and analyzed various errors during point cloud processing. These include systematic doming errors, errors during orthoimage and DEM generation, and errors related to water bodies. Mitigation strategies for various errors have also been discussed. Finally, we have assessed the accuracy of our point cloud data for different geomorphic settings. We concluded that the accuracy is influenced by Ground Sampling Distance (GSD), topographic features, and the placement, density, and distribution of GCPs. This guideline presented in this paper can be extremely beneficial to both experienced long-term users and newcomers for planning the UAV-based topographic survey and processing the data acquired.

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3D modeling-based area-volume power-law relationships for incipient rotational slides

He,

Yu,

Yuan

et al. 2023

Geomorphology

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Volume Estimation of Landslide Affected Soil Moisture Using TRIGRS: A Case Study of Longxi River Small Watershed in Wenchuan Earthquake Zone, China

Cited by 3 publications

References 40 publications

Accelerating Effect of Vegetation on the Instability of Rainfall-Induced Shallow Landslides

Accelerating Effect of Vegetation on the Instability of Rainfall-Induced Shallow Landslides

Towards a Guideline for UAV-Based Data Acquisition for Geomorphic Applications

3D modeling-based area-volume power-law relationships for incipient rotational slides

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