Soil Erosion and Shallow Landslides: Prediction of the Phenomena and Measures of Sediments Delivery

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Natural Hazards".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 9664

Special Issue Editors

Department of Earth and Environmental Sciences, University of Pavia, Pavia, Italy
Interests: : landslide monitoring; landslides prediction; soil hydrology; geological modeling; A-DInSAR technique
Department of Earth and Environmental Sciences, University of Milano-Bicocca, 20126 Milan, MI, Italy
Interests: soil erosion assessment; badlands; gully; landforms modelling; field measurements; land use change
Department of Earth and Environmental Sciences, University of Pavia, 27100 Pavia, Italy
Interests: 3D engineering geological modeling; landslide monitoring; A-DInSAR technique for landslide and subsidence identification and monitoring
Department of Earth and Environmental Sciences, University of Pavia, 27100 Pavia, Italy
Interests: terrain analysis; natural hazard; pedology; sustainable development; soil erosion
Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Studentski trg 1, Beograd, Serbia
Interests: landscape sensitivity; badlands; weathering processes; mineralogy and geochemistry; laboratory measurements
Department of Geography & Environmental Studies, University of Regina, Regina, SK S4S 0A2, Canada
Interests: badland erosion; subsurface erosion and flow; slope stability; geomorphic hazards; land degradation; landscape sensibility to climate change

Special Issue Information

Dear Colleagues,

Rill–inter-rill erosion, piping, gully erosion, and the formation of badlands and shallow landslides are the most important forms of soil loss that can be observed all over the world. This interplay of runoff and gravitational processes leads to the loss of fertile soils, the modification of the landscape, and damages to agricultural activities and to infrastructures. The mapping and prediction of these phenomena of soil loss becomes increasingly important also in terms of informing climate change adaptation strategies. In recent decades, scientific efforts have included (i) the classification of erosional and shallow landslide landforms, (ii) the preparation of inventory maps, (iii) the analysis of susceptibility and hazard toward these phenomena, and (iv) the application of techniques to measure soil loss and sediment delivery. However, soil erosion and shallow slope instabilities remain crucial geo-ecological and geomorphological issues, and targeted studies are fundamental to adapt models and to identify the appropriate combination of strategies in each affected area to reduce vulnerability toward these phenomena.

This Special Issue aims at collecting new developments and methodologies, best practices, and applications of techniques for the prediction of soil erosion and shallow landslides and for the quantification of the sediment delivery induced by these phenomena. Without constraining the range of topics that are potentially suitable for inclusion in the Special Issue, we provide the following as examples:

  • Soil erosion and shallow landslide mapping and classification;
  • Analyses of predisposing and triggering factors of the abovementioned natural hazards, focusing also on the effects of climate change;
  • Monitoring techniques of these phenomena, allowing to predict their occurrence;
  • Models of spatiotemporal prediction, susceptibility, and hazard toward these phenomena;
  • Field measurements and modeling of soil erosion and sediment mobilization due to runoff processes and shallow landslides;
  • Innovative land use strategies to prevent soil erosion and shallow landslides in wide areas.

Dr. Massimiliano Bordoni
Dr. Alberto Bosino
Prof. Dr. Claudia Meisina
Prof. Dr. Michael Maerker
Dr. Milica Kašanin-Grubin
Prof. Dr. Ulrike Hardenbicker
Guest Editors

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Keywords

  • shallow landslides
  • susceptibility
  • hazard
  • sediment dynamics
  • field surveys
  • sediment dynamics
  • climate change

Published Papers (5 papers)

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Research

18 pages, 3663 KiB  
Article
Sediment Transport Modeling in the Pasig River, Philippines Post Taal Volcano Eruption
by Joan Cecilia Casila, Howard Lee Andres, Soufiane Haddout and Katsuhide Yokoyama
Geosciences 2024, 14(2), 45; https://0-doi-org.brum.beds.ac.uk/10.3390/geosciences14020045 - 05 Feb 2024
Viewed by 1060
Abstract
Following the eruption of the Taal Volcano in January 2020 and its continuous signs of unrest in the preceding years, this study delves into the investigation of sediment transport in the Pasig River, Philippines. The historical data of total suspended solids (TSS) and [...] Read more.
Following the eruption of the Taal Volcano in January 2020 and its continuous signs of unrest in the preceding years, this study delves into the investigation of sediment transport in the Pasig River, Philippines. The historical data of total suspended solids (TSS) and arsenic indicated a notable increase starting from the year 2020. The field measurements were conducted in February and March of 2022, two years after the eruption. Due to the observed homogeneity in the river’s mixing, a refined 1D sediment transport model was developed. In this study, HEC-RAS modeling software was employed. The calibration process using the Laursen transport function yielded an impressive R2 value of 0.9989 for the post-eruption model. This predictive accuracy underscores the robustness of the developed model. The study’s scope was further expanded by creating a model for February 2020, incorporating water quality data gathered by the Pasig River Coordinating and Management Office. The model simulation results showed peak TSS values of 120.63 mg/L and 225.15 mg/L in February 2022 and February 2020, respectively. The results of the study highlight the probable impact of geological events on sediment dynamics within the Pasig River, which could help manage and sustain ongoing river improvements. Full article
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27 pages, 7483 KiB  
Article
Soil Erosion and Landslide Susceptibility Mapping in Western Attica, Greece: A Rock Engineering System Approach
by Nikolaos Tavoularis
Geosciences 2023, 13(11), 338; https://0-doi-org.brum.beds.ac.uk/10.3390/geosciences13110338 - 03 Nov 2023
Cited by 1 | Viewed by 1769
Abstract
Two of the eight main soil degradation processes with which soils worldwide are confronted are soil erosion and landslides. Specifically, landslides are a major threat in particular areas across Europe, often leading to serious impacts on population, property, and infrastructure. Regarding the abovementioned [...] Read more.
Two of the eight main soil degradation processes with which soils worldwide are confronted are soil erosion and landslides. Specifically, landslides are a major threat in particular areas across Europe, often leading to serious impacts on population, property, and infrastructure. Regarding the abovementioned processes, the case study of the fatal Mandra flash flood (November 2017) in the Attica Region (Greece), which caused 24 deaths, and much infrastructure and building damage, is presented with the intention of assessing the relationship between soil erosion and landslide incidents. Investigations were executed from 2018 to 2022, and their outcomes were taken into consideration by the Technical Authority of the Attica Region. Soil erosion lines were delineated in a GIS and were validated using a previously generated regional Web-GIS landslide susceptibility map. The study presents soil erosion types from the Mandra fatal flash flood event and correlates them with already existing landslide susceptibility analyses for the Attica Region. The produced susceptibility map is a cartographic product on a regional scale (1:100,000) generated via a semiquantitative heuristic methodology named the Rock Engineering System (RES). The way in which both soil erodibility and landslide susceptibility maps were generated and validated could be the basis for proposing modeling approaches that can respond to new developments in European landslide policies. Full article
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19 pages, 4856 KiB  
Article
Time-Series Variation of Landslide Expansion in Areas with a Low Frequency of Heavy Rainfall
by Ken’ichi Koshimizu and Taro Uchida
Geosciences 2023, 13(10), 314; https://0-doi-org.brum.beds.ac.uk/10.3390/geosciences13100314 - 18 Oct 2023
Viewed by 1160
Abstract
After multiple simultaneous landslides caused by heavy rainfall, expanding landslides continue to occur for a certain duration. Evaluation of the influencing period of sediment yield due to expanding landslides is vital for comprehensive sediment management of the basin. In this study, we investigated [...] Read more.
After multiple simultaneous landslides caused by heavy rainfall, expanding landslides continue to occur for a certain duration. Evaluation of the influencing period of sediment yield due to expanding landslides is vital for comprehensive sediment management of the basin. In this study, we investigated a region with a low frequency of heavy rainfall that has not received its due level of attention until now. Consequently, the transition of expanding landslides depends on the transition of the number of remaining landslides, based on the difference in the frequency of heavy rainfall. Furthermore, the transition of expanding landslides depends on the maximum daily rainfall after the landslides. These findings indicate that “the number of remaining landslides” and “maximum daily rainfall after a landslide” are related factors that determine the period during which expanding landslides frequently occur. An estimation formula based on elapsed time was developed to calculate the number of remaining landslides. An empirical formula for the number of expanding landslides was obtained by multiplying the function of the daily maximum rainfall after the landslide by the estimation formula for the number of remaining landslides. The developed empirical formula can be used effectively for evaluation during periods when rainfall-induced landslides are subject to subsequent expansion. Full article
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21 pages, 5955 KiB  
Article
High-Resolution Lidar-Derived DEM for Landslide Susceptibility Assessment Using AHP and Fuzzy Logic in Serdang, Malaysia
by Jude Okoli, Haslinda Nahazanan, Faten Nahas, Bahareh Kalantar, Helmi Zulhaidi Mohd Shafri and Zailani Khuzaimah
Geosciences 2023, 13(2), 34; https://0-doi-org.brum.beds.ac.uk/10.3390/geosciences13020034 - 28 Jan 2023
Cited by 7 | Viewed by 2043
Abstract
Landslide impact is potentially hazardous to an urban environment. Landslides occur at certain slope levels over time and require practical slope analysis to assess the nature of the slope where a landslide is likely to occur. Thus, acquiring very high-resolution remote sensing data [...] Read more.
Landslide impact is potentially hazardous to an urban environment. Landslides occur at certain slope levels over time and require practical slope analysis to assess the nature of the slope where a landslide is likely to occur. Thus, acquiring very high-resolution remote sensing data plays a significant role in determining the slope surface. For this study, 12 landslide conditioning parameters with 10 × 10 cell sizes that have never been previously collectively applied were created. These factors were created directly from the LiDAR (Light Detection and Ranging) DEM (digital elevation model)using their layer toolboxes, which include slope, aspect, elevation, curvature, and hill shade. Stream power index (SPI), topographic wetness index (TWI), and terrain roughness index (TRI) were created from spatial layers such as slope, flow direction, and flow accumulation. Shapefiles of distances to roads, lakes, trees, and build-up were digitized as land use/cover from the LiDAR image and produced using the Euclidean distance method in ArcGIS. The parameters were selected based on expert knowledge, previous landslide literature, and the study area characteristics. Moreover, multicriteria decision-making analysis, which includes the analytic hierarchy process (AHP) and fuzzy logic approaches not previously utilized with a LiDAR DEM, was used in this study to predict the possibility of a landslide. The receiver operating characteristics (ROC) were used for the validation of results. The area under the curve (AUC) values obtained from the ROC method for the AHP and fuzzy were 0.859 and 0.802, respectively. The final susceptibility results will be helpful to urban developers in Malaysia and for sustainable landslide hazard mitigation. Full article
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19 pages, 26241 KiB  
Article
Assessment of Badlands Erosion Dynamics in the Adriatic Side of Central Italy
by Margherita Bufalini, Adel Omran and Alberto Bosino
Geosciences 2022, 12(5), 208; https://0-doi-org.brum.beds.ac.uk/10.3390/geosciences12050208 - 13 May 2022
Cited by 3 | Viewed by 2079
Abstract
Badlands are unique soil erosion landforms distributed in numerous geological, geomorphological, and climate contexts in several Mediterranean countries. The aim of this study was to map, classify, and analyze the temporal evolution of the badlands that crop out between the Tesino and Tronto [...] Read more.
Badlands are unique soil erosion landforms distributed in numerous geological, geomorphological, and climate contexts in several Mediterranean countries. The aim of this study was to map, classify, and analyze the temporal evolution of the badlands that crop out between the Tesino and Tronto Rivers in the Marche region, Central Apennines (Italy). In this study, 328 badlands landforms were mapped through Google Earth, orthophoto analysis (year 2016), and field surveys. Moreover, badlands were classified from a morphological point of view based on the active processes detected in the field. Additionally, badlands were studied from a lithological point of view, meaning they were strictly related to the soft sedimentary formations of the study area. Subsequently, through the analysis of a 10 × 10 m DEM, the most significant morphometric indices were extrapolated and badlands were classified. Finally, through the orthophotos from 1988, another badlands dataset was created and the area of each landform was compared with respect to the orthophotos from 2016. The multi-temporal air photo analysis, combined with the NDVI results, identified a general reduction trend in badlands areas, with increases in green cover and dense vegetation and changes in badlands morphotypes. Full article
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