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Keywords = terrace damages

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24 pages, 45986 KiB  
Article
What If an Intense Rain Event Should Trigger Diffuse Shallow Landslides in a Small Mediterranean Catchment? Numerical Modeling Through Remote Sensing Techniques
by Guido Paliaga, Steven N. Ward, Fabio Luino, Francesco Faccini and Laura Turconi
Remote Sens. 2024, 16(24), 4658; https://doi.org/10.3390/rs16244658 - 12 Dec 2024
Viewed by 588
Abstract
The Mediterranean region is increasingly experiencing intense and short-term rainfall, whose effects on the ground trigger widespread and quickly evolving phenomena including debris flows and shallow landslides which cause damage to buildings and infrastructure and occasionally even loss of life. In this research, [...] Read more.
The Mediterranean region is increasingly experiencing intense and short-term rainfall, whose effects on the ground trigger widespread and quickly evolving phenomena including debris flows and shallow landslides which cause damage to buildings and infrastructure and occasionally even loss of life. In this research, we focus on the central Mediterranean in an area exposed to high-intensity rainfall that impacts small catchments which have been intensively anthropogenically modified through the years. The Portofino Promontory is characterized by a high cultural and landscape value where nature and historical anthropogenic landforms and signs coexist. The Promontory attracts tourists from all over the world, but it is exposed to a high number of hazards related to debris–mud flow processes that may impact cultural heritage, tourism facilities and infrastructure. In addition, the ancient man-made terraces that are widespread along the Promontory’s slopes may play the role of being a source for shallow landslides, as this similarly happens in many Mediterranean regions. In 2011, heavy rainfall impacted the similar landscape of the Cinque Terre, triggering hundreds of small mud–debris flows whose combined effect was devastating. To this end, a ground effects simulation was developed as part of the H2020 project RECONECT which aims to contribute to a European reference framework on nature-based solutions, based on the high-detail and -precision remote sensing data acquired within the project. The data allowed us to assess the triggering areas, the transport channel, the observed deposition zones and the interaction with the exposed elements before building a possible risk scenario. The simulation and the entire approach may be upscaled to many similar areas where shallow landslide hazards originating from man-made terraces threatens buildings, cultural heritage, tourism facilities and infrastructure. Full article
(This article belongs to the Special Issue Geomatics and Natural Hazards)
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Figure 1

Figure 1
<p>The Paraggi catchment localization within the Portofino Promontory and its land cover: 11 urban fabrics; 22 permanent crops (mostly olive groves); 24 other agricultural areas; 31 forests; 32 shrub and herbaceous vegetation associations. The red ellipse shows the Paraggi catchment, while the red square shows the San Fruttuoso small village. Municipalities are located in the inset: Portofino (POR), Camogli (CAM) and Santa Margherita Ligure (SML). The purple dot shows the Cinque Terre area.</p>
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<p>The Paraggi catchment’s geomorphologic features (modified from [<a href="#B53-remotesensing-16-04658" class="html-bibr">53</a>]): (1) active landslide scarp; (2) dormant landslide scarp; (3) degradation scarp; (4) slope erosion; (5) downcutting talweg; (6) unmappable landslide; (7) bedding; (8) debris cover; (9) conglomerates with sandstone layers; (10) marly limestones, clayed marls and marls; (11) terraces; (12) marine flood with a return time of 50 years; (13) landslides; (14) culvert; (15) trail; (16) road; (17) agricultural/rural building; (18) receptive building; (19) residential building.</p>
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<p>Distribution of geo-hydrological events recorded from 1900 to present in Portofino Promontory, shown per year, and, in orange colour, cumulative curve (data source in <a href="#remotesensing-16-04658-t002" class="html-table">Table 2</a>).</p>
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<p>The culvert’s inlet (<b>top</b>) and outlet (<b>bottom</b>); the transversal section decreases significatively, passing from 16.4 m<sup>2</sup> to 5.8 m<sup>2</sup>.</p>
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<p>The flow accumulation of running water (in dark blue) and the possible shallow landslides identified according to the results of previous studies. The square (<b>A</b>) shows the location of <a href="#remotesensing-16-04658-f006" class="html-fig">Figure 6</a>, <a href="#remotesensing-16-04658-f008" class="html-fig">Figure 8</a> and <a href="#remotesensing-16-04658-f010" class="html-fig">Figure 10</a>; the square (<b>B</b>) shows the location of <a href="#remotesensing-16-04658-f007" class="html-fig">Figure 7</a>, <a href="#remotesensing-16-04658-f009" class="html-fig">Figure 9</a> and <a href="#remotesensing-16-04658-f011" class="html-fig">Figure 11</a>.</p>
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<p>Total height of flowing and sedimented debris after 1, 2, 3 and 4 min of simulation.</p>
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<p>The total height of the flowing and sedimented debris after 1, 2, 3 and 4 min of simulation in the lower part of the catchment. In step 1, the culvert is still able to drain away the incoming sediments; in step 2 it is completely overflowing.</p>
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<p>Depth of sedimented debris after 1, 2, 3 and 4 min of simulation.</p>
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<p>The depth of the sedimented debris after 1, 2, 3 and 4 min of simulation in the lower part of the catchment. In step 1, the coarser debris begins to sediment before the culvert inlet.</p>
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<p>The debris flow velocity after 1, 2, 3 and 4 min of simulation.</p>
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<p>The debris flow velocity after 1, 2, 3 and 4 min of simulation in the lower part of the catchment.</p>
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<p>Cross sections in the small flat area at the stream mouth after 1, 2, 3 and 4 min of simulation; coarse, deposited sediments are distinguished from fine, flowing ones.</p>
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<p>The Portofino Promontory: severe rainfall events triggering shallow landslides and mud–debris flows from the beginning of the past century, arranged in five-year periods.</p>
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22 pages, 30203 KiB  
Article
Laboratory Model Tests on the Deformation and Failure of Terraced Loess Slopes Induced by Extreme Rainfall
by Jun Jia, Xiangjun Pei, Xiaopeng Guo, Shenghua Cui, Pingping Sun, Haoran Fan, Xiaochao Zhang and Qi Gu
Land 2024, 13(10), 1631; https://doi.org/10.3390/land13101631 - 8 Oct 2024
Viewed by 550
Abstract
Heavy rainfall is the main factor inducing the failure of loess slopes. However, the failure mechanism and mode of terraced loess slopes under heavy rainfall have not been well investigated and understood. This paper presents the experimental study on the deformation and failure [...] Read more.
Heavy rainfall is the main factor inducing the failure of loess slopes. However, the failure mechanism and mode of terraced loess slopes under heavy rainfall have not been well investigated and understood. This paper presents the experimental study on the deformation and failure of terraced loess slopes with different gradients under extreme rainfall conditions. The deformation and failure processes of the slope and the migration of the wetting front within the slope during rainfall were captured by the digital cameras installed on the top and side of the test box. In addition, the mechanical and hydrological responses of the slope, including earth pressure, water content, pore water pressure, and matric suction, were monitored and analyzed under rainfall infiltration and erosion. The experimental study shows that the deformation and failure of terraced loess slopes under heavy rainfall conditions exhibit the characteristic of progressive erosion damage. In general, the steeper the slope, the more severe the deformation and failure, and the shorter the time required for erosion failure. The data obtained from sensors embedded in the slope can reflect the mechanical and hydraulic characteristics of the slope in response to rainfall. The earth pressure and pore water pressure in the slope exhibit a fluctuating pattern with continued rainfall. The failure mode of terraced loess slopes under extreme rainfall can be summarized into five stages: erosion of slope surface and formation of small gullies and cracks, expansion of gullies and cracks along the slope surface, widening and deepening of gullies, local collapse and flow-slip of the slope, and large-scale collapse of the slope. The findings can provide preliminary data references for researchers to better understand the failure characteristics of terraced loess slopes under extreme rainfall and to further validate the results of numerical simulations and analytical solutions. Full article
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<p>Arrangement of the model test apparatus.</p>
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<p>Arrangement of the model test apparatus.</p>
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<p>Particle size distribution of the loess.</p>
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<p>Soil-water retention behavior of the tested loess.</p>
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<p>Schematic view of laboratory test slope model (taking the slope with a gradient of 60 degrees as an example, units are in mm) with the designated layout of the sensors.</p>
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<p>(<b>a</b>) Model construction, (<b>b</b>) sensor installation, and (<b>c</b>) excavation and rainfall processes of the terraced loess slope.</p>
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<p>View of failure evolution of terraced loess slope during rainfall: (<b>a</b>) slope with 45 degrees, (<b>b</b>) slope with 60 degrees and (<b>c</b>) slope with 75 degrees (Note: red arrows marking the main deformation locations in comparison to the previous image).</p>
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<p>View of failure evolution of terraced loess slope during rainfall: (<b>a</b>) slope with 45 degrees, (<b>b</b>) slope with 60 degrees and (<b>c</b>) slope with 75 degrees (Note: red arrows marking the main deformation locations in comparison to the previous image).</p>
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<p>View of failure evolution of terraced loess slope during rainfall: (<b>a</b>) slope with 45 degrees, (<b>b</b>) slope with 60 degrees and (<b>c</b>) slope with 75 degrees (Note: red arrows marking the main deformation locations in comparison to the previous image).</p>
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<p>Wetting front migration of the slope during rainfall: (<b>a</b>) slope with 45 degrees, (<b>b</b>) slope with 60 degrees and (<b>c</b>) slope with 75 degrees (Note: red arrows marking the initial infiltration location; red dashed line referring to the wetting front).</p>
Full article ">Figure 7 Cont.
<p>Wetting front migration of the slope during rainfall: (<b>a</b>) slope with 45 degrees, (<b>b</b>) slope with 60 degrees and (<b>c</b>) slope with 75 degrees (Note: red arrows marking the initial infiltration location; red dashed line referring to the wetting front).</p>
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<p>Variation of earth pressure in the slope during rainfall: (<b>a</b>) slope with 45 degrees, (<b>b</b>) slope with 60 degrees and (<b>c</b>) slope with 75 degrees.</p>
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<p>Variation of volumetric water content in the slope during rainfall: (<b>a</b>) slope with 45 degrees, (<b>b</b>) slope with 60 degrees and (<b>c</b>) slope with 75 degrees.</p>
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<p>Variation of pore water pressure in the slope during rainfall: (<b>a</b>) slope with 45 degrees, (<b>b</b>) slope with 60 degrees and (<b>c</b>) slope with 75 degrees.</p>
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<p>Variation of matric suction in the slope during rainfall: (<b>a</b>) slope with 45 degrees, (<b>b</b>) slope with 60 degrees and (<b>c</b>) slope with 75 degrees.</p>
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<p>Schematic diagram of failure mode of terraced loess slope under extreme rainfall.</p>
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27 pages, 11535 KiB  
Article
Climate Change Threats to UNESCO-Designated World Heritage Sites: Empirical Evidence from Konso Cultural Landscape, Ethiopia
by Yimer Mohammed Assen, Abiyot Legesse Kura, Engida Esayas Dube, Girma Kelboro Mensuro, Asebe Regassa Debelo and Leta Bekele Gure
Sustainability 2024, 16(19), 8442; https://doi.org/10.3390/su16198442 - 27 Sep 2024
Viewed by 1301
Abstract
The purpose of this study was to investigate temperature and rainfall variations and their effects on the UNESCO World Heritage Sites of Konso cultural landscape, Ethiopia, using dense merged satellite–gauge-station rainfall data (1981–2020) with a spatial resolution of 4 km-by-4 km and observed [...] Read more.
The purpose of this study was to investigate temperature and rainfall variations and their effects on the UNESCO World Heritage Sites of Konso cultural landscape, Ethiopia, using dense merged satellite–gauge-station rainfall data (1981–2020) with a spatial resolution of 4 km-by-4 km and observed maximum and min temperature data (1987–2020), together with qualitative data gathered from cultural leaders, local administrators and religious leaders. The Climate Data tool (CDT) software version 8 was used for rainfall- and temperature-data analysis. The results showed that the north and northeastern regions of Konso had significant increases in rainfall. However, it was highly variable and erratic, resulting in extreme droughts and floods. The study confirmed that there were significant (p < 0.05) increasing trends in the number of days with heavy rainfall, very-heavy rainfall days, and annual total wet-day rainfall (R10 mm, 20 mm, and PRCPTOT). The highest daily minimum temperature, lowest and highest daily maximum-temperature number of warm days and nights, and number of cold days and nights all showed significant rising trends. The increasing trends in rainfall and temperature extremes have resulted in flooding and warming of the study area, respectively. These have led to the destruction of terraces, soil erosion, loss of life and damage of properties, loss of grasses, food insecurity, migration, loss of biodiversity, and commodification of stones. The continuous decline in farmland productivity is affecting the livelihood and traditional ceremonies of the Konso people, which are helpful for the transfer of traditional resource-management knowledge to the next generation. It is therefore necessary to implement local-scale climate change adaptation and mitigation strategies in order to safeguard the Konso cultural landscapes as a worldwide cultural asset and to bolster the resilience of smallholder farmers. Full article
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Figure 1
<p>Study area map.</p>
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<p>(<b>a</b>–<b>d</b>): the spatial distribution of rainfall in the Konso zone (<b>a</b>) annually, and during (<b>b</b>) Katana, (<b>c</b>) Kiremt and (<b>d</b>) Hageya seasons(1981–2020).</p>
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<p>(<b>a</b>–<b>d</b>): spatial distribution of CV (in %) of rainfall in Konso (<b>a</b>) annually, and during the (<b>b</b>) Katana, (<b>c</b>) Kiremt and (<b>d</b>) Hageya seasons (1981–2020).</p>
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<p>Standardized annual rainfall anomalies in the Konso zone shown as the magnitude of departure from the long-term mean rainfall (1981 to 2020).</p>
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<p>(<b>a</b>–<b>d</b>): rainfall trends in Konso Zone, (<b>a</b>) annually, and during the (<b>b</b>) Katana, (<b>c</b>) Kiremt and (<b>d</b>) Hageya seasons (1981–2020). Dots on the plot indicate a significant increasing trend (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Trends of rainfall extreme indices in Konso zone (1981–2020) (<b>a</b>) Rx1, (<b>b</b>) Rx5, (<b>c</b>) R10 mm, (<b>d</b>) R20 mm, (<b>e</b>) SDII, (<b>f</b>) PRCPTOT, (<b>g</b>) CDD, (<b>h</b>) CWD, (<b>i</b>) R95p, (<b>j</b>) R99p. Solid red, solid black and dashed blue lines indicate annual extreme values, long-term trends and five years moving average respectively.</p>
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<p>Trends of rainfall extreme indices in Konso zone (1981–2020) (<b>a</b>) Rx1, (<b>b</b>) Rx5, (<b>c</b>) R10 mm, (<b>d</b>) R20 mm, (<b>e</b>) SDII, (<b>f</b>) PRCPTOT, (<b>g</b>) CDD, (<b>h</b>) CWD, (<b>i</b>) R95p, (<b>j</b>) R99p. Solid red, solid black and dashed blue lines indicate annual extreme values, long-term trends and five years moving average respectively.</p>
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<p>Trends in mean annual Tmax during distinct decades of the study period (1987–2018).</p>
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<p>Trends in mean annual Tmin during distinct decades of the study period (1987–2018).</p>
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<p>Standardized anomalies of the min and max temperature on different timescales (1987–2020).</p>
Full article ">Scheme 1
<p>A typical pafta and its internal features, in a mora in Konso; (<b>a</b>) pafta, (<b>b</b>) sleeping floor under the roof of the pafta (<b>c</b>) roof of pafta from inside. Photo credit: the authors (2023).</p>
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<p>Demolished traditional houses inside the rings (<b>a</b>) and free spaces created as a result of migration (<b>b</b>), in Tara walled village. Credit: the authors (2023).</p>
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<p>Stones in quarry site (<b>a</b>) and collected from farm lands (<b>b</b>) ready for selling in Mechelo Photo credit: Authors (2023).</p>
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<p>(<b>a</b>,<b>b</b>) Damaged terraces as a result of heavy rainfall in Mechelo. Photo credit: the authors (2023).</p>
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<p>Generational marking Ulahita trees (<b>a</b>) and Waka for commemorating heroic leaders (<b>b</b>) in Konso. Photo credit: the authors (2023).</p>
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<p>Dried-up traditional pond (harda) in Mechelo (<b>a</b>) and remote drinking-water sources on the northern border of the Konso zone (<b>b</b>). Photo credit: the authors (2023).</p>
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18 pages, 13495 KiB  
Article
Hydrological Connectivity Response of Typical Soil and Water Conservation Measures Based on SIMulated Water Erosion Model: A Case Study of Tongshuang Watershed in the Black Soil Region of Northeast China
by Muzi Li, Bin Wang, Wengang Wang, Zuming Chen and Shenyao Luo
Water 2024, 16(18), 2568; https://doi.org/10.3390/w16182568 - 10 Sep 2024
Viewed by 689
Abstract
The black soil region of Northeast China is the largest commercial grain production base in China, accounting for about 25% of the total in China. In this region, the water erosion is prominent, which seriously threatens China’s food security. It is of great [...] Read more.
The black soil region of Northeast China is the largest commercial grain production base in China, accounting for about 25% of the total in China. In this region, the water erosion is prominent, which seriously threatens China’s food security. It is of great significance to effectively identify the erosion-prone points for the prevention and control of soil erosion on the slope of the black soil region in Northeast China. This article takes the Tongshuang small watershed (Heilongjiang Province in China) as an example, which is dominated by hilly landforms with mainly black soil and terraces planted with corn and soybeans. Based on the 2.5 cm resolution Digital Elevation Model (DEM) reconstructed by unmanned aerial vehicles (UAVs), we explore the optimal resolution for hydrological simulation research on sloping farmland in the black soil region of Northeast China and explore the critical water depth at which erosion damage occurs in ridges on this basis. The results show that the following: (1) Compared with the 2 m resolution DEM, the interpretation accuracy of field roads, wasteland, damaged points, ridges and cultivated land at the 0.2 m resolution is increased by 4.55–27.94%, which is the best resolution in the study region. (2) When the water depth is between 0.335 and 0.359 m, there is a potential erosion risk of ridges. When the average water depth per unit length is between 0.0040 and 0.0045, the ridge is in the critical range for its breaking, and when the average water depth per unit length is less than the critical range, ridge erosion damage occurs. (3) When local erosion damage occurs, the connectivity will change abruptly, and the remarkable change in the index of connectivity (IC) can provide a reference for predicting erosion damage. Full article
(This article belongs to the Special Issue Research on Soil and Water Conservation and Vegetation Restoration)
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Figure 1
<p>Overview of study area.</p>
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<p>(<b>a</b>) Digital Orthophoto Map of the study area. (<b>b</b>) Map of land surface feature point identification.</p>
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<p>Spatial distribution characteristics of erosion sedimentation at different DEM resolutions. (<b>a</b>) 0.2 m resolution, (<b>b</b>) 0.5 m resolution, (<b>c</b>) 1 m resolution, (<b>d</b>) 2 m resolution, (<b>e</b>) 5 m resolution, (<b>f</b>) 12.5 m resolution. Microdegree: &lt;6.34 × 10<sup>−9</sup> kg/(m<sup>2</sup>·s). Mild: 6.34 × 10<sup>−9</sup>–7.93 × 10<sup>−8</sup> kg/(m<sup>2</sup>·s). Moderate: 7.93 × 10<sup>−8</sup>–1.59 × 10<sup>−7</sup> kg/(m<sup>2</sup>·s). Vehemence: 1.59 × 10<sup>−7</sup>–2.54 × 10<sup>−7</sup> kg/(m<sup>2</sup>·s). Extremely strong and above: &gt;2.54 × 10<sup>−7</sup> kg/(m<sup>2</sup>·s).</p>
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<p>Spatial distribution of correlation coefficient between erosion amount and relative height difference.</p>
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<p>Spatial distribution map of water depth with 0.2 m DEM resolution.</p>
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<p>Site investigation map.</p>
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<p>Spatial distribution map of water depth of undamaged terrain.</p>
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<p>A 0.2 m resolution DEM surface hydrological connectivity index distribution map.</p>
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<p>Frequency distribution of connectivity index (IC) in regions I and II.</p>
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24 pages, 11260 KiB  
Article
Fragility Analysis of Step-Terrace Frame-Energy Dissipating Rocking Wall Structure in Mountain Cities
by Youfa Yang, Yingwei Jia and Hongshen Jin
Appl. Sci. 2024, 14(11), 4731; https://doi.org/10.3390/app14114731 - 30 May 2024
Viewed by 574
Abstract
Rocking walls can control the overall deformation pattern and the distribution of plastic energy dissipation in structures, suppressing the occurrence of weak layers. In the case of step-terrace frame structures, issues such as severe lateral stiffness irregularities, abrupt changes in floor-bearing capacity, and [...] Read more.
Rocking walls can control the overall deformation pattern and the distribution of plastic energy dissipation in structures, suppressing the occurrence of weak layers. In the case of step-terrace frame structures, issues such as severe lateral stiffness irregularities, abrupt changes in floor-bearing capacity, and concentrated deformation in upper ground layers exist. To improve the yielding and failure modes of step-terrace frame structures in mountainous regions, this paper proposes a structural system combining step-terrace frame structures with energy dissipation rocking walls attached to their bottoms, aiming to control the yielding mechanism of the structure, further reduce the seismic response, limit residual deformation, and propose a structural system of step-terrace frame structures with buckling-restrained braces (BRBs) and energy dissipation rocking walls. Two sets of numerical models for step-terrace frame structures with different numbers of dropped layers and spans were established. Through simulating low-cycle repeated loading tests on step-terrace frame structures, the rationality of the models and parameters was verified. Incremental dynamic analysis (IDA) was employed to systematically investigate the vulnerability of step-terrace frame structures with energy dissipation rocking walls under different dropped layer and span configurations. This investigation covered aspects such as IDA curve clusters, percentile curves, seismic demand models, fragility functions, failure state probabilities, vulnerability indices, collapse resistance factors, and safety margins. The results indicated that the change in dropped layer numbers had a far greater impact on the vulnerability of step-terrace frame structures with energy dissipation rocking walls than the change in dropped span numbers. Under seismic excitations with the same peak ground acceleration (PGA), rocking walls can limit the depth of structural plasticity development, reduce the dispersion of peak responses, and lower the probability of exceeding various performance levels, thereby exhibiting good collapse resistance. The addition of buckling-restrained braces (BRBs) can further enhance the seismic performance and collapse resistance of the rocking wall frame structure. By analyzing the correlation between seismic intensity measures and peak structural responses, the validity of using peak ground acceleration as a scaling indicator for incremental dynamic analysis (IDA) has been verified. Full article
(This article belongs to the Section Civil Engineering)
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<p>Seismic damage of mountainous structures.</p>
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<p>Distribution of plastic hinges in low-cycle repeated loading tests for step-terrace frame structures.</p>
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<p>Structural model of the frame-rocking wall: (<b>a</b>) flat model (arrows represent horizontal seismic forces) (<b>b</b>) computing model.</p>
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<p>Three types of step-terrace frame structures.</p>
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<p>Earthquake acceleration response spectra. Each line in the figure represents the acceleration response spectrum of the 15 seismic waves in <a href="#applsci-14-04731-t001" class="html-table">Table 1</a>.</p>
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<p>The test site loading device.</p>
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<p>Structure dimensions and reinforcements of the step-terrace structure in the test.</p>
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<p>Hysteresis curves of horizontal force.</p>
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<p>Comparison of hinge distribution diagrams: (<b>a</b>) experimental results and (<b>b</b>) OPENSEES results.</p>
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<p>PGA curves corresponding to the limit state of the quantile curve for structures with different numbers of dropped spans: (<b>a</b>) immediate occupancy (IO), (<b>b</b>) life safety (LS), and (<b>c</b>) collapse prevention (CP).</p>
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<p>PGA curves corresponding to the limit state of the quantile curve for structures with different numbers of dropped layers: (<b>a</b>) immediate occupancy (IO), (<b>b</b>) life safety (LS), and (<b>c</b>) collapse prevention (CP).</p>
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<p>Earthquake probability demand model for structures with different numbers of dropped spans: (<b>a</b>) the probability demand model for the C2K1YBR structure in civil engineering, (<b>b</b>) the probability demand model for the C2K2YBR structure in civil engineering, and (<b>c</b>) the probability demand model for the C2K3YBR structure in civil engineering.</p>
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<p>Earthquake probability demand model for structures with different numbers of dropped layers: (<b>a</b>) the probability demand model for the C1K2YBR structure in civil engineering, (<b>b</b>) the probability demand model for the C2K2YBR structure in civil engineering, and (<b>c</b>) the probability demand model for the C3K2YBR structure in civil engineering.</p>
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<p>Vulnerability curves for structures with different numbers of dropped spans: (<b>a</b>) the vulnerability curve for the C2K1YBR structure in civil engineering, (<b>b</b>) the vulnerability curve for the C2K2YBR structure in civil engineering, and (<b>c</b>) the vulnerability curve for the C2K3YBR structure in civil engineering.</p>
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<p>Vulnerability curves for structures with different numbers of dropped layers: (<b>a</b>) the vulnerability curve for the C1K2YBR structure in civil engineering, (<b>b</b>) the vulnerability curve for the C2K2YBR structure in civil engineering, and (<b>c</b>) the vulnerability curve for the C3K2YBR structure in civil engineering.</p>
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<p>Damage state probability curves for structures with different numbers of spans: (<b>a</b>) the probability curve of damage states for the C2K1YBR structure in civil engineering, (<b>b</b>) the probability curve of damage states for the C2K2YBR structure in civil engineering, and (<b>c</b>) the probability curve of damage states for the C2K3YBR structure in civil engineering.</p>
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<p>Damage state probability curves for structures with different numbers of dropped layers: (<b>a</b>) the probability curve of damage states for the C1K2YBR structure in civil engineering, (<b>b</b>) the probability curve of damage states for the C2K2YBR structure in civil engineering, and (<b>c</b>) the probability curve of damage states for the C3K2YBR structure in civil engineering.</p>
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<p>Vulnerability index curves for structures with different numbers of spans: (<b>a</b>) C2K1YBR vulnerability index curve, (<b>b</b>) C2K2YBR vulnerability index curve, and (<b>c</b>) C3K2YBR vulnerability index curve.</p>
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<p>Vulnerability index curves for structures with different numbers of dropped layers: (<b>a</b>) C1K1YBR vulnerability index curve, (<b>b</b>) C2K2YBR vulnerability index curve, and (<b>c</b>) C2K3YBR vulnerability index curve.</p>
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<p>Safety margin ratios (SMR) for structures with different numbers of dropped spans: (<b>a</b>) safety margin ratio, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>S</mi> <mi>M</mi> <mi>R</mi> </mrow> <mrow> <mi>F</mi> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>, for structures under multiple earthquakes, (<b>b</b>) safety margin ratio, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>S</mi> <mi>M</mi> <mi>R</mi> </mrow> <mrow> <mi>D</mi> <mi>B</mi> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>, for structures under earthquake preparedness, and (<b>c</b>) safety margin ratio, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>S</mi> <mi>M</mi> <mi>R</mi> </mrow> <mrow> <mi>M</mi> <mi>C</mi> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>, for structures under rare earthquakes.</p>
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<p>Safety margin ratios (SMR) for structures with different numbers of dropped layers: (<b>a</b>) safety margin ratio, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>S</mi> <mi>M</mi> <mi>R</mi> </mrow> <mrow> <mi>F</mi> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>, for structures under multiple earthquakes, (<b>b</b>) safety margin ratio, <math display="inline"><semantics> <mrow> <mi>S</mi> <msub> <mrow> <mi>M</mi> <mi>R</mi> </mrow> <mrow> <mi>D</mi> <mi>B</mi> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>, for structures under earthquake preparedness, and (<b>c</b>) safety margin ratio, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>S</mi> <mi>M</mi> <mi>R</mi> </mrow> <mrow> <mi>M</mi> <mi>C</mi> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>, for structures under rare earthquakes.</p>
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19 pages, 9323 KiB  
Article
Experimental Study on Pore Pressure Variation and Erosion Stability of Sandy Slope Model under Microbially Induced Carbonate Precipitation
by Mingjuan Huang, Youliang Zhang, Jinning Hu, Yunpeng Hei, Zikun Xu and Jinchen Su
Sustainability 2023, 15(16), 12650; https://doi.org/10.3390/su151612650 - 21 Aug 2023
Cited by 3 | Viewed by 1526
Abstract
With the development of a free trade port on Hainan Island, the construction of tourist roads around the island is currently underway. However, the weather conditions on Hainan Island, which include strong typhoons and rainstorms, pose challenges for the construction of highway-cutting slopes [...] Read more.
With the development of a free trade port on Hainan Island, the construction of tourist roads around the island is currently underway. However, the weather conditions on Hainan Island, which include strong typhoons and rainstorms, pose challenges for the construction of highway-cutting slopes on the coastal weak sandy terraces. These slopes are susceptible to sand loss and erosion from rainfall. To address this issue, MICP green spray irrigation solidification technology is used to strengthen the sandy cutting, and pore water pressure monitoring is carried out on the slope model during MICP solidification and rainfall scour. Combined with the model pore water pressure and flow slip failure pattern, a dynamic analysis was conducted. The results show that MICP sprinkler irrigation technology can solidify the surface of the slope model in a short time, and after three sets of rotation reinforcement, the model achieved a cementation depth of 4 cm, with a well-reinforced surface and closely connected sand samples. Under the erosion effect of simulated rainfall intensity, the sand loss of the slope was weakened, without damage to the sand binding, and the integrity was enhanced. The cementation between the sand grains facilitated the conversion of most of the rainfall into runoff. However, despite these efforts, the slope eventually slid after 150 s. During the sliding process, the leading edge of the slope model lost sand and became unloaded, and the failure mode was graded a creep slip failure. Finally, the slope was divided into several blocks due to the continuous expansion of cracks following the slope failure. The erosion stability of the sandy slope under heavy rains was optimized and the sand loss was prevented effectively. This study proposes a new method of MICP remediation techniques that serve as a new test basis for the practical application of MICP technology in engineering projects. Full article
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<p>Engineering field.</p>
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<p>In situ sand sample.</p>
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<p>Grain composition.</p>
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<p>Bacterial stock solution.</p>
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<p>Stress–strain data acquisition instrument in figure: (<b>a</b>) sensor construction; (<b>b</b>) picture of real products.</p>
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<p>Model box size schematic.</p>
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<p>Sprinkler irrigation equipment.</p>
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<p>Double mounting device.</p>
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<p>Internal sensor buried location diagram.</p>
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<p>Experimental model display.</p>
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<p>Overall model design.</p>
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<p>Horizontal direction of the first, second, third wheel reinforcement pore pressure changes.</p>
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<p>Pore pressure changes in the first and second rounds of cementing fluid.</p>
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<p>Pore pressure changes in the third round of reinforcement when bacteria liquid and cementing liquid pass through.</p>
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<p>Changes in 01 time–pore pressure in three rounds.</p>
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<p>Variation in 01–05 pore pressure during rainfall.</p>
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<p>The 01–05 sensors rainfall duration–pore pressure change from 850–1200 s.</p>
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<p>The 01–03 pore pressure changes when the sensor is 0–800 s.</p>
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<p>The 01–03 sensors pore pressure change from 800 to 1050 s.</p>
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<p>The 01–03 pore pressure changes in the sensor at 1050–1200 s.</p>
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<p>Integral slip.</p>
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<p>M-1 model slippage side view.</p>
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<p>View after destruction.</p>
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16 pages, 7917 KiB  
Article
Quantification of Agricultural Terrace Degradation in the Loess Plateau Using UAV-Based Digital Elevation Model and Imagery
by Xuan Fang, Zhujun Gu and Ying Zhu
Sustainability 2023, 15(14), 10800; https://doi.org/10.3390/su151410800 - 10 Jul 2023
Cited by 3 | Viewed by 1292
Abstract
Agricultural terraces are important artificial landforms on the Loess Plateau of China and have many ecosystem services (e.g., agricultural production, soil and water conservation). Due to the loss of rural labor, a large number of agricultural terraces have been abandoned and then the [...] Read more.
Agricultural terraces are important artificial landforms on the Loess Plateau of China and have many ecosystem services (e.g., agricultural production, soil and water conservation). Due to the loss of rural labor, a large number of agricultural terraces have been abandoned and then the degradation of terraces, caused by rainstorm and lack of management, threatens the sustainability of ecological services on terraces. Our previous study has found its geomorphological evidence (sinkhole and collapse). However, no quantitative indicators of terrace degradation are identified from the perspective of microtopography change. A framework for quantifying terrace degradation was established in this study based on unmanned aerial vehicle photogrammetry and digital topographic analysis. The Pujiawa terraces in the Loess Plateau were selected as study areas. Firstly, the terrace ridges were extracted by a Canny edge detector based on high-resolution digital elevation model (DEM) data. The adaptive method was used to calculate the low and high thresholds automatically. This method ensures the low complexity and high-edge continuity and accuracy of the Canny edge detector, which is superior to the manual setting and maximum inter-class variance (Otsu) method. Secondly, the DEMs of the terrace slope before degradation were rebuilt through the terrain analysis method based on the extracted terrace ridges and current DEM data. Finally, the degradation of terraces was quantified by the index series in the line, surface and volume aspects, which are the damage degrees of the terrace ridges, terrace surface and whole terrace. The damage degrees of the terrace ridges were calculated according to the extracted and generalised terrace ridges. The damage degrees of the terrace surface and whole terrace were calculated based on the differences of DEMs before and after degradation. The proposed indices and quantitative methods for evaluating agricultural terrace degradation reflect the erosion status of the terraces in topography. This work provides data and references for loess terrace landscape protection and its sustainable management. Full article
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<p>The study areas and data. (<b>a</b>) Location of Loess Plateau, China. (<b>b</b>) Location of the study area. (<b>c</b>,<b>e</b>,<b>g</b>) The DEMs of the S1, S2 and S3 area, respectively. (<b>d</b>,<b>f</b>,<b>h</b>) The Digital Orthograph Models (DOM) obtained from UAV photogrammetry of the S1, S2 and S3 area, respectively.</p>
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<p>Workflow of this study.</p>
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<p>The results of Canny edge detector in the three study areas. (<b>a</b>–<b>c</b>) The results of the S1, S2 and S3 area, respectively. (<b>d</b>–<b>f</b>) The enlarged parts of the results in the S1, S2 and S3 area, respectively.</p>
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<p>The vector lines of extracted ridges. (<b>a</b>–<b>c</b>) The results of the S1, S2 and S3 area, respectively. (<b>d</b>–<b>f</b>) The enlarged parts of the results in the S1, S2 and S3 area, respectively.</p>
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<p>Reconstructed DEMs of the three study areas. (<b>a</b>–<b>c</b>) The results of the S1, S2, S3 area, respectively.</p>
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<p>The damage degree of terrace ridges. (<b>a</b>–<b>c</b>) The results of the S1, S2, S3 area, respectively.</p>
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<p>The damage degree of terrace surfaces. (<b>a</b>–<b>c</b>) The results of the S1, S2 and S3 area, respectively.</p>
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<p>Terrace ridges extracted from the DEM with a different resolution in the S1 area. (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>) The results extracted by the Canny edge detector are based on the DEM with 0.1 m, 0.2 m, 0.3 m, 0.4 m and 0.5 m resolution, respectively. (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>j</b>) The terrace ridges in vector format are tracked and filtered based on Canny results.</p>
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19 pages, 7546 KiB  
Article
Application of Running Water-Type Retarding Basin to Old Kinu River Floodplain, Japan
by Tadaharu Ishikawa and Ryosuke Akoh
Hydrology 2023, 10(4), 94; https://doi.org/10.3390/hydrology10040094 - 15 Apr 2023
Cited by 1 | Viewed by 2163
Abstract
In the upper and middle reaches of rivers in Japan, river channels used to meander in a comparatively narrow floodplain and heavy rain runoff used to naturally expand over the entire floodplain, retarding floods toward the downstream. Recent continuous levee building to prevent [...] Read more.
In the upper and middle reaches of rivers in Japan, river channels used to meander in a comparatively narrow floodplain and heavy rain runoff used to naturally expand over the entire floodplain, retarding floods toward the downstream. Recent continuous levee building to prevent river overflow has had two kinds of negative effects, namely an increase in flood damage in areas of a floodplain closed by levees and river terraces at the time of runoff over the river channel capacity, and an increase in the flood peak toward the downstream. This study introduces the concept of a running water-type retarding basin that mitigates flood damage by allowing excess runoff to pass through the floodplain, restoring a natural hydrological process. After a description of the concept of the facility design, a design example is presented for a closed floodplain of the Kinu River Floodplain, where excess runoff caused severe flood damage in 2015, to quantify the performance and effects of the running water-type retarding basin. Full article
(This article belongs to the Special Issue Flood Inundation Mapping in Hydrological Systems)
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<p>Shaded relief map of main part of Japanese archipelago.</p>
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<p>River channels of 109 first-class water systems in Japan.</p>
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<p>Example of topography of upper river basin (Abukuma River); (<b>a</b>) shaded relief map and (<b>b</b>) landform classification map for flood control.</p>
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<p>Expected achievement for first river improvement plan.</p>
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<p>Schematic diagrams of upstream floodplain; (<b>a</b>) plan view and (<b>b</b>) cross section.</p>
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<p>Schematic diagram of RWRB.</p>
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<p>Study site (Old Kinu River Floodplain); (<b>a</b>) flood control landform classification map and (<b>b</b>) topographical cross section of survey line indicated by red line in (<b>a</b>) (T.P.: Tokyo Peil).</p>
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<p>Closed floodplain damaged by flooding in 2015; (<b>a</b>) enlarged view of upstream floodplain indicated in <a href="#hydrology-10-00094-f007" class="html-fig">Figure 7</a> and (<b>b</b>) cross sections seen from downstream of three transverse lines in (<b>a</b>).</p>
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<p>Flooding in closed floodplain; (<b>a</b>) time variation in inundation area and (<b>b</b>) south end topography of closed floodplain.</p>
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<p>Application of RWRB to closed basin of Kinu River Floodplain.</p>
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<p>Model of narrow linear embankment.</p>
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<p>Model of topography; (<b>a</b>) ground elevation and (<b>b</b>) roads, irrigation channel, and inlet and outlet locations of inverted siphon.</p>
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<p>Rate of inflow and outflow for 2015 flood; inset shows magnified view.</p>
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<p>(<b>a</b>) Depth and (<b>b</b>) discharge for overflow dike.</p>
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<p>Reproducibility of highest water levels for 2015 flood; (<b>a</b>) highest water level obtained from flood trace and (<b>b</b>) correlation between observed and calculated water level.</p>
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<p>Variation in water depth distribution; (<b>a</b>) drainage by pump station (Case 1) and (<b>b</b>) drainage by inverted siphon (Case 2).</p>
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<p>Water depth variation in RWRB (Case 3).</p>
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<p>RWRB performance for excess flood mitigation.</p>
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21 pages, 10018 KiB  
Article
Development and Testing of a Self-Propelled Machine for Combined Potato Harvesting and Residual Plastic Film Retrieval
by Yuanjin Ju, Wei Sun, Zhiwei Zhao, Hucun Wang, Xiaolong Liu, Hua Zhang, Hui Li and Petru Aurelian Simionescu
Machines 2023, 11(4), 432; https://doi.org/10.3390/machines11040432 - 28 Mar 2023
Cited by 8 | Viewed by 2912
Abstract
A self-propelled machine for combined potato harvesting and residual plastic film retrieval is presented in this paper. The machine was designed collaboratively and built at the College of Mechano-Electronic Engineering of Gansu Agricultural University. It is intended for slow slope and horizontal terraces [...] Read more.
A self-propelled machine for combined potato harvesting and residual plastic film retrieval is presented in this paper. The machine was designed collaboratively and built at the College of Mechano-Electronic Engineering of Gansu Agricultural University. It is intended for slow slope and horizontal terraces in hilly and mountainous areas of Northwest China, where regular-size harvesters cannot operate. The machine can realize the combined operations of potato digging, potato separation from soil and plastic film, potato collection and bagging, and residual plastic film retrieval. Through engineering analyses, the main systems of the machine were calculated, and their operating parameters were estimated. These include the digging and lifting device, the potato–plastic-film separation device, and the residual plastic film retrieval device. Field tests were performed at a 0.5 m/s driving speed of the machine, while the linear speed of the lifting chain of the digging and lifting device was 1.5 m/s, the tilting angle of the conveying chain of the potato and plastic film separation device was 50°, its linear speed was 0.6 m/s, and the linear speed of the lifting screen of the circulating lifting device was 0.7 m/s. With these settings, the average productivity of the machine was 0.12 ha/h. The loss rate, damage rate, and potato bruising rate were 1.8%, 1.4%, and 2.8%, respectively; the potato impurity rate was 3.6%; and the residual plastic film retrieval rate was 83%—all above industry standards. This research provides a solution to the problem of mechanized potato harvesting and plastic mulch retrieval on small, slopped plots of land in Northwest China and in other parts of the world where similar conditions exist. Full article
(This article belongs to the Section Machine Design and Theory)
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<p>Photograph and schematic of operation of the self-propelled machine for combined potato harvesting and residual plastic film retrieval.</p>
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<p>Perspective view and side view of the self-propelled machine for combined potato harvesting and residual plastic film retrieval: 1—digging and lifting device; 2—circulating and lifting device; 3—platform I; 4—manual sorting platform; 5—engine assembly; 6—platform II; 7—potato–plastic-film separation device; 8—frame; 9—crawler chassis; 10—cab; 11—ton-bag handling device; 12—residual-film collecting and bundling device.</p>
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<p>CAD model of the digging and lifting device of the self-propelled machine for combined potato harvesting and residual plastic film retrieval: 1—side plate of the digging device; 2—lifting chain; 3—earth-cutting disc; 4—disc support; 5—connecting plate; 6—profiling crushing roller; 7—connecting crossbar; 8—digging shovel; 9—limiting pull rod; 10—scraper; 11—ear plate; 12—U-shaped connecting rod.</p>
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<p>Working Model 2D simulation of the chain bar of the digging and lifting device with a slowly increasing angle, showing the difference in backsliding between large and average-size potatoes.</p>
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<p>Working Model 2D simulation results for the smooth surface and chain bar transporter with and without vibration.</p>
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<p>The digging components of the machine and the action of one shovel: 1—adjusting screw; 2—limiting lever; 3—hanger plate; 4—digging shovel; 5—digging-shovel shaft; 6—bending beam; 7—shovel holder; 8—potato; 9—soil; 10—plastic film.</p>
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<p>Force and motion analysis of the potatoes as they are transferred by the lifting chain of the digging–lifting device to the potato–plastic-film separation device.</p>
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<p>Working Model 2D simulation of the impact of two potatoes of two different sizes with the moving conveyor of the potato–plastic-film separation device.</p>
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<p>(<b>a</b>) The residual-film collecting and bundling device: 1—plastic film rolling roller; 2—drive chain; 3—roller sprocket; 4—input sprocket; 5—rotating shaft. (<b>b</b>) The operation principle of the residual-film collecting and bundling device: 1—potato–plastic-film separation device; 2—residual plastic film; 3—debris; 4—plastic film rolling roller.</p>
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<p>(<b>a</b>) Diagram of the state of the residual-film collecting and bundling device when collecting the residual plastic film. (<b>b</b>) Diagram of the state of the residual-film collecting and bundling device when unloading residual plastic film. 1—frame; 2—hydraulic cylinders; 3—residual-film collecting and bundling device.</p>
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<p>CAD model of the circulating and lifting device: 1—drive wheel; 2—bracket; 3—guide carrier pulley; 4—lifting scraper; 5—baffle; 6—potato slide plate; 7—lifting screen.</p>
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<p>Force analysis diagram of a potato in the receiving section of the circulating and lifting device.</p>
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<p>Potato force diagram in the unloading section of the circulating and lifting device.</p>
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<p>Diagram of the manual sorting platform: 1—driving wheel; 2—supporting wheel; 3—height-adjusting rod sleeve; 4—height-adjusting rod; 5—connecting frame; 6—conveyor screen; 7—side plate; 8—guiding wheel.</p>
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<p>Large ridges with two rows per ridge and with covering soil on top of the plastic film mulch: 1—black plastic film; 2—potato; 3—potato seedling; 4—covering soil.</p>
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<p>Field test showing the digging and lifting device of the self-propelled machine for combined potato harvesting and residual plastic film retrieval and a bag of harvested potatoes.</p>
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13 pages, 2658 KiB  
Article
Hurricane Kay (September 2022) Impacts Rocky Shores in the Loreto Area of Baja California Sur, Mexico
by Markes E. Johnson and Ginni Callahan
J. Mar. Sci. Eng. 2023, 11(2), 323; https://doi.org/10.3390/jmse11020323 - 2 Feb 2023
Viewed by 1576
Abstract
This project follows a tradition of survey work undertaken to appraise physical and biological damage in the aftermath of hurricane-strength winds and waves at a given locality where conditions were well documented prior to the arrival of a particular storm. The locality is [...] Read more.
This project follows a tradition of survey work undertaken to appraise physical and biological damage in the aftermath of hurricane-strength winds and waves at a given locality where conditions were well documented prior to the arrival of a particular storm. The locality is the 12 m limestone terrace at Arroyo Blanco on the eastern shores of Isla del Carmen in Baja California Sur, Mexico. A study undertaken in February 2018 established that the surface of the terrace is covered by a coastal boulder deposit that features large slabs of limestone pealed from the outer edge by strong surf attributed to storms of hurricane intensity but unknown date. The largest slabs tend to be rectilinear in shape vulnerable to dislodgement along horizonal bedding planes and weaknesses in vertical joints. These blocks are sufficiently large and weigh enough that movement by humans without necessary mechanical equipment would be impossible. Hurricane Kay, rated as a Category 2 storm, struck the island on 8 September 2022 and an effort was made to visit the area for reconnaissance and detailed survey work soon afterwards. Although a Category 2 storm lacked the energy to remobilize the largest limestone slabs on the terrace, it was found that the storm was sufficient to disturb the adjacent seabed and redeposit as many as 44 sea fans onto the terrace by overwash; the sea fans belonged to the species Pacifigorgia adamsi. Moreover, a species of land plant common to the limestone terrace is the Gulf Star Violet (Stenotis mucronate); it suffered significant desiccation and death due to saltwater exposure. The occurrence of large potholes on the limestone terrace represents a style of physical erosion previously undocumented at the locality and rarely seen elsewhere on rocky shores. Full article
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<p>Map showing Mexico’s Baja California peninsula and adjacent Gulf of California: (<b>a</b>) Mexico with key cities indicated and inset box to show map enlargement of the Loreto area; (<b>b</b>) Isla del Carmen near Loreto on the peninsular mainland with the location of the 12 m limestone terrace marked on the island’s eastern shore.</p>
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<p>Map covering approximately 6000 m<sup>2</sup> on the 12 m limestone terrace adjacent to the access beach at Arroyo Blanco on the east coast of Isla del Carmen. The marked locations for displaced sea fans and desiccated land plants are numbered for reference to data supplied in <a href="#jmse-11-00323-t001" class="html-table">Table 1</a> and <a href="#jmse-11-00323-t002" class="html-table">Table 2</a>. Key features showing the effect of wave scour on the platform also are marked.</p>
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<p>Before and after photos showing some of the largest limestone blocks on the 12 m terrace at Arroyo Blanco: (<b>a</b>) Upturned limestone block photographed from the front at midday in February 2018 with person for scale; (<b>b</b>) Same block photographed in the distance from the side (upper right) in context with smaller blocks early on a September day in 2022.</p>
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<p>Evidence for biological disruptions observed on the 12 m limestone terrace at Arroyo Blanco from the east coast of Isla del Carmen: (<b>a</b>) Displaced sea fan (<span class="html-italic">Pacifigorgia adamsi)</span> sitting upright against rocks on the rock platform at locality 1 on the map in <a href="#jmse-11-00323-f002" class="html-fig">Figure 2</a> (12-inch ruler for scale = 30 cm); (<b>b</b>) Completely desiccated land plant identified as the Gulf Star Violet (<span class="html-italic">Stenotis mucronate</span>) grew in place on the rock platform at locality 3 on the map in <a href="#jmse-11-00323-f002" class="html-fig">Figure 2</a> (pocket knife for scale = 9 cm).</p>
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<p>Evidence from a saltwater pool on the coastal terrace at Arroyo Banco: (<b>a</b>) Shallow depression on the limestone surface filled with seawater (blue ruler = 30 cm); (<b>b</b>) Close-up of individual salt crystals recovered from the brine of another pool exhibiting a characteristic cubic habit (maximum crystal size is 5 mm in diameter).</p>
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<p>Photos showing evidence of mechanical erosion on the 12 m limestone terrace at Arroyo Blanco: (<b>a</b>) Large limestone boulder that formed a protective barrier against wave scour that left a line of cobbles undisturbed on the leeward side; (<b>b</b>) Large pothole eroded in limestone near the seaward edge of the limestone terrace, including small boulders that would have swirled around the inner margin during the impact of each wave (person for scale).</p>
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<p>Underwater photo showing the natural habitat of the sea fan <span class="html-italic">Pacifigorgia adamsi</span> growing in place on the seabed at an upper depth limit of about 5 m.</p>
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14 pages, 1829 KiB  
Article
A Topographic Perspective on the Propensity for Degradation of Plateau Swampy Meadows in Maduo County, West China
by Xilai Li, Jing Zhang and Jay Gao
Land 2023, 12(1), 80; https://doi.org/10.3390/land12010080 - 27 Dec 2022
Cited by 1 | Viewed by 1558
Abstract
The swampy meadows atop the vast Qinghai–Tibet Plateau in West China fall into alpine, pediment, valley, floodplain, terrace, lacustrine, and riverine types according to their hydro-geomorphic properties. They have suffered degradation to various levels of severity due to climate change and external disturbance. [...] Read more.
The swampy meadows atop the vast Qinghai–Tibet Plateau in West China fall into alpine, pediment, valley, floodplain, terrace, lacustrine, and riverine types according to their hydro-geomorphic properties. They have suffered degradation to various levels of severity due to climate change and external disturbance. In this paper, we studied the propensity of these types of swampy meadows to degrade from the topographic perspective. Evaluated against four degradation indicators of vegetation, hydrology, soil erosion, and pika (Ochotona curzoniae) damage, degradation severity at 106 swampy meadows representing all types of wetlands was graded to one of four levels, from which the field-based propensity to degrade (PtD) index value was derived. Judged against this index, terrace and alpine swampy meadows are the most prone to degradation while valley, lacustrine, and riverine swampy meadows are the least. The index value of a given swampy meadow type bears a close relationship (R2 = 0.916) with its rate of change during 1990–2013, which confirms the validity of the proposed index in predicting the propensity of swampy meadows to change. The observed differential PtD of different types of swampy meadows is attributed primarily to elevation (R2 = 0.746; p = 0.027) and, secondarily, to surface morphology (R2 = 0.696; p = 0.039). Thus, the elevation at which a swampy meadow is situated is a more important factor to its PtD than its surface morphology. In particular, swampy meadows located at a higher elevation with a convex surface are much more prone to degradation than those at a lower elevation of a concave slope. Such findings can guide the proper management of different types of swampy meadows to achieve sustainable animal husbandry. Full article
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<p>Location of the study area in Qinghai Province, West China.</p>
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<p>Typical severity levels of swampy meadow degradation in the study area. The original state (<b>A</b>) can be used as the reference state against which the severity level of degradation is judged (<a href="#land-12-00080-t001" class="html-table">Table 1</a>). (<b>A</b>) Intact; (<b>B</b>) Slight degradation; (<b>C</b>) Moderate degradation; (<b>D</b>) Severe degradation.</p>
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<p>Regression relationship between the annual rate [(Area<sub>2013</sub>–Area<sub>1990</sub>)/(2013–1990), unit: km<sup>2</sup> per annum] of swampy meadow change during 1990–2013 derived from satellite images [<a href="#B22-land-12-00080" class="html-bibr">22</a>] and the derived propensity for degradation. A-alpine; F-floodplain; L-lacustrine; P-piedmont, R-riverine; V-valley (the same in Figures 4 and 5).</p>
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<p>Regression relationship between propensity to degrade (PtD) and topographic features for six types of swampy meadows. (<b>a</b>) Mean height (m) above sea level; (<b>b</b>) surface morphology.</p>
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<p>Regression relationship between the ratio of degraded swampy meadow sites to the total sampled sites (%) with their mean height among the six types of swampy meadow.</p>
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31 pages, 5422 KiB  
Article
Refining Rates of Active Crustal Deformation in the Upper Plate of Subduction Zones, Implied by Geological and Geodetic Data: The E-Dipping West Crati Fault, Southern Italy
by Marco Meschis, Giordano Teza, Enrico Serpelloni, Letizia Elia, Giovanni Lattanzi, Miriana Di Donato and Silvia Castellaro
Remote Sens. 2022, 14(21), 5303; https://doi.org/10.3390/rs14215303 - 23 Oct 2022
Cited by 9 | Viewed by 2880
Abstract
We investigate crustal deformation within the upper plate of the Ionian Subduction Zone (ISZ) at different time scales by (i) refining geodetic rates of crustal extension from continuous Global Navigation Satellite System (GNSS) measurements and (ii) mapping sequence of Late Quaternary raised marine [...] Read more.
We investigate crustal deformation within the upper plate of the Ionian Subduction Zone (ISZ) at different time scales by (i) refining geodetic rates of crustal extension from continuous Global Navigation Satellite System (GNSS) measurements and (ii) mapping sequence of Late Quaternary raised marine terraces tectonically deformed by the West Crati normal fault, in northern Calabria. This region experienced damaging earthquakes in 1184 (M 6.75) and 1854 (M 6.3), possibly on the E-dipping West Crati fault (WCF) which, however, is not unanimously considered to be a seismogenic source. We report geodetic measurements of extension and strain rates across the strike of the E-dipping WCF and throughout the northern Calabria obtained by using velocities from 18 permanent GNSS stations with a series length longer than 4.5 years. These results suggest that crustal extension may be seismically accommodated in this region by a few normal faults. Furthermore, by applying a synchronous correlation approach, we refine the chronology of understudied tectonically deformed palaeoshorelines mapped on the footwall and along the strike of the WCF, facilitating calculation of the associated fault-controlled uplift rates. Raised Late Quaternary palaeoshorelines are preserved on the footwall of the WCF indicating that “regional” uplift, likely related to the deformation associated either with the subduction or mantle upwelling processes, is affected by local footwall uplift. We show that GIS-based elevations of Late Quaternary palaeoshorelines, as well as temporally constant uplift rates, vary along the strike of the WCF, implying normal faulting activity through time. This suggests that (i) the fault slip rate governing seismic hazard has also been constant over the Late Quaternary, over multiple earthquake cycles, and (ii) our geodetically derived fault throw rate for the WCF is likely a more than reasonable value to be used over longer time scales for an improved seismic hazard assessment. Overall, we emphasize the importance of mapping crustal deformation within the upper plate above subduction zones to avoid unreliable interpretations relating to the mechanism controlling regional uplift. Full article
(This article belongs to the Special Issue Remote Sensing in Earthquake, Tectonics and Seismic Hazards)
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Figure 1
<p>Map of the investigated area. Sketched fault map of the northern Calabria is shown, across the strike of the E-dipping West Crati Fault and where uplifted marine terraces are mapped. Locations of age controls are shown from literature (<a href="#remotesensing-14-05303-t001" class="html-table">Table 1</a>). Green-coloured stars show that historical earthquakes occurred within the investigated area. Pink-coloured dots show the network of continuous GNSS stations. Inset A shows Quaternary active normal faults within the Calabrian–Peloritani Arc and the trace of the Ionian Subduction Zone (ISZ) [<a href="#B29-remotesensing-14-05303" class="html-bibr">29</a>,90].</p>
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<p>A map with locations of serial topographic profiles along the strike of the West Crati Fault is shown. Coloured dots identify inner edges and associated refined ages along a serial of topographic profiles intercepting raised marine terraces. Dashed squares show where a “zoom–in” has been carried out as <a href="#app1-remotesensing-14-05303" class="html-app">Supplementary Material (SM)</a> to better show traces of topographic profiles and locations of inner edges with refined ages on a 10 m high–resolution digital elevation model. Dashed orange trace shows the mapped palaeoshoreline identifying the Last Interglacial Maximum (LIG), MIS 5e [<a href="#B29-remotesensing-14-05303" class="html-bibr">29</a>].</p>
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<p>Evidence of raised marine terraces and their associated palaeoshorelines: in (<b>a</b>) three prominent sea-level highstands such as the 125 ka (MIS 5e), the 240 ka (MIS 7e), and the 340 ka (MIS 9e), which are mapped from Google Earth just south of Paola town, close to our Profile 11; in (<b>b</b>) a modified photo taken from Westaway (1993), showing a sequence of marine terraces from field close to Profile 1, close to Coreca town. Inset A shows a sketch of conceptual evolution when marine terraces form.</p>
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<p>Topographic profiles derived by using 10 m high-resolution DEMs (Tarquini et al., 2012) from fault tips area and the centre of the fault showing modelled palaeoshoreline elevations. Sea-level highstands, identifying and predicting palaeoshoreline elevations, are represented by coloured lines that are calculated by iterating values of uplift rate to find the best match with the mapped (numbered arrows) palaeoshorelines. All topographic profiles are shown in <a href="#remotesensing-14-05303-f002" class="html-fig">Figure 2</a> and <a href="#app1-remotesensing-14-05303" class="html-app">Figures S5–S10</a>. Inner edge elevations with refined ages are also shown in <a href="#remotesensing-14-05303-t004" class="html-table">Table 4</a>.</p>
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<p>Graph showing a linear regression analysis between iteratively calculated sea-level highstand elevations and our mapped palaeoshoreline elevations on DEMs. Note that the predicted elevations have been derived by defining a constant uplift rate through time and iterating this value to find the best match to the measured and mapped palaeoshorelines.</p>
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<p>Crustal uplift (<b>a</b>) and uplift rates (<b>b</b>) over the Quaternary. Topographic profiles from <a href="#remotesensing-14-05303-f002" class="html-fig">Figure 2</a> are labelled. Palaeoshoreline elevations change along the strike of the West Crati Fault, suggesting Late Quaternary faulting activity (<b>a</b>). Spatially changing rates of uplift measured along the strike of the West Crati Fault outcropping on its uplifting footwall are also mapped (<b>b</b>). Values of tilting angles in degrees are calculated for each mapped marine terrace and are presented in (<b>c</b>), showing that older palaeoshorelines have higher tilt angles; this suggests that they have experienced a longer history of differential uplift and that differential uplift was ongoing progressively during the Late Quaternary. Note that values of tilt angle for each investigated marine terrace have been calculated as a tan<sup>−1</sup> of a gradient <span class="html-italic">m</span> of a straight line (equation <span class="html-italic">y</span> = <span class="html-italic">mx</span>), as proposed by previous studies [<a href="#B20-remotesensing-14-05303" class="html-bibr">20</a>,<a href="#B63-remotesensing-14-05303" class="html-bibr">63</a>,<a href="#B73-remotesensing-14-05303" class="html-bibr">73</a>].</p>
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<p>(<b>a</b>) Estimated velocities of GNSS stations in the studied area. The horizontal velocity vectors (for both EU and AF plate fixed reference frames and corresponding error ellipses at 95% confidence level) are shown. The vertical velocity components are shown as colours of the station markers. The KROT station name is magenta-coloured because it is excluded from the strain rate computation; (<b>b</b>) map of interpolated vertical velocity. In <a href="#app1-remotesensing-14-05303" class="html-app">Figure S12</a>, time series and modelled trend/periodic components are shown.</p>
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<p>(<b>a</b>) Principal strain-rate axes, computed in the grid nodes characterized by high geometric significance; (<b>b</b>) map of the field of change in area (i.e., the trace of the strain-rate tensor); (<b>c</b>) map of the field of engineering shear normalized to the change in area. The strain-rate field is also shown in <a href="#app1-remotesensing-14-05303" class="html-app">Figure S13 (Supplementary Material)</a>, where the data related to mid significance nodes are also shown.</p>
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<p>A schematic structural map is shown where active faults are accommodating our geodetically derived crustal extension of 2.3 mm/yr across the strike of the E-dipping West Crati Fault and throughout northern Calabria. The green star indicates the location of the 1184 “Valle del Crati” earthquake (M 6.75) from the INGV historical catalogue [<a href="#B29-remotesensing-14-05303" class="html-bibr">29</a>]. Inset A shows a no-scaled cartoon where homogenous heave rates (HR) from computed extension rates are assigned among the active faults such as the West Crati Fault, East Crati Fault, and the Lakes Fault. Inset B shows a scheme of a normal fault with the three components where the deformation is measured and the fault dip angles: heave, throw, and displacement. Note that for a 45° fault dip, angle, throw, and heave will be equal.</p>
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<p>Modelled co-seismic displacement showing co-seismic uplift and subsidence if the entire fault length of the West Crati Fault (~40 km) would seismically rupture, producing a modelled earthquake of M 6.8. Inset A shows a 3D view of the modelled seismogenic source (the West Crati Fault) with the associated slip distribution in depth, with a maximum value of 3 m. Co-seismic uplift/subsidence contours produced by our preferred modelled fault in the half-elastic space are shown along the profile A-B, with a maximum co-seismic uplift and subsidence of 0.064 m and 0.810 m, respectively, Inset B. Furthermore, a crustal deformation profile (C-D) is produced comparing the co-seismic and long-term footwall uplift along the strike of the fault (<a href="#app1-remotesensing-14-05303" class="html-app">Figure S11</a>). Note that the estimated magnitude for the 1184 “Valle del Crati” earthquake is 6.75 and matches our modelled magnitude (M 6.8); moreover, the location of this historical seismic event lies where we estimate the maximum co-seismic subsidence [<a href="#B29-remotesensing-14-05303" class="html-bibr">29</a>].</p>
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28 pages, 142490 KiB  
Article
Seismic Microzonation of the Pompeii Archaeological Park (Southern Italy): Local Seismic Amplification Factors
by Vincenzo Amato, Marina Covolan, Hélène Dessales and Alfonso Santoriello
Geosciences 2022, 12(7), 275; https://doi.org/10.3390/geosciences12070275 - 8 Jul 2022
Cited by 5 | Viewed by 2834
Abstract
Pompeii Archaeological Park is the best laboratory for the study of the seismic site effects on cultural heritage: the ancient site was destroyed and buried by the 79 AD Vesuvian eruption and, furthermore, it was also affected by the 62–63 AD strong earthquake. [...] Read more.
Pompeii Archaeological Park is the best laboratory for the study of the seismic site effects on cultural heritage: the ancient site was destroyed and buried by the 79 AD Vesuvian eruption and, furthermore, it was also affected by the 62–63 AD strong earthquake. Large sectors of the city were reconstructed after this earthquake while other parts were still under reconstruction when the fall-out and pyroclastic density currents of the eruption buried the Roman city. In order to evaluate the distribution of the damage and reconstructions due to the earthquake, detailed mappings of the structures were carried out using multidisciplinary approaches. In addition, analyses of the topographical features, subsoil stratigraphies, and geophysical surveys, responsible for local seismic amplification (site effects), allow us to define the sectors of the ancient city where the Amplification Factors (AFs) were the main ones responsible for damage. Selected areas and examples of compromised and reconstructed buildings show that the ancient topography and subsoil features (both lithological and seismic) are the main AFs. In particular, the damages caused by the 62–63 AD earthquakes seem to be mainly due to topographical factors such as steep scarps and slopes, ridges, peaks, and terraces, as well as to the major thickness of the soft sediments (loose volcanoclastic layers, paleosols, weathered lavas, and anthropogenic infillings) located over the well-lithified lavas. It is not uncommon to also have the combination of these two factors. For the first time, this multidisciplinary approach allows us to draw a seismic microzonation map for one of the most important archaeological sites of the world. Full article
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<p>Workflow of the materials and methods and related products used for the drawing of the Pompeii seismic microzonation.</p>
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<p>Schematic diagram of possible dissections in relation to a structure affected by a seismic event. Out-of-plane mechanisms: (<b>a</b>) total simple overturning of the wall; (<b>b</b>) partial simple overturning of the wall; (<b>c</b>) horizontal wall deflection; (<b>d</b>) offset of the wall. In-plane mechanisms: (<b>e</b>) bi-directional injuries at jambs; (<b>f</b>) bi-directional injuries in correspondence at sills and lintels; (<b>g</b>) one-way diagonal injuries. Combined mechanisms: (<b>h</b>) partial complex overturning; (<b>i</b>) total complex overturning; (<b>j</b>) rollover of the corner of the building; (<b>k</b>) vertical wall deflection [<a href="#B37-geosciences-12-00275" class="html-bibr">37</a>].</p>
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<p>Geology of the Pompeii area. (<b>a</b>) Geological map (1:25,000 in scale) of the Sarno river alluvial coastal plain. (1) Pompeii Volcano Lava (late Pleistocene); (2) late Holocene volcaniclastic deposits; (3) late Holocene alluvial fan deposits; (4) Holocene lagoonal, marshy deposits; (5) Holocene dunal deposits; (6) Holocene fluvial deposits; (7) 1800 AD Sarno river paleocourse; (8) Nowadays beach deposits; (9) Early Holocene Pompei paleocliff; (10) 79 AD paleoshoreline; (<b>b</b>) Schematic geological cross-section (trace AB) showing a stratigraphic assessment of the subsoil: (a) sandy coastal deposits; (b) silty-clay marshy and lagoonal deposits; (c) 79 CE eruption deposits; (d) alternating of paleosols, volcaniclastic deposits, and weathered lava; (e) Sarno river fluvial deposits; (f) Pompeii volcano lava.</p>
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<p>Schematic of the lithofacies log and related photos of the Pompeii subsoil units.</p>
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<p>Digital terrain model (DTM) of the Pompeii archaeological area with location of the available data (boreholes, outcrops and geophysical surveys). Also, locations of the case-studies highlighted in the Discussion section are showed.</p>
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<p>Geomorphological map of the Pompeii ancient city overlayed onto digital terrain model (DTM).</p>
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<p>Geomorphological zonation (GM): (<b>A</b>) unstable zones; (<b>B</b>) stable zones prone to local amplification; (<b>C</b>) stable zones.</p>
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<p>Geological zonation (SGM) and CT thickness distribution. The <span class="html-italic">Regiones</span> (I–IX) are showed.</p>
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<p>Geological/geophysical model map (GGM) and corrected CT thicknesses (CT + Unit C of the lava bedrock). The <span class="html-italic">Regiones</span> (I–IX) are showed.</p>
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<p>Assessment of damage and post-seismic repairs based on recent scientific literature (elab. M. Covolan); data from [<a href="#B38-geosciences-12-00275" class="html-bibr">38</a>,<a href="#B40-geosciences-12-00275" class="html-bibr">40</a>,<a href="#B41-geosciences-12-00275" class="html-bibr">41</a>,<a href="#B42-geosciences-12-00275" class="html-bibr">42</a>,<a href="#B43-geosciences-12-00275" class="html-bibr">43</a>,<a href="#B44-geosciences-12-00275" class="html-bibr">44</a>,<a href="#B45-geosciences-12-00275" class="html-bibr">45</a>,<a href="#B46-geosciences-12-00275" class="html-bibr">46</a>,<a href="#B47-geosciences-12-00275" class="html-bibr">47</a>,<a href="#B48-geosciences-12-00275" class="html-bibr">48</a>,<a href="#B49-geosciences-12-00275" class="html-bibr">49</a>,<a href="#B50-geosciences-12-00275" class="html-bibr">50</a>,<a href="#B51-geosciences-12-00275" class="html-bibr">51</a>,<a href="#B65-geosciences-12-00275" class="html-bibr">65</a>,<a href="#B66-geosciences-12-00275" class="html-bibr">66</a>,<a href="#B67-geosciences-12-00275" class="html-bibr">67</a>,<a href="#B68-geosciences-12-00275" class="html-bibr">68</a>,<a href="#B69-geosciences-12-00275" class="html-bibr">69</a>,<a href="#B70-geosciences-12-00275" class="html-bibr">70</a>,<a href="#B71-geosciences-12-00275" class="html-bibr">71</a>,<a href="#B72-geosciences-12-00275" class="html-bibr">72</a>,<a href="#B73-geosciences-12-00275" class="html-bibr">73</a>,<a href="#B74-geosciences-12-00275" class="html-bibr">74</a>,<a href="#B75-geosciences-12-00275" class="html-bibr">75</a>,<a href="#B76-geosciences-12-00275" class="html-bibr">76</a>,<a href="#B77-geosciences-12-00275" class="html-bibr">77</a>,<a href="#B78-geosciences-12-00275" class="html-bibr">78</a>,<a href="#B79-geosciences-12-00275" class="html-bibr">79</a>,<a href="#B80-geosciences-12-00275" class="html-bibr">80</a>,<a href="#B81-geosciences-12-00275" class="html-bibr">81</a>].</p>
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<p>Graph of the distribution of the various types of repairs realized in NYT within the different <span class="html-italic">Regiones</span> [<a href="#B50-geosciences-12-00275" class="html-bibr">50</a>].</p>
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<p>Seismic homogeneous microzones and seismic microzonation map of the Pompeii Archaeological Park.</p>
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<p>On the left is the plan of House of the <span class="html-italic">Naviglio</span> (VI 10, 8–10), with in red the structures built up with NYT elements. On the right the plan of the geomorphological evidence in the same area (elab. M. Covolan).</p>
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<p>On the left is the plan of House of <span class="html-italic">Francesco Giuseppe</span> (VIII 2, 29–30), with in red the structures built up with NYT elements. On the right, the plan of the topographical factors in the same area (elab. M. Covolan).</p>
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<p>On the left is the plan of House of Diana II (VI 17, 32–36), with in red the structures built up with NYT elements. On the right, the plan of the geomorphological evidences in the same area (elab. M. Covolan).</p>
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22 pages, 10205 KiB  
Article
Sustainable Conservation and Management of a 20th-Century Landscape in the Alps: The Former Sanatorium Village of Sondalo
by Davide Del Curto, Andrea Garzulino, Giacomo Menini and Carlo Schiesaro
Sustainability 2022, 14(12), 7424; https://doi.org/10.3390/su14127424 - 17 Jun 2022
Cited by 6 | Viewed by 2061
Abstract
This article discusses how to sustainably manage and protect the Alpine landscape from the risk of extreme weather events due to climate change. The authors present the results achieved by applying the Conservation and Management Plan (CMP) method in the case of a [...] Read more.
This article discusses how to sustainably manage and protect the Alpine landscape from the risk of extreme weather events due to climate change. The authors present the results achieved by applying the Conservation and Management Plan (CMP) method in the case of a large terraced healing park built in the Central Alps in the 1930s and damaged in 2018 by the effects of Storm Adrian (also known as Vaia). We thoroughly analysed the state of preservation through historical documentation, aerial shooting with a drone, a tree-by-tree evaluation, and a GIS platform for integrated information management. Such a CMP approach is usually applied to assess the state of decay and plan for the sustainable conservation of historic buildings and gardens. The method of analysis and the performed activities allowed us to evaluate the park’s landscape values and identify the elements of risk, leading to the drafting of a monitoring map and guidelines of intervention. This experience made it possible to test its effectiveness in protecting the Alpine landscape and its specific fragility. Full article
(This article belongs to the Special Issue Sustainable Development in Mountain Areas)
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<p>The Sanatorium Village of Sondalo seen from the east, a vintage postcard from 1940 and the current situation in 2020.</p>
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<p>The general plan of the complex: division into areas (in purple the areas referring to gardens and parks, in blue the areas occupied by the road layout, in brown the pavilions).</p>
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<p>Elaboration of the map of forest types, Lombardy Region [<a href="#B44-sustainability-14-07424" class="html-bibr">44</a>], area of the former Sanatorium Village of Sondalo.</p>
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<p>Elaboration of the Ortho-image, Lombardy Region, LiDAR survey, 2015 [<a href="#B45-sustainability-14-07424" class="html-bibr">45</a>].</p>
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<p>Detail of the orthophoto generated through drone survey in 2019.</p>
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<p>Digital Surface Model (DSM), 2019.</p>
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<p>Section “a” of the form: identification of the tree specimen.</p>
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<p>Section “b” of the form: vegetation characteristics and phytopathological status of the tree specimen.</p>
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<p>Section “c” of the form: elements of risk and interventions on the tree specimen.</p>
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<p>Tree height classes, number of specimens and main species.</p>
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<p>The general plan of the complex. In evidence, the buildings, and the different areas.</p>
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<p>Landscape values map.</p>
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<p>Garden of pavilion n. 5 before (<b>left</b>—photo, April 2019) and after (<b>right</b>—photo, July 2020) the knocking down of the Cedrus atlantica.</p>
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<p>Cedrus atlantica still present (in green) and knocked down (in red).</p>
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<p>Monitoring map.</p>
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<p>Project for the “Piazzale della maternità”, Form n. 5, Solution B.</p>
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15 pages, 17424 KiB  
Article
Estimation of Soil Erosion and Evaluation of Soil and Water Conservation Benefit in Terraces under Extreme Precipitation
by Hao Jia, Xidong Wang, Wenyi Sun, Xingmin Mu, Peng Gao, Guangju Zhao and Zixuan Li
Water 2022, 14(11), 1675; https://doi.org/10.3390/w14111675 - 24 May 2022
Cited by 7 | Viewed by 2743
Abstract
In recent years, soil erosion caused by water erosion has gradually increased due to the increase of extreme precipitation. In order to reduce soil erosion caused by extreme precipitation, it is necessary to monitor soil erosion and found out the factors that affect [...] Read more.
In recent years, soil erosion caused by water erosion has gradually increased due to the increase of extreme precipitation. In order to reduce soil erosion caused by extreme precipitation, it is necessary to monitor soil erosion and found out the factors that affect soil erosion under extreme precipitation. The objective of this study was to assess the amount of soil erosion, the damage degree of soil and water conservation measures and benefit evaluation under extreme precipitation in Henan Province. The results indicated that the ridges of terraces in two small watersheds had been damaged to varying degrees. Terraces, as one of soil and water conservation measures, can better preserve soil and water erosion under extreme precipitation. The amount of soil preserved in two small watersheds were 744.50t and 1121.01t. The amount of soil loss in two small watersheds were reduced by 67.67% and 78.63% when terraces existed. The soil conservation amount of vegetation restoration measures in two small watersheds were 2960.23t and 3320.36t. The amount of soil loss in two small watersheds were reduced by 89.27% and 90.98%, when vegetation restoration measures exist. Compared with soil and water conservation engineering measures, vegetation restoration measures can better reduce soil erosion caused by water erosion under extreme precipitation. In addition to the amount of rainfall, the soil and water conservation benefits of terraces were also affected by the width of the terrace, the slope of the terrace, and whether there were vegetation restoration measures in the terrace. Full article
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<p>Location of the study area.</p>
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<p>UAV remote sensing image measurement (<b>a</b>) and manual field measurement (<b>b</b>).</p>
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<p>The distribution of terraced in XQ and LY watershed; (<b>a</b>) The distribution of terraces in XQ watershed; (<b>b</b>) The distribution of terraces in LY watershed; (<b>c</b>) The damage distribution of terraces in XQ watershed; (<b>d</b>) The damage distribution of terraces in LY watershed; (<b>e</b>) The damage rate of terraces in XQ watershed and (<b>f</b>) The damage rate of terraces in LY watershed.</p>
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<p>Spatial distribution of soil erosion modulus: (<b>a</b>) XQ watershed and (<b>b</b>) LY watershed.</p>
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<p>Distribution of terrace and terrace measures: (<b>a</b>) XQ watershed and (<b>b</b>) LY watershed.</p>
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<p>Remote sensing interpretation results of typical terraces.</p>
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<p>Topographic relief of terrace: (<b>a</b>) XQ watershed and (<b>b</b>) LY watershed.</p>
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<p>The distribution of terrace’s slope: (<b>a</b>) Spatial distribution of slope in XQ watershed and (<b>b</b>) Spatial distribution of slope in LY watershed.</p>
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