Water

Editorial

Jump to: Research

3 pages, 172 KiB

Open AccessEditorial

Soil–Water Conservation, Erosion and Landslide

by Su-Chin Chen

Water 2022, 14(4), 665; https://doi.org/10.3390/w14040665 - 21 Feb 2022

Cited by 1 | Viewed by 1932

Abstract

In the wake of climate change, extreme storm events, catastrophic disasters (including soil erosion, debris and landslide formation, loss of life, etc [...] Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

Research

Jump to: Editorial

24 pages, 9720 KiB

Open AccessFeature PaperArticle

On Dam Failure Induced Seismic Signals Using Laboratory Tests and on Breach Morphology due to Overtopping by Modeling

by Chi-Yao Hung, I-Fan Tseng, Su-Chin Chen and Zheng-Yi Feng

Water 2021, 13(19), 2757; https://doi.org/10.3390/w13192757 - 5 Oct 2021

Cited by 3 | Viewed by 2930

Abstract

Dam models were constructed in an indoor flume to test dam breach failure processes to study the seismic signals induced. A simple dam breach model was also proposed to estimate hydrographs for dam breach floods. The test results showed that when the retrogressive [...] Read more.

Dam models were constructed in an indoor flume to test dam breach failure processes to study the seismic signals induced. A simple dam breach model was also proposed to estimate hydrographs for dam breach floods. The test results showed that when the retrogressive erosion due to seepage of the dam continues, it will eventually reach the crest at the upstream side of the dam, and then trigger overtopping and breaching. The seismic signals corresponding to the failure events during retrogressive erosion and overtopping of the dam models were evaluated. Characteristics of the seismic signals were analyzed by Hilbert–Huang transform. Based on the characteristics of the seismic signals, we found four types of mass movement during the retrogressive erosion process, i.e., the single, intermittent, and successive slides and fall. There were precursor seismic signals found caused by cracking immediately before the sliding events of the dam. Furthermore, the dam breach modeling results coincided well with the test results and the field observations. From the test and modeling results, we confirmed that the overtopping discharge and the lateral sliding masses of the dam are also among the important factors influencing the evolution of the breach. In addition, the widening rate of the breach decreases with decreased discharge. The proposed dam breach model can be a useful tool for dam breach warning and hazard reduction. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

18 pages, 9733 KiB

Open AccessEditor’s ChoiceArticle

Spatiotemporal Hotspots and Decadal Evolution of Extreme Rainfall-Induced Landslides: Case Studies in Southern Taiwan

by Chunhung Wu and Chengyi Lin

Water 2021, 13(15), 2090; https://doi.org/10.3390/w13152090 - 30 Jul 2021

Cited by 11 | Viewed by 2924

Abstract

The 2009 Typhoon Morakot triggered numerous landslides in southern Taiwan, and the landslide ratios in the Ailiao and Tamali river watershed were 7.6% and 10.7%, respectively. The sediment yields from the numerous landslides that were deposited in the gullies and narrow reaches upstream [...] Read more.

The 2009 Typhoon Morakot triggered numerous landslides in southern Taiwan, and the landslide ratios in the Ailiao and Tamali river watershed were 7.6% and 10.7%, respectively. The sediment yields from the numerous landslides that were deposited in the gullies and narrow reaches upstream of Ailiao and Tamali river watersheds dominated the landslide recovery and evolution from 2010 to 2015. Rainfall records and annual landslide inventories from 2005 to 2015 were used to analyze the landslide evolution and identify the landslide hotspots. The landslide recovery time in the Ailiao and Tamali river watershed after 2009 Typhoon Morakot was estimated as 5 years after 2009 Typhoon Morakot. The landslide was easily induced, enlarged, or difficult to recover during the oscillating period, particularly in the sub-watersheds, with a landslide ratio > 4.4%. The return period threshold of rainfall-induced landslides during the landslide recovery period was <2 years, and the landslide types of the new or enlarged landslide were the bank-erosion landslide, headwater landslide, and the reoccurrence of old landslide. The landslide hotspot areas in the Ailiao and Tamali river watershed were 2.67–2.88 times larger after the 2009 Typhoon Morakot using the emerging hot spot analysis, and most of the new or enlarged landslide cases were identified into the oscillating or sporadic or consecutive landslide hotspots. The results can contribute to developing strategies of watershed management in watersheds with a dense landslide. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

14 pages, 4698 KiB

Open AccessFeature PaperArticle

Tree-Ring Based Chronology of Landslides in the Shirakami Mountains, Japan

by Kinuko Noguchi, Ching-Ying Tsou, Yukio Ishikawa, Daisuke Higaki and Chun-Yi Wu

Water 2021, 13(9), 1185; https://doi.org/10.3390/w13091185 - 25 Apr 2021

Cited by 6 | Viewed by 3200

Abstract

The N-Ohkawa landslide, and the southern section of the Ohkawa landslide, occurred during the snow-melt seasons of 1999 and 2006, respectively, in the Shirakami Mountains, Japan. This paper examines the response of trees in the Shirakami Mountains to landslides, and also investigates the [...] Read more.

The N-Ohkawa landslide, and the southern section of the Ohkawa landslide, occurred during the snow-melt seasons of 1999 and 2006, respectively, in the Shirakami Mountains, Japan. This paper examines the response of trees in the Shirakami Mountains to landslides, and also investigates the spatio-temporal occurrence patterns of landslide events in the area. Dendrogeomorphological analysis was used to identify growth suppression and growth increase (GD) markers in tilted deciduous broadleaved trees and also to reveal the timing of the establishment of shade-intolerant tree species. Analysis of the GD markers detected in tree-ring width series revealed confirmatory evidence of landslide events that occurred in 1999 and 2006 and were observed by eyewitnesses, as well as signals from eight additional (previously unrecorded) landslide events during 1986–2005. Furthermore, shade-intolerant species were found to have become established on the N-Ohkawa and southern Ohkawa landslides, but with a lag of up to seven years following the landslide events causing the canopy opening. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

18 pages, 4251 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of Rainfall Erosivity Factor Estimation Using Machine and Deep Learning Models

by Jimin Lee, Seoro Lee, Jiyeong Hong, Dongjun Lee, Joo Hyun Bae, Jae E. Yang, Jonggun Kim and Kyoung Jae Lim

Water 2021, 13(3), 382; https://doi.org/10.3390/w13030382 - 1 Feb 2021

Cited by 18 | Viewed by 6112

Abstract

Rainfall erosivity factor (R-factor) is one of the Universal Soil Loss Equation (USLE) input parameters that account for impacts of rainfall intensity in estimating soil loss. Although many studies have calculated the R-factor using various empirical methods or the USLE method, these methods [...] Read more.

Rainfall erosivity factor (R-factor) is one of the Universal Soil Loss Equation (USLE) input parameters that account for impacts of rainfall intensity in estimating soil loss. Although many studies have calculated the R-factor using various empirical methods or the USLE method, these methods are time-consuming and require specialized knowledge for the user. The purpose of this study is to develop machine learning models to predict the R-factor faster and more accurately than the previous methods. For this, this study calculated R-factor using 1-min interval rainfall data for improved accuracy of the target value. First, the monthly R-factors were calculated using the USLE calculation method to identify the characteristics of monthly rainfall-runoff induced erosion. In turn, machine learning models were developed to predict the R-factor using the monthly R-factors calculated at 50 sites in Korea as target values. The machine learning algorithms used for this study were Decision Tree, K-Nearest Neighbors, Multilayer Perceptron, Random Forest, Gradient Boosting, eXtreme Gradient Boost, and Deep Neural Network. As a result of the validation with 20% randomly selected data, the Deep Neural Network (DNN), among seven models, showed the greatest prediction accuracy results. The DNN developed in this study was tested for six sites in Korea to demonstrate trained model performance with Nash–Sutcliffe Efficiency (NSE) and the coefficient of determination (R²) of 0.87. This means that our findings show that DNN can be efficiently used to estimate monthly R-factor at the desired site with much less effort and time with total monthly precipitation, maximum daily precipitation, and maximum hourly precipitation data. It will be used not only to calculate soil erosion risk but also to establish soil conservation plans and identify areas at risk of soil disasters by calculating rainfall erosivity factors. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

21 pages, 7330 KiB

Open AccessEditor’s ChoiceArticle

Experimental Study on Landslides in Terraced Fields in the Chinese Loessial Region under Extreme Rainfall

by Yongfu Wen, Peng Gao, Xingmin Mu, Mengzhen Li, Yongjun Su and Haixing Wang

Water 2021, 13(3), 270; https://doi.org/10.3390/w13030270 - 22 Jan 2021

Cited by 12 | Viewed by 3295

Abstract

Due to the development of the scale of tractor-ploughed terraces, terraces have been increasing in number, while global climate change is causing frequent extreme rainfall events in the Loess Plateau, resulting in many terrace landslides. To study the mechanism and process of shallow [...] Read more.

Due to the development of the scale of tractor-ploughed terraces, terraces have been increasing in number, while global climate change is causing frequent extreme rainfall events in the Loess Plateau, resulting in many terrace landslides. To study the mechanism and process of shallow landslides and deep slip surface of terraces induced by extreme rainfall in loess hill and gully area, we conducted a laboratory model test of a terrace under artificial rainfall and used the Swedish arc strip method. The research results are as follows. The mechanism of shallow landslides in terraces is rill erosion accelerating rainfall infiltration, suspending the slope, and increasing its bulk density. The destruction process of shallow landslides can be roughly divided into six processes, and the earth volume of the landslide is 0.24 m³. The mechanism of the deep sliding surface in terraces occurs under the combined action of water erosion and gravity erosion. The soil moisture content increases, which decreases the anti-sliding moment and increases the sliding moment, and the safety factor becomes less than the allowable limit for terraces. The deep sliding deformation area of the terrace was 0~1.0 m below the slope surface, slip surface radius was 1.43 m, the slip surface angle was 92^°, and the deep sliding surface began to form earlier than terraced shallow landslides. The displacement of the characteristic points increased from the slope top, to the slope center, and to the slope foot, with maximum displacements of 40.3, 15.5, and 6.0 mm, respectively. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

16 pages, 4950 KiB

Open AccessArticle

A New Method for Wet-Dry Front Treatment in Outburst Flood Simulation

by Dingzhu Liu, Jinbo Tang, Hao Wang, Yang Cao, Nazir Ahmed Bazai, Huayong Chen and Daochuan Liu

Water 2021, 13(2), 221; https://doi.org/10.3390/w13020221 - 18 Jan 2021

Cited by 9 | Viewed by 2827

Abstract

When utilizing a finite volume method to predict outburst flood evolution in real geometry, the processing of wet-dry front and dry cells is an important step. In this paper, we propose a new approach to process wet-dry front and dry cells, including four [...] Read more.

When utilizing a finite volume method to predict outburst flood evolution in real geometry, the processing of wet-dry front and dry cells is an important step. In this paper, we propose a new approach to process wet-dry front and dry cells, including four steps: (1) estimating intercell properties; (2) modifying interface elevation; (3) calculating dry cell elevations by averaging intercell elevations; and (4) changing the value of the first term of slope limiter based on geometry in dry cells. The Harten, Lax, and van Leer with the contact wave restored (HLLC) scheme was implemented to calculate the flux. By combining the MUSCL (Monotone Upstream–centred Scheme for Conservation Laws)-Hancock method with the minmod slope limiter, we achieved second-order accuracy in space and time. This approach is able to keep the conservation property (C-property) and the mass conservation of complex bed geometry. The results of numerical tests in this study are consistent with experimental data, which verifies the effectiveness of the new approach. This method could be applied to acquire wetting and drying processes during flood evolution on structured meshes. Furthermore, a new settlement introduces few modification steps, so it could be easily applied to matrix calculations. The new method proposed in this study can facilitate the simulation of flood routing in real terrain. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

16 pages, 4799 KiB

Open AccessEditor’s ChoiceArticle

A Study on Interaction between Overfall Types and Scour at Bridge Piers with a Moving-Bed Experiment

by Wei-Lin Lee, Chih-Wei Lu and Chin-Kun Huang

Water 2021, 13(2), 152; https://doi.org/10.3390/w13020152 - 11 Jan 2021

Cited by 7 | Viewed by 2763

Abstract

River slopes can be changed due to an extreme event, e.g., a large-scale earthquake. This can uplift a riverbed greatly and thereby change the behavior of the river flow into a free or submerged overfall. Corresponding damage, including extreme erosion, on bridge piers [...] Read more.

River slopes can be changed due to an extreme event, e.g., a large-scale earthquake. This can uplift a riverbed greatly and thereby change the behavior of the river flow into a free or submerged overfall. Corresponding damage, including extreme erosion, on bridge piers located in the river can take place due to the aforementioned flow conditions. A reconstructed bridge pier in the same location would also experience a similar impact if the flow condition is not changed. It is important to identify these phenomena and research the mechanism in the interaction between overfall types and scour at bridge piers. Therefore, this paper is aimed at studying a mechanism of free and submerged overfall flow impacts on bridge piers with different distances by a series of moving-bed experiments. The experiment results showed clearly that bridge pier protection requires attention particularly when the pier is located in the maximum scour hole induced by the submerged overfall due to the z directional flow eddies. In many other cases, such as when the location of the bridge pier was at the upstream slope of a scour hole induced by a flow drop, a deposition mound could be observed at the back of the pier. This indicates that, while a pier is at this location, an additional protection takes place on the bridge pier. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

16 pages, 4724 KiB

Open AccessEditor’s ChoiceArticle

Variations in Soil Erosion Resistance of Gully Head Along a 25-Year Revegetation Age on the Loess Plateau

by Zhuoxin Chen, Mingming Guo and Wenlong Wang

Water 2020, 12(12), 3301; https://doi.org/10.3390/w12123301 - 24 Nov 2020

Cited by 15 | Viewed by 2538

Abstract

The effects of vegetation restoration on soil erosion resistance of gully head, along a revegetation age gradient, remain poorly understood. Hence, we collected undisturbed soil samples from a slope farmland and four grasslands with different revegetation ages (3, 10, 18, 25 years) along [...] Read more.

The effects of vegetation restoration on soil erosion resistance of gully head, along a revegetation age gradient, remain poorly understood. Hence, we collected undisturbed soil samples from a slope farmland and four grasslands with different revegetation ages (3, 10, 18, 25 years) along gully heads. Then, these samples were used to obtain soil detachment rate of gully heads by the hydraulic flume experiment under five unit width flow discharges (2–6 m³ h). The results revealed that soil properties were significantly ameliorated and root density obviously increased in response to restoration age. Compared with farmland, soil detachment rate of revegetated gully heads decreased 35.5% to 66.5%, and the sensitivity of soil erosion of the gully heads to concentrated flow decreased with revegetation age. The soil detachment rate of gully heads was significantly related to the soil bulk density, soil disintegration rate, capillary porosity, saturated soil hydraulic conductivity, organic matter content and water stable aggregate. The roots of 0–0.5 and 0.5–1.0 mm had the highest benefit in reducing soil loss of gully head. After revegetation, soil erodibility of gully heads decreased 31.0% to 78.6%, and critical shear stress was improved by 1.2 to 4.0 times. The soil erodibility and critical shear stress would reach a stable state after an 18-years revegetation age. These results allow us to better evaluate soil vulnerability of gully heads to concentrated flow erosion and the efficiency of revegetation. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

20 pages, 3299 KiB

Open AccessEditor’s ChoiceArticle

Estimating Human Impacts on Soil Erosion Considering Different Hillslope Inclinations and Land Uses in the Coastal Region of Syria

by Safwan Mohammed, Hazem G. Abdo, Szilard Szabo, Quoc Bao Pham, Imre J. Holb, Nguyen Thi Thuy Linh, Duong Tran Anh, Karam Alsafadi, Ali Mokhtar, Issa Kbibo, Jihad Ibrahim and Jesus Rodrigo-Comino

Water 2020, 12(10), 2786; https://doi.org/10.3390/w12102786 - 7 Oct 2020

Cited by 44 | Viewed by 5211

Abstract

Soils in the coastal region of Syria (CRoS) are one of the most fragile components of natural ecosystems. However, they are adversely affected by water erosion processes after extreme land cover modifications such as wildfires or intensive agricultural activities. The main goal of [...] Read more.

Soils in the coastal region of Syria (CRoS) are one of the most fragile components of natural ecosystems. However, they are adversely affected by water erosion processes after extreme land cover modifications such as wildfires or intensive agricultural activities. The main goal of this research was to clarify the dynamic interaction between erosion processes and different ecosystem components (inclination, land cover/land use, and rainy storms) along with the vulnerable territory of the CRoS. Experiments were carried out in five different locations using a total of 15 erosion plots. Soil loss and runoff were quantified in each experimental plot, considering different inclinations and land uses (agricultural land (AG), burnt forest (BF), forest/control plot (F)). Observed runoff and soil loss varied greatly according to both inclination and land cover after 750 mm of rainfall (26 events). In the cultivated areas, the average soil water erosion ranged between 0.14 ± 0.07 and 0.74 ± 0.33 kg/m²; in the BF plots, mean soil erosion ranged between 0.03 ± 0.01 and 0.24 ± 0.10 kg/m². The lowest amount of erosion was recorded in the F plots where the erosion ranged between 0.1 ± 0.001 and 0.07 ± 0.03 kg/m². Interestingly, the General Linear Model revealed that all factors (i.e., inclination, rainfall and land use) had a significant (p < 0.001) effect on the soil loss. We concluded that human activities greatly influenced soil erosion rates, being higher in the AG lands, followed by BF and F. Therefore, the current study could be very useful to policymakers and planners for proposing immediate conservation or restoration plans in a less studied area which has been shown to be vulnerable to soil erosion processes. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

19 pages, 4667 KiB

Open AccessArticle

Impacts of the Degraded Alpine Swamp Meadow on Tensile Strength of Riverbank: A Case Study of the Upper Yellow River

by Haili Zhu, Peng Gao, Zhiwei Li, Jiangtao Fu, Guorong Li, Yabin Liu, Xilai Li and Xiasong Hu

Water 2020, 12(9), 2348; https://doi.org/10.3390/w12092348 - 21 Aug 2020

Cited by 6 | Viewed by 2595

Abstract

In the meandering riverbank of the Upper Yellow River (UYR), the native alpine swamp meadow (AS) has continuously degenerated into an alpine meadow (AM) due to climate change and intensified grazing. Its implication on river morphology is still not well known. This study [...] Read more.

In the meandering riverbank of the Upper Yellow River (UYR), the native alpine swamp meadow (AS) has continuously degenerated into an alpine meadow (AM) due to climate change and intensified grazing. Its implication on river morphology is still not well known. This study examined this effect by in situ measurings of (1) physical properties of roots and their distribution in the soil-root mixture of the upper bank layer, and (2) the tensile strength in terms of excavating tests for triggering cantilever collapses of AS and AM riverbanks. The results showed that the root number in AS was significantly greater than that in AM, though the root distribution in both was similar. Also, the average tensile strength of individual roots in AS was 31,310 kPa, while that in AM was only 16,155 kPa. For the soil-root mixture, it decreased from 67.39 to 21.96 kPa. The weakened mechanical property was mainly ascribed to the lessened root number and the simpler root structure in the soil-root mixture of AM that reduces its ability to resist the external force. These findings confirmed that healthy AS can enhance bank stability and delay the development of tensile cracks in the riverbank of the meandering rivers in the UYR. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

24 pages, 10825 KiB

Open AccessArticle

Static Liquefaction Capacity of Saturated Undisturbed Loess in South Jingyang Platform

by Rui-Xin Yan, Jian-Bing Peng, Jin-Yuan Zhang and Shao-kai Wang

Water 2020, 12(8), 2298; https://doi.org/10.3390/w12082298 - 16 Aug 2020

Cited by 9 | Viewed by 3000

Abstract

According to a previous geological investigation, high-speed and long-distance loess landslides in the South Jingyang platform in Shaanxi Province are closely related to the static liquefaction of loess. Considering the typical loess landslides in this area, isotropic consolidated undrained (ICU) triaxial tests and [...] Read more.

According to a previous geological investigation, high-speed and long-distance loess landslides in the South Jingyang platform in Shaanxi Province are closely related to the static liquefaction of loess. Considering the typical loess landslides in this area, isotropic consolidated undrained (ICU) triaxial tests and scanning electron microscopy analyses were conducted in this study. The main conclusions are as follows: (1) The stress-strain curves indicate strong strain softening under different confining pressures. The pore water pressure increases significantly and then remains at a high level; (2) The liquefaction potential index (LPI) shows an increasing trend followed by stabilization; the larger the LPI is, the smaller the state parameter (Ψ) is. The steady-state points of the loess are in the instability region; however, the steady-state strength is not zero; (3) Based on the ICU test results, the average pore diameter decreases; the shape ratio remains essentially unchanged; and the fractal dimension and roundness show different trends. The proportions of the macropore and mesopore decrease; that of the small pore increases slightly; and that of the micropore increases significantly; (4) The compression deformation of the highly spaced pores causes rapid strain hardening. A rapid strain softening results from the pore throat blockage at the beginning of particle rearrangement and reorganization. A stable strain softening is related to the agglomeration blocking of the reconstructed pore throat in the gradually stable stage of particle rearrangement and reorganization. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

21 pages, 14274 KiB

Open AccessArticle

Climate Change Impacts on Soil Erosion and Sediment Yield in a Watershed

by Ching-Nuo Chen, Samkele S. Tfwala and Chih-Heng Tsai

Water 2020, 12(8), 2247; https://doi.org/10.3390/w12082247 - 10 Aug 2020

Cited by 34 | Viewed by 5775

Abstract

This study analyzed the influence of climate change on sediment yield variation, sediment transport and erosion deposition distribution at the watershed scale. The study was based on Gaoping River basin, which is among the largest basins in southern Taiwan. To carry out this [...] Read more.

This study analyzed the influence of climate change on sediment yield variation, sediment transport and erosion deposition distribution at the watershed scale. The study was based on Gaoping River basin, which is among the largest basins in southern Taiwan. To carry out this analysis, the Physiographic Soil Erosion Deposition (PSED) model was utilized. Model results showed a general increase in soil erosion and deposition volume under the A1B-S climate change scenario. The situation is even worsened with increasing return periods. Total erosion volume and total sediment yield in the watershed were increased by 4–25% and 8–65%, respectively, and deposition volumes increased by 2–23%. The study showed how climate change variability would influence the watershed through increased sediment yields, which might even worsen the impacts of natural disasters. It has further illustrated the importance of incorporating climate change into river management projects. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

17 pages, 3535 KiB

Open AccessArticle

Susceptibility Mapping of Soil Water Erosion Using Machine Learning Models

by Amirhosein Mosavi, Farzaneh Sajedi-Hosseini, Bahram Choubin, Fereshteh Taromideh, Gholamreza Rahi and Adrienn A. Dineva

Water 2020, 12(7), 1995; https://doi.org/10.3390/w12071995 - 14 Jul 2020

Cited by 110 | Viewed by 7052

Abstract

Soil erosion is a serious threat to sustainable agriculture, food production, and environmental security. The advancement of accurate models for soil erosion susceptibility and hazard assessment is of utmost importance for enhancing mitigation policies and laws. This paper proposes novel machine learning (ML) [...] Read more.

Soil erosion is a serious threat to sustainable agriculture, food production, and environmental security. The advancement of accurate models for soil erosion susceptibility and hazard assessment is of utmost importance for enhancing mitigation policies and laws. This paper proposes novel machine learning (ML) models for the susceptibility mapping of the water erosion of soil. The weighted subspace random forest (WSRF), Gaussian process with a radial basis function kernel (Gaussprradial), and naive Bayes (NB) ML methods were used in the prediction of the soil erosion susceptibility. Data included 227 samples of erosion and non-erosion locations through field surveys to advance models of the spatial distribution using predictive factors. In this study, 19 effective factors of soil erosion were considered. The critical factors were selected using simulated annealing feature selection (SAFS). The critical factors included aspect, curvature, slope length, flow accumulation, rainfall erosivity factor, distance from the stream, drainage density, fault density, normalized difference vegetation index (NDVI), hydrologic soil group, soil texture, and lithology. The dataset cells of samples (70% for training and 30% for testing) were randomly prepared to assess the robustness of the different models. The functional relevance between soil erosion and effective factors was computed using the ML models. The ML models were evaluated using different metrics, including accuracy, the kappa coefficient, and the probability of detection (POD). The accuracies of the WSRF, Gaussprradial, and NB methods were 0.91, 0.88, and 0.85, respectively, for the testing data; 0.82, 0.76, and 0.71, respectively, for the kappa coefficient; and 0.94, 0.94, and 0.94, respectively, for POD. However, the ML models, especially the WSRF, had an acceptable performance regarding producing soil erosion susceptibility maps. Maps produced with the most robust models can be a useful tool for sustainable management, watershed conservation, and the reduction of soil and water loss. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

25 pages, 8293 KiB

Open AccessArticle

Characteristics of a Debris Flow Disaster and Its Mitigation Countermeasures in Zechawa Gully, Jiuzhaigou Valley, China

by Xing-Long Gong, Kun-Ting Chen, Xiao-Qing Chen, Yong You, Jian-Gang Chen, Wan-Yu Zhao and Jie Lang

Water 2020, 12(5), 1256; https://doi.org/10.3390/w12051256 - 28 Apr 2020

Cited by 18 | Viewed by 5743

Abstract

On 8 August 2017, an Ms 7.0 earthquake struck Jiuzhaigou Valley, triggering abundant landslides and providing a huge source of material for potential debris flows. After the earthquake debris flows were triggered by heavy rainfall, causing traffic disruption and serious property losses. This [...] Read more.

On 8 August 2017, an Ms 7.0 earthquake struck Jiuzhaigou Valley, triggering abundant landslides and providing a huge source of material for potential debris flows. After the earthquake debris flows were triggered by heavy rainfall, causing traffic disruption and serious property losses. This study aims to describe the debris flow events in Zechawa Gully, calculate the peak discharges of the debris flows, characterize the debris flow disasters, propose mitigation countermeasures to control these disasters and analyse the effectiveness of countermeasures that were implemented in May 2019. The results showed the following: (1) The frequency of the debris flows in Zechawa Gully with small- and medium-scale will increase due to the influence of the Ms 7.0 Jiuzhaigou earthquake. (2) An accurate debris flow peak discharge can be obtained by comparing the calculated results of four different methods. (3) The failure of a check dam in the channel had an amplification effect on the peak discharge, resulting in a destructive debris flow event on 4 August 2016. Due to the disaster risk posed by dam failure, both blocking and deposit stopping measures should be adopted for debris flow mitigation. (4) Optimized engineering countermeasures with blocking and deposit stopping measures were proposed and implemented in May 2019 based on the debris flow disaster characteristics of Zechawa Gully, and the reconstructed engineering projects were effective in controlling a post-earthquake debris flow disaster on 21 June 2019. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

17 pages, 36260 KiB

Open AccessArticle

A Landslide Probability Model Based on a Long-Term Landslide Inventory and Rainfall Factors

by Chun-Yi Wu and Yen-Chu Yeh

Water 2020, 12(4), 937; https://doi.org/10.3390/w12040937 - 26 Mar 2020

Cited by 12 | Viewed by 5056

Abstract

The prediction and advanced warning of landslide hazards in large-scale areas must deal with a large amount of uncertainty, therefore a growing number of studies are using stochastic models to analyze the probability of landslide occurrences. In this study, we used a modified [...] Read more.

The prediction and advanced warning of landslide hazards in large-scale areas must deal with a large amount of uncertainty, therefore a growing number of studies are using stochastic models to analyze the probability of landslide occurrences. In this study, we used a modified Thiessen’s polygon method to divide the research area into several rain gauge control areas, and divided the control areas into slope units reflecting the topographic characteristics to enhance the spatial resolution of a landslide probability model. We used a 2000–2015 long-term landslide inventory, daily rainfall, and effective accumulated rainfall to estimate the rainfall threshold that can trigger landslides. We then employed a Poisson probability model and historical rainfall data from 1987 to 2016 to calculate the exceedance probability that rainfall events will exceed the threshold value. We calculated the number of landslides occurring from the events when rainfall exceeds the threshold value in the slope units to estimate the probability that a landslide will occur in this situation. Lastly, we employed the concept of conditional probability by multiplying this probability with the exceedance probability of rainfall events exceeding the threshold value, which yielded the probability that a landslide will occur in each slope unit for one year. The results indicated the slope units with high probability that at least one rainfall event will exceed the threshold value at the same time that one landslide will occur within any one year are largely located in the southwestern part of the Taipei Water Source Domain, and the highest probability is 0.26. These slope units are located in parts of the study area with relatively weak lithology, high elevations, and steep slopes. Compared with probability models based solely on landslide inventories, our proposed landslide probability model, combined with a long-term landslide inventory and rainfall factors, can avoid problems resulting from an incomplete landslide inventory, and can also be used to estimate landslide occurrence probability based on future potential changes in rainfall. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

24 pages, 3804 KiB

Open AccessArticle

Estimation of Soil Erosion and Sediment Yield in the Lancang–Mekong River Using the Modified Revised Universal Soil Loss Equation and GIS Techniques

by Pavisorn Chuenchum, Mengzhen Xu and Wenzhe Tang

Water 2020, 12(1), 135; https://doi.org/10.3390/w12010135 - 31 Dec 2019

Cited by 85 | Viewed by 9229

Abstract

The Lancang–Mekong River basin, as an important transboundary river in Southeast Asia, is challenged by rapid socio-economic development, especially the construction of hydropower dams. Furthermore, substantial factors, such as terrain, rainfall, soil properties and agricultural activity, affect and are highly susceptible to soil [...] Read more.

The Lancang–Mekong River basin, as an important transboundary river in Southeast Asia, is challenged by rapid socio-economic development, especially the construction of hydropower dams. Furthermore, substantial factors, such as terrain, rainfall, soil properties and agricultural activity, affect and are highly susceptible to soil erosion and sediment yield. This study aimed to estimate average annual soil erosion in terms of spatial distribution and sediment deposition by using the revised universal soil loss equation (RUSLE) and GIS techniques. This study also applied remote sensing and available data sources for soil erosion analysis. Annual soil erosion in most parts of the study area range from 700 to 10,000 t/km²/y with a mean value of 5350 t/km²/y. Approximately 45% of the total area undergoes moderate erosion. Moreover, the assessments of sediment deposition and erosion using the modified RUSLE and the GIS techniques indicate high sediment erosion along the flow direction of the mainstream, from the upper Mekong River to the Mekong Delta. The northern part of the upper Mekong River and the central and southern parts of the lower Mekong River are the most vulnerable to the increase in soil erosion rates, indicating sediment deposition. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Graphical abstract

21 pages, 3232 KiB

Open AccessArticle

The Impact of Vegetation Successional Status on Slope Runoff Erosion in the Loess Plateau of China

by Enhao Chang, Peng Li, Zhanbin Li, Yuanyi Su, Yi Zhang, Jianwen Zhang, Zhan Liu and Zhineng Li

Water 2019, 11(12), 2614; https://doi.org/10.3390/w11122614 - 11 Dec 2019

Cited by 20 | Viewed by 3615

Abstract

Slope vegetation restoration is known to influence erosion in the Loess Plateau region in China. The ability of vegetation to mitigate soil erosion under extreme runoff, however, has not been studied in great detail in this region. Here, we examine five typical vegetation [...] Read more.

Slope vegetation restoration is known to influence erosion in the Loess Plateau region in China. The ability of vegetation to mitigate soil erosion under extreme runoff, however, has not been studied in great detail in this region. Here, we examine five typical vegetation communities in the Loess Plateau region that originated from restoration efforts enacted at different times (1, 11, 15, 25, and 40 years). Water scouring experiments were carried out to monitor vegetation community succession and its effects on erosion. These results indicate that the sum of plant importance values increased from 260.72 to 283.06, species density increased from 2.5 to 4.5 per m², and the amount of litter and humus increased from 24.50 to 605.00 g/m² during the 1 to 40 years of vegetation community succession. Root biomass and root diameter reached a maximum of approximately 10.80 mg·cm⁻³ and 0.65 mm at 40 years of recovery. Slope runoff velocity decreased by 47.89% while runoff resistance increased by 35.30 times. The runoff power decreased by 19.75%, the total runoff volume decreased by 2.52 times, and the total sediment yield decreased by 11.60 times in the vegetation community. Slope runoff velocity and power had the largest correlation with aboveground vegetation (0.76, 0.74), total runoff had the largest correlation with underground roots (0.74), and runoff resistance was most strongly correlated with soil structure (0.71). Studies have shown that the succession of vegetation communities can enhance the aboveground ecological functions of plants, thereby significantly reducing the runoff velocity and power. The development of plant root system significantly reduces the runoff volume; the improved soil structure significantly increased the runoff resistance coefficient. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

26 pages, 6503 KiB

Open AccessArticle

Landslide Susceptibility Based on Extreme Rainfall-Induced Landslide Inventories and the Following Landslide Evolution

by Chunhung Wu

Water 2019, 11(12), 2609; https://doi.org/10.3390/w11122609 - 11 Dec 2019

Cited by 17 | Viewed by 4328

Abstract

Landslide susceptibility assessment is crucial for mitigating and preventing landslide disasters. Most landslide susceptibility studies have focused on creating landslide susceptibility models for specific rainfall or earthquake events, but landslide susceptibility in the years after specific events are also valuable for further discussion, [...] Read more.

Landslide susceptibility assessment is crucial for mitigating and preventing landslide disasters. Most landslide susceptibility studies have focused on creating landslide susceptibility models for specific rainfall or earthquake events, but landslide susceptibility in the years after specific events are also valuable for further discussion, especially after extreme rainfall events. This research provides a new method to draw an annual landslide susceptibility map in the 5 years after Typhoon Morakot (2009) in the Chishan River watershed in Taiwan. This research establishes four landslide susceptibility models by using four methods and 12 landslide-related factors and selects the model with the optimum performance. This research analyzes landslide evolution in the 5 years after Typhoon Morakot and estimates the average landslide area different ratio (LAD) in upstream, midstream, and downstream of the Chishan River watershed. We combine landslide susceptibility with the model with the highest performance and average annual LAD to draw an annual landslide susceptibility map, and its mean correct ratio ranges from 62.5% to 73.8%. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

15 pages, 4341 KiB

Open AccessArticle

The Analysis on Similarity of Spectrum Analysis of Landslide and Bareland through Hyper-Spectrum Image Bands

by Shiuan Wan, Tsu Chiang Lei, Hong Lin Ma and Ru Wen Cheng

Water 2019, 11(11), 2414; https://doi.org/10.3390/w11112414 - 17 Nov 2019

Cited by 6 | Viewed by 3504

Abstract

Landslides of Taiwan occur frequently in high mountain areas. Soil disturbance causes by the earthquake and heavy rainfall of the typhoon seasons often produced the earth and rock to landslide in the upper reaches of the catchment area. Therefore, the landslide near the [...] Read more.

Landslides of Taiwan occur frequently in high mountain areas. Soil disturbance causes by the earthquake and heavy rainfall of the typhoon seasons often produced the earth and rock to landslide in the upper reaches of the catchment area. Therefore, the landslide near the hillside has an influence on the catchment area. The hyperspectral images are effectively used to monitor the landslide area with the spectral analysis. However, it is rarely studied how to interpret it in the image of the landslide. If there are no elevation data on the slope disaster, it is quite difficult to identify the landslide zone and the bareland area. More specifically, this study used a series of spectrum analysis to identify the difference between them. Therefore, this study conducted a spectrum analysis for the classification of the landslide, bareland, and vegetation area in the mountain area of NanXi District, Tainan City. On the other hand, this study used the following parallel study on Support Vector Machine (SVM) for error matrix and thematic map for comparison. The study simultaneously compared the differences between them. The spectral similarity analysis reaches 85% for testing data, and the SVM approach has 98.3%. Full article

(This article belongs to the Special Issue Soil–Water Conservation, Erosion, and Landslide)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Soil–Water Conservation, Erosion, and Landslide

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (20 papers)

Editorial

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI