Geohazards in the three Gorges Reservoir Area, China – Lessons learned from decades of research

Abstract The impoundment of the 660-km long reservoir behind the huge Three Gorges Dam, the world's largest hydropower station, increased regional seismicity and reactivated severe geohazards. Before the reservoir filling was initiated in 2003, the region had approximately two earthquakes per year with magnitudes between 3.0 and 4.9; after the full impoundment in 2008, approximately 14 earthquakes per year occurred with magnitudes between 3.0 and 5.4. In addition, hundreds of landslides were reactivated and are now in a state of intermittent creep. Many landslides exhibit step-like annual pattern of displacement in response to quasi-regular variations in seasonal rainfall and reservoir level. Additional problems include rock avalanches, impulse waves and debris flows. The seriousness of these events motivated numerous studies that resulted in 1) Better insight into the behavior and evolution mechanism of geohazards in the Three Gorges Reservoir Area (TGRA); 2) Implementation of monitoring and early-warning systems of geohazards; and 3) Design and construction of preventive countermeasures including lattice anchors, stabilizing piles, rock bolts, drainage canals and tunnels, and huge revetments. This paper reviews the hydro-geologic setting of TGRA geohazards, examines their occurrence and evolution in the past few decades, offers insight learned from extensive research on TGRA geohazards, and suggests topics for future research to address the remaining challenges

Weight of Evidence Method and Its Applications and Development

AbstractThe development and applications about the weight of evidence technology in recent years are reviewed. This paper introduced the improved weight of evidence in remote sensing image processing and in different fields of application. Summary its constraints and existent problems. Look forward to the weight of evidence for the practical application

Landslide Susceptibility Mapping Using Statistical Methods along the Asian Highway, Bhutan

In areas prone to frequent landslides, the use of landslide susceptibility maps can greatly aid in the decision-making process of the socio-economic development plans of the area. Landslide susceptibility maps are generally developed using statistical methods and geographic information systems. In the present study, landslide susceptibility along road corridors was considered, since the anthropogenic impacts along a road in a mountainous country remain uniform and are mainly due to road construction. Therefore, we generated landslide susceptibility maps along 80.9 km of the Asian Highway (AH48) in Bhutan using the information value, weight of evidence, and logistic regression methods. These methods have been used independently by some researchers to produce landslide susceptibility maps, but no comparative analysis of these methods with a focus on road corridors is available. The factors contributing to landslides considered in the study are land cover, lithology, elevation, proximity to roads, drainage, and fault lines, aspect, and slope angle. The validation of the method performance was carried out by using the area under the curve of the receiver operating characteristic on training and control samples. The area under the curve values of the control samples were 0.883, 0.882, and 0.88 for the information value, weight of evidence, and logistic regression models, respectively, which indicates that all models were capable of producing reliable landslide susceptibility maps. In addition, when overlaid on the generated landslide susceptibility maps, 89.3%, 85.6%, and 72.2% of the control landslide samples were found to be in higher-susceptibility areas for the information value, weight of evidence, and logistic regression methods, respectively. From these findings, we conclude that the information value method has a better predictive performance than the other methods used in the present study. The landslide susceptibility maps produced in the study could be useful to road engineers in planning landslide prevention and mitigation works along the highway

Rapid characterisation of the extremely large landslide threatening the Rules Reservoir (Southern Spain)

When an active landslide is first identified in an artificial reservoir, a comprehensive study has to be quickly conducted to analyse the possible hazard that it may represent to such a critical infrastructure. This paper presents the case of the El Arrecife Landslide, located in a slope of the Rules Reservoir (Southern Spain), as an example of geological and motion data integration for elaborating a preliminary hazard assessment. For this purpose, a field survey was carried out to define the kinematics of the landslide: translational in favour of a specific foliation set, and rotational at the foot of the landslide. A possible failure surface has been proposed, as well as an estimation of the volume of the landslide: 14.7 million m3. At the same time, remote sensing and geophysical techniques were applied to obtain historical displacement rates. A mean subsidence rate of the landslide around 2 cm/year was obtained by means of synthetic aperture radar interferometry (InSAR) and ground-penetrating radar (GPR) data, during the last 5 and 22 years, respectively. The structure-from-motion (SfM) technique provided a rate up to 26 cm/year during the last 14 years of a slag heap located within the foot of the landslide, due to compaction of the anthropical deposits. All of this collected information will be valuable to optimise the planning of future monitoring surveys (i.e. differential global positioning systems, inclinometers, ground drilling, and InSAR) that should be applied in order to prevent further damage on the reservoir and related infrastructures.This work was mainly supported by the European Regional Development Fund (ERDF) through the project “RISKCOAST” (SOE3/P4/E0868) of the Interreg SUDOE Programme. The work of J.P.G., M.M-S., P.R. and J.M.A. was also supported by the “Ramón y Cajal” Programme (RYC-2017–23335) of the Spanish Ministry of Science, the project “MORPHOMED”—PID2019-107138RB-I00 / SRA (State Research Agency / https://doi.org/10.13039/501100011033) and the project “RADANDALUS” (P18-RT-3632) and B-RNM-305-UGR1818 of the FEDER / Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades

Sinkhole susceptibility mapping: A comparison between Bayes-based machine learning algorithms

Land degradation has been recognized as one of the most adverse environmental impacts during the last century. The occurrence of sinkholes is increasing dramatically in many regions worldwide contributing to land degradation. The rise in the sinkhole frequency is largely due to human-induced hydrological alterations that favour dissolution and subsidence processes. Mitigating detrimental impacts associated with sinkholes requires understanding different aspects of this phenomenon such as the controlling factors and the spatial distribution patterns. This research illustrates the development and validation of sinkhole susceptibility models in Hamadan Province, Iran, where a large number of sinkholes are occurring under poorly understood circumstances. Several susceptibility models were developed with a training sample of sinkholes, a number of conditioning factors, and four different statistical approaches: naïve Bayes, Bayes net (BN), logistic regression, and Bayesian logistic regression. Ten conditioning factors were initially considered. Factors with negligible contribution to the quality of predictions, according to the information gain ratio technique, were discarded for the development of the final models. The validation of susceptibility models, performed using different statistical indices and receiver operating characteristic curves, revealed that the BN model has the highest prediction capability in the study area. This model provides reliable predictions on the future distribution of sinkholes, which can be used by watershed and land use managers for designing hazard and land-degradation mitigation plans

Reservoir landslide monitoring and mechanism analysis based on UAV photogrammetry and sub-pixel offset tracking: a case study of Wulipo landslide

Introduction: Reservoir landslides undergo large deformations during the early stages of impoundment and maintain long-term persistent deformations during the operational period of the reservoir. The management of reservoir landslides mostly focuses on the early identification, risk assessment during the large deformations, and long-sequence monitoring during long-term persistent deformations, which requires sufficient continuity and integrity of the landslide monitoring data.Methods: Taking the Wulipo (WLP) landslide in Baihetan Reservoir as example, this paper proposes a reservoir landslide monitoring method that integrates field survey, unmanned aerial vehicle (UAV) photogrammetry and global navigation satellite system (GNSS) monitoring, which can effectively eliminate the practical monitoring gaps between multiple monitoring methods and improve the continuity and completeness of monitoring data.Results and discussion: First, this study determined the initiation time of the landslide through the field investigation and collected five period of UAV data to analyze the overall displacement vector of the WLP landslide using sub-pixel offset tracking (SPOT). On the basis of the above data, we compensated for the missing data in GNSS system due to the practical monitoring vacancies by combining the field survey and the landslide-water level relationship. Based on these monitoring data, this paper points out that the WLP landslide is a buoyancy-driven landslide, and whether or not accelerated deformation will occur is related to the maximum reservoir water level. Finally, this study analyzed and discussed the applicability of UAV photogrammetry for reservoir landslide monitoring in the absence of ground control points (GCPs), and concluded that this method can be quickly and flexibly applied to the stage of large deformation of reservoir landslides

Soil Erosion in a Highly Dynamic, Terraced Environment - the Effect of the Three Gorges Dam in China

Worldwide, soil erosion is one of the most pressing environmental problems of present times. Particularly, soil erosion triggered by overland flow and runoff seriously affects the productivity and stability of ecosystems. The loss of fertile topsoil and soil's water storage capacity, and the discharge of sediments and associated contamination of waterbodies due to diffuse matter transport of particle-bounded agrochemicals from cropland highly elicit call a for action to combat soil erosion for a future securing of food supply and high drinking water quality. Globally, China belongs to one of those countries most affected by soil erosion. Technical problems as well as high economic off-site damages and costs resulting from reservoir siltation and thus, reduced project's lifespan due to soil erosion are typical for numerous large-scale dam projects in China. In addition to the natural disposition to soil erosion, especially, anthropogenic impacts associated to the dam construction distinctly affect the soil erosion risk potential in the adjacent ecosystems. This can be exemplarily seen at the currently worldwide largest dam project, the Three Gorges Dam at the Yangtze River in Central China. This megaproject has been controversially discussed since its planning, and most recently since its construction and full operation in 2007. It contains the largest installed hydropower capacity worldwide, and is supposed to distinctly improve the river navigation and to secure the water supply to the northern country in the long-term. The realization of the dam project has already required massive resettlements of rural and urban population of more than one million people long before its start of operation. Additionally, large-scale land use changes, e.g., land reclamation for the road and settlement construction, for small scale subsistence farming and for cash crop production as well as shifts in land uses, on the steep sloping uphill-site above the impounded area are expected to considerably foster the soil erosion in the short- to long-term. Due to their partially direct connection to the stream network agriculturally used land with high soil erosion potential affects the water quality. Precise knowledge on the quality and quantity of soil loss, and its spatial and temporal variability can help to control the soil erosion by developing an adapted land use management and identifying conducive soil conservation measures, such as contour-aligned bench terraces. Under optimum conditions, bench terraces balance the geomorphic settings and anthropogenic use and can present a fair and sound basis for economic growth in mountainous areas. The focus of the present thesis lies on the risk potential of soil erosion by water in the newly created reservoir of the Three Gorges Dam. Therefore, the central research questions aimed at the natural soil erosion risk potential and the effect of the dam-induced land use dynamics on the dimension and spatial and temporal distribution of soil losses. Due to the data scarcity and limited access to the terrain, a further focus of the research conducted lied on the data-based regionalization of soil erosion factors to use as input in soil erosion modeling. The research was conducted in the subtropical Xiangxi catchment (3,200 km²) that was considered to adequately represent the Three Gorges Area in terms of physical settings and human interventions attributing to the dam project. The Xiangxi River joins the Yangtze River as a first class tributary approximately 40 km upstream the Three Gorges Dam. Due to the dam construction, the widely terraced landscape of the Xiangxi catchments is also affected by rapid, high land use dynamics with consequences on the slope stability. Particularly, the backwater area in the southern catchment area with the impounded lower reach of the Xiangxi River is characterized by steep to extremely steep sloping terrain and predominantly shallow soils with moderate to very high soil erodibility. Additionally, the very high rainfall erosivity increases the high physical vulnerability of the entire Xiangxi catchment. Between 1987 and 2007, a governmental-driven decrease of arable land and an increase of woodland and shrubland affected the northern headwater zone of the catchment. In the immediate reservoir area, the land use change from 1987 to 2007 was mainly controlled by a distinct conversion of arable land to orange orchards. Within the framework of this thesis, methods for data survey and data processing were tested and adapted in order to evaluate the risk potential of soil erosion. In addition, comprehensive field investigations focusing on soil erosion processes and on pedological properties and further erosion-relevant factors were conducted. Relevant parameters derived from remote sensing data and land use classifications as well as the documented land use change from 1987 to 2007 were used for the parameterization of the empirical soil erosion model RUSLE. This model was applied to estimate and evaluate the spatial distribution and dynamic of the soil erosion risk potential, and to spatially localize high-risk areas. The new conceptual model TerraCE was developed and tested for the identification and spatial analysis of different terrace conditions and their causes. By means of data mining approaches, a prediction of the spatial distribution of the identified terrace conditions was computed. By integrating environmental and anthropogenic indicators on the impact of the terrain and the human influence, the causes and the strength of disturbances on the terrace conditions, and thus terrace degradation were analyzed. During the observation period from 1987 to 2007, the Xiangxi catchment is generally characterized by a decrease of average annual soil losses and their maxima due to implemented environmental programs. However, a very high soil erosion risk potential in the entire catchment must be assumed. Frequency and intensity of soil erosion mainly concentrate in the backwater area at the lower reaches of the Xiangxi River. Here, land use changes, resettlements, and infrastructure construction have the highest impact. An inadequate construction of terraces that is not adapted to the local terrain conditions and an insufficient maintenance of the farming terraces can further strongly affect the soil erosion dynamic. Moreover, rapid ecosystem changes and an associated intensification and reclamation of terraces can lead to their degradation. The tempo of the land use dynamics hardly considers available capital and labor for the cost and time-consuming restoration and maintenance of terraces, mainly cultivated with oranges. The high increase of the reclaimed area for the orange production within very short term caused a surplus production and thus, a price decline on the local and regional markets. Due to the not very profitable sale of oranges, a lack of farmers' motivation and little or no capital are made responsible for the gradual worsening of the terrace conditions. As many of the resettled peasants, that were formerly used to farm the flat valley bottoms, are often not familiar with the new and difficult terrain settings and farming techniques, there is also a lack of knowledge on adequate terrace cultivation. Subsequently, inappropriate management of those terraces leads to an increase in the soil erosion The findings of the present thesis suggest designating the terraces as important, sensitive ecosystem service as they present - if properly maintained - a very effective soil erosion control and enable for a sustainable land use in the mountainous Xiangxi catchment and throughout the entire Three Gores Area. Considering the data scarcity in terms of spatial and temporal resolution, the results further show that soil erosion factors can be successfully regionalized and used for a valid soil erosion modeling. Against the background of ongoing research within the 'Yangtze Project' as well as further projected large dam projects at the Yangtze River and worldwide, the research conducted offers an important starting point for further research on the soil erosion risk potential and associated environmental threats, such as water pollution