Land subsidence: A global challenge Bagheri-Gavkosh, Mehdi; Hosseini, Seiyed Mossa; Ataie-Ashtiani, Behzad ...
The Science of the total environment,
07/2021, Letnik:
778
Journal Article
Recenzirano
This study presents a comprehensive review of the Land subsidence (LS) cases, as a worldwide environmental, geological, and global geohazard concern. Here, 290 case studies around the world mostly ...conducted in large metropolitan cities (e.g. Bangkok, Beijing, California, Houston, Mexico City, Shanghai, Jakarta, and Tokyo) in 41 countries were collected. The spatial distribution of LS characteristics (e.g. intensity, magnitude, and affected area), impacts, and influential factors are scrutinized. Worldwide attempts to remedy the crisis of LS were also investigated in this review. It is shown that the coastal plains and river deltaic regions are of high-frequent subsided areas around the world (~47% of 290 study areas). The spaceborne monitoring of LS is the more prevalent technique (~ 38% of total cases) compared to the ground-investigation (e.g. geological surveying, leveling, GPS, and modeling). Human-induced LS cases are 76.92% of all the LS cases around the world and groundwater extraction contributes 59.75% of these cases. Strong direct correlations with the exponential trend are observed between the average LS rate (LSavg) with groundwater withdrawal (R2 = 0.950) and groundwater level decline (R2 = 0.888). To understand the influential factors on LS occurrences, the relationship of LS rate with climate factors, hydrogeological characteristics of the aquifer, human-induced factors are investigated. Finally, we provide future research guidelines and implications that need to be expanded in order to better monitor and reduce the impact of the LS phenomenon. The outcomes of this study can be used to derive a framework helpful for interpreting the observed LS phenomena and for forecasting future situations to mitigate or control this geohazard.
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•LS rates, areas, drivers, and hazards were analyzed in 290 case studies around the world.•Correlation of LS rate and its drivers were analyzed.•Human-induced LS cases are 78.5% of all the LS cases.•Coastal plains and river deltaic regions are of high-frequent LS areas.•Mitigation methods of LS impacts were provided.
Natural hazards could have devastating consequences globally, making hazard assessment and spatial prediction crucial for enhancing the resilience of urbanized regions. However, current disaster ...prediction and assessment research often neglect the compound effects between multiple geohazards highly in urbanized regions. To address the concern, we employed comparative methodology, evaluating four machine learning algorithms—Extreme Gradient Boosting (XGBoost), Random Forest (RF), Back Propagation Neural Network (BP), and Long Short-Term Memory (LSTM)—in the creation of Geohazard Susceptibility Maps (GSM) for the highly urbanized Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Additionally, the study investigated the triggering mechanisms and the compound interaction between multiple geohazards using the conditional vine copula model. The results showed that the XGBoost model outperformed other models (AUC = 0.89) for predicting multiple geohazards. Geohazards were predominantly concentrated in urban areas in the GBA, with surface subsidence being the most severe, followed by collapse and landslide. The primary triggers for multi-geohazards include distance to roads, slope length, and lithology, with slope length and lithology identified as the primary causative factors in urban areas. Urbanization within the GBA increased the probability of multi-geohazards by 10%, compared to their univariate counterparts. Urban regions exhibited increased risks of landslides, surface subsidence, and collapse by approximately 31%, 44%, and 32%, respectively compared to non-urban regions. Additionally, compound geohazards in the GBA were primarily triggered by heavy rainfall, resulting in the formation of landslide-collapse and collapse-landslide geohazard chains. The probability of compound geohazards is approximately 5% lower than that of univariate geohazards. This is because compound geohazards necessitate a higher cumulative rainfall, and the rainfall threshold was approximately 2–3 times higher than that of univariate geohazards. In the cascading hazard pattern, the occurrence of primary geohazards during local heavy rain increased the probability of secondary geohazards by approximately 10%. The study provides essential insights for mitigating compound geohazards in urbanized areas.
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.
Over the past 50 years, catastrophic rock-ice avalanches have frequently occurred in the Parlung Zangbo Basin, such as those involving the Guxiang and Tianmo gullies, causing serious casualties. The ...initial slope failures generally occurred in high mountains at an elevation of >4000 m above sea level (asl), which subsequently triggered long run-out geohazard chains, such as debris avalanches, debris flows and outburst floods. In this paper, based on satellite imagery, aerial photography, interferometric synthetic aperture radar (InSAR) technology, and field surveys, the characteristics of these rock-ice avalanches are analyzed. The results indicate that high-risk zones are located in the upstream and downstream sections of the Parlung River, where intense geohazards occurred. Based on the movement characteristics of geohazards, four disaster chain modes were summarized, namely rockslide-river blocking-flood, rock and ice avalanche-glacier lake outburst-flood, rockslide/rock-ice avalanche-debris avalanche/debris flow-river blocking-flood, and debris flow-river blocking-flood. Several factors jointly determined the propagation mode and high mobility observed during rock-ice avalanche events: (i) the pipe-like terrain favoured long-runout propagation; (ii) detached ice and snow quantities can be greatly increased via entrainment, thus reducing friction between the moving mass and basal layer. (iii) The debris-moraine may provide abundant materials easily scraped by debris flows. (iv) Meltwater provided by ice and snow at the base of the flow could lubricate debris to improve mobility after mixing with avalanches' debris. Choosing Tianmo gully as an example, dynamics analysis was conducted in by DAN-3D. In the future, possible increases of failure events in formerly glaciated and permafrost areas are likely because of ongoing changes in climatic conditions. This study provides insight into multi-stage avalanche motion in the glacier regions. The results constitute a reference for hazard zonation in similar mountainous areas.
Earth fissures are the cracks on the surface of the earth mainly formed in the arid and the semi-arid basins. The excessive withdrawal of groundwater, as well as the other underground natural ...resources, has been introduced as the significant causing of land subsidence and potentially, the earth fissuring. Fissuring is rapidly turning into the nations’ major disasters which are responsible for significant economic, social, and environmental damages with devastating consequences. Modeling the earth fissure hazard is particularly important for identifying the vulnerable groundwater areas for the informed water management, and effectively enforce the groundwater recharge policies toward the sustainable conservation plans to preserve existing groundwater resources. Modeling the formation of earth fissures and ultimately prediction of the hazardous areas has been greatly challenged due to the complexity, and the multidisciplinary involved to predict the earth fissures. This paper aims at proposing novel machine learning models for prediction of earth fissuring hazards. The Simulated annealing feature selection (SAFS) method was applied to identify key features, and the generalized linear model (GLM), multivariate adaptive regression splines (MARS), classification and regression tree (CART), random forest (RF), and support vector machine (SVM) have been used for the first time to build the prediction models. Results indicated that all the models had good accuracy (>86%) and precision (>81%) in the prediction of the earth fissure hazard. The GLM model (as a linear model) had the lowest performance, while the RF model was the best model in the modeling process. Sensitivity analysis indicated that the hazardous class in the study area was mainly related to low elevations with characteristics of high groundwater withdrawal, drop in groundwater level, high well density, high road density, low precipitation, and Quaternary sediments distribution.
•Machine learning (ML) prediction of earth fissure hazard.•Key features selection using the simulated annealing (SA) method.•Good performance of the ML models (Accuracy >86%; Precision >81%).•The worst and best models respectively were GLM (as a linear model) and RF.
The Tonga volcano eruption at 04:14:45 UT on 2022-01-15 released enormous amounts of energy into the atmosphere, triggering very significant geophysical variations not only in the immediate proximity ...of the epicenter but also globally across the whole atmosphere. This study provides a global picture of ionospheric disturbances over an extended period for at least 4 days. We find traveling ionospheric disturbances (TIDs) radially outbound and inbound along entire Great-Circle loci at primary speeds of ∼300–350 m/s (depending on the propagation direction) and 500–1,000 km horizontal wavelength for front shocks, going around the globe for three times, passing six times over the continental US in 100 h since the eruption. TIDs following the shock fronts developed for ∼8 h with 10–30 min predominant periods in near- and far- fields. TID global propagation is consistent with the effect of Lamb waves which travel at the speed of sound. Although these oscillations are often confined to the troposphere, Lamb wave energy is known to leak into the thermosphere through channels such as atmospheric resonance at acoustic and gravity wave frequencies, carrying substantial wave amplitudes at high altitudes. Prevailing Lamb waves have been reported in the literature as atmospheric responses to the gigantic Krakatoa eruption in 1883 and other geohazards. This study provides substantial first evidence of their long-duration imprints up in the global ionosphere. This study was enabled by ionospheric measurements from 5,000+ world-wide Global Navigation Satellite System (GNSS) ground receivers, demonstrating the broad implication of the ionosphere measurement as a sensitive detector for atmospheric waves and geophysical disturbances.
During the past decades, significant progress has been made in the development of induced seismicity monitoring for related human activities. Hydraulic fracturing and induced seismicity monitoring ...are operating procedures for safe and effective production of oil and gas from unconventional resources, particularly shales. Hydraulic fracturing can induce seismicity through fluid injection and disturbance of subsurface stress in tight reservoirs. Most seismic events associated with hydraulic fracturing exhibit magnitude of Mw ≤ 3 and are referred to as microseismicity, while a few larger-magnitude earthquakes (e.g. Mw > 3) could also be induced by reactivating pre-existing faults. Here, we review the current status of research concerning induced seismicity monitoring for shale hydraulic fracturing. Induced seismicity contains information relating to important subsurface characteristics, e.g. rock failure potential and seismogenic zones. Microseismic monitoring is essential for reservoir characterization, e.g. fracture geometry delineation and reservoir geomechanical analysis. It is carried out with advanced acquisition, processing, and interpretation techniques, while larger-magnitude earthquakes are mainly exploited for potential geohazard management and mitigation. Challenges and prospects associated with multi-disciplines for future research and applications of induced seismicity monitoring are identified, and it contributes to achieve safe and efficient unconventional (tight) oil and gas resource exploitation.
•Enhanced InSAR stacking with atmospheric correction for geohazard detection.•Atmospheric correction reduces stacking bias due to nonstationary signals.•Efficient for geohazard inventory generation ...and update.
Earth observation technologies have great potential in the investigation, monitoring and assessment of various geohazards. Stacking is an efficient InSAR method for estimating deformation rates and helps in the generation and update of the geohazard inventories. However, it relies on the assumption that the atmospheric statistics are stationary, which does not always hold in large-scale interferograms processing. The nonstationary signal, caused by turbulence and stratification of atmosphere, will bias the deformation estimate and lead to misinterpretations of the geophysical processes. In this paper, we propose an enhanced InSAR stacking method integrated with atmospheric correction. Atmospheric errors in the interferograms are first corrected, and then the mean deformation rate is estimated based on least squares. Applications are conducted in ground subsidence monitoring in the Yellow River Delta as well as landslide detection along the Jinsha River, China, with the deformation results evaluated by spatial structure function, semi-variogram and correlation. Spatial dependence in the subsidence results of the Yellow River Delta decreases from 757 km to 220 km, suggesting that the influence of atmospheric turbulence on deformation is mitigated. Correlation between deformation rate and elevation along the Jinsha River reduces from 0.40 to 0.15, indicating that stratification is suppressed. The proposed method adopts the strategies of simplicity and effectiveness, and the outcomes, which can meet the requirements of geohazards general survey, will be beneficial to rapid geohazard detection.
Traversing the Qinghai–Tibetan Plateau, the Sichuan–Tibet Railway is by far the most difficult railway project in the world. The Qinghai–Tibetan Plateau features the most active crustal dynamics on ...earth, the strongest coupling effects of endogenic and exogenic dynamics, and the environment most sensitive to global climate change. The project area is characterized by extremely cold climate, high elevation and relief, high seismic intensity, high geothermal activity, and high tectonic stress. Consequently, the threat of various disaster risks is ever-present at different stages of the entire life cycle of the Sichuan–Tibet Railway. There is urgent need to systematically study these problems at various levels from the fundamental science to the development of key technologies. This article investigates the different disaster risks recognized during the various stages of construction of the Sichuan–Tibet Railway project, and summarizes the scientific challenges and technical problems faced in relation to disaster risk prevention and control. This work also introduces the scientific deployment and relevant research progress of the Sichuan–Tibet Fund special project initiated by the National Natural Science Foundation of China. Here, we also aim to solve the major fundamental scientific challenges in terms of long-term risk prevention and control during the construction of the Sichuan–Tibet Railway, and lay a theoretical foundation to promote breakthroughs in the bottleneck of key technologies. The scientific challenges addressed in the study of disaster risk associated with the Sichuan–Tibet Railway include the following: The quantitative assessment of the activity of deep-large faults and strong earthquake prediction, the evolution of physical fields in areas of strong tectonic activity, the development mechanisms of tunnel hazards, the slope evolution processes under coupled endogenic and exogenic dynamics in alpine gorges, the impact of climate change on the formation and evolution of surface hazards, and the evolution of extreme wind fields in deep-cut canyons. The technical problems faced in disaster risk prevention and mitigation in relation to the Sichuan–Tibet Railway are as follows: Advanced identification, monitoring, and early warning of geological disasters in mountainous areas with steep and complex terrain; risk analysis, prevention, and control of railway engineering disasters based on their dynamic processes; tunnel engineering hazard monitoring, early warning, risk analysis, prevention, and control technologies; key technologies for emergency response; and the green and resilient railway system and lifecycle risk management. The Sichuan–Tibet Fund special project will include five key research topics: (1) the interior geological structure and dynamic evolution of the eastern plateau; (2) the hazard-inducing mechanisms of coupled internal and external forces in canyons and gullies within plateaus; (3) the cataclysm mechanics of deeply buried long-distance tunnel engineering; (4) risk identification and projection of major disasters affecting the railway; and (5) the integrated management of scientific innovations and super large-scale railway construction. Systematic research is expected to reveal the evolution of earth surface movements and coupled engineering-disturbance related disasters. It will also enable the formation of a comprehensive risk analysis method for major engineering disasters, and promote the development of green, safe, efficient, and resilient engineering disaster risk reduction technologies that will support the disaster risk management during the entire lifecycle of the Sichuan–Tibet Railway.
•Investigated the natural and anthropic disaster risks in different construction stages of the Sichuan–Tibet Railway.•Identified the scientific challenges and technical gaps faced in disaster risk reduction of the Sichuan–Tibet Railway.•Proposed fundamental research and technologies development directions for a safe and resilient Sichuan–Tibet Railway.
•A framework is proposed for the wide area automated detection of active geohazards.•The first inventory of active geohazards (AGs) in the Hexi Corridor is established.•Elevation, temperature and ...precipitation are the primary conditioning factors of AGs.•Faults have more control on very slow-moving landslides than on slow-moving ones.•Dual conditioning factor interaction contributes to a bivariate enhancement of AGs.
With the escalation of global climate change and human activity, geohazards become increasingly frequent which cause severe casualties and property losses to local communities. To alleviate this situation and provide scientific guidance for risk reduction, it is imperative to address some of the basic questions related to geohazards, including: i) how to detect active geohazards (AGs) rapidly and automatically over a wide area; ii) how to determine the region with a high level of hazard activity; iii) what are the primary conditioning factors (CFs) of AGs; and iv) do factors operate independently or are they interconnected. To tackle these issues, we propose a universally applicable framework for wide area automated detection of AGs. The framework is based on multi-source Earth observations which capture surface deformation ranging from millimeters to meters. Our study has focused on the Hexi Corridor (HXC) in Gansu Province, China, covering an area of 210,000 km2 with a length of 1100 km. First, we construct an AGs database for the HXC with high automatic and rapid update capabilities, including a total of 4492 AGs (3652 active landslides and 840 land subsidence areas). Second, using the Geographic Detectors method, we determine the primary CFs including elevation, land surface temperature, and precipitation. We find that faults exert greater control over very slow-moving landslides, but are less effective over slow-moving landslides. Third, we analyzed the interactive effects of dual CFs on geohazard actives. Any interaction effect of dual CFs contributes to the bivariate enhancement of geohazard activity. This study significantly enhances the capabilities of the wide area automated detection of AGs, and provides a crucial dataset for hazard prediction and mitigation along the HXC.
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