This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs)such as schools,colleges,hospitals,and fire stations to improve flood emergency planning in the Sylhet region of...This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs)such as schools,colleges,hospitals,and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs)for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step,flood susceptibility maps were developed using machine learning models(MLMs),including:Levenberg-Marquardt back propagation(LM-BP)neural network and decision trees(DT)and multi-criteria decision making(MCDM)method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC)curve.Mathematical approaches in a geographic information system(GIS)for four well-known LAM problems affecting emergency rescue time are proposed:maximal covering location problem(MCLP),the maximize attendance(MA),p-median problem(PMP),and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed,and that some areas were not adequately served by EECs(i.e.,not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs,and that application of the models could contribute to reducing human casualties,property losses,and improve emergency operation.展开更多
The volume fraction of the solid and liquid phase of debris flows, which evolves simultaneously across terrains, largely determines the dynamic property of debris flows. The entrainment process significantly influence...The volume fraction of the solid and liquid phase of debris flows, which evolves simultaneously across terrains, largely determines the dynamic property of debris flows. The entrainment process significantly influences the amplitude of the volume fraction. In this paper, we present a depth-averaged two-phase debris-flow model describing the simultaneous evolution of the phase velocity and depth, the solid and fluid volume fractions and the bed morphological evolution. The model employs the Mohr–Coulomb plasticity for the solid stress, and the fluid stress is modeled as a Newtonian viscous stress. The interfacial momentum transfer includes viscous drag and buoyancy. A new extended entrainment rate formula that satisfies the boundary momentum jump condition （Iverson and Ouyang, 2015） is presented. In this formula, the basal traction stress is a function of the solid volume fraction and can take advantage of both the Coulomb and velocity-dependent friction models. A finite volume method using Roe’s Riemann approximation is suggested to solve the equations. Three computational cases are conducted and compared with experiments or previous results. The results show that the current computational model and framework are robust and suitable for capturing the characteristics of debris flows.展开更多
Landslide distribution and susceptibility mapping are the fundamental steps for landslide-related hazard and disaster risk management activities, especially in the Himalaya region which has resulted in a great deal of...Landslide distribution and susceptibility mapping are the fundamental steps for landslide-related hazard and disaster risk management activities, especially in the Himalaya region which has resulted in a great deal of death and damage to property. To better understand the landslide condition in the Nepal Himalaya, we carried out an investigation on the landslide distribution and susceptibility using the landslide inventory data and 12 different contributing factors in the Dailekh district, Western Nepal. Based on the evaluation of the frequency distribution of the landslide, the relationship between the landslide and the various contributing factors was determined.Then, the landslide susceptibility was calculated using logistic regression and statistical index methods along with different topographic(slope, aspect, relative relief, plan curvature, altitude, topographic wetness index) and non-topographic factors(distance from river, normalized difference vegetation index(NDVI), distance from road, precipitation, land use and land cover, and geology), and 470(70%) of total 658 landslides. The receiver operating characteristic(ROC) curve analysis using 198(30%) of total landslides showed that the prediction curve rates(area under the curve, AUC) values for two methods(logistic regression and statistical index) were 0.826, and 0.823with success rates of 0.793, and 0.811, respectively. The values of R-Index for the logistic regression and statistical index methods were83.66 and 88.54, respectively, consisting of high susceptible hazard classes. In general, this research concluded that the cohesive and coherent natural interplay of topographic and non-topographic factors strongly affects landslide occurrence, distribution, and susceptibility condition in the Nepal Himalaya region. Furthermore, the reliability of these two methods is verified for landslide susceptibility mapping in Nepal’s central mountain region.展开更多
Englacial and subglacial drainage systems of temperate glaciers have a strong influence on glacier dynamics, glacier-induced floods, glacier-weathering processes, and runoff from glacierized drainage basins. Proglacia...Englacial and subglacial drainage systems of temperate glaciers have a strong influence on glacier dynamics, glacier-induced floods, glacier-weathering processes, and runoff from glacierized drainage basins. Proglacial discharge is partly controlled by the geometry of the glacial drainage network and by the process of producing meltwater. The glacial-drainage system of some alpine glaciers has been characterized using a model based on proglacial discharge analysis. In this paper, we apply cross-correlation analysis to hourly hydro-climatic data collected from China＇s Hailuogou Glacier, a typical temperate glacier in Mt. Gongga, to study the seasonal status changes of the englacial and subglacial drainage systems by discharge-temperature （Q-T） time lag analy-sis. During early ablation season （April-May） of 2003, 2004 and 2005, the change of englacial and subglacial drainage system usually leads several outburst flood events, which are also substantiated by observing the leakage of supraglacial pond and cre-vasses pond water during field works in April, 2008. At the end of ablation season （October-December）, the glacial-drainage net-works become less hydro-efficient. Those events are evidenced by hourly hydro-process near the terminus of Hailuogou Glacier, and the analysis of Q-T time lags also can be a good indicator of those changes. However, more detailed observations or experi-ments, e.g. dye-tracing experiment and recording borehole water level variations, are necessary to describe the evolutionary status and processes of englacial and subglacial drainage systems evolution during ablation season.展开更多
In this paper, a generalized limit equilibrium method of solving the active earth pressure problem behind a retaining wall is proposed.Differing from other limit equilibrium methods, an arbitrary slip surface shape wi...In this paper, a generalized limit equilibrium method of solving the active earth pressure problem behind a retaining wall is proposed.Differing from other limit equilibrium methods, an arbitrary slip surface shape without any assumptions of pre-defined shapes is needed in the current framework, which is verified to find the most probable failure slip surface. Based on the current computational framework, numerical comparisons with experiment, discrete element method and other methods are carried out. In addition, the influences of the inclination of the wall, the soil cohesion, the angle of the internal friction of the soil, the slope inclination of the backfill soil on the critical pressure coefficient of the soil, the point of application of the resultant earth pressure and the shape of the slip surface are also carefully investigated. The results demonstrate that limit equilibrium solution from predefined slip plane assumption, including Coulomb solution, is a special case of current computational framework. It is well illustrated that the current method is feasible to evaluate the characteristics of earth pressure problem.展开更多
Debris flows are typical two-phase flows, which commonly accompany erosion in mountainous areas, and may destroy bridge engineering by scouring. In this study, a physically-based two-phase model is applied for the sim...Debris flows are typical two-phase flows, which commonly accompany erosion in mountainous areas, and may destroy bridge engineering by scouring. In this study, a physically-based two-phase model is applied for the simulation of debris flow scouring of bridge pier. In this model, the shear stress of debris flow on an erodible bed is considered to be a function of the solid shear stress, fluid shear stress, and volume fraction; accordingly, the erosion is incorporated into the two-phase model. Using a highaccuracy computational scheme based on the finite volume method, the model is employed for simulating a dynamic debris flow over an erodible bed. The numerical results are consistent with the experimental data, and verify the feasibility of the two-phase model. Moreover, a simple numerical test is performed to exhibit the fundamental behaviour of debris flow scouring of bridge pier, which shows that the degree of erosion on each side of the pier is higher compared to other areas. The scouring depth is influenced by the variations of solid volume fraction and velocity of debris flow and pier width.展开更多
Bangladesh experiences frequent hydro-climatic disasters such as flooding.These disasters are believed to be associated with land use changes and climate variability.However,identifying the factors that lead to floodi...Bangladesh experiences frequent hydro-climatic disasters such as flooding.These disasters are believed to be associated with land use changes and climate variability.However,identifying the factors that lead to flooding is challenging.This study mapped flood susceptibility in the northeast region of Bangladesh using Bayesian regularization back propagation(BRBP)neural network,classification and regression trees(CART),a statistical model(STM)using the evidence belief function(EBF),and their ensemble models(EMs)for three time periods(2000,2014,and 2017).The accuracy of machine learning algorithms(MLAs),STM,and EMs were assessed by considering the area under the curve—receiver operating characteristic(AUC-ROC).Evaluation of the accuracy levels of the aforementioned algorithms revealed that EM4(BRBP-CART-EBF)outperformed(AUC>90%)standalone and other ensemble models for the three time periods analyzed.Furthermore,this study investigated the relationships among land cover change(LCC),population growth(PG),road density(RD),and relative change of flooding(RCF)areas for the period between 2000 and 2017.The results showed that areas with very high susceptibility to flooding increased by 19.72%between 2000 and 2017,while the PG rate increased by 51.68%over the same period.The Pearson correlation coefficient for RCF and RD was calculated to be 0.496.These findings highlight the significant association between floods and causative factors.The study findings could be valuable to policymakers and resource managers as they can lead to improvements in flood management and reduction in flood damage and risks.展开更多
To investigate the movement mechanism of debris flow, a two-dimensional, two-phase, depthintegrated model is introduced. The model uses Mohr-Coulomb plasticity for the solid rheology, and the fluid stress is modeled a...To investigate the movement mechanism of debris flow, a two-dimensional, two-phase, depthintegrated model is introduced. The model uses Mohr-Coulomb plasticity for the solid rheology, and the fluid stress is modeled as a Newtonian fluid. The interaction between solid and liquid phases, which plays a major role in debris flow movement, is assumed to consist of drag and buoyancy forces. The applicability of drag force formulas is discussed. Considering the complex interaction between debris flow and the bed surface, a combined friction boundary condition is imposed on the bottom, and this is also discussed. To solve the complex model equations, a numerical method with second-order accuracy based on the finite volume method is proposed. Several numerical experiments are performed to verify the feasibilities of model and numerical schemes. Numerical results demonstrate that different solid volume fractions substantially affect debris flow movement.展开更多
This study aimed to develop a physical-based approach for predicting the spatial likelihood of shallow landslides at the regional scale in a transition zone with extreme topography.Shallow landslide susceptibility stu...This study aimed to develop a physical-based approach for predicting the spatial likelihood of shallow landslides at the regional scale in a transition zone with extreme topography.Shallow landslide susceptibility study in an area with diverse vegetation types as well as distinctive geographic factors(such as steep terrain,fractured rocks,and joints)that dominate the occurrence of shallow landslides is challenging.This article presents a novel methodology for comprehensively assessing shallow landslide susceptibility,taking into account both the positive and negative impacts of plants.This includes considering the positive efects of vegetation canopy interception and plant root reinforcement,as well as the negative efects of plant gravity loading and preferential fow of root systems.This approach was applied to simulate the regional-scale shallow landslide susceptibility in the Dadu River Basin,a transition zone with rapidly changing terrain,uplifting from the Sichuan Plain to the Qinghai–Tibet Plateau.The research fndings suggest that:(1)The proposed methodology is efective and capable of assessing shallow landslide susceptibility in the study area;(2)the proposed model performs better than the traditional pseudo-static analysis method(TPSA)model,with 9.93%higher accuracy and 5.59%higher area under the curve;and(3)when the ratio of vegetation weight loads to unstable soil mass weight is high,an increase in vegetation biomass tends to be advantageous for slope stability.The study also mapped the spatial distribution of shallow landslide susceptibility in the study area,which can be used in disaster prevention,mitigation,and risk management.展开更多
1 Introduction The Sendai Framework for Disaster Risk Reduction 2015–2030 shifts the focus from managing disasters to reducing risks.Such a shift requires a better understanding of risk in all its dimensions of envir...1 Introduction The Sendai Framework for Disaster Risk Reduction 2015–2030 shifts the focus from managing disasters to reducing risks.Such a shift requires a better understanding of risk in all its dimensions of environment,hazards,exposure,and vulnerability;a disaster risk governance that展开更多
The widely distributed sediments following an earthquake presents a continuous threat to local residential areas and infrastructure. These materials become more easily mobilized due to reduced rainfall thresholds. Bef...The widely distributed sediments following an earthquake presents a continuous threat to local residential areas and infrastructure. These materials become more easily mobilized due to reduced rainfall thresholds. Before establishing an effective management plan for debris flow hazards, it is crucial to determine the potential reach of these sediments. In this study, a deep learning-based method-Dual Attention Network(DAN)-was developed to predict the runout distance of potential debris flows after the 2022 Luding Earthquake, taking into account the topography and precipitation conditions. Given that the availability of reliable precipitation data remains a challenge, attributable to the scarcity of rain gauge stations and the relatively coarse resolution of satellite-based observations, our approach involved three key steps. First, we employed the DAN model to refine the Global Precipitation Measurement(GPM) data, enhancing its spatial and temporal resolution. This refinement was achieved by leveraging the correlation between precipitation and regional environment factors(REVs) at a seasonal scale. Second, the downscaled GPM underwent calibration using observations from rain gauge stations. Third,mean absolute error(MAE), mean square error(MSE), and root mean square error(RMSE) were employed to evaluate the performance of both the downscaling and calibration processes. Then the calibrated precipitation, catchment area, channel length, average channel gradient, and sediment volume were selected to develop a prediction model based on debris flows following the Wenchuan Earthquake. This model was applied to estimate the runout distance of potential debris flows after the Luding Earthquake. The results show that:(1) The calibrated GPM achieves an average MAE of 1.56 mm, surpassing the MAEs of original GPM(4.25 mm) and downscaled GPM(3.83 mm);(2) The developed prediction model reduces the prediction error by 40 m in comparison to an empirical equation;(3) The potential runout distance of debris flows after the Luding Earthquake reaches 0.77 km when intraday rainfall is 100 mm, while the minimum distance value is only 0.06 km.Overall, the developed model offers a scientific support for decision makers in taking reasonable measurements for loss reduction caused by post-seismic debris flows.展开更多
基金funded by the National Natural Science Foundation of China(Grant Nos.41861134008 and 41671112)the 135 Strategic Program of the Institute of Mountain Hazards and Environment(IMHE),Chinese Academy of Sciences(CAS)(Grant No.SDS-135-1705)。
文摘This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs)such as schools,colleges,hospitals,and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs)for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step,flood susceptibility maps were developed using machine learning models(MLMs),including:Levenberg-Marquardt back propagation(LM-BP)neural network and decision trees(DT)and multi-criteria decision making(MCDM)method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC)curve.Mathematical approaches in a geographic information system(GIS)for four well-known LAM problems affecting emergency rescue time are proposed:maximal covering location problem(MCLP),the maximize attendance(MA),p-median problem(PMP),and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed,and that some areas were not adequately served by EECs(i.e.,not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs,and that application of the models could contribute to reducing human casualties,property losses,and improve emergency operation.
基金Financial support from NSFC(Grant No.41572303,4151001059,41101008)Key Projects in the National Science & Technology Pillar Program(2014BAL05B01)CAS "Light of West China" Program
文摘The volume fraction of the solid and liquid phase of debris flows, which evolves simultaneously across terrains, largely determines the dynamic property of debris flows. The entrainment process significantly influences the amplitude of the volume fraction. In this paper, we present a depth-averaged two-phase debris-flow model describing the simultaneous evolution of the phase velocity and depth, the solid and fluid volume fractions and the bed morphological evolution. The model employs the Mohr–Coulomb plasticity for the solid stress, and the fluid stress is modeled as a Newtonian viscous stress. The interfacial momentum transfer includes viscous drag and buoyancy. A new extended entrainment rate formula that satisfies the boundary momentum jump condition （Iverson and Ouyang, 2015） is presented. In this formula, the basal traction stress is a function of the solid volume fraction and can take advantage of both the Coulomb and velocity-dependent friction models. A finite volume method using Roe’s Riemann approximation is suggested to solve the equations. Three computational cases are conducted and compared with experiments or previous results. The results show that the current computational model and framework are robust and suitable for capturing the characteristics of debris flows.
基金Under the auspices of the CAS Overseas Institutions Platform Project (No. 131C11KYSB20200033)the National Natural Science Foundation of China (No. 42071349)the Sichuan Science and Technology Program (No. 2020JDJQ0003)。
文摘Landslide distribution and susceptibility mapping are the fundamental steps for landslide-related hazard and disaster risk management activities, especially in the Himalaya region which has resulted in a great deal of death and damage to property. To better understand the landslide condition in the Nepal Himalaya, we carried out an investigation on the landslide distribution and susceptibility using the landslide inventory data and 12 different contributing factors in the Dailekh district, Western Nepal. Based on the evaluation of the frequency distribution of the landslide, the relationship between the landslide and the various contributing factors was determined.Then, the landslide susceptibility was calculated using logistic regression and statistical index methods along with different topographic(slope, aspect, relative relief, plan curvature, altitude, topographic wetness index) and non-topographic factors(distance from river, normalized difference vegetation index(NDVI), distance from road, precipitation, land use and land cover, and geology), and 470(70%) of total 658 landslides. The receiver operating characteristic(ROC) curve analysis using 198(30%) of total landslides showed that the prediction curve rates(area under the curve, AUC) values for two methods(logistic regression and statistical index) were 0.826, and 0.823with success rates of 0.793, and 0.811, respectively. The values of R-Index for the logistic regression and statistical index methods were83.66 and 88.54, respectively, consisting of high susceptible hazard classes. In general, this research concluded that the cohesive and coherent natural interplay of topographic and non-topographic factors strongly affects landslide occurrence, distribution, and susceptibility condition in the Nepal Himalaya region. Furthermore, the reliability of these two methods is verified for landslide susceptibility mapping in Nepal’s central mountain region.
基金supported by the National Natural Science Foundation of China (Grant No. 40801030 and 40801025)the Major State Basic Research Development Program of China (973 Program) (2007CB411506)+1 种基金the Innovation Project of Chinese Academy Sciences (Kzcx2-yw-301)the National Basic Work Program of Chinese MST (Glacier Inventory of China Ⅱ, Grant No. 2006FY110200)
文摘Englacial and subglacial drainage systems of temperate glaciers have a strong influence on glacier dynamics, glacier-induced floods, glacier-weathering processes, and runoff from glacierized drainage basins. Proglacial discharge is partly controlled by the geometry of the glacial drainage network and by the process of producing meltwater. The glacial-drainage system of some alpine glaciers has been characterized using a model based on proglacial discharge analysis. In this paper, we apply cross-correlation analysis to hourly hydro-climatic data collected from China＇s Hailuogou Glacier, a typical temperate glacier in Mt. Gongga, to study the seasonal status changes of the englacial and subglacial drainage systems by discharge-temperature （Q-T） time lag analy-sis. During early ablation season （April-May） of 2003, 2004 and 2005, the change of englacial and subglacial drainage system usually leads several outburst flood events, which are also substantiated by observing the leakage of supraglacial pond and cre-vasses pond water during field works in April, 2008. At the end of ablation season （October-December）, the glacial-drainage net-works become less hydro-efficient. Those events are evidenced by hourly hydro-process near the terminus of Hailuogou Glacier, and the analysis of Q-T time lags also can be a good indicator of those changes. However, more detailed observations or experi-ments, e.g. dye-tracing experiment and recording borehole water level variations, are necessary to describe the evolutionary status and processes of englacial and subglacial drainage systems evolution during ablation season.
基金Financial support from the Key Research Program of Chinese Academy of Sciences (Grant No. KZZD-EW-05-01)the NSFC (Grant Nos. 41101008, 41272346)the Youth Talent Team Program of the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Opening Fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (Chengdu University of Technology) (Grant No. SKLGP2011K010)
文摘In this paper, a generalized limit equilibrium method of solving the active earth pressure problem behind a retaining wall is proposed.Differing from other limit equilibrium methods, an arbitrary slip surface shape without any assumptions of pre-defined shapes is needed in the current framework, which is verified to find the most probable failure slip surface. Based on the current computational framework, numerical comparisons with experiment, discrete element method and other methods are carried out. In addition, the influences of the inclination of the wall, the soil cohesion, the angle of the internal friction of the soil, the slope inclination of the backfill soil on the critical pressure coefficient of the soil, the point of application of the resultant earth pressure and the shape of the slip surface are also carefully investigated. The results demonstrate that limit equilibrium solution from predefined slip plane assumption, including Coulomb solution, is a special case of current computational framework. It is well illustrated that the current method is feasible to evaluate the characteristics of earth pressure problem.
基金Financial support from the NSFC-ICIMOD (41661144041)Key Research and Development Program (2017SZ0041)Sichuan Province Science and Technology Support Project (2016SZ0067)
文摘Debris flows are typical two-phase flows, which commonly accompany erosion in mountainous areas, and may destroy bridge engineering by scouring. In this study, a physically-based two-phase model is applied for the simulation of debris flow scouring of bridge pier. In this model, the shear stress of debris flow on an erodible bed is considered to be a function of the solid shear stress, fluid shear stress, and volume fraction; accordingly, the erosion is incorporated into the two-phase model. Using a highaccuracy computational scheme based on the finite volume method, the model is employed for simulating a dynamic debris flow over an erodible bed. The numerical results are consistent with the experimental data, and verify the feasibility of the two-phase model. Moreover, a simple numerical test is performed to exhibit the fundamental behaviour of debris flow scouring of bridge pier, which shows that the degree of erosion on each side of the pier is higher compared to other areas. The scouring depth is influenced by the variations of solid volume fraction and velocity of debris flow and pier width.
基金This work was supported by the National Natural Science Foundation of China(Grant No.41861134008)the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)of China(Grant No.2019QZKK0902)+1 种基金the National Key Research and Development Program of China(Project No.2018YFC1505202)the Key R&D Projects of Sichuan Science and Technology(Grant No.18ZDYF0329).
文摘Bangladesh experiences frequent hydro-climatic disasters such as flooding.These disasters are believed to be associated with land use changes and climate variability.However,identifying the factors that lead to flooding is challenging.This study mapped flood susceptibility in the northeast region of Bangladesh using Bayesian regularization back propagation(BRBP)neural network,classification and regression trees(CART),a statistical model(STM)using the evidence belief function(EBF),and their ensemble models(EMs)for three time periods(2000,2014,and 2017).The accuracy of machine learning algorithms(MLAs),STM,and EMs were assessed by considering the area under the curve—receiver operating characteristic(AUC-ROC).Evaluation of the accuracy levels of the aforementioned algorithms revealed that EM4(BRBP-CART-EBF)outperformed(AUC>90%)standalone and other ensemble models for the three time periods analyzed.Furthermore,this study investigated the relationships among land cover change(LCC),population growth(PG),road density(RD),and relative change of flooding(RCF)areas for the period between 2000 and 2017.The results showed that areas with very high susceptibility to flooding increased by 19.72%between 2000 and 2017,while the PG rate increased by 51.68%over the same period.The Pearson correlation coefficient for RCF and RD was calculated to be 0.496.These findings highlight the significant association between floods and causative factors.The study findings could be valuable to policymakers and resource managers as they can lead to improvements in flood management and reduction in flood damage and risks.
基金Financial support from the NSFC-ICIMOD(41661144041)NSFC(Grant No.41772312)+1 种基金Key Research and Development Program(2017SZ0041)Sichuan Province Science and Technology Support Project(2016SZ0067)
文摘To investigate the movement mechanism of debris flow, a two-dimensional, two-phase, depthintegrated model is introduced. The model uses Mohr-Coulomb plasticity for the solid rheology, and the fluid stress is modeled as a Newtonian fluid. The interaction between solid and liquid phases, which plays a major role in debris flow movement, is assumed to consist of drag and buoyancy forces. The applicability of drag force formulas is discussed. Considering the complex interaction between debris flow and the bed surface, a combined friction boundary condition is imposed on the bottom, and this is also discussed. To solve the complex model equations, a numerical method with second-order accuracy based on the finite volume method is proposed. Several numerical experiments are performed to verify the feasibilities of model and numerical schemes. Numerical results demonstrate that different solid volume fractions substantially affect debris flow movement.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA23090303)the National Natural Science Foundation of China(Grant No.42171085)+1 种基金the Light of West China Program of the Chinese Academy of Sciences(Grant No.xbzg-zdsys-202104)the Key R&D Project of Sichuan Provincial Department of Science and Technology(Grant No.2023YFS0434).
文摘This study aimed to develop a physical-based approach for predicting the spatial likelihood of shallow landslides at the regional scale in a transition zone with extreme topography.Shallow landslide susceptibility study in an area with diverse vegetation types as well as distinctive geographic factors(such as steep terrain,fractured rocks,and joints)that dominate the occurrence of shallow landslides is challenging.This article presents a novel methodology for comprehensively assessing shallow landslide susceptibility,taking into account both the positive and negative impacts of plants.This includes considering the positive efects of vegetation canopy interception and plant root reinforcement,as well as the negative efects of plant gravity loading and preferential fow of root systems.This approach was applied to simulate the regional-scale shallow landslide susceptibility in the Dadu River Basin,a transition zone with rapidly changing terrain,uplifting from the Sichuan Plain to the Qinghai–Tibet Plateau.The research fndings suggest that:(1)The proposed methodology is efective and capable of assessing shallow landslide susceptibility in the study area;(2)the proposed model performs better than the traditional pseudo-static analysis method(TPSA)model,with 9.93%higher accuracy and 5.59%higher area under the curve;and(3)when the ratio of vegetation weight loads to unstable soil mass weight is high,an increase in vegetation biomass tends to be advantageous for slope stability.The study also mapped the spatial distribution of shallow landslide susceptibility in the study area,which can be used in disaster prevention,mitigation,and risk management.
文摘1 Introduction The Sendai Framework for Disaster Risk Reduction 2015–2030 shifts the focus from managing disasters to reducing risks.Such a shift requires a better understanding of risk in all its dimensions of environment,hazards,exposure,and vulnerability;a disaster risk governance that
基金supported by the European Union’s Horizon 2020 research and innovation program Marie Skłodowska-Curie Actions Research and Innovation Staf Exchange(RISE)(Grant No.778360)the National Natural Science Foundation of China(Grant No.U22A20603)+1 种基金the Science and Technology Development Fund(Grant No.001/2024/SKL)the State Key Laboratory of Internet of Things for Smart City(University of Macao)(Ref.No.SKL-IoTSC(UM)-2024-2026/ORP/GA09/2023).
文摘The widely distributed sediments following an earthquake presents a continuous threat to local residential areas and infrastructure. These materials become more easily mobilized due to reduced rainfall thresholds. Before establishing an effective management plan for debris flow hazards, it is crucial to determine the potential reach of these sediments. In this study, a deep learning-based method-Dual Attention Network(DAN)-was developed to predict the runout distance of potential debris flows after the 2022 Luding Earthquake, taking into account the topography and precipitation conditions. Given that the availability of reliable precipitation data remains a challenge, attributable to the scarcity of rain gauge stations and the relatively coarse resolution of satellite-based observations, our approach involved three key steps. First, we employed the DAN model to refine the Global Precipitation Measurement(GPM) data, enhancing its spatial and temporal resolution. This refinement was achieved by leveraging the correlation between precipitation and regional environment factors(REVs) at a seasonal scale. Second, the downscaled GPM underwent calibration using observations from rain gauge stations. Third,mean absolute error(MAE), mean square error(MSE), and root mean square error(RMSE) were employed to evaluate the performance of both the downscaling and calibration processes. Then the calibrated precipitation, catchment area, channel length, average channel gradient, and sediment volume were selected to develop a prediction model based on debris flows following the Wenchuan Earthquake. This model was applied to estimate the runout distance of potential debris flows after the Luding Earthquake. The results show that:(1) The calibrated GPM achieves an average MAE of 1.56 mm, surpassing the MAEs of original GPM(4.25 mm) and downscaled GPM(3.83 mm);(2) The developed prediction model reduces the prediction error by 40 m in comparison to an empirical equation;(3) The potential runout distance of debris flows after the Luding Earthquake reaches 0.77 km when intraday rainfall is 100 mm, while the minimum distance value is only 0.06 km.Overall, the developed model offers a scientific support for decision makers in taking reasonable measurements for loss reduction caused by post-seismic debris flows.
