Rigid barrier deflectors can effectively prevent overspilling landslides,and can satisfy disaster prevention requirements.However,the mechanisms of interaction between natural granular flow and rigid barrier deflector...Rigid barrier deflectors can effectively prevent overspilling landslides,and can satisfy disaster prevention requirements.However,the mechanisms of interaction between natural granular flow and rigid barrier deflectors require further investigation.To date,few studies have investigated the impact of deflectors on controlling viscous debris flows for geological disaster prevention.To investigate the effect of rigid barrier deflectors on impact mechanisms,a numerical model using the smoothed particle hydrodynamics(SPH)method with the Herschel–Bulkley model is proposed to simulate the interaction between natural viscous flow and single/dual barriers with and without deflectors.This model was validated using laboratory flume test data from the literature.Then,the model was used to investigate the influence of the deflector angle and multi-barrier arrangements.The optimal configuration of multi-barriers was analyzed with consideration to the barrier height and distance between the barriers,because these metrics have a significant impact on the viscous flow pile-up,run-up,and overflow mechanisms.The investigation considered the energy dissipation process,retention efficiency,and dead-zone formation.Compared with bare barriers with similar geometric characteristics and spatial distribution,rigid barriers with deflectors exhibit superior effectiveness in preventing the overflow and overspilling of viscous debris flow.Recommendations for the rational design of deflectors and the optimal arrangement of multi-barriers are provided to mitigate geological disasters.展开更多
The selection of important factors in machine learning-based susceptibility assessments is crucial to obtain reliable susceptibility results.In this study,metaheuristic optimization and feature selection techniques we...The selection of important factors in machine learning-based susceptibility assessments is crucial to obtain reliable susceptibility results.In this study,metaheuristic optimization and feature selection techniques were applied to identify the most important input parameters for mapping debris flow susceptibility in the southern mountain area of Chengde City in Hebei Province,China,by using machine learning algorithms.In total,133 historical debris flow records and 16 related factors were selected.The support vector machine(SVM)was first used as the base classifier,and then a hybrid model was introduced by a two-step process.First,the particle swarm optimization(PSO)algorithm was employed to select the SVM model hyperparameters.Second,two feature selection algorithms,namely principal component analysis(PCA)and PSO,were integrated into the PSO-based SVM model,which generated the PCA-PSO-SVM and FS-PSO-SVM models,respectively.Three statistical metrics(accuracy,recall,and specificity)and the area under the receiver operating characteristic curve(AUC)were employed to evaluate and validate the performance of the models.The results indicated that the feature selection-based models exhibited the best performance,followed by the PSO-based SVM and SVM models.Moreover,the performance of the FS-PSO-SVM model was better than that of the PCA-PSO-SVM model,showing the highest AUC,accuracy,recall,and specificity values in both the training and testing processes.It was found that the selection of optimal features is crucial to improving the reliability of debris flow susceptibility assessment results.Moreover,the PSO algorithm was found to be not only an effective tool for hyperparameter optimization,but also a useful feature selection algorithm to improve prediction accuracies of debris flow susceptibility by using machine learning algorithms.The high and very high debris flow susceptibility zone appropriately covers 38.01%of the study area,where debris flow may occur under intensive human activities and heavy rainfall events.展开更多
Machine learning(ML)-based prediction models for mapping hazard(e.g.,landslide and debris flow)susceptibility have been widely developed in recent research.However,in some specific areas,ML models have limited applica...Machine learning(ML)-based prediction models for mapping hazard(e.g.,landslide and debris flow)susceptibility have been widely developed in recent research.However,in some specific areas,ML models have limited application because of the uncertainties in identifying negative samples.The Parlung Tsangpo Basin exemplifies a region prone to recurrent glacial debris flows(GDFs)and is characterized by a prominent landform featuring deep gullies.Considering the limitations of the ML model,we developed and compared two combined statistical models(FA-WE and FA-IC)based on factor analysis(FA),weight of evidence(WE),and the information content(IC)method.The final GDF susceptibility maps were generated by selecting 8 most important static factors and considering the influence of precipitation.The results show that the FA-IC model has the best performance.The areas with a very high susceptibility to GDFs are primarily located in the narrow valley section upstream,on both sides of the valley in the middle and downstream of the Parlung Tsangpo River,and in the narrow valley section of each tributary.These areas encompass 86 gullies and are characterized as"narrow and steep".展开更多
Knowledge of glacier changes and associated hazards is of great importance for the safety consideration of the population and infrastructure in the mountainous regions of Upper Indus Basin(UIB).In this study,we assess...Knowledge of glacier changes and associated hazards is of great importance for the safety consideration of the population and infrastructure in the mountainous regions of Upper Indus Basin(UIB).In this study,we assessed the variations in glacier velocity,glacier surface elevation change,meteorological conditions,and permafrost distribution in Badswat and Shishkat catchments located in UIB to access the potential impact on the occurrence of debris flow in both catchments.We find that the glacier surface velocity increased during the debris flow event in the Badswat catchment and the mean daily temperature was 3.7℃to 3.9℃higher in most of the locations.The enhanced glacier surface elevation lowering period coincide with the rise in temperature during spring and autumn months between 2015 to 2019 in Badswat catchment.The source region of debris flow falls within the lower boundary of permafrost occurrence zone and lies below the 0℃isotherm during late spring and summer months.In Shishkat catchment the 0℃isotherm reaches above the debris flow source area during August and the glacier do not show any significant variations in velocity and surface elevation change.The debris flow source area is adjacent to the slow-moving rock glacier in Shishkat catchment while in Badswat catchment the debris flow initiated from the former glacier moraine.Both catchments are largely glacierized and thus sensitive to changes in climatic conditions and changes in the cryosphere response possess significant threats to the population downstream.Continuous monitoring of cryosphere-climate change in the region can contribute toward the improvement of disaster risk reduction and mitigation policies.展开更多
The debris flow dam is a common type of barrier dams,which shows significant differences from other types of barrier dam such as landslide dam,moraine dam in their formation processes,dam body shapes,and internal comp...The debris flow dam is a common type of barrier dams,which shows significant differences from other types of barrier dam such as landslide dam,moraine dam in their formation processes,dam body shapes,and internal compositions.The basic breaching parameters such as flood peak discharge are vital indicators of risk assessment.In this study,we elucidated the failure process of the debris flow dam through the flume experiment,and built the calculation equation of the breaching parameters by selecting critical factors.The result shows that the overtopping failure process of the debris flow dam is capable of forming significantly retrogressive scarps,and the failure process experiences three stages,the formation of the retrogressive scarp,the erosion of the retrogressive scarp,and the decline of the retrogressive scarp.Five factors used for establishing the calculation equations for peak discharge(Qp),final width(Wb)of the breach,and duration(T)of the debris flow dam failure are dam height(h),reservoir capacity(V),the fine grain content(P0.075)of the soil,the nonuniformity coefficient(Cu)of the soil,and the upper limit grain size(D90)of the soil,respectively.In the three equations,the correlation coefficients between Qp,Wb,T and the five factors were 0.86,0.70,0.63,respectively.The equations still need to be modified and verified in actual cases.展开更多
The use of open-type check dams in mountainous areas has become common practice in order to mitigate the effects of debris flow and extend the service life of engineering structures.The beam dam,a common debris flow c...The use of open-type check dams in mountainous areas has become common practice in order to mitigate the effects of debris flow and extend the service life of engineering structures.The beam dam,a common debris flow control system,has received less attention in research on the impact process of debris flow and check dams compared to solid check dams.Additionally,the estimation of impact pressure in debris flow primarily considers debris flow characteristics,without taking into account the influence of geometric characteristics of the transmission structure.To better understand the impact process of debris flow on beam dams,a series of small-scale debris flow impact tests were conducted in a model flume.Key parameters,including velocity,depth,and impact pressure,were measured.The results show that the maximum impact pressure of debris flow is affected by both the characteristics of the debris flow and the relative opening size of the beam dam.Due to flow and edge occlusion in the middle of the beam dam,the discharge of debris flow is enhanced,resulting in a longer impact process and higher maximum impact pressure.Based on these findings,a calculation model of the maximum impact pressure of debris flow at the midpoint of the middle beam is proposed,which can be used to estimate the impact of debris flow on the discharge part of the beam dam.展开更多
To accurately predict impact loads can ensure the safe operation of debris flow control projects.The instantaneous impact process is usually considered in the calculation of the debris flow impact force;however,the re...To accurately predict impact loads can ensure the safe operation of debris flow control projects.The instantaneous impact process is usually considered in the calculation of the debris flow impact force;however,the redistribution of an impact load after structural regulation is unclear.In this study we deduced the theoretical calculation of a debris flow impact on a double-row slit dam,and carried out a verification experiment on the debris flow impact.The calculation model considers the influence of the debris flow properties,dam arrangement and pile material.The results show that the impact force of the debris flow is obviously affected by the bulk density.When the bulk density is 21 kg/m^(3),the maximum impact force on the pile dam is 1.15 times that when the bulk density is 15 kg/m^(3),but the time it takes for the debris flow to pass through the dam body is reduced by 60%.The larger the relative pile spacing,the more sufficient the flow space and the lower the maximum impact force.The maximum impact force of relative pile spacing of 0.8 is 12%less than that of elative pile spacing of 0.5.The horizontal distribution of the impact force in the mud depth range is parabolic.The maximum impact force on the centre pier is 1.3 times that of a side pier,and the maximum impact force on the dam body appears at the top of the mud depth range.From the vertical distribution of the impact force,the maximum impact force at the highest mud mark is approximately 70%of that of the bottom.With the increase in the relative pile spacing,the longitudinal maximum impact force distribution first decreases and then increases.展开更多
Loose deposits, rainfall and topography are three key factors that triggering debris flows.However, few studies have investigated the effects of loose deposits on the whole debris flow process.On June 28, 2012, a cata...Loose deposits, rainfall and topography are three key factors that triggering debris flows.However, few studies have investigated the effects of loose deposits on the whole debris flow process.On June 28, 2012, a catastrophic debris flow occurred in the Aizi Valley, resulting in 40 deaths.The Aizi Valley is located in the Lower Jinsha River,southwestern Sichuan Province, China. The Aizi Valley debris flow has been selected as a case for addressing loose deposits effects on the whole debris flow process through remote sensing, field investigation and field experiments. Remote sensing interpretation and laboratory experiments were used to obtain the distribution and characteristics of the loose deposits, respectively. A field experiment was conducted to explore the mechanics of slope debris flows, and another field investigation was conducted to obtain the processes of debris flow formation, movement and amplification. The results showed that loose deposits preparation, slope debris flow initiation,gully debris flow confluence and valley debris flow amplification were dominated by the loose deposits.Antecedent droughts and earthquake activities may have increased the potential for loose soil sources in the Aizi Valley, which laid the foundation for debris flow formation. Slope debris flow initiated under rainfall, and the increase in the water content as well as the pore water pressure of the loose deposits were the key factors affecting slope failure. The nine gully debris flows converged in the valley, and the peak discharge was amplified 3.3 times due to a blockage and outburst caused by a large boulder. The results may help in predicting and assessing regional debris flows in dry-hot and seismic-prone areas based on loose deposits, especially considering large boulders.展开更多
The Digital Elevation Model(DEM)data of debris flow prevention engineering are the boundary of a debris flow prevention simulation,which provides accurate and reliable DEM data and is a key consideration in debris flo...The Digital Elevation Model(DEM)data of debris flow prevention engineering are the boundary of a debris flow prevention simulation,which provides accurate and reliable DEM data and is a key consideration in debris flow prevention simulations.Thus,this paper proposes a multi-source data fusion method.First,we constructed 3D models of debris flow prevention using virtual reality technology according to the relevant specifications.The 3D spatial data generated by 3D modeling were converted into DEM data for debris flow prevention engineering.Then,the accuracy and applicability of the DEM data were verified by the error analysis testing and fusion testing of the debris flow prevention simulation.Finally,we propose the Levels of Detail algorithm based on the quadtree structure to realize the visualization of a large-scale disaster prevention scene.The test results reveal that the data fusion method controlled the error rate of the DEM data of the debris flow prevention engineering within an allowable range and generated 3D volume data(obj format)to compensate for the deficiency of the DEM data whereby the 3D internal entity space is not expressed.Additionally,the levels of detailed method can dispatch the data of a large-scale debris flow hazard scene in real time to ensure a realistic 3D visualization.In summary,the proposed methods can be applied to the planning of debris flow prevention engineering and to the simulation of the debris flow prevention process.展开更多
Debris flows are rapid mass movements with a mixture of rock,soil and water.High-intensity rainfall events have triggered multiple debris flows around the globe,making it an important concern from the disaster managem...Debris flows are rapid mass movements with a mixture of rock,soil and water.High-intensity rainfall events have triggered multiple debris flows around the globe,making it an important concern from the disaster management perspective.This study presents a numerical model called debris flow simulation 2D(DFS 2D)and applicability of the proposed model is investigated through the values of the model parameters used for the reproduction of an occurred debris flow at Yindongzi gully in China on 13 August 2010.The model can be used to simulate debris flows using three different rheologies and has a userfriendly interface for providing the inputs.Using DFS 2D,flow parameters can be estimated with respect to space and time.The values of the flow resistance parameters of model,dry-Coulomb and turbulent friction,were calibrated through the back analysis and the values obtained are 0.1 and 1000 m/s^(2),respectively.Two new methods of calibration are proposed in this study,considering the crosssectional area of flow and topographical changes induced by the debris flow.The proposed methods of calibration provide an effective solution to the cumulative errors induced by coarse-resolution digital elevation models(DEMs)in numerical modelling of debris flows.The statistical indices such as Willmott's index of agreement,mean-absolute-error,and normalized-root-mean-square-error of the calibrated model are 0.5,1.02 and 1.44,respectively.The comparison between simulated and observed values of topographic changes indicates that DFS 2D provides satisfactory results and can be used for dynamic modelling of debris flows.展开更多
This research describes a quantitative,rapid,and low-cost methodology for debris flow susceptibility evaluation at the basin scale using open-access data and geodatabases.The proposed approach can aid decision makers ...This research describes a quantitative,rapid,and low-cost methodology for debris flow susceptibility evaluation at the basin scale using open-access data and geodatabases.The proposed approach can aid decision makers in land management and territorial planning,by first screening for areas with a higher debris flow susceptibility.Five environmental predisposing factors,namely,bedrock lithology,fracture network,quaternary deposits,slope inclination,and hydrographic network,were selected as independent parameters and their mutual interactions were described and quantified using the Rock Engineering System(RES)methodology.For each parameter,specific indexes were proposed,aiming to provide a final synthetic and representative index of debris flow susceptibility at the basin scale.The methodology was tested in four basins located in the Upper Susa Valley(NW Italian Alps)where debris flow events are the predominant natural hazard.The proposed matrix can represent a useful standardized tool,universally applicable,since it is independent of type and characteristic of the basin.展开更多
On August 7^(th),2010,Sanyanyu and Luojiayu debris flows triggered by a heavy rain have lashed Zhouqu City around midnight,leading to catastrophic destruction which killed 1765 people and resulted in enormous economic...On August 7^(th),2010,Sanyanyu and Luojiayu debris flows triggered by a heavy rain have lashed Zhouqu City around midnight,leading to catastrophic destruction which killed 1765 people and resulted in enormous economic loss.The ZHQ Seismic Station is located approximately 170 m west of the outlet of the Sanyanyu Gully.The seismometer deployed at the seismic station started recording seismic signals of ever-enlarging amplitude around 10 minutes before the debris flow rushed out of the Sanyanyu Gully,showing ever approaching seismic source,i.e.the debris flow.In this study,we analyze this seismic event and propose an inversion algorithm to estimate the velocity of the debris flow by searching the best-fitting pairs of envelopes in the synthetic seismograms and the corresponding field seismic records in a least-square sense.Inversion results reveal that,before rushing out of the outlet,the average velocity of the debris flow gradually increased from 6.2 m/s to 7.1 m/s and finally reached 15 m/s at approximately 0.5 km above the outlet and kept this value since then.Obviously,the ever-increasing velocity of the debris flow is the key factor for the following disasters.Compared with other studies,our approach can provide the velocity distribution for the debris flow before its outbreak;Besides,it has the potential to provide technological support for a better understanding of the disaster process of a debris flow.展开更多
Turkey is highly prone to landslides because of the geological and geographic location.The study area,which is located in a tectonically active region,has been significantly affected by mass movements.Flow type landsl...Turkey is highly prone to landslides because of the geological and geographic location.The study area,which is located in a tectonically active region,has been significantly affected by mass movements.Flow type landslides are frequently observed due to this location.This study aims at determining the source area and propagation of debris flows in the study area.We used the heuristic method to extract source areas of debris flow,and then used receiver operating characteristic(ROC)curve analysis to assess the performance of the method,and finally calculated the Area under curve(AUC)values being 83.64%and 80.39%for the success rate and prediction rate,respectively.We calculated potential propagation area and runout distance with Flow-R software.In conclusion,the obtained results(susceptibility map,propagation and runout distance)are very important for decisionmakers at the region located on an active fault zone,which is highly prone to natural disasters.The outputs of this study could be used in site selection studies,designing erosion prevention systems and protecting existing human-made structures.展开更多
The quality of debris flow susceptibility mapping varies with sampling strategies. This paper aims at comparing three sampling strategies and determining the optimal one to sample the debris flow watersheds. The three...The quality of debris flow susceptibility mapping varies with sampling strategies. This paper aims at comparing three sampling strategies and determining the optimal one to sample the debris flow watersheds. The three sampling strategies studied were the centroid of the scarp area(COSA), the centroid of the flowing area(COFA), and the centroid of the accumulation area(COAA) of debris flow watersheds. An inventory consisting of 150 debris flow watersheds and 12 conditioning factors were prepared for research. Firstly, the information gain ratio(IGR) method was used to analyze the predictive ability of the conditioning factors. Subsequently, 12 conditioning factors were involved in the modeling of artificial neural network(ANN), random forest(RF) and support vector machine(SVM). Then, the receiver operating characteristic curves(ROC) and the area under curves(AUC) were used to evaluate the model performance. Finally, a scoring system was used to score the quality of the debris flow susceptibility maps. Samples obtained from the accumulation area have the strongest predictive ability and can make the models achieve the best performance. The AUC values corresponding to the best model performance on the validation dataset were 0.861, 0.804 and 0.856 for SVM, ANN and RF respectively. The sampling strategy of the centroid of the scarp area is optimal with the highest quality of debris flow susceptibility maps having scores of 373470, 393241 and 362485 for SVM, ANN and RF respectively.展开更多
An increase in extreme precipitation events due to future climate change will have a decisive influence on the formation of debris flows in earthquake-stricken areas. This paper aimed to describe the possible impacts ...An increase in extreme precipitation events due to future climate change will have a decisive influence on the formation of debris flows in earthquake-stricken areas. This paper aimed to describe the possible impacts of future climate change on debris flow hazards in the Upper Minjiang River basin in Northwest Sichuan of China, which was severely affected by the 2008 Wenchuan earthquake. The study area was divided into 1285 catchments, which were used as the basic assessment units for debris flow hazards. Based on the current understanding of the causes of debris flows, a binary logistic regression model was used to screen key factors based on local geologic, geomorphologic, soil,vegetation, and meteorological and climatic conditions. We used the weighted summation method to obtain a composite index for debris flow hazards, based on two weight allocation methods: Relative Degree Analysis and rough set theory. Our results showed that the assessment model using the rough set theory resulted in better accuracy. According to the bias corrected and downscaled daily climate model data, future annual precipitation(2030-2059) in the study area are expected to decrease, with an increasing number of heavy rainfall events. Under future climate change, areas with a high-level of debris flow hazard will be even more dangerous, and 5.9% more of the study area was categorized as having a high-level hazard. Future climate change will cause an increase in debris flow hazard levels for 128 catchments, accounting for 10.5% of the total area. In the coming few decades, attention should be paid not only to traditional areas with high-level of debris flow hazards, but also to those areas with an increased hazard level to improve their resilience to debris flow disasters.展开更多
The estimation of the value on the engineering project in tourist towns is usually very challenging and controversial. In this study, an attempt has been made to evaluate the economic value of the debris flow control ...The estimation of the value on the engineering project in tourist towns is usually very challenging and controversial. In this study, an attempt has been made to evaluate the economic value of the debris flow control engineering in tourist towns by integrating both welfare and disaster economics. The total value of debris flow prevention and control engineering in tourist towns(VDFE) includes investment cost(IC), disaster mitigation benefit(DMB), and loss of brand value(LBV). Here DMB is assessed by the cost-benefit method. The LBV is estimated by incorporating brand equity and costbenefit methods. The engineering for debris flow control in the Hongchun Gully of southwest China was built to protect Yingxiu tourist town and was assessed as an example. The IC for the engineering is180 million RMB, however, the VDFE reaches as high as 3401 million RMB, of which the LBV is 169 million RMB, and the input-output ratio is 1:18. Thus, the LBV cannot be neglected in case of VDFE estimation process. The more developed the tourism in one town or city is, the greater the LBV and the higher the VDFE are.展开更多
Glacial debris flows(GDFs) often occur in alpine regions that are subject to rapid climate change, and pose a serious threat to road systems. However, the ways that climate change impacts GDF risks along road systems ...Glacial debris flows(GDFs) often occur in alpine regions that are subject to rapid climate change, and pose a serious threat to road systems. However, the ways that climate change impacts GDF risks along road systems remain poorly understood. Aierkuran Gully, located in eastern Pamir along Karakoram Highway(KKH), is a hotspot for GDF activity and climate change, and was thus selected to investigate the GDF risk to road systems under climate change conditions. Reg CM4.6 climate data for northwestern China were selected as climate projections during baseline(2011–2020) and future periods(2031–2040) under the Representative Concentration Pathway(RCP) 8.5. To reflect the coupling effect of rainfall and melt water that triggers GDF, a glacial hydrological model DETIM that considers both factors was applied to calculate the peak debris flow discharge. A FLO-2D model was calibrated based on high-quality data collected from a detailed field investigation and historical debris flow event. The FLO-2D model was used to simulate the debris flow depth and velocity during baseline and future periods under RCP8.5. The debris flow hazard was analyzed by integrating the maximum flow depth and momentum. Road structure vulnerability was further determined based on the economic value and susceptibility of hazard-affected objects. The GDF risk along KKH was assessed based on the GDF hazard and vulnerability analysis. Our results show that climate change would lead to amplified peak debris flow discharge, trigger highermagnitude GDF, and induce more severe damage and threats to the road system. Compared with the baseline period, the debris flow damage risk for culverts and bridges would increase and the areas that inundate the road and pavement would expand. Our findings provide valuable insights for the development of mitigation strategies to adapt road systems to climate change, especially in alpine regions with highly active GDFs.展开更多
At present,most researches on the critical rainfall threshold of debris flow initiation use a linear model obtained through regression.With relatively weak fault tolerance,this method not only ignores nonlinear effect...At present,most researches on the critical rainfall threshold of debris flow initiation use a linear model obtained through regression.With relatively weak fault tolerance,this method not only ignores nonlinear effects but also is susceptible to singular noise samples,which makes it difficult to characterize the true quantization relationship of the rainfall threshold.Besides,the early warning threshold determined by statistical parameters is susceptible to negative samples(samples where no debris flow has occurred),which leads to uncertainty in the reliability of the early warning results by the regression curve.To overcome the above limitations,this study develops a data-driven multiobjective evolutionary optimization method that combines an artificial neural network(ANN)and a multiobjective evolutionary optimization implemented by particle swarm optimization(PSO).Firstly,the Pareto optimality method is used to represent the nonlinear and conflicting critical thresholds for the rainfall intensity I and the rainfall duration D.An ANN is used to construct a dual-target(dual-task)predictive surrogate model,and then a PSO-based multiobjective evolutionary optimization algorithm is applied to train the ANN and stochastically search the trained ANN for obtaining the Pareto front of the I-D surrogate prediction model,which is intended to overcome the limitations of the existing linear regression-based threshold methods.Finally,a double early warning curve model that can effectively control the false alarm rate and negative alarm rate of hazard warnings are proposed based on the decision space and target space maps.This study provides theoretical guidance for the early warning and forecasting of debris flows and has strong applicability.展开更多
Based on two-phase flow theory and shallow water flow assumption,a mathematical model is applied to simulate debris flow.The model considers a two-phase mixture of sediments and water fluid.Assuming that the sediments...Based on two-phase flow theory and shallow water flow assumption,a mathematical model is applied to simulate debris flow.The model considers a two-phase mixture of sediments and water fluid.Assuming that the sediments and the water fluid move downstream with the same velocity,the flow of the mixture is described using a two dimensional depth averaged model with a unique 2-D momentum equation and two mass balance e- quations for the mixture and the sediments,respectively.The finite volume method is used f...展开更多
Pore water pressure and water content are important indicators to both deposition and consolidation of debris flows, enabling a direct assessment of consolidation degree. This article gained a more comprehensive under...Pore water pressure and water content are important indicators to both deposition and consolidation of debris flows, enabling a direct assessment of consolidation degree. This article gained a more comprehensive understanding about the entire consolidation process and focused on exploring pore water pressure and volumetric water content variations of the deposit body during natural consolidation under different conditions taking the viscous debris flow mass as a study subject and by flume experiments. The results indicate that, as the color of the debris changed from initial dark green to grayish-white color, the initial deposit thickness declined by 3% and 2.8% over a permeable and impermeable sand bed, respectively. A positive correlation was observed between pore water pressure and depth in the deposit for both scenarios, with deeper depths being related to greater pore water pressure. For the permeable environment, the average dissipation rate of pore water pressure measured at depths of 0.10 m and 0.05 m were 0.0172 Pa/d and 0.0144 Pa/d, respectively, showing a positivechanging trend with increasing depth. Under impermeable conditions, the average dissipation rates at different depths were similar, while the volumetric water content in the deposit had a positive correlation with depth. The reduction of water content in the deposit accelerated with depth under impermeable sand bed boundary conditions, but was not considerably correlated with depth under permeable sand bed boundary conditions. However, the amount of discharged water from the deposit was greater and consolidation occurred faster in permeable conditions. This indicates that the permeability of the boundary sand bed has a significant impact on the progress of consolidation. This research demonstrates that pore water and pressure dissipations are present during the entire viscous debris consolidation process. Contrasting with dilute flows, pore pressure dissipation in viscous flows cannot be completed in a matter of minutes or even hours, requiring longer completion time — 3 to 5 days and even more. Additionally, the dissipation of the pore water pressure lagged the reduction of the water content. During the experiment, the dissipation rate fluctuated substantially, indicating a close relationship betweenthe dissipation process and the physical properties of broadly graded soils.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42120104008 and 42207198).
文摘Rigid barrier deflectors can effectively prevent overspilling landslides,and can satisfy disaster prevention requirements.However,the mechanisms of interaction between natural granular flow and rigid barrier deflectors require further investigation.To date,few studies have investigated the impact of deflectors on controlling viscous debris flows for geological disaster prevention.To investigate the effect of rigid barrier deflectors on impact mechanisms,a numerical model using the smoothed particle hydrodynamics(SPH)method with the Herschel–Bulkley model is proposed to simulate the interaction between natural viscous flow and single/dual barriers with and without deflectors.This model was validated using laboratory flume test data from the literature.Then,the model was used to investigate the influence of the deflector angle and multi-barrier arrangements.The optimal configuration of multi-barriers was analyzed with consideration to the barrier height and distance between the barriers,because these metrics have a significant impact on the viscous flow pile-up,run-up,and overflow mechanisms.The investigation considered the energy dissipation process,retention efficiency,and dead-zone formation.Compared with bare barriers with similar geometric characteristics and spatial distribution,rigid barriers with deflectors exhibit superior effectiveness in preventing the overflow and overspilling of viscous debris flow.Recommendations for the rational design of deflectors and the optimal arrangement of multi-barriers are provided to mitigate geological disasters.
基金supported by the Second Tibetan Plateau Scientific Expedition and Research Program(Grant no.2019QZKK0904)Natural Science Foundation of Hebei Province(Grant no.D2022403032)S&T Program of Hebei(Grant no.E2021403001).
文摘The selection of important factors in machine learning-based susceptibility assessments is crucial to obtain reliable susceptibility results.In this study,metaheuristic optimization and feature selection techniques were applied to identify the most important input parameters for mapping debris flow susceptibility in the southern mountain area of Chengde City in Hebei Province,China,by using machine learning algorithms.In total,133 historical debris flow records and 16 related factors were selected.The support vector machine(SVM)was first used as the base classifier,and then a hybrid model was introduced by a two-step process.First,the particle swarm optimization(PSO)algorithm was employed to select the SVM model hyperparameters.Second,two feature selection algorithms,namely principal component analysis(PCA)and PSO,were integrated into the PSO-based SVM model,which generated the PCA-PSO-SVM and FS-PSO-SVM models,respectively.Three statistical metrics(accuracy,recall,and specificity)and the area under the receiver operating characteristic curve(AUC)were employed to evaluate and validate the performance of the models.The results indicated that the feature selection-based models exhibited the best performance,followed by the PSO-based SVM and SVM models.Moreover,the performance of the FS-PSO-SVM model was better than that of the PCA-PSO-SVM model,showing the highest AUC,accuracy,recall,and specificity values in both the training and testing processes.It was found that the selection of optimal features is crucial to improving the reliability of debris flow susceptibility assessment results.Moreover,the PSO algorithm was found to be not only an effective tool for hyperparameter optimization,but also a useful feature selection algorithm to improve prediction accuracies of debris flow susceptibility by using machine learning algorithms.The high and very high debris flow susceptibility zone appropriately covers 38.01%of the study area,where debris flow may occur under intensive human activities and heavy rainfall events.
基金funded by the National Natural Science Foundation of China(Grant Nos.42377170).
文摘Machine learning(ML)-based prediction models for mapping hazard(e.g.,landslide and debris flow)susceptibility have been widely developed in recent research.However,in some specific areas,ML models have limited application because of the uncertainties in identifying negative samples.The Parlung Tsangpo Basin exemplifies a region prone to recurrent glacial debris flows(GDFs)and is characterized by a prominent landform featuring deep gullies.Considering the limitations of the ML model,we developed and compared two combined statistical models(FA-WE and FA-IC)based on factor analysis(FA),weight of evidence(WE),and the information content(IC)method.The final GDF susceptibility maps were generated by selecting 8 most important static factors and considering the influence of precipitation.The results show that the FA-IC model has the best performance.The areas with a very high susceptibility to GDFs are primarily located in the narrow valley section upstream,on both sides of the valley in the middle and downstream of the Parlung Tsangpo River,and in the narrow valley section of each tributary.These areas encompass 86 gullies and are characterized as"narrow and steep".
基金part of a Master research project supported by the Alliance of International Science Organizations(ANSO)supported by the Second Tibetan Plateau Scientific Expedition and Research Program(STEP,Grant Nos.2019QZKK0902 and 2019QZKK0903)+2 种基金the National Natural Science Foundation of China(Grant No.42071017)the CAS President’s International Fellowship Initiative(Grant No.2021VEA0005)the Science and Technology Research Program of Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(No.IMHE-ZDRW-03)。
文摘Knowledge of glacier changes and associated hazards is of great importance for the safety consideration of the population and infrastructure in the mountainous regions of Upper Indus Basin(UIB).In this study,we assessed the variations in glacier velocity,glacier surface elevation change,meteorological conditions,and permafrost distribution in Badswat and Shishkat catchments located in UIB to access the potential impact on the occurrence of debris flow in both catchments.We find that the glacier surface velocity increased during the debris flow event in the Badswat catchment and the mean daily temperature was 3.7℃to 3.9℃higher in most of the locations.The enhanced glacier surface elevation lowering period coincide with the rise in temperature during spring and autumn months between 2015 to 2019 in Badswat catchment.The source region of debris flow falls within the lower boundary of permafrost occurrence zone and lies below the 0℃isotherm during late spring and summer months.In Shishkat catchment the 0℃isotherm reaches above the debris flow source area during August and the glacier do not show any significant variations in velocity and surface elevation change.The debris flow source area is adjacent to the slow-moving rock glacier in Shishkat catchment while in Badswat catchment the debris flow initiated from the former glacier moraine.Both catchments are largely glacierized and thus sensitive to changes in climatic conditions and changes in the cryosphere response possess significant threats to the population downstream.Continuous monitoring of cryosphere-climate change in the region can contribute toward the improvement of disaster risk reduction and mitigation policies.
基金supported by the National Natural Science Foundation of China(Grant Nos.U20A20112,U19A2049)Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(Grant No.2019QZKK0904)CAS Light of West China Program。
文摘The debris flow dam is a common type of barrier dams,which shows significant differences from other types of barrier dam such as landslide dam,moraine dam in their formation processes,dam body shapes,and internal compositions.The basic breaching parameters such as flood peak discharge are vital indicators of risk assessment.In this study,we elucidated the failure process of the debris flow dam through the flume experiment,and built the calculation equation of the breaching parameters by selecting critical factors.The result shows that the overtopping failure process of the debris flow dam is capable of forming significantly retrogressive scarps,and the failure process experiences three stages,the formation of the retrogressive scarp,the erosion of the retrogressive scarp,and the decline of the retrogressive scarp.Five factors used for establishing the calculation equations for peak discharge(Qp),final width(Wb)of the breach,and duration(T)of the debris flow dam failure are dam height(h),reservoir capacity(V),the fine grain content(P0.075)of the soil,the nonuniformity coefficient(Cu)of the soil,and the upper limit grain size(D90)of the soil,respectively.In the three equations,the correlation coefficients between Qp,Wb,T and the five factors were 0.86,0.70,0.63,respectively.The equations still need to be modified and verified in actual cases.
基金jointly funded by the National Natural Science Foundation of China(Grant No.42201095)the Natural Science Foundation of Sichuan(Grant No.2022NSFSC1032)。
文摘The use of open-type check dams in mountainous areas has become common practice in order to mitigate the effects of debris flow and extend the service life of engineering structures.The beam dam,a common debris flow control system,has received less attention in research on the impact process of debris flow and check dams compared to solid check dams.Additionally,the estimation of impact pressure in debris flow primarily considers debris flow characteristics,without taking into account the influence of geometric characteristics of the transmission structure.To better understand the impact process of debris flow on beam dams,a series of small-scale debris flow impact tests were conducted in a model flume.Key parameters,including velocity,depth,and impact pressure,were measured.The results show that the maximum impact pressure of debris flow is affected by both the characteristics of the debris flow and the relative opening size of the beam dam.Due to flow and edge occlusion in the middle of the beam dam,the discharge of debris flow is enhanced,resulting in a longer impact process and higher maximum impact pressure.Based on these findings,a calculation model of the maximum impact pressure of debris flow at the midpoint of the middle beam is proposed,which can be used to estimate the impact of debris flow on the discharge part of the beam dam.
基金funded by the Second Scientific Expedition to Qinghai-Tibet Plateau (Grant No.2019QZKK0902)the National Natural Science Foundation of China (Grant No.42201095)+2 种基金the Natural Science Foundation of Sichuan (Grant No.2022NSFSC1032)the Sichuan Provincial Transportation Science and Technology Project (2021-A-08)the Key science and technology projects of transportation industry (2021-MS4-104)
文摘To accurately predict impact loads can ensure the safe operation of debris flow control projects.The instantaneous impact process is usually considered in the calculation of the debris flow impact force;however,the redistribution of an impact load after structural regulation is unclear.In this study we deduced the theoretical calculation of a debris flow impact on a double-row slit dam,and carried out a verification experiment on the debris flow impact.The calculation model considers the influence of the debris flow properties,dam arrangement and pile material.The results show that the impact force of the debris flow is obviously affected by the bulk density.When the bulk density is 21 kg/m^(3),the maximum impact force on the pile dam is 1.15 times that when the bulk density is 15 kg/m^(3),but the time it takes for the debris flow to pass through the dam body is reduced by 60%.The larger the relative pile spacing,the more sufficient the flow space and the lower the maximum impact force.The maximum impact force of relative pile spacing of 0.8 is 12%less than that of elative pile spacing of 0.5.The horizontal distribution of the impact force in the mud depth range is parabolic.The maximum impact force on the centre pier is 1.3 times that of a side pier,and the maximum impact force on the dam body appears at the top of the mud depth range.From the vertical distribution of the impact force,the maximum impact force at the highest mud mark is approximately 70%of that of the bottom.With the increase in the relative pile spacing,the longitudinal maximum impact force distribution first decreases and then increases.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41861134008 and 41601476)the National Key Research and Development Program of China (Grant No. 2018YFC1505202)the 135 Strategic Program of the IMHE, CAS (Grant No. SDS-1351705)
文摘Loose deposits, rainfall and topography are three key factors that triggering debris flows.However, few studies have investigated the effects of loose deposits on the whole debris flow process.On June 28, 2012, a catastrophic debris flow occurred in the Aizi Valley, resulting in 40 deaths.The Aizi Valley is located in the Lower Jinsha River,southwestern Sichuan Province, China. The Aizi Valley debris flow has been selected as a case for addressing loose deposits effects on the whole debris flow process through remote sensing, field investigation and field experiments. Remote sensing interpretation and laboratory experiments were used to obtain the distribution and characteristics of the loose deposits, respectively. A field experiment was conducted to explore the mechanics of slope debris flows, and another field investigation was conducted to obtain the processes of debris flow formation, movement and amplification. The results showed that loose deposits preparation, slope debris flow initiation,gully debris flow confluence and valley debris flow amplification were dominated by the loose deposits.Antecedent droughts and earthquake activities may have increased the potential for loose soil sources in the Aizi Valley, which laid the foundation for debris flow formation. Slope debris flow initiated under rainfall, and the increase in the water content as well as the pore water pressure of the loose deposits were the key factors affecting slope failure. The nine gully debris flows converged in the valley, and the peak discharge was amplified 3.3 times due to a blockage and outburst caused by a large boulder. The results may help in predicting and assessing regional debris flows in dry-hot and seismic-prone areas based on loose deposits, especially considering large boulders.
基金support provided by the National Natural Sciences Foundation of China(No.41771419)Student Research Training Program of Southwest Jiaotong University(No.191510,No.182117)。
文摘The Digital Elevation Model(DEM)data of debris flow prevention engineering are the boundary of a debris flow prevention simulation,which provides accurate and reliable DEM data and is a key consideration in debris flow prevention simulations.Thus,this paper proposes a multi-source data fusion method.First,we constructed 3D models of debris flow prevention using virtual reality technology according to the relevant specifications.The 3D spatial data generated by 3D modeling were converted into DEM data for debris flow prevention engineering.Then,the accuracy and applicability of the DEM data were verified by the error analysis testing and fusion testing of the debris flow prevention simulation.Finally,we propose the Levels of Detail algorithm based on the quadtree structure to realize the visualization of a large-scale disaster prevention scene.The test results reveal that the data fusion method controlled the error rate of the DEM data of the debris flow prevention engineering within an allowable range and generated 3D volume data(obj format)to compensate for the deficiency of the DEM data whereby the 3D internal entity space is not expressed.Additionally,the levels of detailed method can dispatch the data of a large-scale debris flow hazard scene in real time to ensure a realistic 3D visualization.In summary,the proposed methods can be applied to the planning of debris flow prevention engineering and to the simulation of the debris flow prevention process.
基金financially supported by Department of Space,India(Grant No.ISRO/RES/4/663/18-19)。
文摘Debris flows are rapid mass movements with a mixture of rock,soil and water.High-intensity rainfall events have triggered multiple debris flows around the globe,making it an important concern from the disaster management perspective.This study presents a numerical model called debris flow simulation 2D(DFS 2D)and applicability of the proposed model is investigated through the values of the model parameters used for the reproduction of an occurred debris flow at Yindongzi gully in China on 13 August 2010.The model can be used to simulate debris flows using three different rheologies and has a userfriendly interface for providing the inputs.Using DFS 2D,flow parameters can be estimated with respect to space and time.The values of the flow resistance parameters of model,dry-Coulomb and turbulent friction,were calibrated through the back analysis and the values obtained are 0.1 and 1000 m/s^(2),respectively.Two new methods of calibration are proposed in this study,considering the crosssectional area of flow and topographical changes induced by the debris flow.The proposed methods of calibration provide an effective solution to the cumulative errors induced by coarse-resolution digital elevation models(DEMs)in numerical modelling of debris flows.The statistical indices such as Willmott's index of agreement,mean-absolute-error,and normalized-root-mean-square-error of the calibrated model are 0.5,1.02 and 1.44,respectively.The comparison between simulated and observed values of topographic changes indicates that DFS 2D provides satisfactory results and can be used for dynamic modelling of debris flows.
文摘This research describes a quantitative,rapid,and low-cost methodology for debris flow susceptibility evaluation at the basin scale using open-access data and geodatabases.The proposed approach can aid decision makers in land management and territorial planning,by first screening for areas with a higher debris flow susceptibility.Five environmental predisposing factors,namely,bedrock lithology,fracture network,quaternary deposits,slope inclination,and hydrographic network,were selected as independent parameters and their mutual interactions were described and quantified using the Rock Engineering System(RES)methodology.For each parameter,specific indexes were proposed,aiming to provide a final synthetic and representative index of debris flow susceptibility at the basin scale.The methodology was tested in four basins located in the Upper Susa Valley(NW Italian Alps)where debris flow events are the predominant natural hazard.The proposed matrix can represent a useful standardized tool,universally applicable,since it is independent of type and characteristic of the basin.
基金sponsored by the 973 Program(2013CB733206)the 863 Program(2012AA121300)。
文摘On August 7^(th),2010,Sanyanyu and Luojiayu debris flows triggered by a heavy rain have lashed Zhouqu City around midnight,leading to catastrophic destruction which killed 1765 people and resulted in enormous economic loss.The ZHQ Seismic Station is located approximately 170 m west of the outlet of the Sanyanyu Gully.The seismometer deployed at the seismic station started recording seismic signals of ever-enlarging amplitude around 10 minutes before the debris flow rushed out of the Sanyanyu Gully,showing ever approaching seismic source,i.e.the debris flow.In this study,we analyze this seismic event and propose an inversion algorithm to estimate the velocity of the debris flow by searching the best-fitting pairs of envelopes in the synthetic seismograms and the corresponding field seismic records in a least-square sense.Inversion results reveal that,before rushing out of the outlet,the average velocity of the debris flow gradually increased from 6.2 m/s to 7.1 m/s and finally reached 15 m/s at approximately 0.5 km above the outlet and kept this value since then.Obviously,the ever-increasing velocity of the debris flow is the key factor for the following disasters.Compared with other studies,our approach can provide the velocity distribution for the debris flow before its outbreak;Besides,it has the potential to provide technological support for a better understanding of the disaster process of a debris flow.
文摘Turkey is highly prone to landslides because of the geological and geographic location.The study area,which is located in a tectonically active region,has been significantly affected by mass movements.Flow type landslides are frequently observed due to this location.This study aims at determining the source area and propagation of debris flows in the study area.We used the heuristic method to extract source areas of debris flow,and then used receiver operating characteristic(ROC)curve analysis to assess the performance of the method,and finally calculated the Area under curve(AUC)values being 83.64%and 80.39%for the success rate and prediction rate,respectively.We calculated potential propagation area and runout distance with Flow-R software.In conclusion,the obtained results(susceptibility map,propagation and runout distance)are very important for decisionmakers at the region located on an active fault zone,which is highly prone to natural disasters.The outputs of this study could be used in site selection studies,designing erosion prevention systems and protecting existing human-made structures.
基金This work was supported by National Natural Science Foundation of China(Grant no.41972267 and no.41572257)Graduate Innovation Fund of Jilin University(Grant no.101832020CX232)。
文摘The quality of debris flow susceptibility mapping varies with sampling strategies. This paper aims at comparing three sampling strategies and determining the optimal one to sample the debris flow watersheds. The three sampling strategies studied were the centroid of the scarp area(COSA), the centroid of the flowing area(COFA), and the centroid of the accumulation area(COAA) of debris flow watersheds. An inventory consisting of 150 debris flow watersheds and 12 conditioning factors were prepared for research. Firstly, the information gain ratio(IGR) method was used to analyze the predictive ability of the conditioning factors. Subsequently, 12 conditioning factors were involved in the modeling of artificial neural network(ANN), random forest(RF) and support vector machine(SVM). Then, the receiver operating characteristic curves(ROC) and the area under curves(AUC) were used to evaluate the model performance. Finally, a scoring system was used to score the quality of the debris flow susceptibility maps. Samples obtained from the accumulation area have the strongest predictive ability and can make the models achieve the best performance. The AUC values corresponding to the best model performance on the validation dataset were 0.861, 0.804 and 0.856 for SVM, ANN and RF respectively. The sampling strategy of the centroid of the scarp area is optimal with the highest quality of debris flow susceptibility maps having scores of 373470, 393241 and 362485 for SVM, ANN and RF respectively.
基金jointly funded by the 135 Strategic Program of the Institute of Mountain Hazards and Environment,CAS(Grant No.SDS135-1703)the National Key Basic Research Program of China(973 program)(Grant No.2015CB452702)
文摘An increase in extreme precipitation events due to future climate change will have a decisive influence on the formation of debris flows in earthquake-stricken areas. This paper aimed to describe the possible impacts of future climate change on debris flow hazards in the Upper Minjiang River basin in Northwest Sichuan of China, which was severely affected by the 2008 Wenchuan earthquake. The study area was divided into 1285 catchments, which were used as the basic assessment units for debris flow hazards. Based on the current understanding of the causes of debris flows, a binary logistic regression model was used to screen key factors based on local geologic, geomorphologic, soil,vegetation, and meteorological and climatic conditions. We used the weighted summation method to obtain a composite index for debris flow hazards, based on two weight allocation methods: Relative Degree Analysis and rough set theory. Our results showed that the assessment model using the rough set theory resulted in better accuracy. According to the bias corrected and downscaled daily climate model data, future annual precipitation(2030-2059) in the study area are expected to decrease, with an increasing number of heavy rainfall events. Under future climate change, areas with a high-level of debris flow hazard will be even more dangerous, and 5.9% more of the study area was categorized as having a high-level hazard. Future climate change will cause an increase in debris flow hazard levels for 128 catchments, accounting for 10.5% of the total area. In the coming few decades, attention should be paid not only to traditional areas with high-level of debris flow hazards, but also to those areas with an increased hazard level to improve their resilience to debris flow disasters.
基金supported by the program of increasing resilience to natural hazards in earthquake prone regions in China:The NationalNatural Science Foundation of China(Grant No.41661134012 and 41501012)
文摘The estimation of the value on the engineering project in tourist towns is usually very challenging and controversial. In this study, an attempt has been made to evaluate the economic value of the debris flow control engineering in tourist towns by integrating both welfare and disaster economics. The total value of debris flow prevention and control engineering in tourist towns(VDFE) includes investment cost(IC), disaster mitigation benefit(DMB), and loss of brand value(LBV). Here DMB is assessed by the cost-benefit method. The LBV is estimated by incorporating brand equity and costbenefit methods. The engineering for debris flow control in the Hongchun Gully of southwest China was built to protect Yingxiu tourist town and was assessed as an example. The IC for the engineering is180 million RMB, however, the VDFE reaches as high as 3401 million RMB, of which the LBV is 169 million RMB, and the input-output ratio is 1:18. Thus, the LBV cannot be neglected in case of VDFE estimation process. The more developed the tourism in one town or city is, the greater the LBV and the higher the VDFE are.
基金This research was jointly funded by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA20030301)the Comprehensive Investigation and Assessment of Natural Hazards in China-Pakistan Economic Corridor(Grant No.2018FY100506)+1 种基金the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(Grant No.2019QZKK0906)the International Science&Technology Cooperation Program of China(Grant No.2018YFE0100100)。
文摘Glacial debris flows(GDFs) often occur in alpine regions that are subject to rapid climate change, and pose a serious threat to road systems. However, the ways that climate change impacts GDF risks along road systems remain poorly understood. Aierkuran Gully, located in eastern Pamir along Karakoram Highway(KKH), is a hotspot for GDF activity and climate change, and was thus selected to investigate the GDF risk to road systems under climate change conditions. Reg CM4.6 climate data for northwestern China were selected as climate projections during baseline(2011–2020) and future periods(2031–2040) under the Representative Concentration Pathway(RCP) 8.5. To reflect the coupling effect of rainfall and melt water that triggers GDF, a glacial hydrological model DETIM that considers both factors was applied to calculate the peak debris flow discharge. A FLO-2D model was calibrated based on high-quality data collected from a detailed field investigation and historical debris flow event. The FLO-2D model was used to simulate the debris flow depth and velocity during baseline and future periods under RCP8.5. The debris flow hazard was analyzed by integrating the maximum flow depth and momentum. Road structure vulnerability was further determined based on the economic value and susceptibility of hazard-affected objects. The GDF risk along KKH was assessed based on the GDF hazard and vulnerability analysis. Our results show that climate change would lead to amplified peak debris flow discharge, trigger highermagnitude GDF, and induce more severe damage and threats to the road system. Compared with the baseline period, the debris flow damage risk for culverts and bridges would increase and the areas that inundate the road and pavement would expand. Our findings provide valuable insights for the development of mitigation strategies to adapt road systems to climate change, especially in alpine regions with highly active GDFs.
基金financially supported by the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(No.2019QZKK0906)National Natural Science Foundation of China(No.41901008 and No.61976046)+3 种基金National Key R&D Program of China(No.2017YFC1502504)the Fundamental Research Funds for the Central Universities(Grant No.2682018CX05)Beijing Municipal Science and Technology Project(Z191100001419015)financially supported by the China Scholarship Council。
文摘At present,most researches on the critical rainfall threshold of debris flow initiation use a linear model obtained through regression.With relatively weak fault tolerance,this method not only ignores nonlinear effects but also is susceptible to singular noise samples,which makes it difficult to characterize the true quantization relationship of the rainfall threshold.Besides,the early warning threshold determined by statistical parameters is susceptible to negative samples(samples where no debris flow has occurred),which leads to uncertainty in the reliability of the early warning results by the regression curve.To overcome the above limitations,this study develops a data-driven multiobjective evolutionary optimization method that combines an artificial neural network(ANN)and a multiobjective evolutionary optimization implemented by particle swarm optimization(PSO).Firstly,the Pareto optimality method is used to represent the nonlinear and conflicting critical thresholds for the rainfall intensity I and the rainfall duration D.An ANN is used to construct a dual-target(dual-task)predictive surrogate model,and then a PSO-based multiobjective evolutionary optimization algorithm is applied to train the ANN and stochastically search the trained ANN for obtaining the Pareto front of the I-D surrogate prediction model,which is intended to overcome the limitations of the existing linear regression-based threshold methods.Finally,a double early warning curve model that can effectively control the false alarm rate and negative alarm rate of hazard warnings are proposed based on the decision space and target space maps.This study provides theoretical guidance for the early warning and forecasting of debris flows and has strong applicability.
基金Supported by the National Excellent Youth Foundation of P,R,China(40025103)
文摘Based on two-phase flow theory and shallow water flow assumption,a mathematical model is applied to simulate debris flow.The model considers a two-phase mixture of sediments and water fluid.Assuming that the sediments and the water fluid move downstream with the same velocity,the flow of the mixture is described using a two dimensional depth averaged model with a unique 2-D momentum equation and two mass balance e- quations for the mixture and the sediments,respectively.The finite volume method is used f...
基金funded by the Topic of National Sci-tech Support Plan(2014BAL05B01)Chinese Academy of Sciences STS-Network Projects(KFJ-EW-STS-094)Key Laboratory of Mountain Hazards and Earth Surface Processes under Major Research Projects(Y3K2040040)of Chinese Academy of Sciences
文摘Pore water pressure and water content are important indicators to both deposition and consolidation of debris flows, enabling a direct assessment of consolidation degree. This article gained a more comprehensive understanding about the entire consolidation process and focused on exploring pore water pressure and volumetric water content variations of the deposit body during natural consolidation under different conditions taking the viscous debris flow mass as a study subject and by flume experiments. The results indicate that, as the color of the debris changed from initial dark green to grayish-white color, the initial deposit thickness declined by 3% and 2.8% over a permeable and impermeable sand bed, respectively. A positive correlation was observed between pore water pressure and depth in the deposit for both scenarios, with deeper depths being related to greater pore water pressure. For the permeable environment, the average dissipation rate of pore water pressure measured at depths of 0.10 m and 0.05 m were 0.0172 Pa/d and 0.0144 Pa/d, respectively, showing a positivechanging trend with increasing depth. Under impermeable conditions, the average dissipation rates at different depths were similar, while the volumetric water content in the deposit had a positive correlation with depth. The reduction of water content in the deposit accelerated with depth under impermeable sand bed boundary conditions, but was not considerably correlated with depth under permeable sand bed boundary conditions. However, the amount of discharged water from the deposit was greater and consolidation occurred faster in permeable conditions. This indicates that the permeability of the boundary sand bed has a significant impact on the progress of consolidation. This research demonstrates that pore water and pressure dissipations are present during the entire viscous debris consolidation process. Contrasting with dilute flows, pore pressure dissipation in viscous flows cannot be completed in a matter of minutes or even hours, requiring longer completion time — 3 to 5 days and even more. Additionally, the dissipation of the pore water pressure lagged the reduction of the water content. During the experiment, the dissipation rate fluctuated substantially, indicating a close relationship betweenthe dissipation process and the physical properties of broadly graded soils.
