Impact of glacier changes and permafrost distribution on debris flows in Badswat and Shishkat catchments,Northern Pakistan

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.

Features of Sandy Debris Flows of the Yanchang Formation in the Ordos Basin and Its Oil and Gas Exploration Significance

Sandy debris flow is a new genetic type of sand bodies,which has gained much attention in recent years and its corresponding theory is proved to be a significant improvement and even partial denial to the 'Bouma Sequence' and 'turbidite fan' deep-water sedimentary theories to some point. Oil exploration researchers are highly concerned with sandy debris flows for its key role in controlling oil and gas accumulation processes.In this article,by applying sandy debris flows theory and combining a lot work of core,outcrop observation and analysis plus seismic profile interpretation,we recognized three types of sedimentary gravity flows that are sandy debris flows,classic turbidites and slumping rocks in chang-6 member of Yanchang Formation in the deep-water area of central Ordos Basin.Among the three types,the sandy debris flows are the most prominent and possesses the best oil bearing conditions.On the contrary,the classic turbidites formed by turbidity currents are limited in distribution;therefore,previous Yanchang Formation deep-water sedimentary studies have exaggerated the importance of turbidite currents deposition.Further study showed that the area distribution of deep water gravity flow sand bodies in Yanchang Formation were controlled by the slope of the deep-water deposits and the flows had vast distribution,huge depth and prevalent advantages for oil forming,which make it one of the most favorable new areas for Ordos Basin prospecting.

Fractality of grain composition of debris flows

Debris flows in essence are the process of mass transportation controlled by the constitution featured by a wide-ranged distribution of grain size. Debris-flow samples of different densities collected from different regions and gullies reveal that cumulative curve of grain composition, in particular for debris flows of high density, ρ5〉2 g/cm^3, can be fitted well by exponential function with exponents varying with regions and gullies. Debris flows fall into a narrow-valued domain of the exponent, as evidenced by Jiangjiagou Gully （JJG） with high occurrence frequency of debris flows. Furthermore, fractality of grain composition and porosity have been derived from cumulative curves in a certain size range, a range that determines the upper limit of grains constituting the matrix of debris flows. One can conclude that fractal structure of porosity plays crucial roles in soil fluidization that initiates debris flows, and debris flows occur at some range of fractal dimension, in coincidence with field observations.

Classification and Facies Sequence Model of Subaqueous Debris Flows

Objective Debris flows are cohesive sediment gravity flows which occur in both subaerial and subaqueous settings. Compared to subaerial debris flows which have been well studied as a geological hazard, subaqueous debris flows showing complicated sediment composition and sedimentary processes were poorly understood. The main objective of this work is to establish a classification scheme and facies sequence models of subaqueous debris flows for well understanding their sedimentary processes and depositional characteristics.

Debris flow simulation 2D(DFS 2D):Numerical modelling of debris flows and calibration of friction parameters

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.

Characteristics and Causes of Disastrous Debris Flows on July 4, 2013, in Shimian County, Sichuan, China

Debris flow is an abrupt phenomenon of earth surface movement and typical disaster in mountainous areas with steep terrace, quantity of loose soil and abundant surface runoff. Intense rainfall and rainstorm easily triggered debris flows and generated huge losses. The disastrous debris flows, on July 4, 2013 at the gullies of Hou, Heilinzi and Xiongjia in Shimian County, Sichuan Province, resulted in 18 casualties and endangering Shimian city with a population of 50,000. These debris flows were characterized by low viscosity with only 0.9% - 1.4% clay soil of less than 0.05mm, density of 1.77 - 1.84 t/m3, velocity of 4.4 - 13.5m/s and discharge of 827 - 1248 m3/s, respectively, and also delivered sediment of 16.8 × 104m3, 12.7 - 13.5 × 104 m3, 20.5 × 104m3 out of the outlet, respectively. These three events all generated a hazard chain, which involved in flash flood, channelized debris flow, dammed lake and outburst flood. The threshold conditions of debris flow blocking Nanya River and forming this hazard chain are that the unit width peak discharge and the deposition volume in river channel are more than 37.0 m3/s and 4500 m3, respectively. These debris flows were initiated by intense rainfall with the antecedent rainfall of over 52 mm and triggering rainstorm of over 36 mm/h. And, the property losses and casualties mainly originated from impacting and scouring, burying and blocking, highway destructing and river channel rising. The irrational location of constructions and the destruction of under-standard prevention constructions were responsible for loss worsening. It was strongly recommended for mitigating that hazards reassessment, integrated control, emergency plan and integrated risk management were made at mountainous urban areas, especially in high-hazard areas.

Hazards Assessment of Regional Debris Flows Based on Geographic Information Science

Supported by the spatial analysis feature of geographic information science and assessment model of regional debris flows, hazards degrees of the debris flows in the Upper Yangtze River Watershed （UYRW） are divided into five grades based on grid cell. The area of no danger, light danger, medium danger, severe danger and extreme severe danger regions respectively are 278 000, 288 000, 217 000, 127 000, 15 000 km^2. Furthermore, the counties in the UYRW are classified into four classes based on the hazards degrees in each county. The number of severe danger, medium danger, light danger and no danger counties respectively are 49, 82, 77 and 105. The assessment results will be provided for the hazards forecasting and mitigation in the UYRW and ongoing regionalization of Main Function Regions in China as data and technique framework.

An Overview of Formation Mechanism and Disaster Characteristics of Post-seismic Debris Flows Triggered by Subsequent Rainstorms in Wenchuan Earthquake Extremely Stricken Areas

The Wenchuan earthquake induced large amounts of debris flows and catastrophic incidents triggered by subsequent rainstorms occurred frequently in the past 6 rainy seasons, and thus resulted in serious casualties, huge economic loss and long-term impact. In this paper, post-seismic debris flows distributed in 10 Wenchuan earthquake extremely stricken counties were verified and debris flow database consisting of 609 debris flows was established based on detailed investigation organized by Land and Resources Department of Sichuan Province. Combined with database and related studies, the impact of Wenchuan earthquake on debris flows was analyzed. And then variation of formation conditions including rainfall threshold and landform condition was analyzed by contrasting pre-seismic and post-seismic debris flows. Followed are some typical viewpoints on initiation mechanism of post-seismic debris flows. In the end of this paper, characteristics of postseismic debris flows triggered by subsequent rainstorms were comprehensively summarized, such as regional group occurrence, high frequency, high viscosity, chain effect, huge dynamics, large scale and long duration. We hope this paper will be helpful in understanding the formation mechanism, disaster characteristics and prevention countermeasures of post-seismic debris flows in Wenchuan earthquake extremely stricken areas.

Disaster Reduction Decision Support System Against Debris Flows and Landslides Along Highway in Mountainous Area

Highways in mountainous areas are easy to be damaged by such natural disasters as debris flows and landslides and disaster reduction decision support system (DRDSS) is one of the important means to mitigate these disasters. Guided by the theories and technologies of debris flow and landslide reduction and supported by geographical information system (GIS), remote sensing and database techniques, a DRDSS against debris flow and landslide along highways in mountainous areas has been established on the basis of such principles as pertinence, systematicness, effectiveness, easy to use, open and expandability. The system consists of database, disaster analysis models and decisions on reduction of debris flows and landslides, mainly functioning to zone disaster dangerous degree, analyze debris flow activity, simulate debris flow deposition and diffusion, analyze landslide stability, select optimal highway renovation scheme and plan disaster prevention and control engineering. This system has been applied successfully to the debris flow and landslide treatment works along Palongzangbu Section of Sichuan-Tibet Highway.

A multiobjective evolutionary optimization method based critical rainfall thresholds for debris flows initiation

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.

Landscape change in response to multiperiod glacial debris flows in Peilong catchment,southeastern Tibet

High-magnitude glacial debris flows in small basins in Himalayas have a significant impact on landscape.The Peilong catchment,a tributary of the Parlung Zangbo river in southeastern Tibet,was chosen as a case study of topographic response to multi-period glacial debris flows.There are few large debris flow records in the catchment before 1983,but four large-scale glacial debris flows with peak discharge up to 8195 m3/s blocked the river during 1983–1985 and in 2015.A combination of field survey,examination of historical records and interpretation of multi-period remote sensing images was used to assess triggering factors and geomorphic impact of the events.The results show that the debris flows during 1983 and 1985 may be attributed to seismic events in 1981 and 1982,while the event in 2015 resulted from large amount of landslide deposits caused by glacier retreat during 1993~2013 and high precipitation in 2015.In the upper-midstream broad valley,erosion and accumulation of the debris flows changed the channel morphology,resulting in course diversion.In the lower-midstream narrow valley,lateral erosion of debris flows induced a large number of landslides but had little impact on the channel longitudinal profile.The ability of massive glacial debris flows to change valley topography is more than ten times that of regular water flows.The landscape of the accumulation fan at the outlet of the valley is controlled by the interaction between the sediment transportation capacity of debris flows and erosional capacity of the main river.The sediment transport capacity of the Peilong river is greater than the delivery capacity of the Parlung Zangbo river,resulting in continuous aggradation of the confluence zone.

Activity evolution of landslides and debris flows after the Wenchuan earthquake in the Qipan catchment,Southwest China

The Wenchuan earthquake that occurred on 12 May 2008 induced numerous landslides.Loose landslide materials were deposited on hillslopes,and deep channels were easily remobilized and transformed into debris flows by extreme rainstorms.Twelve years after the Wenchuan earthquake,debris flows were still active in the Qipangou Ravine in the quake-hit area.In this paper,we continuously tracked the spatiotemporal evolution of the landslides and vegetation restoration and evaluated the evolution of debris flow activity in the Qipan catchment with the aid of a GIS platform and field investigations from 2008 to 2019.We observed that the area with active landslides increased sharply immediately following the earthquake,and then decreased with time;however,the total area of landslides continued to increase from 6.93 km^(2)in 2008 to 10.55 km^(2)in 2019.The active landslides shifted towards lower angles and higher elevations after 2013.Since 2009,the vegetation coverage has been gradually increasing and approaching the coverage present before the earthquake as of 2019.The landslide activity was high and the vegetation recovery rates were rapidly rising during the first five years after the earthquake;the recovery rates then slowed over time.Therefore,we divided the evolution that occurred during the post landslide period into an active period(2008-2013),a self-adjustment period(2013-2026)and a stable period(after 2026).We then proposed a quantitative model to determine the trends of landslide activity rates and NDVI values in the catchment,which indicated that the landslide activities and postseismic vegetation restoration rates in this catchment will return to preseismic levels within approximately two decades.We also analysed the runout volumes of the debris flows after the earthquakes(Diexi and Wenchuan)and the standard deviation of the vegetation coverage and predicted that the debris flow activities will last for an additional 50 years or more.

Artificial Neural Network-based prediction of glacial debris flows in the ParlungZangbo Basin, southeastern Tibetan Plateau,China

Accurate prediction on geological hazards can prevent disaster events in advance and greatly reduce property losses and life casualties.Glacial debris flows are the most serious hazards in southeastern Tibet in China due to their complexity in formation mechanism and the difficulty in prediction.Data collected from 102 glacier debris flow events from 31 gullies since 1970 and regional meteorological data from 1970 to 2019 in ParlungZangbo River Basin in southeastern Tibet were used for Artificial Neural Network(ANN)-based prediction of glacial debris flows.The formation mechanism of glacial debris flows in the ParlungZangbo Basin was systematically analyzed,and the calculations involving the meteorological data and disaster events were conducted by using the statistical methods and two layers fully connected neural networks.The occurrence probabilities and scales of glacial debris flows(small,medium,and large)were predicted,and promising results have been achieved.Through the proposed model calculations,a prediction accuracy of 78.33%was achieved for the scale of glacial debris flows in the study area.The prediction accuracy for both large-and medium-scale debris flows are higher than that for small-scale debris flows.The debris flow scale and the probability of occurrence increase with increasing rainfall and temperature.In addition,the K-fold cross-validation method was used to verify the reliability of the model.The average accuracy of the model calculated under this method is about 93.3%,which validates the proposed model.Practices have proved that the combination of ANN and disaster events can provide sound prediction on geological hazards under complex conditions.

Sedimentary Microfacies and Porosity Modeling of Deep-Water Sandy Debris Flows by Combining Sedimentary Patterns with Seismic Data： An Example from Unit I of Gas Field A, South China Sea

Sandy debris flow deposits are present in Unit I during Miocene of Gas Field A in the Baiyun Depression of the South China Sea. The paucity of well data and the great variability of the sedimentary microfacies make it difficult to identify and predict the distribution patterns of the main gas reservoir, and have seriously hindered further exploration and development of the gas field. Therefore, making full use of the available seismic data is extremely important for predicting the spatial distribution of sedimentary microfacies when constructing three-dimensional reservoir models. A suitable reservoir modeling strategy or workflow controlled by sedimentary microfacies and seismic data has been developed. Five types of seismic attributes were selected to correlate with the sand percentage, and the root mean square （RMS） amplitude performed the best. The relation between the RMS amplitude and the sand percentage was used to construct a reservoir sand distribution map. Three types of main sedimentary microfacies were identified： debris channels, fan lobes, and natural levees. Using constraints from the sedimentary microfacies boundaries, a sedimentary microfacies model was constructed using the sequential indicator and assigned value simulation methods. Finally, reservoir models of physical properties for sandy debris flow deposits controlled by sedimentary microfacies and seismic inversion data were established. Property cutoff values were adopted because the sedimentary microfacies and the reservoir properties from well-logging interpretation are intrinsically different. Selection of appropriate reservoir property cutoffs is a key step in reservoir modeling when using simulation methods based on sedimentary microfacies control. When the abnormal data are truncated and the reservoir properties probability distribution fits a normal distribution, microfacies-controlled reservoir property models are more reliable than those obtained from the sequence Gauss simulation method. The cutoffs for effective porosity of the debris channel, fan lobe, and natural levee facies were 0.2, 0.09, and 0.12, respectively; the corresponding average effective porosities were 0.24, 0.13, and 0.15. The proposed modeling method makes full use of seismic attributes and seismic inversion data, and also makes the property data of single-well depositional microfacies more conformable to a normal distribution with geological significance. Thus, the method allows use of more reliable input data when we construct a model of a sandy debris flow.

Potential sediment sources identification of debris flows in the Jiangjia Gully,China

It is of great significance for gully prevention and management to identify the potential sediment source of debris flow.Debris flow in a gully always originates from tributaries that have different gravity potential energies and sediment condition.In this study,tributaries of the Jiangjia Gully(JJG) in Yunnan province,China,are taken as the study area to determine the possible sediment sources of debris flow.It was found that tributaries with a high evolution index(EI,the integral of the hypsometric curve) always had high gravity potential energy,which favors the occurrence of landslide activity.Furthermore,the relationship between sediment distribution,gravity potential energy,and EI is compared,respectively.The results showed that the EI had a greater influence on the occurrence of landslides,and sediments were concentrated in tributaries with EI between 0.5 and 0.6.Accordingly,tributaries with EI > 0.5 were identified as the sediment sources of debris flow.In addition,the shape of a tributary was related to EI and can reflect the condition of water and sediment storage.

Modelling of debris-flow susceptibility and propagation: a case study from Northwest Himalaya

The geological and geographical position of the Northwest Himalayas makes it a vulnerable area for mass movements particularly landslides and debris flows. Mass movements have had a substantial impact on the study area which is extending along Karakorum Highway(KKH) from Besham to Chilas. Intense seismicity, deep gorges, steep terrain and extreme climatic events trigger multiple mountain hazards along the KKH, among which debris flow is recognized as the most destructive geohazard. This study aims to prepare a field-based debris flow inventory map at a regional scale along a 200 km stretch from Besham to Chilas. A total of 117 debris flows were identified in the field, and subsequently, a point-based debris-flow inventory and catchment delineation were performed through Arc GIS analysis. Regional scale debris flow susceptibility and propagation maps were prepared using Weighted Overlay Method(WOM) and Flow-R technique sequentially. Predisposing factors include slope, slope aspect, elevation, Topographic Roughness Index(TRI), Topographic Wetness Index(TWI), stream buffer, distance to faults, lithology rainfall, curvature, and collapsed material layer. The dataset was randomly divided into training data(75%) and validation data(25%). Results were validated through the Receiver Operator Characteristics(ROC) curve. Results show that Area Under the Curve(AUC) using WOM model is 79.2%. Flow-R propagation of debris flow shows that the 13.15%, 22.94%, and 63.91% areas are very high, high, and low susceptible to debris flow respectively. The propagation predicated by Flow-R validates the naturally occurring debris flow propagation as observed in the field surveys. The output of this research will provide valuable input to the decision makers for the site selection, designing of the prevention system, and for the protection of current infrastructure.

Interaction Mechanisms between Natural Debris Flow and Rigid Barrier Deflectors:A New Perspective for Rational Design and Optimal Arrangement

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.

Comparison of debris flow susceptibility assessment methods:support vector machine,particle swarm optimization,and feature selection techniques

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.

Glacial debris flow susceptibility mapping based on combined models in the Parlung Tsangpo Basin,China

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".

Analysis of debris flow control effect and hazard assessment in Xinqiao Gully,Wenchuan M_(s)8.0 earthquake area based on numerical simulation

Xinqiao Gully is located in the area of the 2008 Wenchuan M_(s)8.0 earthquake in Sichuan province,China.Based on the investigation of the 2023"6-26"Xinqiao Gully debris flow event,this study assessed the effectiveness of the debris flow control project and evaluated the debris flow hazards.Through field investigation and numerical simulation methods,the indicators of flow intensity reduction rate and storage capacity fullness were proposed to quantify the effectiveness of the engineering measures in the debris flow event.The simulation results show that the debris flow control project reduced the flow intensity by41.05%to 64.61%.The storage capacity of the dam decreases gradually from upstream to the mouth of the gully,thus effectively intercepting and controlling the debris flow.By evaluating the debris flow of different recurrence intervals,further measures are recommended for managing debris flow events.