Debris Flow Risk Research Articles

Process-driven susceptibility assessment of glacial lake outburst debris flow in the Himalayas under climate change

Global warming is causing glaciers to retreat and glacial lakes to expand in the Himalayas, which amplifies the risk of glacial lake outburst debris flows (GLODFs) and poses a significant threat to downstream lives and infrastructures. However, the complex interplay between GLODF occurrences and associated indicators, coupled with the lack of a comprehensive susceptibility indicator system that considers the entire GLODF process, presents a substantial challenge in assessing GLODF susceptibility in the Himalayas. This study proposes a process-driven GLODF susceptibility assessment indicator system responding to climate change that considers the complete process of GLODF formation, incorporating relevant parameters about upstream, themselves, and downstream of glacial lakes. Furthermore, to mitigate subjective factors associated with traditional evaluation methods, we developed three novel hybrid machine-learning models by integrating classic machine-learning algorithms with the whale optimization algorithm (WOA) to delineate the distribution of GLODF susceptibility in the Himalayas. All the hybrid models effectively predicted the GLODFs occurrence, with the WOA-SVC model demonstrating the highest prediction accuracy. Approximately 34% of the catchments exhibit high and very high susceptibility levels, primarily concentrated along the north and south sides of the Himalayan ridge, particularly in the eastern and central Himalayas. Indicators capturing the physical formation process of hazards, such as topographic potential (highest relative importance value of 40%), can precisely identify GLODF. A total of 128 catchments pose potential transboundary threats, with 24 classified as having a very high susceptibility level and 25 as having a high susceptibility level. Notably, the border region between China and Nepal is a prominent hotspot for transboundary threats of GLODF. These findings can provide valuable clues for disaster prevention, mitigation, and cross-border coordination in the Himalayas.

Hybridization of Machine Learning Algorithms and an Empirical Regression Model for Predicting Debris-Flow-Endangered Areas

Accurate delineation of debris-flow-endangered areas (e.g., the maximum runout distance) is a necessary prerequisite for the debris-flow risk assessment and countermeasures design. Recently, machine-learning models have been proved to be an effective tool in predicting debris-flow parameters. However, existing machine-learning models are generally developed based on a very limited number of observation data, which may result in the predictive model overfitting or underfitting. How to develop a robust model for accurate forecasting of debris-flow-endangered areas still remains a difficult task. This paper proposes a hybrid method for predicting debris-flow hazard zone by integrating machine-learning algorithms and an empirical regression model. The proposed method takes the calculated maximum runout distance obtained from the empirical model as supplementary inputs to increase the amount of training data to construct hybrid machine-learning models. Three commonly used machine-learning models (i.e., multivariate adaptive regression splines (MARS), random forest (RF), and support vector machine (SVM)) are developed based on the training datasets of a specific debris basin. Then, these three machine-learning models are combined with an empirical relationship developed using the same training datasets to generate corresponding hybrid models. Finally, the performance metrics (i.e., coefficient of determination (R2), root-mean-square error (RMSE), and mean absolute error (MAE)) of the proposed hybrid models are comprehensively investigated and compared with the single predictive model (i.e., MARS, RF, SVM, and the empirical model) under fivefold cross-validation. The proposed method is illustrated using 134 channelized debris-flow events in Sichuan province, China. Results show that compared with the three individual machine-learning models, hybridization of machine-learning algorithms and the empirical model results in R2, RMSE, and MAE improved by 70.5%, 32.9%, and 41.1%, respectively. In contrast to the empirical model, the R2, RMSE, and MAE value of the proposed hybrid models are improved by 29.6%, 22.3%, and 32.5%, respectively. The proposed hybrid models generally perform better than the single machine-learning and the empirical model, providing a promising tool for accurate forecasting of a debris-flow-endangered area.

Risk assessment of debris flow disaster in mountainous area of northern Yunnan province based on FLO-2D under the influence of extreme rainfall

The stratum in Yunlong mountain area is unstable, and it is more likely to have extreme damage to the mountain in extreme rainfall weather, and even cause the occurrence of mountain disasters such as debris flow. This paper conducted field geological surveys and used the FLO-2D professional simulation system to scientifically evaluate the risk probability of three debris flow in Yunlong County. The risk prediction before and after engineering control was compared for the county’s urban areas.This paper uses construction drawings and remote sensing images to assist in positioning methods for debris flow simulation. After dividing the debris flow simulation grid, the control project is added to the simulation project in the form of a plug-in, and specific engineering parameters are imported into the simulation project file by modifying its properties. The setting of the control project in numerical simulation is completed, solving the problem of setting engineering measures. By this method, the probability analysis of debris flow under three different rainfall frequencies of 1%, 2% and 5%, namely once in 20 years, once in 50 years and once in 100 years, is simulated, and the flow and sedimentation characteristics of debris flow before and after engineering control are compared. The results show that under 5% rainfall frequency, the simulated results before engineering control were compared with the actual deposition range, and the evaluation accuracy is within a reasonable error range. After debris flow engineering control, the proportion of high risk areas of debris flow in urban areas decreased significantly, especially when the frequency of rainfall was once in 100 years, and the area of non-danger areas increased by 5.92% compared with that before control. In the end, this paper combines the depth of mud, the velocity of mud and the outbreak frequency to get the debris flow risk assessment map before and after engineering treatment, and puts forward suggestions for further prevention and control measures of debris flow disaster. The research results of this paper will provide good guidance for the occurrence and control of debris flow hazards under the influence of extreme rainfall in the mountainous area of northern Yunnan.

Analysis of land use/land cover change (LULCC) and debris flow risks in Adama district, Ethiopia, aided by numerical simulation and deep learning-based remote sensing

Analysis of land use/land cover change (LULCC) and debris flow risks in Adama district, Ethiopia, aided by numerical simulation and deep learning-based remote sensing

Application of remote sensing monitoring to the spatiotemporal variation in debris flow activity in the catastrophic Wenchuan seismic area

Debris flows are typical compounded geohazards with long-term activity in earthquake-stricken areas. Numerous debris flows were simultaneously induced by subsequent extreme precipitation and caused serious property losses and casualties. Monitoring the dynamic variation in debris flow activity and its decay process over time is key for debris flow risk management and mitigation of the impact of debris flows. In this study, the spatiotemporal variation in debris flow activity of the Wenchuan seismic area over the past ten years was monitored based on multiperiod satellite data and field monitoring. The hillslope landslide sediment delivery to the channel gradually decreased, and the area with higher sediment transfer potential gradually changed from southern Wenchuan County to the northern area, which caused the area with high susceptibility to debris flows to gradually move towards northern Wenchuan County. Impacted by the decrease in available materials and coarsening of channel materials, the power of rainfall runoff required for driving debris flows gradually increased. This resulting debris flow is more likely to occur in this basin with a larger catchment area, longer channel length, and higher elevation difference. The changes in the debris flow activity index indicated that the debris flow activity evolves with an impulse type, and it may last for decades. The decay processes of the debris flow activity were summed up in three periods, i.e., high-activity period (2008–2015), unstable period (2015–2035), and recession period (after 2035), based on the dynamic evolution of material, hydrodynamics, and the coefficient of debris flow activity. Simultaneously, the active characteristics of debris flows in different periods were revealed, which is of great significance to the risk management of debris flows in the next period.

Risk Assessment of Single-Gully Debris Flow Based on Dynamic Changes in Provenance in the Wenchuan Earthquake Zone: A Case Study of the Qipan Gully

After the Wenchuan earthquake on 12 May 2008, a huge amount of loose deposits was generated on the mountain surface in the earthquake zone, and vegetation was severely damaged, providing a rich source of material for debris flow, greatly increasing the danger. For many years, researchers have mainly considered the recovery of slope vegetation in assessing the risk of debris flow post-earthquake. However, field investigations have found that large amounts of the dynamic reserve materials in the gully have an important impact on the risk. Thus, based on field survey data, this paper takes the Qipan gully in Wenchuan County as an object and uses multi-source and multi-scale monitoring methods (Landsat series, Quickbird, and Unmanned Air Vehicle) to analyze and statistically study the provenance of the slope and gully both pre- and post- the earthquake. By comprehensively using game theory combination weighting and the cloud model, a dynamic risk assessment model for debris flow was constructed to evaluate the risk of debris flow from 2005 to 2019. The results show that the slope provenance post-earthquake was 7.7 times that of pre-earthquake, and by 2019 the slope provenance had recovered to the pre-earthquake level. Based on the statistical estimation of the amount of debris flow outbreak and the dredging of the blocking dam recorded in relevant data, the dynamic provenance of debris flow had decreased by about 781.3 × 104 m3 by 2019. Compared with considering slope provenance only, the assessment result of debris flow risk considering both slope and gully provenance is more realistic. The results are expected to provide reference and guidance for dynamic assessment of the risk of debris flow faced by increasing projects in high-seismic-intensity mountainous areas and to ensure the safety of people’s lives and property effectively.

Risk Assessment of Debris Flows Along the Karakoram Highway (Kashgar-Khunjerab Section) in the Context of Climate Change

The Karakoram highway (KKH) is renowned for its complex natural environment and geological conditions. The climate changes drastically and directly influences the frequency and magnitude of debris flows in this region, resulting in significant casualties and economic losses. However, the risk assessment of debris flows along the KKH in the context of climate change has been rarely explored. Therefore, in this study we used the debris flow data, historical meteorological data and future climate prediction data to assess the debris flow risk of the study region during the baseline period (2009–2018), 2025s (2021–2030), 2035s (2031–2040) and 2045s (2041–2050) under the Representative Concentration Pathway 8.5 scenario. The results show that the risk of debris flows increases with climate change, with the highest risk level in the 2025s. Among different parts of this highway, the upper reaches of the Ghez River and the second half of Tashkorgan-Khunjerab are the sections with the highest risk. These findings are helpful for debris flow prevention and can offer coping strategies for the existing line of the KKH. They also provide some reference for the renovation, improvement, operation, and maintenance of the KKH.

Medical resource accessibility in areas with frequent and hazardous debris flows

Debris flow threats human lives and safety worldwide, with greater impacts on undeveloped regions with uneven medical resource allocation. In this study, we take Sichuan Province, China as a case study area, where debris flow disasters are frequent and medical resources concentrate in developed regions. Based on factor analysis method, 16 socioeconomic indicators are applied to obtain the vulnerability of the population under debris flow threat, which is combined with debris flow susceptibility and historical debris flow inventory to estimate the potential casualty for each county or district. Based on the potential casualties and the number of beds at the second-tier hospitals and above, two-step floating catchment area method is used to calculate the medical resource accessibility. The results show that: (1) The prevention and mitigation measures and sufficient medical resources have positive effects on reducing potential casualties at the present stage. (2) The present medical resource allocation can provide treatments for more than 85% of the injured within 30 minutes. (3) Regionalized management can further promote the efficiency of mitigating potential casualties caused by debris flows. The findings of this study provide references for administrators and policymakers to conduct regionalized management by considering the distributions of debris flow risks and medical resources, aiming at mitigating efficiently the potential casualties due to debris flows

Debris Flow Classification and Risk Assessment Based on Combination Weighting Method and Cluster Analysis: A Case Study of Debris Flow Clusters in Longmenshan Town, Pengzhou, China

Debris flows can damage infrastructure and threaten human life and property safety, especially in tourist attractions. Therefore, it is crucial to classify and evaluate the risk of debris flows. This article takes 14 debris flows in Longmenshan Town, Pengzhou, Sichuan, China, as the research object. Based on on-site geological surveys, combined with drone images and multiple remote sensing images, the essential characteristics of each debris flow are comprehensively determined. A total of nine factors are used as the primary indicators affecting the risk of debris flow: drainage density, roundness, the average gradient of the main channel, maximum elevation difference, bending coefficient of the main channel, the loose-material supply length ratio, vegetation area ratio, population density, and loose-material volume of unit area. The subjective weights of each indicator are obtained using the Analytic Hierarchy Process, while the objective weights are obtained using the CRITIC method. Based on this, the distance function is introduced to couple the subjective and objective weights, determine each indicator’s combined weights, and obtain the integrated evaluation score values of different debris flow hazards. Considering the integrated evaluation score of debris flow, cluster analysis was used to classify 14 debris flows and cluster effectiveness indicators were introduced to determine the effectiveness of debris flow classification. A quantitative standard for the risk of debris flow within the study area was proposed, and finally, a risk assessment of debris flow in the study area was made. Comparing the results of this paper with the gray correlation method, the coupled synergistic method, and the geological field survey results, proves that the proposed method is feasible and provides a reasonable scientific basis for the study of the hazard assessment of regional debris flow clusters and other related issues within the scope of the Jianjiang River basin and other areas.

Factors influencing flood risk mitigation after wildfire: Insights for individual and collective action after the 2010 Schultz Fire

Post-fire flooding is of significant concern in the U.S. Southwest, where burned areas can drastically alter local hydrology to increase the risk of floods and debris flows, posing new and dynamic flood risk to communities downslope that necessitate coordinated response across jurisdictional boundaries. However, limited research explores how residents in affected communities respond to post-fire flood risk, both individually and collectively. We address this need by exploring factors that may influence the uptake of individual and collective actions for post-fire flood mitigation after an extreme fire event. We conducted a mixed-mode survey of 1,804 households in Flagstaff, Arizona, within the 100-year modeled post-fire flood risk area created by the Schultz Fire in 2010. We received 407 completed questionnaires for a 22.6% response rate. Survey questions focused on mitigation actions, addressing community flood risk, and responsibility for post-fire management among other topics. We found that respondents most readily engage in temporary mitigation actions, such as sandbag placement, that require less time and lower financial commitment. Respondent mitigation actions were primarily influenced by their personal flood experience and risk perceptions, with concerns about longevity of flood risk prioritized above current risk levels. Those who participated in individual actions were more likely to participate in collective action and vice versa, indicating a close relationship between mitigation actions across scales. We provide implications for practitioners working in post-fire environments, with a focus on communication and outreach about flood risk that motivate resident action to facilitate shared responsibility and cross-jurisdictional management of post-fire flood risk.

Risk assessment of rain-induced debris flow in the lower reaches of Yajiang River based on GIS and CF coupling models

Abstract In order to reduce the adverse impact of debris flow disasters on engineering construction facilities and social security in the lower reaches of the Yajiang River, this article selected 11 risk assessment factors such as elevation, aspect, profile curvature, Relief, and rainfall to study the occurrence rule of debris flow in this area. The data of disaster factors caused by debris flow points were derived and analyzed in ArcGIS. Then, factor correlation test and factor sensitivity level were established. The coupling model of qualitative mathematical model (analytic Hierarchy Process, AHP), quantitative mathematical model (binary logistic regression [LR]), machine learning model (random forest RF), and certainty factor (CF) were, respectively, used to predict the risk of debris flow disaster in the study area. After comparison, it was found that the CF–LR model had the highest accuracy. The results show that the areas with high debris flow risk are mainly concentrated in the first half of the lower reaches of the Yajiang River and distributed along both sides of the river bank. The annual rainfall range of 600–700 mm is the critical water source saturation value of debris flow in the study area.

Risk assessment of debris flow along the northern line of the Sichuan-Tibet highway

Debris flow occurs frequently in mountainous areas due to the special geographical and geological environment, causing significant damage to linear infrastructure. However, a systematic assessment of debris flow risk to the national highway is limited by the lack of regional vulnerability data. Based on a detailed inventory of debris flow and highway structure characteristics, this study presents a comprehensive regional risk assessment framework on the northern line of the Sichuan-Tibet Highway in China. The proposed framework consists of three main procedures: (1) debris flow hazard analyses by the weight-of-evidence method, (2) analyses of physical vulnerability using 12 vulnerability indexes, and (3) risk calculation which considers the natural attributes of debris flow and the social characteristics of a linear highway. The predictive performance was evaluated through receiver operating characteristic (ROC) curves, and the validation results showed that areas under the ROC curves were 83.77%. The risk zoning map indicated that the high-risk areas were particularly distributed in Dege County and Daofu County, with a high disaster frequency and a low highway protection standard. The regional risk assessment framework supports decision-making for disaster prevention and highway rehabilitation in mountainous areas.

Zoning technology for the management of ecological and clean small-watersheds via k-means clustering and entropy-weighted TOPSIS: A case study in Beijing

In the functional zoning and comprehensive management of ecological and clean small-watersheds (ECSWs), measures to increase the carrying capacity of the environment should be taken around water resources protection and ecological risk governance. An objective zoning technology for ECSWs was recommended in this paper to tackle problems such as soil erosion and water pollution efficiently. Taking eight typical ECSWs in Changping District of Beijing as a case study, the essential data, including the land use, digital elevation, administrative division, leaf area index and annual precipitation, can be initially accessed. Subsequently, two topographic features (i.e., elevation and slope) and seven ecosystem disservices (i.e., collapse risks, debris flow risks, nitrogen pollution, phosphorus pollution, sediment export, quick flow and surface runoff) were evaluated and quantified based on Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Geographic Information System (GIS). The quantitative attribute matrix was herein operated as a calculation object of k-means clustering and entropy-weighted TOPSIS for the classification and delineation. According to the analysis results, the category and hierarchical control zones of each ECSW were determined, deducing the preliminary management layout. Several practical measures that have been verified to be available were marked in the layout map based on the high-resolution remote sensing technology, contributing to guiding the high-efficiency construction of ECSWs in the future.

Risk assessment of debris flow disaster based on the cloud model-Probability fusion method.

This paper proposes a new debris flow risk assessment method based on the Monte Carlo Simulation and an Improved Cloud Model. The new method tests the consistency of coupling weights according to the characteristics of the Cloud Model firstly, so as to determine the weight boundary of each evaluation index. Considering the uncertain characteristics of weights, the Monte Carlo Simulation is used to converge the weights in a minimal fuzzy interval, then the final weight value of each evaluation index is obtained. Finally, a hierarchical comprehensive cloud is established by the Improving Cloud Model, which is used to input the comprehensive expectation composed of weights to obtain the risk level of debris flow. Through statistical analysis, this paper selects Debris flow scale (X1), Basin area (X2), Drainage density (X3), Basin relative relief (X4), Main channel length (X5), Maximum rainfall (X6) as evaluation indexes. A total of 20 debris flow gullies were selected as study cases (8 debris flow gullies as model test, 12 debris flow gullies in reservoir area as example study). The comparison of the final evaluation results with those of other methods shows that the method proposed in this paper is a more reliable evaluation method for debris flow prevention and control.

Debris flow gully zoning and risk assessment based on numerical simulation

In order to evaluate the zoning and risk of debris flow gully based on numerical simulation, a set of theoretical system and technical process of debris flow quantitative risk analysis suitable for mountainous towns in southwest China was constructed, taking buildings and roads as the research objects, in view of the particularity of disaster-bearing body types and debris flow disaster modes. It is mainly divided into three steps: (1) Using FLO-2D numerical model, the risk of debris flow is expressed by intensity index IDF; The simulation results of debris flow in Gully A 7·11 show that the area of correctly judged area is 50.02×104m2, the comprehensive accuracy index ω is 1.22, and the maximum IDF can reach 1013.25m3/s2, showing a general trend that the upstream is higher than the downstream, and the center of the drainage channel is higher than both sides. Using the data of debris flow damage in A ditch 7·11 in A city, a material vulnerability curve based on the probability of exceeding loss is constructed. Based on the establishment of disaster-bearing body database, the expected loss of disaster-bearing body can be expressed quantitatively by setting different future debris flow scenarios. The model verification and case application of A ditch in A city show that the quantitative risk analysis system of debris flow can well reflect the response mechanism of disaster-bearing body and debris flow, and can provide scientific basis for disaster prevention and mitigation in debris flow threat areas.

Risk Assessment of Transport Linear Infrastructures to Debris Flow

For the assessment of debris flow risk, it is essential to consider not only the triggering and propagation stages but also to perform analyses of its effects and consequences. The study aims at developing a procedure based on a quantitative risk assessments able to estimate the different levels of risk with reference to transport linear infrastructures. This includes numerical modelling for debris flows to determine the zones where the elements at risk could suffer an impact. A detailed comparison between the performances of two different approaches to debris flow modelling was carried out. In particular, the results of a mono-phase Bingham model (FLO-2D) and that of a single-phase model (RASH-3D) with reference to the Enna area (Sicily). The results can be applied for the risk calculations. The purpose is to define a priority of intervention for the identification of the infrastructures exposed at risk, leading to the choice of safety measures.

Performance of the debris flow alarm system ALMOND-F on the Rochefort Torrent (Val d’Aosta) on August 5, 2022

On August 5, 2022 in the Rochefort torrent (Val Ferret, Mont Blanc), a debris flow occurred that invaded the road connecting the valley with the village of Courmayeur. The debris flow interrupted the car traffic and damaged the bridge that crosses the torrent and the aqueduct that serves the municipality of Courmayeur. Due to the recurrence of similar events, in 2017 the Valle d’Aosta Region had decided to install a monitoring and warning system for debris flows, close to the bridge on the Rochefort torrent, to interrupt the traffic in both directions through a pair of traffic lights in case of debris flow. The system, named ALMOND-F (ALarm and MONitoring system for Debris-Flow), has been installed along the torrent, few tens of meters upstream of the bridge. ALMOND-F adopts a warning algorithm that is based on the variation of the seismic signal intensity produced by debris flows and that had been thoroughly tested in previous years in the instrumented area of the Gadria basin. On August 5, 2022 the warning system activated the traffic lights and stopped the traffic about three minutes before the debris flow invaded the road. It is the first time that the ALMOND-F system is utilized in a real risk situation to protect the population, after some years of controlled tests carried out in an instrumented area. Even though this represents an undoubted technological success, the installation of ALMOND-F requires several issues to be addressed to grant the highest level of safety. For instance, the presence of other active debris-flow channels and/or natural risks in the same valley may represent a limitation to the installation of a site-specific alarm system. The installation of the Rochefort torrent, opportunely optimized also on the basis of the feedbacks of the August 5, 2022 debris flow event, could become a useful case study and so provide indications and suggestions on the mitigation of the debris flow risk through the use of warning systems.

Keynote lecture. Towards reliability-management for debris flow risk assessment

Recent progress in data-integrated simulation methods excelled our understanding of debris flows including triggering mechanisms and dynamic run-out behavior. Research groups and geohazard practitioners worldwide successfully integrate advanced simulations into workflows for hazard mapping. However, many challenges remain in predictively applying such tools for accepted decision support. One reason is our lack of a systematic approach to managing the simulations’ reliability. In this contribution, we present results on an investigation to which extent the choice of data used for calibration influences the simulation’s reliability. We start with introducing building blocks of a modular and extendible data-integrated debris flow simulation toolchain developed by our group. Next, we introduce reliability as one quality measure of a holistic debris flow simulation and discuss how it can be assessed. Based on a synthetic example, we then show how different types of observed calibration data, such as impact area, deposit volume or localized velocity measurements impacts on the subsequent forward simulation’s posterior probability distribution, hence the simulation’s reliability. We conclude by discussing how linking a debris flow simulation’s reliability to type, scope and resolution of the calibration data could offer a novel pathway towards reliability management for debris flow risk assessment.

Development of An Automatic Calculation Algorithm for Rainfall Thresholds of Debris Flow in Korea

Climate change has increased the amount and intensity of rainfall, increasing debris flow risk. Debris flow damage has become a social issue in Korea, and the need for research related to rainfall thresholds for debris flow has increased. In this study, an automatic calculation algorithm was developed to derive criteria suitable for the Korean region for the rainfall thresholds of debris flow. The study area selected was Gangwon-do, where a significant amount of debris flow occurred recently, and information on rainfall and the occurrence of debris flow were collected. As a result of applying an algorithm based on the R programming language, an equation for the relationship between the rainfall intensity and duration in Gangwon-do was automatically derived using debris flow occurrence point information and meteorological rainfall information.

Numerical modeling of debris flows using basic equations in generalized curvilinear coordinate system and its application to debris flows in Kinryu River Basin in Saga City, Japan

Each year, structures installed in rivers and valleys (e.g., bank protections, bridges, and sabo dams) are damaged by debris flows; therefore, it is necessary to predict the flow characteristics of debris flows accurately to design river and valley structures that are robust against such debris flows. In recent years, several two-dimensional models have been developed to simulate debris flow. However, the basic equations in the numerical simulation models are in the Cartesian coordinate system, and the shape of each numerical analysis grid is square or rectangular. It is impossible to use numerical grids that match the horizontal shape of the river or valley structures, such as bank protections and sabo dams, when employing square or rectangular grids. This makes it difficult to calculate the fluid forces acting on river or valley structures. In this study, the basic equations of debris flow are provided in the generalized curvilinear coordinate system and a numerical simulation model of debris flow designed using an orthogonal curved grid along the horizontal shape of rivers and valleys is developed. Numerical simulations of a periodical meandering valley are conducted using the basic equations in the generalized curvilinear and Cartesian coordinate systems; the difference between the two results is discussed. Further, numerical simulations of the debris flow that occurred in the Kinryu River Basin in Saga City, Japan, in 2019 are performed using the basic equations in the generalized curvilinear and Cartesian coordinate systems, and the difference between the two simulation results is discussed. The numerical simulation results of debris flow in a periodical meandering channel suggest a slow propagation of debris flow when equations in the Cartesian coordinate system are used; this is attributed to the rough boundaries of debris flow when a square grid is used, which causes numerical energy dissipation that does not exist physically. The inundation areas and land surface deformation of debris flow in Kinryu River Basin were reproduced well by the developed numerical analysis model; the basic equations were written in the generalized curvilinear coordinate system. The development and decrescence of debris flows were reproduced using the developed model; the first debris flow in Kinryu River Basin was stopped in the upstream mild slope area, while the second flowed into the residential area. Reproducing the flow depth, velocity, and discharge could be improved by the model using basic equations in the generalized curvilinear coordinate system, as compared with those reproduced using basic equations in the Cartesian coordinate system. When the Cartesian coordinate system was used, the volume of the debris flow was evaluated to be small and the travel distance of the debris flow was evaluated to be short; thus, the debris flow does not arrive at the residential area and the risk of debris flows is underestimated.