Debris flow susceptibility evaluation method, system and equipment based on outbreak frequency and rushing-out volume, and storage medium

Abstract

The invention discloses a debris flow susceptibility evaluation method, system and device based on outbreak frequency and rushing-out volume, and a storage medium. The method comprises the following steps: providing an influence factor X value; providing a debris flow development degree Y value, wherein the calculation formula of the debris flow development degree Y value is # imgabs0 #; inputting the impact factor X value and the debris flow development degree Y value into a geographic detector-frequency ratio model to obtain susceptibility indexes # imgabs1 # of all debris flows; and carrying out susceptibility grade division on the obtained susceptibility indexes # imgabS2 # of all the debris flow to obtain a debris flow susceptibility evaluation result. The spatial distribution result of the drainage basins with high susceptibility and above obtained by the method is closer to the actual field investigation result, while the number of the high-susceptibility drainage basins obtained by a Y value model in the traditional method is only 59 and is far smaller than the field investigation result, which also shows that the method provided by the invention has superiority compared with the traditional method.

Description

Technical Field

[0001] The present invention belongs to the technical field of debris flow disaster assessment, and in particular relates to a debris flow susceptibility assessment method, system, equipment and storage medium based on the frequency of the outbreak and the volume of the outburst. Background Art

[0002] Debris flow is one of the most common and destructive geological disasters in mountainous areas. It not only seriously threatens people's lives and property safety, but also restricts the economic development of mountainous areas. Debris flow susceptibility assessment can reflect the location where debris flow may occur. It plays an important role in debris flow prevention and control decision-making and is also a global research hotspot in the field of debris flow. The selection of appropriate analysis units is one of the important links in the evaluation of debris flow susceptibility. Regarding debris flow analysis units, most predecessors use grid units, which can fully consider the influencing factors of continuity and type. Such research is due to the confusion of the concepts of landslide and debris flow. Grid units can represent sufficient information in landslide susceptibility assessment, but in the study of debris flow susceptibility assessment, watershed units can obtain richer disaster characteristics and spatial information than grid units. At present, some scholars have used watershed units to evaluate and compare the performance of different susceptibility assessment models, but their values ​​for debris flow are limited to yes or no (1 or 0). Although there has been some progress, it is still difficult to reflect the development degree and disaster information of debris flow, highlighting the individual differences of debris flow. Summary of the invention

[0003] The purpose of the present invention is to provide a method, system, device and storage medium for evaluating the susceptibility of debris flows based on the frequency of outbreaks and the volume of outbursts, so as to solve the problem that the prior art is difficult to reflect the development degree and disaster information of debris flows and cannot highlight the individual differences of debris flows.

[0004] The embodiment of the present application is implemented by providing a method for evaluating the susceptibility of debris flow based on the frequency of the outbreak and the volume of the outflow, including: providing an influencing factor X value; Provide the debris flow development degree Y value, the calculation formula of the debris flow development degree Y value is as follows: ; In the formula, is the frequency of debris flow in the past 50 years, in times per year; The volume of the debris flow in the most recent outburst, in m 3 ; The influence factor X value and debris flow development degree Y value are input into the geographic detector-frequency ratio model to obtain the susceptibility index of all debris flows. ; The susceptibility index of all debris flows obtained The susceptibility levels are classified and the debris flow susceptibility evaluation results are obtained.

[0005] In some embodiments, the influencing factor X value includes one or more of the average slope of the watershed, the longitudinal gradient of the channel, the watershed area, NDVI, the rainfall index, the density of the fault distribution line, the lithology, the land use type and the relative height difference.

[0006] In some embodiments, the proportion of soft rock distribution area in the debris flow basin to the entire basin area is used to represent the lithology; and / or the proportion of cultivated land area to the entire basin area is used to represent the land use type.

[0007] In some embodiments, the influencing factor X value and the debris flow development degree Y value are input into the geographic detector, the weight of the influencing factor X value is extracted, and the main controlling factor F is screened out according to the debris flow development degree Y value.

[0008] In some embodiments, each debris flow basin is used as an analysis unit, and a geographic detector model is used to detect the influence of each influencing factor X value on the development of debris flow, and the weight of the influencing factor X value is represented by the q value.

[0009] In some embodiments, the main control factor F is introduced into the frequency ratio model to obtain the debris flow susceptibility index: .

[0010] In some embodiments, the master control factor F is divided into n types or n levels, namely F i (i=1, 2, 3…, n), then F i The frequency ratio FR i Defined as: ; In the formula, Indicates that the known debris flow D The frequency, Indicates the debris flows to be evaluated in the study area. The frequency, Indicates that the known debris flow D The number of represents the total number of debris flows D, Indicates the debris flows to be evaluated in the study area. The total number of A Represents the total number of all debris flows to be evaluated in the study area.

[0011] For a certain study area, the frequency ratios of different types of main controlling factors of a debris flow D in the study area are added together to obtain the susceptibility index of the debris flow D. : ; In the formula, represents the susceptibility index, represents the number of master controlling factors, Indicates the frequency ratio of different types of main controlling factors; Same as above, the susceptibility index of all debris flows in the study area is obtained in turn .

[0012] Accordingly, the embodiment of the present application also provides a debris flow susceptibility assessment system based on the frequency of the outbreak and the volume of the outflow, including: An impact factor X value module, used to provide an impact factor X value; The debris flow development degree Y value module is used to provide the debris flow development degree Y value. The calculation formula of the debris flow development degree Y value is as follows: ; In the formula, is the frequency of debris flow in the past 50 years, in times per year; The volume of the debris flow in the most recent outburst, in m 3 ; Debris flow susceptibility index The acquisition module is used to input the influencing factor X value and the debris flow development degree Y value into the geographic detector-frequency ratio model to obtain the susceptibility index of all debris flows ; The debris flow susceptibility evaluation result acquisition module is used to obtain the susceptibility index of all debris flows The susceptibility levels are classified and the debris flow susceptibility evaluation results are obtained.

[0013] Accordingly, an embodiment of the present application also provides a computer device, including a storage device and a processor, wherein the storage device stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the above method.

[0014] Accordingly, an embodiment of the present application also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the processor executes the steps of the above method.

[0015] In this application: NDVI is the Normalized Difference Vegetation Index; In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: This application proposes to use the product of the one-time outflow volume and the frequency of debris flow outbreaks within 50 years to characterize the development degree of the debris flow valley that has erupted, that is, the Y value. The physical meaning of the Y value is the average annual solid matter outflow over many years, which can better reflect the development degree of the debris flow; this application inputs the influencing factor X value and the debris flow development degree Y value into the geographic detector-frequency ratio model to obtain the susceptibility index of all debris flows , the susceptibility index of all debris flows obtained The susceptibility levels are classified and the debris flow susceptibility evaluation results are obtained. The spatial distribution results of the high-susceptibility basins and above obtained in this application are closer to the results of the actual field investigation, while the susceptibility results obtained by the traditional method as the Y value model have only 59 high-susceptibility basins, which is much smaller than the results of the field investigation. This also shows that the new invention method of this application is superior to the traditional method. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A disaster-pregnancy condition factor diagram for debris flow susceptibility assessment provided by an embodiment of the present invention; Figure 2 A debris flow susceptibility evaluation diagram for the study area under the Y1 value method provided in an embodiment of the present invention; Figure 3 A debris flow susceptibility evaluation diagram for the study area using the Y2 value method provided in an embodiment of the present invention; Figure 4 This is a diagram of the on-site investigation results of the debris flow in the main stream of Nujiang River provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0018] In the past, for debris flow susceptibility assessment methods based on debris flow basins, the Y value was limited to yes or no (1 or 0). For debris flows with a value of 1, there was no distinction between debris flows of different scales and frequencies. Obviously, this would reduce the accuracy of the assessment.

[0019] The technical solution of this application is as follows: In a first aspect, the embodiments of the present application provide a method for evaluating the susceptibility of debris flows based on the frequency of the outbreak and the volume of the outflow, including: S01. Provide the impact factor X value; S02. Provide a debris flow development degree Y value. The calculation formula for the debris flow development degree Y value is as follows: ; In the formula, is the frequency of debris flow in the past 50 years, in times per year; The volume of the debris flow in the most recent outburst, in m 3 ; S03. Input the influencing factor X value and the debris flow development degree Y value into the geographic detector-frequency ratio model to obtain the susceptibility index of all debris flows ; S04, the susceptibility index of all debris flows obtained The susceptibility levels are classified and the debris flow susceptibility evaluation results are obtained.

[0020] This application proposes to use the product of the one-time outflow volume and the frequency of debris flow outbreaks within 50 years to characterize the development degree of the debris flow valley that has erupted, that is, the Y value. The physical meaning of the Y value is the average annual solid matter outflow over many years, which can better reflect the development degree of the debris flow; this application inputs the influencing factor X value and the debris flow development degree Y value into the geographic detector-frequency ratio model to obtain the susceptibility index of all debris flows , the susceptibility index of all debris flows obtained The susceptibility levels are classified and the debris flow susceptibility evaluation results are obtained. The spatial distribution results of the high-susceptibility basins and above obtained in this application are closer to the results of the actual field investigation, while the susceptibility results obtained by the traditional method as the Y value model have only 59 high-susceptibility basins, which is much smaller than the results of the field investigation. This also shows that the new invention method of this application is superior to the traditional method.

[0021] This application takes each debris flow basin as the analysis unit, and adopts the geographic detector model to detect the influence of each influencing factor on the development of debris flow, and uses the q value to represent the weight of the influencing factor. The value range is between 0-1. The larger the q value, the more obvious the stratified heterogeneity. Since the development of debris flow is the result of the joint action of various factors, the larger the q value, the stronger the explanatory power of the influencing factor on the development of debris flow, and vice versa. When q=1, it indicates that the influencing factor completely controls the development of debris flow; when q=0, it indicates that the development of debris flow is not affected by the factor.

[0022] In the S01: See also Figure 1 In some implementations, the influencing factor X value includes one or more of the average slope of the watershed, the longitudinal gradient of the channel, the watershed area, NDVI, the rainfall index, the density of the fault distribution line, the lithology, the land use type and the relative height difference.

[0023] Furthermore, the proportion of soft rock distribution area in the debris flow basin to the entire basin area is used to represent the lithology.

[0024] Furthermore, the proportion of cultivated land in the entire basin area was used to represent the land use type.

[0025] It can be understood that the occurrence of debris flow requires three conditions: terrain conditions - factors such as slope and longitudinal gradient to a certain extent characterize the terrain conditions that are conducive to water collection and material flow; material source conditions - fault distribution, lithology, etc. provide loose material sources for the occurrence of debris flow through physical effects and material supply; precipitation conditions - sufficient water sources; the influencing factor X value is obtained based on these three conditions.

[0026] In the S02: Understandably, and The two parameters are obtained based on field surveys, interviews and data collection.

[0027] It can be understood that the Y value of the traditional debris flow susceptibility evaluation model is limited to yes and no (1 or 0), which is difficult to reflect the development degree and disaster information of the debris flow, and highlight the individual differences of the debris flow. Therefore, this application proposes a new way of expressing the Y value, that is, using the product of the volume of the most recent debris flow outbreak and the debris flow outbreak frequency in the past 50 years as the Y value, instead of the traditional yes and no (1 or 0) expression.

[0028] In said S03: Furthermore, the influencing factor X value and the debris flow development degree Y value are input into the geographic detector, the weight of the influencing factor X value is extracted, and the main controlling factor F is screened out according to the debris flow development degree Y value.

[0029] In some implementations, each debris flow basin is used as an analysis unit, and a geographic detector model is used to detect the influence of each influencing factor X value on the development of debris flow, and the weight of the influencing factor X value is represented by the q value.

[0030] It can be understood that the value range of q is between 0 and 1. The larger the q value, the more obvious the stratified heterogeneity. Since the development of debris flow is the result of the combined effect of various influencing factors, the larger the q value, the stronger the explanatory power of the corresponding influencing factor on the development of debris flow, and vice versa. When q=1, it indicates that the influencing factor completely controls the development of debris flow; when q=0, it indicates that the development of debris flow is not affected by the influencing factor.

[0031] It can be understood that the method of combining geographic detectors with frequency ratios is adopted, in which the geographic detectors are mainly used to screen the main controlling factor F of debris flow. The geographic detector is a set of statistical methods to detect spatial heterogeneity and reveal the driving force behind it. The basic idea is: assuming that the study area is divided into several sub-regions, if the sum of the variances of the sub-regions is less than the total regional variance, there is spatial heterogeneity; assuming that the spatial distribution of a set of independent variables X and dependent variables Y tends to be consistent, the geographic detector can detect their statistical correlation, and then reveal the correlation between the two, measure spatial heterogeneity, detect explanatory factors, and then obtain the main controlling factor F.

[0032] It can be understood that the acquisition of the main control factor F needs to include topography, geological structure, rainfall and other environmental factors. Topography includes the average slope of the basin, the longitudinal gradient of the channel, the basin area and the relative height difference. The geological structure includes the density of fault distribution lines and lithology. The rainfall includes the rainfall index. Other environmental factors also include NDVI representing the vegetation coverage and the land use type representing the land use situation.

[0033] Furthermore, the main control factor F is introduced into the frequency ratio model to obtain the debris flow susceptibility index: .

[0034] It can be understood that the frequency ratio model analyzes the spatial relationship between debris flow distribution and various environmental factors, specifically: the ratio of the percentage of debris flow in a certain factor classification interval to the percentage of the basin in this interval to all basins in the study area.

[0035] Furthermore, the main control factor F is divided into n types or n levels, namely F i (i=1, 2, 3…, n), then F i The frequency ratio FR i Defined as: ; In the formula, Indicates that the known debris flow D The frequency, Indicates the debris flows to be evaluated in the study area. The frequency, Indicates that the known debris flow D The number of represents the total number of debris flows D, Indicates the debris flows to be evaluated in the study area. The total number of A Represents the total number of all debris flows to be evaluated in the study area.

[0036] For a certain study area, the frequency ratios of different types of main controlling factors of a debris flow D in the study area are added together to obtain the susceptibility index of the debris flow D. : ; In the formula, represents the susceptibility index, represents the number of master controlling factors, Indicates the frequency ratio of different types of main controlling factors; Same as above, the susceptibility index of all debris flows in the study area is obtained in turn .

[0037] In said S04: In some embodiments, the susceptibility index of all debris flows obtained is The method for classifying susceptibility levels is the natural breakpoint method.

[0038] It can be understood that the Natural Breaks method is a commonly used classification method, which is mainly used to segment continuous data (such as hazard index, disaster risk value, etc.) in order to more clearly express the internal structure and differences of the data. This method divides the data set into several groups by minimizing the intra-class differences and maximizing the inter-class differences, and defines each group as a different level. The calculation of the Natural Breaks method can be automatically completed using existing GIS tools (such as ArcGIS, QGIS, etc.) or statistical software (such as R language). For example, ArcGIS provides the option of directly using the Jenks Natural Breaks method for classification.

[0039] In a second aspect, the embodiment of the present application provides a debris flow susceptibility assessment system based on the frequency of the outbreak and the volume of the outflow, including: An impact factor X value module, used to provide an impact factor X value; The debris flow development degree Y value module is used to provide the debris flow development degree Y value. The calculation formula of the debris flow development degree Y value is as follows: ; In the formula, is the frequency of debris flow in the past 50 years, in times per year; The volume of the debris flow in the most recent outburst, in m 3 ; Debris flow susceptibility index The acquisition module is used to input the influencing factor X value and the debris flow development degree Y value into the geographic detector-frequency ratio model to obtain the susceptibility index of all debris flows ; The debris flow susceptibility evaluation result acquisition module is used to obtain the susceptibility index of all debris flows The susceptibility levels are classified and the debris flow susceptibility evaluation results are obtained.

[0040] In the impact factor X value module: See also Figure 1 In some implementations, the influencing factor X value includes one or more of the average slope of the watershed, the longitudinal gradient of the channel, the watershed area, NDVI, the rainfall index, the density of the fault distribution line, the lithology, the land use type and the relative height difference.

[0041] Furthermore, the proportion of soft rock distribution area in the debris flow basin to the entire basin area is used to represent the lithology.

[0042] Furthermore, the proportion of cultivated land in the entire basin area was used to represent the land use type.

[0043] It can be understood that the occurrence of debris flow requires three conditions: terrain conditions - factors such as slope and longitudinal gradient to a certain extent characterize the terrain conditions that are conducive to water collection and material flow; material source conditions - fault distribution, lithology, etc. provide loose material sources for the occurrence of debris flow through physical effects and material supply; precipitation conditions - sufficient water sources; the influencing factor X value is obtained based on these three conditions.

[0044] In the debris flow development degree Y value module: Understandably, and The two parameters are obtained based on field surveys, interviews and data collection.

[0045] It can be understood that the Y value of the traditional debris flow susceptibility evaluation model is limited to yes and no (1 or 0), which is difficult to reflect the development degree and disaster information of the debris flow, and highlight the individual differences of the debris flow. Therefore, this application proposes a new way of expressing the Y value, that is, using the product of the volume of the most recent debris flow outbreak and the debris flow outbreak frequency in the past 50 years as the Y value, instead of the traditional yes and no (1 or 0) expression.

[0046] The susceptibility index of all debris flows mentioned Get the module: Furthermore, the influencing factor X value and the debris flow development degree Y value are input into the geographic detector, the weight of the influencing factor X value is extracted, and the main controlling factor F is screened out according to the debris flow development degree Y value.

[0047] In some implementations, each debris flow basin is used as an analysis unit, and a geographic detector model is used to detect the influence of each influencing factor X value on the development of debris flow, and the weight of the influencing factor X value is represented by the q value.

[0048] It can be understood that the value range of q is between 0 and 1. The larger the q value, the more obvious the stratified heterogeneity. Since the development of debris flow is the result of the combined effect of various influencing factors, the larger the q value, the stronger the explanatory power of the corresponding influencing factor on the development of debris flow, and vice versa. When q=1, it indicates that the influencing factor completely controls the development of debris flow; when q=0, it indicates that the development of debris flow is not affected by the influencing factor.

[0049] It can be understood that the method of combining geographic detectors with frequency ratios is adopted, in which the geographic detectors are mainly used to screen the main controlling factor F of debris flow. The geographic detector is a set of statistical methods to detect spatial heterogeneity and reveal the driving force behind it. The basic idea is: assuming that the study area is divided into several sub-regions, if the sum of the variances of the sub-regions is less than the total regional variance, there is spatial heterogeneity; assuming that the spatial distribution of a set of independent variables X and dependent variables Y tends to be consistent, the geographic detector can detect their statistical correlation, and then reveal the correlation between the two, measure spatial heterogeneity, detect explanatory factors, and then obtain the main controlling factor F.

[0050] Furthermore, the main control factor F is introduced into the frequency ratio model to obtain the debris flow susceptibility index: .

[0051] It can be understood that the frequency ratio model analyzes the spatial relationship between debris flow distribution and various environmental factors, specifically: the ratio of the percentage of debris flow in a certain factor classification interval to the percentage of the basin in this interval to all basins in the study area.

[0052] Furthermore, the main control factor F is divided into n types or n levels, namely F i (i=1, 2, 3…, n), then F i The frequency ratio FR i Defined as: ; In the formula, Indicates that the known debris flow D The frequency, Indicates the debris flows to be evaluated in the study area. The frequency, Indicates that the known debris flow D The number of represents the total number of debris flows D, Indicates the debris flows to be evaluated in the study area. The total number of A Represents the total number of all debris flows to be evaluated in the study area.

[0053] For a certain study area, the frequency ratios of different types of main controlling factors of a debris flow D in the study area are added together to obtain the susceptibility index of the debris flow D. : ; In the formula, represents the susceptibility index, represents the number of master controlling factors, Indicates the frequency ratio of different types of main controlling factors; Same as above, the susceptibility index of all debris flows in the study area is obtained in turn .

[0054] In the debris flow susceptibility assessment result acquisition module: In some embodiments, the susceptibility index of all debris flows obtained is The method for classifying susceptibility levels is the natural breakpoint method.

[0055] It can be understood that the Natural Breaks method is a commonly used classification method, which is mainly used to segment continuous data (such as hazard index, disaster risk value, etc.) in order to more clearly express the internal structure and differences of the data. This method divides the data set into several groups by minimizing the intra-class differences and maximizing the inter-class differences, and defines each group as a different level. The calculation of the Natural Breaks method can be automatically completed using existing GIS tools (such as ArcGIS, QGIS, etc.) or statistical software (such as R language). For example, ArcGIS provides the option of directly using the Jenks Natural Breaks method for classification.

[0056] In a third aspect, the present application provides a computer device including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the above-mentioned method for evaluating debris flow susceptibility based on outbreak frequency and outflow volume.

[0057] The computer device may be a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with the user through a keyboard, a mouse, a remote control, a touch pad, or a voice control device.

[0058] The memory includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or D interface display memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory can be an internal storage unit of the computer device, such as a hard disk or memory of the computer device. In other embodiments, the memory can also be an external storage device of the computer device, such as a plug-in hard disk equipped on the computer device, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), etc. Of course, the memory can also include both the internal storage unit of the computer device and its external storage device. In this embodiment, the memory is often used to store the operating system and various application software installed on the computer device, such as the program code of the debris flow scale-frequency calculation method based on disaster history data, etc. In addition, the memory can also be used to temporarily store various types of data that have been output or are to be output.

[0059] The processor may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor is generally used to control the overall operation of the computer device. In the present embodiment, the processor is used to run the program code or process data stored in the memory, such as running the program code of the debris flow susceptibility evaluation method based on the frequency of the outbreak and the volume of the outflow.

[0060] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the above-mentioned method for evaluating the susceptibility of debris flows based on outbreak frequency and outflow volume.

[0061] Among them, the computer-readable storage medium stores an interface display program, and the interface display program can be executed by at least one processor to enable the at least one processor to perform the steps of the above-mentioned debris flow susceptibility assessment method based on outbreak frequency and flushing volume.

[0062] Test example The Yunnan section of the Nujiang River is one of the areas with the most developed debris flow disasters in Yunnan Province, and it is also one of the areas with the most developed debris flow disasters in southwest my country. Debris flow events occur frequently, with a total of 134 major debris flow events from 1950 to 2021. The hydrological analysis results based on the GIS platform show that there are 233 first-level tributary valleys in the Nujiang River, including 95 debris flow basins obtained through field surveys. This test case refers to a large number of influencing factors used in the evaluation of debris flow susceptibility. Combined with the geological environment characteristics of the Nujiang River basin, the experience of field investigations, and the difficulty of data acquisition, 9 influencing factors were selected, including the average slope of the basin, the longitudinal gradient of the channel, the basin area, NDVI (normalized vegetation index), the rainfall index, the density of fault distribution lines, lithology, land use type, and relative height difference. Figure 1 . Figure 1 In the figure, a-basin horizontal slope; b-basin relative height difference; c-basin area; d-basin longitudinal gradient; e-average vegetation coverage NDVI; f-land use type; g-basin average rainfall; h-basin fault line density; I-lithology.

[0063] The debris flow development degree Y value is compared by two methods, one is the traditional yes and no (1 or 0) expression Y1, and the other is the expression Y2 of the product of the latest debris flow outburst volume and the frequency of outbursts within 50 years; First, the X values ​​of 95 debris flows and their corresponding classification values ​​were extracted, and their Y1 and Y2 values ​​were extracted. Taking the Qiunatong debris flow located in the northernmost part of the basin as an example, the 9 influencing factor X values ​​and corresponding classification values ​​corresponding to the debris flow, as well as the values ​​of Y1 and Y2 are shown in Table 1.

[0064] Table 1 Values ​​of independent variables, classification and dependent variables of Qiunatong debris flow

[0065] All X values, traditional Y1, and all X values, Y2 of the present invention are input into the geographic detector respectively, and the weights of 9 influencing factors are obtained respectively. And for traditional Y1 and Y2 of the present invention, 6 main control factors F1 and F2 are screened out respectively, as shown in Table 2 and Table 3, Table 2 Results of the main controlling factors F1 obtained through the geographic detector based on Y1

[0066] Table 3 Results of the main controlling factors F2 obtained through the geographic detector based on Y2

[0067] As can be seen from Table 2 and Table 3, the results of F1 show the average slope, elevation difference, longitudinal gradient, average NDVI, average rainfall, and average fracture density, while the results of F2 show the average slope, elevation difference, basin area, longitudinal gradient, average NDVI, and cultivated land ratio. It can be seen that there are obvious differences between F1 and F2. Since the X values of the input samples are the same, the reason for the difference mainly comes from the change of the Y value.

[0068] Divide the above main control factor F (main control factor F1 or main control factor F2) into n types or n levels, which are F i (i = 1, 2, 3…, n). For example, the average slope of the gully is divided into 8 levels, that is, n = 8. Then, according to the aforementioned frequency ratio calculation method, obtain the frequency ratio of each classification F i as shown in Table 4.

[0069] Furthermore, use the same method to obtain the frequency ratio results of all the main control factors corresponding to 233 debris flows in the whole region.

[0070] Table 4 Classification of the average slope of the main control factor in the frequency ratio model

[0071] This application establishes a historical event database of debris flows in the Yunnan section of the main stream of the Nujiang River to the greatest extent through data collection, remote sensing interpretation, field investigation, and on-site visits, and uses this as the judgment basis for evaluating the accuracy of the susceptibility results of Y1 and Y2 values.

[0072] It can be understood that the development situation of debris flows obtained based on field investigations is the most reliable basis for determining whether the susceptibility degree of debris flows is reasonable.

[0073] Based on the traditional yes / no expression method (Y1 value), obtain the susceptibility results of debris flows in the first-level tributary valleys of the main stream of the Nujiang River, and use the susceptibility index p of each watershed unit as an indication, that is, the probability of debris flow occurrence predicted by the frequency ratio model. Through ArcGIS10.8 software, divide the debris flow susceptibility into five categories: extremely high susceptibility ( ), high susceptibility ( ), medium susceptibility ( ), low susceptibility ( ), and extremely low susceptibility ( ), and generate the debris flow susceptibility evaluation map ( Figure 2 ) of the study area under the Y1 value method. Among them, there are 26 watersheds with extremely high susceptibility, 33 watersheds with high susceptibility, 31 watersheds with medium susceptibility, and 143 watersheds with low susceptibility.

[0074] After the debris flow susceptibility evaluation model based on the expression of the product of the one-time outflow volume and the frequency of outbreaks within 50 years (Y2 value) is running normally, the debris flow susceptibility result S2 of the study area can be calculated. Similarly, the susceptibility index p of each watershed unit is used as an indicator, and the susceptibility level is divided according to the method consistent with the above, and the debris flow susceptibility evaluation map of the study area under the Y2 value method is generated ( Figure 3 ). Among them, there are 32 basins with extremely high risk, 42 ​​basins with high risk, 21 basins with medium risk, and 138 basins with low risk.

[0075] The debris flow susceptibility evaluation results based on the two Y values ​​were compared, and the two susceptibility results were compared with the actual situation of the debris flow field investigation in the Nujiang River Basin ( Figure 3 ). Although the results of the two susceptibility assessments are high in the basin ( Figure 2 , Figure 3 ) and the results of the field survey ( Figure 4 ) are not completely consistent, but it can be clearly concluded that the susceptibility results of the model with the new invention Y2 value of this application, the number of basins with high susceptibility is roughly equal to the result of the actual field investigation, while the susceptibility results obtained by the model with the traditional method as the Y value are only 59 basins with high susceptibility, which is much less than the result of the field investigation.

[0076] On the other hand, by visually comparing the spatial distribution of extremely high-probability watersheds obtained by the two models, it is obvious that the spatial distribution results of high-probability watersheds obtained by the model based on the new invention of this application are closer to the results of actual field investigations, especially in the areas around Lushui County, which also shows the superiority of the new invention of this patent over traditional methods.

[0077] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A debris flow susceptibility assessment method based on the frequency of occurrence and the volume of debris flow, characterized in that: include: Provide impact factor X value; Provide the debris flow development degree Y value, the calculation formula of the debris flow development degree Y value is as follows: ； In the formula, is the frequency of debris flow in the past 50 years, in times per year; The volume of the debris flow in the most recent outburst, in m 3 ; The influence factor X value and debris flow development degree Y value are input into the geographic detector-frequency ratio model to obtain the susceptibility index of all debris flows. ; The susceptibility index of all debris flows obtained The susceptibility levels are classified and the debris flow susceptibility evaluation results are obtained.

2. The debris flow susceptibility assessment method based on the frequency and volume of debris flow according to claim 1 is characterized in that: The influencing factor X value includes one or more of the average slope of the basin, the longitudinal gradient of the channel, the basin area, NDVI, the rainfall index, the density of the fault distribution line, the lithology, the land use type and the relative height difference.

3. The debris flow susceptibility assessment method based on the frequency and volume of debris flow according to claim 2, characterized in that: The proportion of soft rock distribution area in the debris flow basin to the entire basin area is used to represent the lithology; and / or the proportion of cultivated land area to the entire basin area is used to represent the land use type.

4. The debris flow susceptibility assessment method based on the frequency and volume of debris flow according to claim 1, characterized in that: The influencing factor X value and the debris flow development degree Y value are input into the geographic detector, the weight of the influencing factor X value is extracted, and the main controlling factor F is screened out according to the debris flow development degree Y value.

5. The debris flow susceptibility assessment method based on the frequency and volume of debris flow according to claim 4, characterized in that: Each debris flow basin is taken as the analysis unit, and the geographic detector model is used to detect the influence of each influencing factor X value on the development of debris flow, and the q value represents the weight of the influencing factor X value.

6. The debris flow susceptibility assessment method based on the frequency and volume of debris flow according to claim 4, characterized in that: Substituting the main control factor F into the frequency ratio model, we can get the debris flow susceptibility index: .

7. The debris flow susceptibility assessment method based on the frequency and volume of debris flow according to claim 6, characterized in that: The main control factor F is divided into n types or n levels, namely F i (i=1, 2, 3…, n), then F i The frequency ratio FR i Defined as: ； In the formula, Indicates that the known debris flow D The frequency, Indicates the debris flows to be evaluated in the study area. The frequency, Indicates that the known debris flow D The number of represents the total number of debris flows D, Indicates the debris flows to be evaluated in the study area. The total number of A It represents the total number of all debris flows to be evaluated in the study area; For a certain study area, the frequency ratios of different types of main controlling factors of a debris flow D in the study area are added together to obtain the susceptibility index of the debris flow D. : ； In the formula, represents the susceptibility index, represents the number of master controlling factors, Indicates the frequency ratio of different types of main controlling factors; Same as above, the susceptibility index of all debris flows in the study area is obtained in turn .

8. The debris flow susceptibility assessment system based on the frequency and volume of debris flow is characterized by: include: An impact factor X value module, used to provide an impact factor X value; The debris flow development degree Y value module is used to provide the debris flow development degree Y value. The calculation formula of the debris flow development degree Y value is as follows: ； In the formula, is the frequency of debris flow in the past 50 years, in times per year; The volume of the debris flow in the most recent outburst, in m 3 ; Debris flow susceptibility index The acquisition module is used to input the influencing factor X value and the debris flow development degree Y value into the geographic detector-frequency ratio model to obtain the susceptibility index of all debris flows ; The debris flow susceptibility evaluation result acquisition module is used to obtain the susceptibility index of all debris flows The susceptibility levels are classified and the debris flow susceptibility evaluation results are obtained.

9. Computer device, characterized in that The invention comprises a storage and a processor, wherein the storage stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that A computer program is stored, and when the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 7.

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