WO2019073937A1

WO2019073937A1 - Risk evaluation system

Info

Publication number: WO2019073937A1
Application number: PCT/JP2018/037473
Authority: WO
Inventors: 雄騎松四; 清孝内田; 川崎　栄嗣; 真仁菊田
Original assignee: 日本信号株式会社; 国立大学法人京都大学
Priority date: 2017-10-10
Filing date: 2018-10-05
Publication date: 2019-04-18
Also published as: TW201928400A; JP2019070961A; TWI802599B; JP6941319B2

Abstract

The purpose of the present invention is to identify a region having a high probability of experiencing the occurrence of a life-threatening sediment disaster due to rainfall. Provided is a risk evaluation system comprising: a sediment productivity index calculation unit 1106 which calculates a sediment productivity index indicating a sediment productivity with respect to each of cells to be monitored in a sediment collapse monitoring region which is a region including an infrastructural risk evaluation cell and a plurality of cells to be monitored; an arrival probability index calculation unit 1107 which, with respect to each of the cells to be monitored, calculates an arrival probability index indicating the probability of arrival of collapsed sediment to the risk evaluation cell; and an infrastructural risk index calculation unit 1109 which calculates, using the sediment productivity index and the arrival probability index with respect to each of the cells to be monitored, an infrastructural risk index indicating the probability of the risk evaluation cell being subjected to a damage from collapsed sediment. The risk index and a threshold value are compared to evaluate a sediment disaster occurrence risk in the risk evaluation cell.

Description

Risk assessment system

The present invention relates to a technology for evaluating the risk of landslide caused by rainfall.

Landslides caused by rainfall can cause life-threatening damage. Then, in order to reduce the damage of the landslide, the risk of the landslide caused by rainfall is specified, and when the risk is increased, a technique for notifying that effect has been proposed.

For example, in Patent Document 1, the processing apparatus wirelessly receives rainfall information measured by a rain gauge installed in the observation area, and calculates the moisture content in the soil in consideration of the geographical condition of the observation area, A mechanism for making a notification based on the calculated water content is described.

In addition, based on the rainfall, the patent document 2 determines the sediment water level at the upper end of the danger area where the occurrence of the landslide disaster is assumed and indicates that the possibility of the occurrence of the landslide disaster is high based on rainfall. In the light of the estimated water level at the point, a mechanism is identified to identify a high alert area for landslide disaster occurrence.

JP 10-232286 A JP, 2016-122239, A

If rainfall continues for a long period, all areas receiving rainfall will be regarded as dangerous areas to monitor landslides, or banning people from entering all areas will avoid risks and risks. It is not realistic because it is not balanced with the cost.

If it is possible to identify an area where landslide disasters likely to cause human life are likely to occur, risk should be avoided efficiently by intensively monitoring the area or prohibiting the entry of people only in that area. Can.

SUMMARY OF THE INVENTION In view of the above-described circumstances, the present invention provides a means for identifying an area where there is a high possibility that landslides that cause human life may occur due to rainfall.

In order to solve the problems described above, according to the present invention, a region including a risk assessment cell and a plurality of monitoring target cells is used as a monitoring region of landslide, and sediment productivity for each monitoring target cell and each monitoring target cell The risk evaluation system for evaluating the risk of occurrence of landslide disaster in the risk evaluation cell is provided as a first aspect based on the reachability of the fallen soil to the risk evaluation cell.

According to the degree-of-risk evaluation system according to the first aspect described above, it is possible to know the risk of landslide disaster occurrence at a certain point.

In the risk assessment system according to the first aspect, with respect to each of the plurality of monitoring target cells, a gradient of each of the plurality of cells configuring an area including the monitoring region and a region supplying water flowing into the cell The index using the ratio between the gradient according to the area of the water collection area of the monitoring target cell and the gradient of the monitoring target cell calculated according to the regression equation that approximates the relationship with the area of the water collection area The configuration of using as a sediment productivity index indicating sediment productivity for each of the monitoring target cells may be adopted as a second aspect.

In the risk evaluation system according to the first aspect, regarding each of the plurality of monitoring target cells, the height difference between the monitoring target cell and the risk evaluation cell, and the horizontal distance between the monitoring target cell and the risk evaluation cell A configuration may be adopted as a third aspect in which an index using the ratio of and is used as a reachability index indicating the reachability of the fallen soil for each monitoring target cell to the risk evaluation cell. .

In the risk evaluation system according to the second aspect, regarding each of the plurality of monitoring target cells, the height difference between the monitoring target cell and the risk evaluation cell, and the horizontal distance between the monitoring target cell and the risk evaluation cell A configuration in which an index using the ratio of and is used as a reachability index indicating the reachability of the fallen soil for each monitoring target cell to the risk evaluation cell may be adopted as a fourth aspect .

In the risk evaluation system according to the fourth aspect, the risk is calculated based on a statistic of an index calculated using the sediment productivity index and the reachability index for each of the plurality of monitoring target cells. A configuration of evaluating the risk of occurrence of landslide disaster in the evaluation cell may be adopted as a fifth aspect.

According to the risk evaluation system according to the above-described second to fifth aspects, the landslide disaster occurrence risk at a certain point in the area can be known by the digital elevation model of the area including the monitoring area.

In the risk rating system according to any one of the above first to fifth aspects, with respect to each of a plurality of cells on an infrastructure, the risk of occurrence of earth and sand disaster when the cell is the risk assessment cell is evaluated. According to the sixth aspect, the configuration may be adopted in which a dangerous cell on the infrastructure is identified.

According to the degree-of-risk evaluation system according to the sixth aspect described above, it is possible to find out the area where the risk of landslide disaster occurrence is high in the infrastructure where there are many people entering.

In the risk rating system according to any one of the first to sixth aspects, the occurrence time of landslide in the monitoring area is estimated based on the temporal change of rainfall amount in the area including the monitoring area. The configuration may be adopted as a seventh aspect.

According to the degree-of-risk evaluation system according to the seventh aspect described above, it is possible to know the time when the risk of landslide disaster increases.

Further, according to the present invention, there is provided a computer-implemented sediment productivity index, which is an index indicating sediment productivity for each of the monitoring target cells, in a monitoring area of landslides consisting of a plurality of monitoring target cells including risk assessment cells; A program for calculating an index indicating a risk of occurrence of a landslide disaster in the risk evaluation cell based on a reachability index that is an index indicating the reachability of the fallen soil for each target cell to the risk evaluation cell is Provided as an aspect of

According to the program of the eighth aspect, the computer realizes the degree-of-risk evaluation system of the first aspect.

BRIEF DESCRIPTION OF THE DRAWINGS The figure which showed the whole structure of the danger degree evaluation system which concerns on one Embodiment. The figure showing the composition of the computer used as hardware of the terminal unit concerning one embodiment. The figure showing the composition of the computer used as hardware of the server apparatus concerning one embodiment. The figure showing the functional composition of the terminal unit concerning one embodiment. The figure which showed the relationship of the danger evaluation cell which the terminal device which concerns on one Embodiment specifies, and a monitoring area | region. The figure which illustrated the information which the indicator concerning one embodiment displays. The figure which illustrated the information which the indicator concerning one embodiment displays. The figure showing the functional composition of the terminal unit concerning one embodiment. The figure which illustrated the information which the indicator concerning one embodiment displays.

[Embodiment]
Hereinafter, the risk evaluation system 1 according to the embodiment of the present invention will be described. The risk assessment system 1 notifies the user of the area where the risk of landslide disaster occurrence due to rainfall is high among infrastructures such as railways in the target area, and the time when the landslide disaster is estimated to occur Is a system for notifying the user.

FIG. 1 is a view showing the entire configuration of the risk level evaluation system 1. The risk level evaluation system 1 is used by the user to generate information to notify the user, and the terminal device 11 to notify the user of the generated information, and the terminal device 11 to the terminal device 11 the history of the temporal change of the rainfall amount in the target area The server device 12 distributes rainfall amount data indicating values and estimated values. The terminal device 11 and the server device 12 are communicably connected via a network.

The hardware of the terminal device 11 and the server device 12 is a computer. FIG. 2 is a diagram showing the configuration of the computer 10 used as the hardware of the terminal device 11. FIG. 3 is a diagram showing the configuration of the computer 20 used as the hardware of the server device 12.

The computer 10 includes a memory 101 for storing various data, a processor 102 for performing various data processing in accordance with a program stored in the memory 101, a communication unit 103 for performing data communication with an external device, and various users. A display 104 for displaying information and a keyboard 105 for receiving data input operation of a user are provided. Note that at least one of the display 104 and the keyboard 105 may not be built in the computer 10, and may be connected to the computer 10 as an external device.

The computer 20 includes a memory 201 for storing various data, a processor 202 for performing various data processing in accordance with a program stored in the memory 201, and a communication unit 203 for performing data communication with an external apparatus.

When the processor 202 performs various data processing in accordance with the program stored in the memory 201, the computer 20 operates as the server device 12 for distributing rainfall amount data to the terminal device 11. The functional configuration of the server device 12 is the same as the functional configuration of the server device that performs general data distribution, and thus the description thereof is omitted.

FIG. 4 is a diagram showing a functional configuration for performing processing for notifying the user of a place where the risk of occurrence of earth and sand disaster is high among the functional configurations of the terminal device 11. The functional configuration shown in FIG. 4 will be described below.

The storage unit 111 is mainly realized by the memory 101 and stores various data. The storage unit 111 stores in advance numerical elevation model data indicating a numerical elevation model of the target area, and route data indicating a passing position of a railway (an example of infrastructure) in the target area. The storage unit 111 also stores various data generated by the calculation unit 110 described below.

The operation unit 110 is mainly realized by the processor 102 and performs various operations. The calculation unit 110 includes a water collection area calculation unit 1101 that calculates a water collection area of each of a plurality of cells forming the target area. In the present application, the cell means each of a plurality of rectangular areas of a predetermined size obtained by dividing the target area. The water collection area of a cell is the area of a water collection area which is an area for supplying water flowing into the cell. The water collection area calculation unit 1101 calculates the water collection area of each cell in the target area by known topographical hydrological analysis using the digital elevation model indicated by the digital elevation model data. Data indicating the water collection area of each cell calculated by the water collection area calculation unit 1101 is stored in the storage unit 111 as water collection area data.

The calculation unit 110 includes a gradient calculation unit 1102 that calculates the gradient of each cell in the target area. The gradient calculation unit 1102 performs spatial differentiation of the digital elevation model indicated by the digital elevation model data, and calculates the gradient of each cell in the target area. Data indicating the gradient of each cell calculated by the gradient calculation unit 1102 is stored in the storage unit 111 as gradient data.

The calculation unit 110 includes a regression equation identification unit 1103 that identifies a regression equation indicating a combination of a water collection area and a gradient that brings about a standard soil erosion ease in the target area. The regression equation identification unit 1103 associates the water collection area indicated by the water collection area data with the gradient indicated by the gradient data for each cell in the target area, and sets of the correlated water collection area and the gradient are used as samples. The regression equation is specified by regression analysis for the target population.

In the present embodiment, the regression equation identified by the regression equation identifying unit 1103 has the structure of Equation 1 below.

However, S is a gradient (unit: m / m) and A _f is a water collection area (unit: m ² ). Also, B and p are constants determined by the characteristics of the soil in the target area, and are identified by regression analysis.

Equation 1 is derived from Equation 2 below.

However, E is the erosion rate of soil (unit: m / yr), K is the erosion efficiency of soil (unit: eg yr ⁻¹ (depends on the power number m)). Also, m and n are numerical values (m> 0, n> 0) indicating the weighting of the water collection area A _f and the slope S. As shown in Equation 2, it is known that the erosion rate of soil has a relationship approximately proportional to the product of the slope and the power of the water collection area. The constant of equation 1 and the constant of equation 2 have the relationships shown in equations 3 and 4 below.

Data indicating the regression equation identified by the regression equation identifying unit 1103 is stored in the storage unit 111 as regression equation data.

The calculation unit 110 includes a risk evaluation cell extraction unit 1104 that extracts a cell through which the railway passes from among cells in the target area as a risk evaluation cell. The risk evaluation cell extraction unit 1104 extracts a risk evaluation cell based on the route data. Data indicating the danger evaluation cell extracted by the danger evaluation cell extraction unit 1104 is stored in the storage unit 111 as danger evaluation cell data.

The calculation unit 110 includes a monitoring area specifying unit 1105 that specifies a water collection area of the risk evaluation cell as a monitoring area for each of the risk evaluation cells. The monitoring area specifying unit 1105 specifies a water collection area by known topographical hydrological analysis for each of the risk evaluation cells using the digital elevation model indicated by the digital elevation model data, and identifies the specified water collection area as the risk evaluation cell. And monitoring area. Hereinafter, cells in the monitoring area are referred to as monitoring target cells.

Figure 5 is a diagram showing one and risk assessment cell P _i on line r in the target area U, the monitoring area Q _i of the risk assessment cell P _i. Data indicating the monitoring area of each risk assessment cell specified by the monitoring area specifying unit 1105 is stored in the storage unit 111 as monitoring area data.

Arithmetic unit 110 (FIG. 4) relates to sediment productivity for each monitoring target cell in the monitoring area specified by monitoring area specifying unit 1105 for each of the plurality of risk evaluation cells extracted by risk evaluation cell extracting unit 1104. The sediment productivity index calculation unit 1106 is provided to calculate the sediment productivity index, which is an index indicating.

In the present embodiment, the sediment productivity index calculation unit 1106 calculates the sediment productivity index SAI according to the following equation 5.

However, S _local is the gradient of the monitoring object cell which gradient data show, A _flocal is the water collection area of the monitoring area which water collection area data show. Further, S (A _flocal ) is a gradient corresponding to the water collection area A _flocal of the monitoring area, which is calculated according to the regression equation (Equation 1) represented by the regression data.

Data indicating the sediment productivity index SAI for each monitoring target cell of each risk evaluation cell calculated by the sediment productivity index calculation unit 1106 is stored in the storage unit 111 as sediment productivity index data.

For each of the monitoring target cells in the monitoring area identified by the monitoring area identifying unit 1105, the computing unit 110 relates to each of the plurality of danger assessment cells extracted by the risk assessment cell extracting unit 1104; A reachability indicator calculation unit 1107 is provided which calculates a reachability indicator that is an indicator indicating the reachability of the terminal.

In the present embodiment, the reachability index calculation unit 1107 calculates the reachability index IEFC in accordance with Equation 6 below.

However, H _S is the height (unit: m) of the monitoring target cell based on the hazard evaluation cell indicated by the digital elevation model data, that is, the value obtained by subtracting the height of the hazard evaluation cell from the height of the monitoring target cell is there. L is a horizontal distance (unit: m) indicated by the digital elevation model data and indicating the danger evaluation cell and the monitoring target cell.

Data indicating the reachability index IEFC of each of the monitoring target cells of each risk evaluation cell calculated by the reachability index calculation unit 1107 is stored in the storage unit 111 as reachability index data.

The calculation unit 110 can reach the danger evaluation cell for each of the monitoring target cells in the monitoring area specified by the monitoring area specifying unit 1105 for each of the plurality of danger evaluation cells extracted by the risk evaluation cell extraction unit 1104. A hazard index calculation unit 1108 that calculates a hazard index that is an index indicating productivity of fallen soil is provided.

In the present embodiment, the hazard index calculation unit 1108 calculates the hazard index TGI according to the following equation 7.

Data indicating the hazard index TGI for each monitoring target cell of each hazard evaluation cell calculated by the hazard index calculation unit 1108 is stored in the storage unit 111 as hazard index data.

The calculation unit 110 calculates an infrastructure risk index for calculating the statistics of the hazard index TGI calculated by the hazard index calculation unit 1108 for each of the plurality of danger evaluation cells extracted by the danger evaluation cell extraction unit 1104 as an infrastructure risk index. A unit 1109 is provided.

In the present embodiment, the infrastructure risk index calculator 1109 calculates an arithmetic mean of the hazard indexes TGI as the infrastructure risk index SLPR. Data indicating the infrastructure risk indicator SLPR calculated for each risk evaluation cell by the infrastructure risk indicator calculation unit 1109 is stored in the storage unit 111 as infrastructure risk indicator data.

The display unit 112 is mainly realized by the display 104, and displays information indicated by various data generated by the calculation unit 110 and stored in the storage unit 111. 6 and 7 are diagrams exemplifying information displayed by the display unit 112. FIG.

FIG. 6 shows a hazard map displayed by the display unit 112. In the hazard map illustrated in FIG. 6, among the hazard evaluation cells on the line r in the target area U, the hazard evaluation cells P ₁ , P ₂ , P ₃ are regarded as hazard evaluation cells in which the infrastructure risk indicator SLPR is greater than or equal to a predetermined threshold. Is illustrated. Further, in the hazard map illustrated in FIG. 6, among the monitoring target cells included in the monitoring areas Q ₁ , Q ₂ and Q ₃ corresponding to each of the risk assessment cells P ₁ , P ₂ and P ₃ , the hazard index TGI is Monitored cells above a predetermined threshold are indicated by crosses.

The user sees the hazard map, and can know a place susceptible to landslide disasters on the track r and a place prone to landslides causing landslide disasters in the target area.

FIG. 7 shows a along-line risk line displayed by the display unit 112. The risk line along the road has a horizontal axis representing the distance from the predetermined reference point on the line r to the risk evaluation cell on the line r (distance along the line r), and the infrastructure of the risk evaluation cell according to the distance shown on the horizontal axis. It is the graph which plotted risk index SLPR on the vertical axis. The user can see the risk line along the road and know the susceptibility of each point on the track r to landslide disaster.

FIG. 8 is a diagram showing a functional configuration for performing processing for notifying the user of the time at which it is estimated that earth and sand fall will occur among the functional configurations of the terminal device 11. The terminal device 11 includes a receiving unit 113 that receives rainfall data from the server device 12 in addition to the storage unit 111, the arithmetic unit 110, and the display unit 112 described above as a configuration unit for estimating occurrence time of landslide. . The receiving unit 113 is mainly realized by the communication unit 103.

The calculation unit 110 includes a pressure head calculation unit 1110, a stability index calculation unit 1111, and an occurrence time estimation unit 1112 as a component for estimating the occurrence time of landslide.

The pressure head calculation unit 1110 calculates the time t (that is, the time when time t (unit: s) has elapsed from the rainfall start time) based on the rainfall start time according to the following equation 8 for each of the cells in the target area Calculate the pressure head (t) (unit: m) at. The following equation 8 is a model equation proposed in a paper "Landslide triggering by rain infiltration" published in 2000 by Richard M. Iverson.

However, t ^* is a value shown by the following equation 9.

However, D ₀ is a diffusion coefficient (unit: m ² / s), α is a slope inclination angle (unit: deg), and Z is a depth (unit: m).

Moreover, T ^* is a value shown by the following equation 10.

Where T is the rainfall duration (unit: s).

Ψ0 is the initial value of pressure head, I _Z is the rainfall intensity (unit: m / s), K _Z is the permeability coefficient in the depth direction (m / s), R (t ^* ) is x in the following equation 11 A value obtained by substituting t ^* into R, and R (t ^* -T ^* ) is a value obtained by substituting (t ^* -T ^* ) into x in the following Expression 11.

Data indicating the pressure head (t) at time t for each cell calculated by the pressure head calculation unit 1110 is stored in the storage unit 111 as pressure head data.

In the storage unit 111, as data used by the pressure head calculation unit 1110 to calculate the pressure head (t) at time t of each cell, diffusion coefficient data indicating the diffusion coefficient D ₀ , slope inclination angle α of each cell slope inclination angle data indicating the depth data indicating the depth Z of each cell, rainfall intensity data indicating the rainfall intensity I _Z, permeability data indicating the permeability K _Z in the depth direction, rain indicating rainfall duration T Duration data is stored.

The diffusion coefficient D ₀ indicated by the diffusion coefficient data and the water permeability coefficient K _Z indicated by the permeability coefficient data are values specified by fitting of the hydrological observation values at representative points in the target area with the model equation shown in Equation 8. is there.

The slope inclination angle α of each cell indicated by the slope inclination data and the depth Z of each cell indicated by the depth data are values specified based on the digital elevation model data.

The rainfall intensity I _Z indicated by the rainfall intensity data and the rainfall duration T indicated by the rainfall duration data are values specified based on the rainfall amount data received by the receiving unit 113 from the server device 12.

The initial value ψ ₀ of the pressure head used by the pressure head calculation unit 1110 to calculate the pressure head (t) at time t is the pressure head at the rainfall start time indicated by the pressure head data.

The stability index calculator 1111 calculates the slope stability index F _S at time t according to the following equation 12 for each of the cells in the target area. Equation 12 below is a calculation equation proposed in the paper "Stability of Natural Slopes in London Clay" published in 1957 by A. W. Skempton and F. A. Delory.

Where c is the adhesion of the soil layer (unit: kPa), Δc is the increase in adhesion by the tree root system (unit: kPa), γ is the saturation unit weight of the soil layer (unit: N / m ³ ), γ _W Is a unit weight of water (unit: N / m ³ ), h is a soil layer thickness (unit: m), α is a slope inclination angle (unit: deg), and φ is a shear resistance angle (unit: deg).

Moreover, m is a groundwater level parameter (ratio of pressure head to soil layer thickness h) calculated according to the following equation 13.

The slope stability index F _S indicates that the slope is stable if it is 1 or more and that landslide does not occur. If the slope stability index F _S is less than 1, it indicates that the slope is unstable and landslide occurs.

In the storage unit 111, as data used by the stability index calculation unit 1111 to calculate the slope stability index F _S at time t of each cell, adhesion data indicating the adhesion c of the soil layer, soil by the tree root system Adhesion force increase data showing increase amount Δc of layer adhesion, saturation unit weight data showing saturation unit weight γ of soil layer, unit weight data showing unit weight γ _{W of} water, soil layer thickness h of each cell The stored soil layer thickness data, the slope inclination angle data indicating the slope inclination angle α of each cell, and the shear resistance angle data indicating the shear resistance angle φ are stored.

The adhesion force c of the soil layer indicated by the adhesion data, the saturation unit weight γ of the soil layer indicated by the saturation unit weight data, and the shear resistance angle φ indicated by the shear resistance angle data are performed using samples taken from within the target area It is the value specified by the shear test etc. Adhesion increase amount Δc of the soil layer indicated by the adhesion increase amount data is empirically determined by the number density and root diameter distribution of the plant root system as a function of depth in the soil layer and the reverse analysis of the past disaster cases Value.

The slope inclination angle α of each cell indicated by the slope inclination angle data is a value specified based on digital elevation model data.

The soil layer thickness h of each cell indicated by the soil layer thickness data is a value calculated by substituting the slope curvature C specified based on the digital elevation model data into the following equation 14.

However, h ₀ is the soil layer thickness of the flat plate type slope portion inclined curvature C is 0, a is an exponential factor.

The index coefficient a in Equation 14 represents, for each of a plurality of cells randomly selected from the target area, a combination of the slope curvature C specified based on the digital elevation model data and the measured value of the soil layer thickness h as a sample Use the values specified by regression analysis for the target population. Although the function used to estimate the soil layer thickness h from the slope curvature C can be obtained by regression analysis, the type of the function is not limited to the exponential function illustrated in Equation 14, and the significance of the soil slope layer h from the slope curvature C For example, any type of function such as a linear function, a polynomial function, or a power function may be used as long as it is possible to derive an estimated value.

Data indicating the slope stability index F _S at time t for each cell calculated by the stability index calculation unit 1111 is stored in the storage unit 111 as slope stability index data.

The occurrence time estimation unit 1112 determines the time when the slope stability index data becomes less than 1 for each of the monitoring target cells included in the monitoring area according to each of the risk evaluation cells in which the infrastructure risk indicator SLPR is equal to or more than a predetermined threshold. It is estimated as the time when a landslide occurs in the monitoring target cell.

The display unit 112 displays the occurrence location and occurrence time of the landslide that is estimated by the occurrence time estimation unit 1112. FIG. 9 is a view exemplifying a hazard map displayed by the display unit 112. In the hazard map illustrated in FIG. 9, in addition to the information included in the hazard map illustrated in FIG. 6, places and times at which occurrence of landslides is estimated are displayed.

The user may look at the hazard map to know at which location and at which time the landslide will occur in the monitoring area that may cause the fallen soil to a location susceptible to landslide disasters on the track r. it can.

[Modification]
The present invention may be implemented in a form different from the embodiment described above. Below, the modification of embodiment mentioned above is shown. Moreover, the following modifications may be combined respectively.

(1) In the embodiment described above, the infrastructure is a railway, but the type of infrastructure is not limited to a railway, and may be any of a road, a power plant, a substation or the like.

(2) In the embodiment described above, SAI defined in Equation 5 is used as an index indicating sediment productivity for each monitoring target cell, but it is an index indicating sediment productivity for each monitoring target cell For example, other indicators may be used.

(3) In the embodiment described above, the IEFC defined in the equation 6 is used as an index indicating the reachability of the fallen soil for each monitoring target cell to the risk evaluation cell. Other indicators may be used as long as they indicate the reachability of the fallen soil to the risk assessment cell.

(4) In the embodiment described above, TGI defined in Equation 7 is used as an index indicating productivity of fallen soil that can reach the danger evaluation cell for each monitoring target cell. Other indexes may be used as long as they are calculated using the index indicating the productivity of sediment and the index indicating the possibility of reaching the risk evaluation cell of the fallen soil for each monitoring target cell.

(5) In the above-described embodiment, the arithmetic mean of the hazard indicator TGI is used as the infrastructure risk indicator SLPR indicating the possibility that the hazard evaluation cell on the infrastructure may be damaged by the fallen soil. If it is a statistic of an index calculated using an index indicating sediment productivity for each time and an index indicating reachability to the risk evaluation cell of fallen soil for each monitoring target cell, another statistic is the infrastructure It may be used as a risk indicator SLPR.

(6) In the embodiment described above, the slope stability index F _S defined in Equation 12 is used as an index for estimating occurrence time of landslide in the monitoring area, but in the target area Other indicators may be used as long as they are indicators indicating slope stability of each cell, which are calculated based on time-dependent changes in rainfall.

(7) In the embodiment described above, the terminal device 11 and the server device 12 are realized by the computer executing the process according to the program, but at least one of the terminal device 11 and the server device 12 is a dedicated device May be configured as

DESCRIPTION OF SYMBOLS 1 ... danger degree evaluation system, 10 ... computer, 11 ... terminal device, 12 ... server apparatus, 20 ... computer, 101 ... memory, 102 ... processor, 103 ... communication unit, 104 ... display, 105 ... keyboard, 110 ... calculating part , 111: storage unit, 112: display unit, 113: reception unit, 201: memory, 202: processor, 203: communication unit, 1101: water collection area calculation unit, 1102: slope calculation unit, 1103: regression expression identification unit, 1104 ... hazard evaluation cell extraction unit, 1105 ... monitoring area identification unit, 1106 ... sediment productivity index calculation unit, 1107 ... reachability index calculation unit, 1108 ... hazard index calculation unit, 1109 ... infrastructure risk index calculation unit, 1110 ... Pressure head calculation unit, 1111 ... stability index calculation unit, 1112 ... generation time estimation unit

Claims

An area including a risk evaluation cell and a plurality of monitoring target cells is used as a monitoring area of sediment loss, and sediment productivity for each of the monitoring target cells and reachability to the risk evaluation cell of falling sediment for each of the monitoring target cells And a risk evaluation system for evaluating the risk of landslide disaster occurrence in the risk evaluation cell based on.
Regression for approximating the relationship between the gradient of each of the plurality of cells constituting the area including the monitoring area and the area of the water collection area that is the area supplying water flowing into the cell for each of the plurality of monitoring target cells Sediment production showing sediment productivity for each of the monitoring target cells, an index using the ratio of the gradient according to the area of the water collection area of the monitoring target cell calculated according to the formula and the gradient of the monitoring target cell The risk evaluation system according to claim 1, wherein the risk evaluation system is used as a gender index.
For each of the plurality of monitoring target cells, an index using the ratio of the height difference between the monitoring target cell and the risk evaluation cell and the horizontal distance between the monitoring target cell and the risk evaluation cell is the monitoring target cell. The risk level evaluation system according to claim 1, wherein the risk level evaluation system is used as a reachability index indicating the reachability of the fallen soil to the risk evaluation cell.
For each of the plurality of monitoring target cells, an index using the ratio of the height difference between the monitoring target cell and the risk evaluation cell and the horizontal distance between the monitoring target cell and the risk evaluation cell is the monitoring target cell. The risk level evaluation system according to claim 2, wherein the risk level evaluation system is used as a reachability index indicating the reachability of the fallen soil to the risk evaluation cell.
The risk of occurrence of landslide disaster in the risk evaluation cell is evaluated based on the statistics of the index calculated using the sediment productivity index and the reachability index for each of the plurality of monitoring target cells. Risk assessment system described.
The risk degree according to claim 1, wherein the dangerous cell on the infrastructure is identified by evaluating the risk of occurrence of the earth-and-sand disaster when the cell is regarded as the risk evaluation cell for each of a plurality of cells on the infrastructure. Evaluation system.
The risk degree evaluation system according to any one of claims 1 to 6, wherein the occurrence time of landslide in the monitoring area is estimated based on a temporal change of rainfall amount in an area including the monitoring area.
The risk degree evaluation system according to claim 1, wherein the plurality of monitoring target cells are a plurality of cells constituting a water collection area of the risk evaluation cell, which is an area for supplying water flowing into the risk evaluation cell.
A sediment production index calculation unit that calculates a sediment productivity index indicating the sediment productivity for each of the monitoring target cells;
A reachability index calculation unit that calculates a reachability index indicating the reachability of the fallen soil to the risk evaluation cell for each of the monitoring target cells;
A risk index calculation unit that calculates a risk index indicating the possibility that the risk evaluation cell may be damaged by the fallen soil using the sediment productivity index and the reachability index for each of the monitoring target cells;
Including
The risk assessment system according to claim 1, wherein the risk of landslide disaster occurrence in the risk assessment cell is evaluated by comparing the risk indicator with a threshold.
Sediment productivity index, which is an index indicating sediment productivity for each of the monitoring target cells in a monitoring area of landslides including a risk evaluation cell and a plurality of monitoring target cells, on a computer, and fallen soil for each of the monitoring target cells And a program for calculating an index indicating a risk of occurrence of landslide disaster in the risk evaluation cell based on the reachability index which is an index indicating the reachability to the risk evaluation cell.