JP6941319B2 - Risk assessment system - Google Patents

Description

The present invention relates to a technique for evaluating the risk of landslides due to rainfall.

Landslides caused by rainfall can cause life-threatening damage. Therefore, in order to reduce the damage caused by landslides, a technique has been proposed in which the risk of landslides due to rainfall is specified and when the risk increases, a technique is notified to that effect.

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

Further, in Patent Document 2, a sediment-related disaster water level, which is the water level at the upper end of a dangerous area where a sediment-related disaster is expected to occur and indicates that a sediment-related disaster is likely to occur, is determined and specified based on the amount of rainfall. It describes a mechanism to identify a caution area where sediment-related disasters are likely to occur in light of the estimated water level at the point.

Japanese Unexamined Patent Publication No. 10-232286 JP-A-2016-122239

If rainfall continues for a long period of time, it is possible to avoid risks and risks by treating all areas subject to rainfall as dangerous areas and monitoring landslides, or by prohibiting people from entering all of these areas. It lacks a balance with the price for it and is not realistic.

If we can identify areas where life-threatening sediment-related disasters are likely to occur, we should effectively avoid risks by intensively monitoring those areas and keeping people out of the area. Can be done.

In view of the above circumstances, the present invention provides a means for identifying an area where there is a high possibility that a sediment-related disaster that may be fatal to human life will occur due to rainfall.

In order to solve the above-mentioned problems, the present invention presents the sediment productivity of each monitored cell and the collapse of each monitored cell in a landslide monitoring area composed of a plurality of monitored cells including a risk assessment cell. As the first aspect, a risk assessment system for evaluating the risk of sediment-related disaster occurrence in the risk assessment cell based on the reachability of the sediment to the risk assessment cell is provided.

According to the risk assessment system according to the first aspect described above, the risk of sediment-related disasters at a certain point can be known.

In the risk assessment system according to the first aspect, for each of the plurality of monitored cells, the gradient of each of the plurality of cells constituting the area including the monitored area and the area for supplying water flowing into the cell. An index using the ratio of the gradient according to the area of the catchment area of the monitored cell and the gradient of the monitored cell, which is calculated according to a regression equation that approximates the relationship with the area of the catchment area. , The configuration of using it as a sediment productivity index indicating the sediment productivity of each monitored cell may be adopted as the second aspect.

In the risk assessment system according to the first aspect, for each of the plurality of monitored cells, the altitude difference between the monitored cell and the risk assessment cell, and the horizontal distance between the monitored cell and the risk assessment cell. A configuration in which an index using the ratio of and is used as a reachability index indicating the reachability of the collapsed sediment for each monitored cell to the risk assessment cell may be adopted as the third aspect. ..

Further, in the risk assessment system according to the second aspect, for each of the plurality of monitored cells, the altitude difference between the monitored cell and the risk assessment cell, and the horizontal distance between the monitored cell and the risk assessment cell. A configuration in which an index using the ratio of and is used as a reachability index indicating the reachability of the collapsed sediment for each monitored cell to the risk assessment cell may be adopted as the fourth aspect. ..

In the risk assessment system according to the fourth aspect, the risk is based on the statistic of the index calculated by using the sediment productivity index and the reachability index for each of the plurality of monitored cells. A configuration in which the risk of sediment-related disasters in the evaluation cell is evaluated may be adopted as the fifth aspect.

According to the risk assessment system according to the second to fifth aspects described above, the risk of sediment-related disasters at a certain point in the area can be known from the digital elevation model of the area including the monitoring area.

In the risk assessment system according to any one of the first to fifth aspects, the risk of sediment-related disaster occurrence when the cell is used as the risk assessment cell is evaluated for each of the plurality of cells on the infrastructure. A configuration of identifying dangerous cells on the infrastructure may be adopted as the sixth aspect.

According to the risk assessment system according to the sixth aspect described above, it is possible to find out the areas where the risk of sediment-related disasters is high among the infrastructures that are frequently visited by people.

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

According to the risk assessment system according to the seventh aspect described above, the time when the risk of sediment-related disasters increases can be known.

Further, the present invention uses a computer to obtain a sediment productivity index, which is an index indicating the sediment productivity of each monitored cell in a landslide monitoring area composed of a plurality of monitored cells including a risk assessment cell, and the monitoring. A program for calculating an index indicating the risk of sediment-related disasters in the risk evaluation cell based on the reachability index, which is an index indicating the reachability of the collapsed sediment for each target cell, is the eighth. Provided as an aspect of.

According to the program according to the eighth aspect, the computer realizes the risk assessment system according to the first aspect.

The figure which showed the whole structure of the risk assessment system which concerns on one Embodiment. The figure which showed the structure of the computer used as the hardware of the terminal apparatus which concerns on one Embodiment. The figure which showed the structure of the computer used as the hardware of the server apparatus which concerns on one Embodiment. The figure which showed the functional structure of the terminal apparatus which concerns on one Embodiment. The figure which showed the relationship between the risk evaluation cell and the monitoring area specified by the terminal apparatus which concerns on one Embodiment. The figure which illustrated the information displayed by the display part which concerns on one Embodiment. The figure which illustrated the information displayed by the display part which concerns on one Embodiment. The figure which showed the functional structure of the terminal apparatus which concerns on one Embodiment. The figure which illustrated the information displayed by the display part which concerns on one Embodiment.

[Embodiment]
Hereinafter, the risk assessment system 1 according to the embodiment of the present invention will be described. The risk assessment system 1 notifies the user of the areas of the infrastructure such as railways in the target area where the risk of sediment-related disasters is high due to rainfall, and the time when it is estimated that sediment-related disasters will occur in the areas where the risk of sediment-related disasters is high. Is a system that notifies the user.

FIG. 1 is a diagram showing the overall configuration of the risk assessment system 1. The risk assessment system 1 is used by the user to generate information to be notified to the user, and the terminal device 11 to notify the user of the generated information, and a record of changes in the amount of rainfall over time in the target area to the terminal device 11. A server device 12 for distributing rainfall data showing values and estimated values is provided. The terminal device 11 and the server device 12 are communicated and 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 a configuration of a computer 10 used as hardware of the terminal device 11. Further, FIG. 3 is a diagram showing a configuration of a computer 20 used as hardware of the server device 12.

The computer 10 includes a memory 101 that stores various data, a processor 102 that performs various data processing according to a program stored in the memory 101, a communication unit 103 that performs data communication between an external device, and various types of users. A display 104 for displaying information and a keyboard 105 for accepting a user's data input operation are provided. 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 that stores various data, a processor 202 that performs various data processing according to a program stored in the memory 201, and a communication unit 203 that performs data communication between an external device.

When the processor 202 performs various data processing according to the program stored in the memory 201, the computer 20 operates as a server device 12 that distributes rainfall data to the terminal device 11. Since the functional configuration of the server device 12 is the same as the functional configuration of the server device that performs general data distribution, the description thereof will be omitted.

FIG. 4 is a diagram showing a functional configuration for performing a process for notifying the user of a location having a high risk of sediment-related disasters 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 digital elevation model of the target area and route data indicating a position through which a railway (an example of infrastructure) in the target area passes. In addition, various data generated by the calculation unit 110 described below are stored in the storage unit 111.

The calculation unit 110 is mainly realized by the processor 102 and performs various calculations. The calculation unit 110 includes a water collection area calculation unit 1101 for calculating the water collection area of each of the plurality of cells constituting 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 catchment area of a cell is the area of a catchment area which is a region for supplying water flowing into the cell. The catchment area calculation unit 1101 calculates the catchment area of each cell in the target area by the known topographical water analysis using the digital elevation model indicated by the digital elevation model data. The 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 the water collection area data.

The calculation unit 110 includes a gradient calculation unit 1102 that calculates the slope 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. The data indicating the gradient of each cell calculated by the gradient calculation unit 1102 is stored in the storage unit 111 as the gradient data.

The calculation unit 110 includes a regression equation specifying unit 1103 that specifies a regression equation indicating a combination of a catchment area and a gradient that brings about a standard ease of scraping of earth and sand in the target area. The regression equation identification unit 1103 associates the catchment area indicated by the catchment area data with the gradient indicated by the gradient data for each cell in the target area, and sets the associated catchment area and gradient as a sample. Regression analysis is used to identify the regression equation for the population to be used.

ただし、Ｓは勾配（単位：ｍ／ｍ）、Ａ_fは集水面積（単位：ｍ²）である。また、Ｂ及びｐは対象地域の土砂の特性により定まる定数であり、回帰分析により特定される。 In the present embodiment, the regression equation specified by the regression equation specifying unit 1103 has the structure of the following equation 1.

However, S is the gradient (unit: m / m), and A _f is the catchment area (unit: m ² ). In addition, B and p are constants determined by the characteristics of the earth and sand in the target area, and are specified by regression analysis.

ただし、Ｅは土砂の侵食速度（単位：ｍ／ｙｒ）、Ｋは土砂の侵食効率（単位：例えばｙｒ^-1（べき数ｍに依存））である。また、ｍ及びｎは集水面積Ａ_fと勾配Ｓの重み付けを示す数値（ｍ＞０、ｎ＞０）である。式２に示されるように、土砂の侵食速度が勾配と集水面積のべき乗の積に概ね比例する関係を有する点は既知である。なお、式１の定数と式２の定数には以下の式３及び式４に示す関係がある。

Equation 1 is derived from Equation 2 below.

However, E is the sediment erosion rate (unit: m / yr), and K is the sediment erosion efficiency (unit: yr ^-1 (depending on the power number m)). Further, m and n are numerical values (m> 0, n> 0) indicating the weighting _{of the catchment area A f and the gradient S.} As shown in Equation 2, it is known that the erosion rate of earth and sand has a relationship that is roughly proportional to the product of the gradient and the power of the catchment area. The constant of Equation 1 and the constant of Equation 2 have the relationship shown in Equations 3 and 4 below.

The data indicating the regression equation specified by the regression equation specifying 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 the cells in the target area as a risk evaluation cell. The risk assessment cell extraction unit 1104 extracts the risk assessment cell based on the route data. The data indicating the risk evaluation cell extracted by the risk evaluation cell extraction unit 1104 is stored in the storage unit 111 as the risk evaluation cell data.

The calculation unit 110 includes a monitoring area specifying unit 1105 that specifies the water collecting area of the risk evaluation cell as a monitoring area for each of the risk evaluation cells. The monitoring area identification unit 1105 identifies the catchment area by known topographical hydrological analysis for each of the risk assessment cells using the digital elevation model indicated by the digital elevation model data, and identifies the identified catchment area as the risk assessment cell. It is the monitoring area of. Hereinafter, the cells in the monitored area are referred to as monitored cells.

FIG. 5 is a diagram showing _{one risk assessment cell P i} on the track r in the target area U and the monitoring area Q _i of the risk assessment cell P _i. The 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.

The calculation unit 110 (FIG. 4) has a sediment productivity for each of the plurality of risk evaluation cells extracted by the risk evaluation cell extraction unit 1104 for each monitored cell in the monitoring area specified by the monitoring area identification unit 1105. The sediment productivity index calculation unit 1106 for calculating the sediment productivity index, which is an index indicating the above, is provided.

ただし、Ｓ_localは勾配データが示す監視対象セルの勾配、Ａ_flocalは集水面積データが示す監視領域の集水面積である。また、Ｓ（Ａ_flocal）は回帰式データが示す回帰式（式１）に従い算出される、監視領域の集水面積Ａ_flocalに応じた勾配である。 In the present embodiment, the sediment productivity index calculation unit 1106 calculates the sediment productivity index SAI according to the following formula 5.

However, S _local is the gradient of the monitored cell indicated by the gradient data, and A _flocal is the catchment area of the monitoring area indicated by the catchment area data. Further, S (A _flocal ) is a gradient according to _{the catchment area A flocal} in the monitoring area, which is calculated according to the regression equation (Equation 1) indicated by the regression equation data.

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

The calculation unit 110 refers to each of the plurality of risk evaluation cells extracted by the risk evaluation cell extraction unit 1104, and for each of the monitored cells in the monitoring area specified by the monitoring area specifying unit 1105, the risk evaluation cell of the collapsed sediment. The reachability index calculation unit 1107 for calculating the reachability index, which is an index indicating the reachability of the user, is provided.

ただし、Ｈ_Sは数値標高モデルデータが示す、危険評価セルを基準とする監視対象セルの高さ（単位：ｍ）、すなわち監視対象セルの高さから危険評価セルの高さを減じた値である。また、Ｌは数値標高モデルデータが示す、危険評価セルと監視対象セルの水平距離（単位：ｍ）である。 In the present embodiment, the reachability index calculation unit 1107 calculates the reachability index IEFC according to the following equation 6.

However, H _S represents the digital elevation model data, the height of the monitored cell relative to the risk evaluation cell (unit: m), i.e., a value obtained by subtracting the height of the hazard evaluation cells from the height of the monitored cell be. Further, L is the horizontal distance (unit: m) between the risk evaluation cell and the monitored cell indicated by the digital elevation model data.

The data indicating the reachability index IEFC for each monitored cell of each risk assessment 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 risk evaluation cell for each of the plurality of risk evaluation cells extracted by the risk evaluation cell extraction unit 1104 for each monitored cell in the monitoring area specified by the monitoring area specifying unit 1105. A hazard index calculation unit 1108 for calculating a hazard index, which is an index indicating the productivity of collapsed sediment, is provided.

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

The data indicating the hazard index TGI for each monitored cell of each risk 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 the infrastructure risk index calculation using the statistics of the hazard index TGI calculated by the hazard index calculation unit 1108 as the infrastructure risk index for each of the plurality of risk evaluation cells extracted by the risk evaluation cell extraction unit 1104. A unit 1109 is provided.

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

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

FIG. 6 shows a hazard map displayed by the display unit 112. _{In the hazard map illustrated in FIG. 6, risk assessment cells P 1} , P ₂ , and P ₃ are shown as risk assessment cells whose infrastructure risk index SLPR is equal to or higher than a predetermined threshold among the risk assessment cells on the track r in the target area U. Is illustrated. Further, Illustrative of the hazard map in FIG. 6, the hazard indicators TGI of monitored cells included in risk assessment cell P _1, P _2, the monitoring region Q ₁ corresponding to each of P _3, Q _2, Q ₃ The cells to be monitored that are equal to or higher than a predetermined threshold value are indicated by a cross.

By looking at the hazard map, the user can know the places on the track r that are susceptible to sediment-related disasters and the locations in the target area where sediment-related disasters are likely to occur.

FIG. 7 shows a risk line along the line displayed by the display unit 112. The risk line along the line has the horizontal axis of the distance from the predetermined reference point of 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 a graph which plotted the risk index SLPR on the vertical axis. The user can see the risk line along the railroad track and know the susceptibility to sediment-related disasters at each point on the railroad track r.

FIG. 8 is a diagram showing a functional configuration for performing a process for notifying the user of the time when the landslide is estimated to 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 above-mentioned storage unit 111, calculation unit 110, and display unit 112 as a component for estimating the occurrence time of a 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 components for estimating the occurrence time of a landslide.

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

ただし、Ｄ₀は拡散係数（単位：ｍ²／ｓ）、αは斜面傾斜角（単位：ｄｅｇ）、Ｚは深さ（単位：ｍ）である。 However, t ^* is a value represented by the following equation 9.

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

ただし、Ｔは降雨持続時間（単位：ｓ）である。 Further, T ^* is a value represented by the following equation 10.

However, T is the duration of rainfall (unit: s).

In addition, ψ ₀ is the initial value of the pressure head, I _Z is the rainfall intensity (unit: m / s), K _Z is the hydraulic conductivity in the depth direction (m / s), and R (t ^* ) is the following equation 11. the value obtained by substituting t ^* to ^{x, R (t * -T *} ) is a value obtained by substituting (t ^* -T ^*) to x in the following equation 11.

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

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

_{The diffusion coefficient D 0} shown by the diffusion coefficient data _{and the hydraulic conductivity K Z} indicated by the hydraulic conductivity data are the values specified by fitting the hydrological observation values at the representative points in the target area and the model equation shown in Equation 8. be.

The slope inclination angle α of each cell indicated by the slope inclination angle 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 data received from the server device 12 by the receiving unit 113.

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

Stability index calculating section 1111, it relates to each of the cells in the target area, and calculates the slope stability index F _S at time t in accordance with equation 12 below. The following formula 12 is a calculation formula proposed in the paper "Stability of Natural Slopes in London Clay" published in 1957 by AW Skempton and FA Delory.

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

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

If the slope stability index F _S is 1 or more, it indicates that the slope is stable and no landslide occurs, and if it is less than 1, the slope is unstable and landslide occurs.

The storage unit 111, as data to be used for stability index calculating section 1111 calculates the slope stability index F _S at time t of each cell adhesion data showing adhesion c soil layer, earth by tree root system Adhesive strength increase data indicating the increase amount Δc of the adhesive force of the layer, saturation unit weight data indicating the saturation unit weight γ of the soil layer, unit weight data indicating _{the unit weight γ W of water, and the soil layer thickness h of each cell.} The soil layer thickness data shown, 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 adhesive strength c of the soil layer indicated by the adhesive strength 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 determined using samples collected from within the target area. It is a value specified by a shear test or the like. The amount of increase in the adhesive strength of the soil layer shown by the data on the amount of increase in adhesive strength Δc was empirically obtained by the number density and root diameter distribution of the plant root system as a function of the depth in the soil layer and the inverse analysis of past disaster cases. It is the value that was given.

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

ただし、ｈ₀は傾斜曲率Ｃが０の箇所の平板型斜面の土層厚であり、ａは指数係数である。 The soil layer thickness h of each cell indicated by the soil layer thickness data is a value calculated by substituting the inclination 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 where the inclination curvature C is 0, and a is an exponential coefficient.

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

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

The occurrence time estimation unit 1112 sets the time when the slope stability index data is less than 1 for each of the monitored cells included in the monitoring area corresponding to each of the risk evaluation cells whose infrastructure risk index SLPR is equal to or higher than a predetermined threshold. It is estimated as the time when a landslide occurs in the monitored cell.

The display unit 112 displays the location and time of occurrence of the landslide estimated by the occurrence time estimation unit 1112. FIG. 9 is a diagram illustrating 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 shown in FIG. 6, the place and time at which the landslide is estimated to occur are displayed.

By looking at the hazard map, the user can know where and at what time the landslide will occur in the monitoring area that may bring landslides to places vulnerable to landslides on the track r. can.

[Modification example]
The present invention may be implemented in a form different from the above-described embodiment. A modified example of the above-described embodiment is shown below. In addition, the following modifications may be combined.

(1) In the above-described embodiment, the infrastructure is assumed to be a railway, but the type of infrastructure is not limited to railways, and may be any of roads, power plants, substations, and the like.

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

(3) In the above-described embodiment, IEFC defined in Equation 6 is used as an index indicating the reachability of the collapsed sediment risk evaluation cell for each monitored cell, but for each monitored cell. Other indicators may be used as long as they are indicators of the reachability of the collapsed sediment risk assessment cell.

(4) In the above-described embodiment, the TGI defined in Equation 7 is used as an index showing the productivity of the collapsed sediment that can reach the risk assessment cell for each monitored cell, but for each monitored cell. Any index may be used as long as it is an index calculated by using an index showing the sediment productivity of the above and an index showing the reachability of the collapsed sediment risk evaluation cell for each monitored cell.

(5) In the above-described embodiment, the arithmetic mean of the hazard index TGI is used as the infrastructure risk index SLPR indicating the possibility that the risk assessment cell on the infrastructure will be damaged by the collapsed sediment. If the statistic is an index calculated using an index showing the sediment productivity for each and an index showing the reachability of the collapsed sediment risk evaluation cell for each monitored cell, other statistics are infrastructure. It may be used as a risk index SLPR.

(6) In the above-described embodiment, as an index for estimating the time of occurrence of soil collapse in the monitoring area, it is assumed that the slope stability index F _S defined in formula 12 is used, the target area Other indicators may be used as long as they are indicators of slope stability of each cell, which are calculated based on changes in rainfall over time.

(7) In the above-described embodiment, 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. It may be configured as.

1 ... Risk assessment system, 10 ... Computer, 11 ... Terminal device, 12 ... Server device, 20 ... Computer, 101 ... Memory, 102 ... Processor, 103 ... Communication unit, 104 ... Display, 105 ... Keyboard, 110 ... Calculation unit , 111 ... storage unit, 112 ... display unit, 113 ... receiver unit, 201 ... memory, 202 ... processor, 203 ... communication unit, 1101 ... water collection area calculation unit, 1102 ... gradient calculation unit, 1103 ... regression equation identification unit, 1104 ... Danger 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 ... Occurrence time estimation unit.

Claims (8)

In a landslide monitoring area consisting of a plurality of monitored cells including a risk assessment cell, the sediment productivity of each monitored cell, the reachability of the landslide sediment of each monitored cell to the risk assessment cell, and the like. A risk assessment system that evaluates the risk of sediment-related disasters in the risk assessment cell based on. For each of the plurality of monitored cells, a regression that approximates the relationship between the gradient of each of the plurality of cells constituting the area including the monitored area and the area of the catchment area which is the area for supplying water flowing into the cell. Sediment production indicating the sediment productivity of each monitored cell is an index using the ratio of the gradient according to the area of the catchment area of the monitored cell calculated according to the formula and the gradient of the monitored cell. The risk assessment system according to claim 1, which is used as a sex index. For each of the plurality of monitored cells, an index using the ratio of the altitude difference between the monitored cell and the risk evaluation cell and the horizontal distance between the monitored cell and the risk evaluation cell is used as the monitored cell. The risk assessment system according to claim 1, which is used as a reachability index indicating the reachability of each collapsed sediment to the risk assessment cell. For each of the plurality of monitored cells, an index using the ratio of the altitude difference between the monitored cell and the risk evaluation cell and the horizontal distance between the monitored cell and the risk evaluation cell is used as the monitored cell. The risk assessment system according to claim 2, which is used as a reachability index indicating the reachability of each collapsed sediment to the risk assessment cell. Claim 4 for evaluating the risk of sediment-related disasters in the risk assessment cell based on the statistic of the index calculated by using the sediment productivity index and the reachability index for each of the plurality of monitored cells. The listed risk assessment system. Any of claims 1 to 5 for identifying a dangerous cell on the infrastructure by evaluating the risk of sediment-related disaster occurrence when the cell is used as the risk evaluation cell for each of a plurality of cells on the infrastructure. The risk assessment system described in item 1. The risk assessment system according to any one of claims 1 to 6, which estimates the time of occurrence of a landslide in the monitoring area based on the time course of rainfall in the area including the monitoring area. The computer has a sediment productivity index, which is an index showing the sediment productivity of each monitored cell in a landslide monitoring area composed of a plurality of monitored cells including a risk assessment cell, and a landslide sediment for each monitored cell. A program for calculating an index indicating the risk of sediment-related disasters in the risk evaluation cell based on the reachability index, which is an index indicating the reachability of the risk evaluation cell.

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