WO2019176836A1 - Slope monitoring system, slope monitoring method, and recording medium - Google Patents

Slope monitoring system, slope monitoring method, and recording medium Download PDF

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Publication number
WO2019176836A1
WO2019176836A1 PCT/JP2019/009609 JP2019009609W WO2019176836A1 WO 2019176836 A1 WO2019176836 A1 WO 2019176836A1 JP 2019009609 W JP2019009609 W JP 2019009609W WO 2019176836 A1 WO2019176836 A1 WO 2019176836A1
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WIPO (PCT)
Prior art keywords
safety factor
current
slope
soil
risk level
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PCT/JP2019/009609
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French (fr)
Japanese (ja)
Inventor
梓司 笠原
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日本電気株式会社
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Publication of WO2019176836A1 publication Critical patent/WO2019176836A1/en

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    • E—FIXED CONSTRUCTIONS
    • E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
    • E02D—FOUNDATIONS; EXCAVATIONS; EMBANKMENTS; UNDERGROUND OR UNDERWATER STRUCTURES
    • E02D17/00—Excavations; Bordering of excavations; Making embankments
    • E02D17/20—Securing of slopes or inclines

Definitions

  • the present invention relates to a slope monitoring system, a slope monitoring method, and a recording medium for monitoring slopes on topography such as mountains and valleys.
  • the safety factor is used as an index for evaluating the safety of the risk of collapse of slopes in terrain such as mountains and valleys, or the degree of no risk of slope collapse during heavy rain.
  • the safety factor is an index for evaluating the safety of a slope, and is represented by a ratio in which a sliding force for sliding down the slope is used as a denominator and a resistance force for preventing the sliding is used as a numerator. When this value is less than 1, that is, when the sliding force becomes larger than the resistance force, it is evaluated that there is a possibility of collapse.
  • Patent Documents 1 and 2 disclose this type of slope safety monitoring technology.
  • the slope monitoring system disclosed in Patent Document 1 changes the moisture content of the test layer measured from a test environment having a test layer that is substantially the same material layer as the material layer constituting the monitored slope. Measure each value of a predetermined analytical expression variable. Then, the slope monitoring system constructs a model that defines the relationship between the amount of water and the value of each analytical expression variable for each of the analytical expression variables based on the value of each analytical expression variable and the amount of water. The slope monitoring system calculates the value of each analytical expression variable when measuring the water content of the monitored slope using the constructed model, and based on the calculated value of each analytical expression variable, the slope stability analysis Calculate the safety factor of the slope to be monitored using the formula.
  • the disaster prediction system disclosed in Patent Document 2 acquires the amount of moisture in the soil at a specific point, and acquires the amount of water on the ground surface in a certain range including the specific point. And the disaster prediction system is based on the moisture content in the soil at a specific point and the moisture content on the ground surface in a certain range. Estimate the parameters representing the characteristics of the soil at any point included.
  • the disaster prediction system determines that there is a risk of landslide disaster in the area when the safety factor calculated using the slope stability analysis formula gradually decreases and approaches 1, and lives in the vicinity of the point By issuing evacuation advisories and evacuation instructions to residents, it is intended to realize timely warnings that do not miss time.
  • Patent Document 1 and Patent Document 3 calculate the value of each analytical expression variable when the moisture content of the monitored slope is measured using the constructed model, and the calculated analytical expression variable
  • the safety factor of the slope to be monitored is calculated using the slope stability analysis formula based on the value, and an alarm is issued if it falls below a predetermined threshold.
  • Patent Document 1 and Patent Document 3 do not disclose a configuration in which the degree of danger is determined in two stages, that is, the safety factor is equal to or less than a predetermined threshold value, and a gradual evaluation in more stages is possible.
  • Patent Document 2 discloses a configuration in which it is determined that there is a risk of a landslide disaster when the safety factor approaches 1, and an evacuation recommendation or evacuation instruction is issued. There is no disclosure of a configuration that can perform stepwise evaluation in more stages than two stages of near risk or not.
  • a slope monitoring system is based on a measurement unit that measures a soil parameter in association with a moisture content of a material layer that constitutes a monitored slope, and based on the measured soil parameter and the moisture content.
  • a modeling unit that generates a model equation, an optimal state water amount estimation unit that estimates the optimal amount of water with the maximum safety factor based on the soil parameter, and a current water amount on the monitored slope.
  • a moisture meter to be measured a current safety factor calculation unit that calculates a current safety factor using a current soil parameter estimated from the current moisture content based on the model equation; and the optimum state based on the model equation
  • An optimum state safety factor calculation unit that calculates the optimum factor safety factor using an optimum soil parameter estimated from the water content of the water, the current safety factor and the optimum factor safety factor
  • a risk output unit for outputting the risk level of the current relative to the said optimum state based on.
  • a soil layer is measured by associating a moisture content with a substance layer constituting a slope to be monitored, and a model formula is based on the measured soil parameter and the moisture content.
  • Generating an optimal amount of water with a maximum safety factor based on the soil parameter measuring the current amount of water on the slope to be monitored, and based on the model formula
  • Calculate the current safety factor using the current soil parameter estimated from calculate the optimal state safety factor using the optimal soil parameter estimated from the water content of the optimal state based on the model formula, Based on the current safety factor and the optimum safety factor, a current risk level based on the optimum state is output.
  • a recording medium that generates, on a computer, a model formula based on a soil parameter measured in association with a moisture content and a moisture content of a material layer constituting a monitoring target slope.
  • a process for estimating the optimum amount of water that maximizes the safety factor based on the soil parameter a process for obtaining the current amount of water on the slope to be monitored, and the current amount of water based on the model formula Processing to calculate the current safety factor using the estimated current soil parameter, processing to calculate the safety factor of the optimal state using the optimal soil parameter estimated from the water content of the optimal state based on the model formula And a process for outputting a current risk level based on the optimum state based on the current safety factor and the optimum factor safety factor.
  • the safety factor and the degree of danger that change according to the amount of moisture in the soil can be grasped step by step, and step by step warning and evacuation can be issued.
  • FIG. 1 is a block diagram illustrating an example of the configuration of the first embodiment.
  • FIG. 2 is a flowchart illustrating an example of a method for acquiring soil parameters related to slope stability of the measurement unit in FIG.
  • FIG. 3 is a flowchart showing details of the triaxial compression test (shear test) in step S11 of FIG.
  • FIG. 4 is a flowchart illustrating an example of a water addition test of the measurement unit in FIG.
  • FIG. 5 is a flowchart showing an example of the modeling operation of FIG. 1 and the operation of estimating the optimum amount of water.
  • FIG. 6 is a flowchart showing the safety factor calculation operation of the first embodiment.
  • FIG. 1 is a block diagram illustrating an example of the configuration of the first embodiment.
  • FIG. 2 is a flowchart illustrating an example of a method for acquiring soil parameters related to slope stability of the measurement unit in FIG.
  • FIG. 3 is a flowchart showing details of the triaxial compression test (shear test)
  • FIG. 7 is a diagram illustrating an example of the current risk level output based on the optimum state of the risk output unit of FIG.
  • FIG. 8 is a block diagram illustrating an example of the configuration of the second embodiment.
  • FIG. 9 is a diagram illustrating a first setting example of each risk level.
  • FIG. 10 is a diagram illustrating a second setting example of each risk level.
  • FIG. 11 is a block diagram showing a configuration of a risk output unit that sets the width of each risk level as shown in FIG.
  • FIG. 2 is a diagram illustrating a third setting example of each risk level.
  • FIG. 13 is a block diagram showing a configuration of a risk output unit that sets the width of each risk level as shown in FIG.
  • FIG. 14 is a diagram illustrating an example of a configuration of a computer that implements each unit of each embodiment.
  • Fs is the safety factor
  • ⁇ is the slope angle
  • C, W, u, and ⁇ are the soil parameters representing the properties of the soil, adhesive strength, mass weight, pore water pressure, and internal friction angle, respectively.
  • the shear stress of each divided piece (such as a lump) is represented by the lump weight W as the gravity applied to the divided piece and the slope gradient angle ⁇ (see the denominator of equation (1)). ).
  • the shear resistance of each divided piece is expressed by the adhesive force C of the divided piece (clump) and the resistance force ((Wu) cos ⁇ ⁇ tan ⁇ ) based on the vertical stress (of the equation (1)) See molecule).
  • the safety of a slope is evaluated by a safety factor Fs calculated using a ratio of a shear stress acting in the slope direction of each divided piece and a shear resistance force that prevents sliding due to the shear stress.
  • FIG. 1 is a block diagram showing an example of the configuration of the first embodiment.
  • the slope monitoring system 1 includes a measurement unit 11, a modeling unit 12, an optimum state moisture amount estimation unit 13, and a storage unit 14.
  • the measurement part 11 measures the soil parameter relevant to slope stability previously linked
  • the soil parameters related to the slope stability are the adhesive force C, the internal friction angle ⁇ , the pore water pressure u, and the clot weight W.
  • soil parameters for a specimen (soil mass) of one or more water amounts m 1 , m 2 ,..., Max which are created using a material layer (sediment) collected in advance from a slope to be monitored and have different water content ratios, That is, adhesive forces C 1 , C 2 ,...
  • FIG. 2 is a flowchart showing an example of a method for acquiring soil parameters related to the slope stability of the measurement unit in FIG.
  • the measuring unit 11 performs a triaxial compression test (shear test) to calculate the adhesive force C and the internal friction angle ⁇ (step S11).
  • FIG. 3 is a flowchart showing details of the triaxial compression test (shear test) in step S11 of FIG.
  • a test body soil mass
  • the soil of the test body is the same as the soil of the actual slope.
  • a plurality of test bodies are formed by changing the water content ratio of soil blocks made of soil having the same type, dry density and compaction as the soil on the actual slope.
  • the measuring unit 11 measures the water content of the prepared earth clot using a moisture meter (step S112).
  • the measurement unit 11 performs compression by setting the prepared soil block in a triaxial compression test apparatus including a stress sensor included in the measurement unit 11, and calculates the vertical stress ⁇ and shear stress ⁇ during compression. Measurement is performed (step S113).
  • step S114 the compression and stress measurement in steps S112 to S113 is repeated (step S114). Usually at least three compression and stress measurements are performed. Thereby, the normal stress data and the shear stress data at the time of shearing corresponding to at least a plurality of vertical loads are obtained for one soil block.
  • the measurement unit 11 obtains moisture amount data, and normal stress data and shear stress data during shearing corresponding to a plurality of vertical loads, for each of the soil blocks having different moisture contents.
  • the measuring unit 11 is obtained. Based on the normal stress data and the shear stress data, the adhesive force C and the internal friction angle ⁇ are calculated (step S12 in FIG. 2).
  • the shear strength s is represented by the sum of the adhesive force C of the soil and the resistance force ( ⁇ tan ⁇ ) based on the normal stress ⁇ acting on the shear surface.
  • tan ⁇ is an effective friction coefficient based on the internal friction angle ⁇ , which is one of the soil parameters representing the properties of the soil.
  • s C + ⁇ tan ⁇
  • the measuring unit 11 sets the shear stress at the time of fracture of the soils having moisture amounts m 1 , m 2 ,..., Max to the shear strength s 1 , s 2 ,. , ⁇ 1 , ⁇ 2 ,... ⁇ max .
  • the water content m 1, m 2 corresponds to ⁇ ⁇ ⁇ m max, adhesion C 1, C 2, ⁇ C max, internal friction angle phi 1, phi 2 ... ⁇ max can be calculated.
  • the measurement part 11 implements a hydration test using the test body (soil mass) which is the same as the soil used in the shear test in Step S11, that is, a soil (soil mass) made of soil of the same type, dry density and compaction degree ( Step S13).
  • FIG. 4 is a flowchart showing an example of the water addition test of the measurement unit in FIG.
  • a specimen made of soil of the same type, dry density and compaction as the soil used in the shear test and having a relatively low water content is prepared (Ste S131).
  • the test body a soil block adjusted so as to have a test layer with a lower water content ratio than a test body having a test layer with the minimum water content ratio among the test bodies used in the shear test is used.
  • the measurement unit 11 sets the prepared clot on a test machine including the moisture meter, the pore water pressure meter, and the weight meter included in the measurement unit 11, and measures the moisture content, the pore water pressure, and the clot weight. (Steps S132 to S134). As a result, at least the water content, pore water pressure, and soil weight of the soil mass in a state where the water content ratio before the addition is known are obtained.
  • moisture content data, pore water pressure data, and soil mass weight data of the soil mass in each state (before and after each addition) in the hydrolysis process until the soil is saturated are acquired.
  • saturated of the soil specifically means a state where water does not soak into the soil.
  • the measurement unit 11 has one or more water amounts m 1 , m 2 ,..., M max that differ in water content ratios created using the material layer (earth and sand) collected from the slope to be monitored by the water test.
  • Pore water pressures u 1 , u 2 ,... U max , and clot weights W 1 , W 2 ,... W max are acquired (step S14).
  • the water test is performed after the shear test, but the order of the test is not particularly limited.
  • the measurement unit 11 is, for example, a soil parameter obtained by measuring in advance in association with the water content m 1 , m 2 ,... M max , that is, adhesive force, internal friction angle, pore water pressure, and soil mass.
  • the weight and a plurality of moisture amounts m 1 , m 2 ,... M max may be associated with each other and stored in a storage unit (not shown).
  • the modeling unit 12 uses, for example, an adhesive force-moisture amount model, an internal friction angle-moisture amount model, based on an adhesive force, an internal friction angle, a clot weight, and a pore water pressure that are acquired from a storage unit (not shown).
  • the optimum state moisture amount estimation unit 13 calculates a safety factor for each moisture amount based on, for example, the adhesive force, the internal friction angle, the clot weight, and the pore water pressure obtained by linking each moisture amount from a storage unit (not shown). Estimate the optimal amount of water that maximizes the safety factor.
  • the storage unit 14 stores the model formula generated by the modeling unit 12 and the optimal amount of water estimated by the optimal state water amount estimation unit 13.
  • the slope monitoring system 1 also includes a moisture meter 15 installed on the monitored slope, and a current safety factor calculation unit 16 that calculates the current safety factor from the current moisture amount mt measured on the monitored slope. .
  • the slope monitoring system 1 includes an optimum state safety factor calculating unit 17 that calculates the safety factor of the optimum state from the amount of moisture in the optimum state, and the current state of the safety factor and the safety factor of the optimum state calculated based on the calculated current safety factor.
  • a risk output unit 18 for determining the risk is provided.
  • the current safety factor calculation unit 16 and the optimum state safety factor calculation unit 17 obtain in advance the slope length l of the slope to be monitored, the slope inclination angle ⁇ of the slope, and the slip layer depth d. Further, the current safety factor calculation unit 16 stores a soil parameter (current soil parameter) corresponding to the moisture amount mt measured on the monitoring target slope, that is, the adhesive force Ct, the internal friction angle ⁇ t, the pore water pressure ut, and the clot weight Wt. 14 based on the model formula stored in FIG.
  • the current safety factor calculation unit 16 calculates the current safety factor of the slope according to the equation (1) using the estimated soil parameters, that is, the adhesive force Ct, the internal friction angle ⁇ t, the pore water pressure ut, and the clot weight Wt.
  • the optimum state safety factor calculation unit 17 is a soil parameter (optimum soil parameter) corresponding to the optimum amount of water stored in the storage unit 14, that is, adhesive force Ct, internal friction angle ⁇ t, pore water pressure ut, and lump weight Wt. Is estimated based on the model formula stored in the storage unit 14. Then, the optimum state safety factor calculation unit 17 uses the soil parameters corresponding to the estimated optimum amount of water, that is, the adhesive force Ct, the internal friction angle ⁇ t, the pore water pressure ut, and the mass of the soil mass Wt according to the equation (1). Calculate the optimal safety factor.
  • the risk output unit 18 determines the risk of the slope to be monitored based on the calculated current safety factor and the optimum safety factor.
  • each component of the slope monitoring system of 1st embodiment shown in FIG. 1 and other embodiment mentioned later has shown the block of the functional unit. Part or all of the components of the slope monitoring system of each embodiment may be realized by any combination of a computer 50 and a program as shown in FIG. 14, for example.
  • the computer 50 includes the following configuration as an example.
  • CPU Central Processing Unit
  • ROM Read Only Memory
  • RAM Random Access Memory
  • a program 54 loaded into the RAM 53
  • a storage device 55 for storing the program 54
  • a drive device 57 that reads and writes the recording medium 56
  • Each component of each embodiment is implement
  • the modeling unit 12 uses the model based on the soil parameter and the water content measured by the CPU 51 that has acquired the program 54 in association with the water content based on the program 54.
  • a function may be realized by performing processing for generating an expression.
  • the optimum state water amount estimation unit 13 estimates the optimum amount of water with the maximum safety factor based on the above-mentioned soil parameters based on the program 54, and the CPU 51 that has acquired the program 54 calculates the optimum amount of water.
  • the function may be realized by performing processing stored in the storage device 55.
  • the CPU 51 that has acquired the program 54 performs processing for acquiring the current water content measured on the slope to be monitored based on the program 54.
  • CPU51 which acquired the program 54 performs the process which estimates a soil parameter (present soil parameter) based on said model formula memorize
  • CPU51 which acquired the program 54 performs the process which calculates the present safety factor using the estimated soil parameter based on the program54.
  • the function of the current safety factor calculation unit 16 may be realized by performing these processes.
  • the CPU 51 that has acquired the program 54 stores the optimum state stored in the storage device 55 based on the model formula stored in the storage device 55 based on the program 54.
  • the soil parameter (optimum soil parameter) is estimated from the water content of the soil.
  • CPU51 which acquired the program 54 performs the process which calculates the safety factor of an optimal state using the estimated soil parameter based on the program54.
  • the function of the optimum state safety factor calculation unit 17 may be realized by performing these processes.
  • the risk output unit 18 obtains the current risk level based on the optimum state based on the current safety factor and the optimum state safety factor calculated as described above based on the program 54 by the CPU 51 that has acquired the program 54.
  • a function may be realized by performing a process of outputting a level.
  • the program 54 that realizes the function of each component of each embodiment is stored in advance in the storage device 55, the ROM 52, or the RAM 53, for example, and may be configured to be read by the CPU 51 as necessary.
  • the program 54 may be supplied to the CPU 51 via the communication network 59, or may be stored in advance in the recording medium 56, and the drive device 57 may read the program and supply it to the CPU 51.
  • FIG. 5 is a flowchart showing the soil parameter modeling and optimum state determination operation of the first embodiment.
  • the modeling unit 12 constructs a soil mass-water content model and a pore water pressure-water content model from the soil mass weight and pore water pressure obtained in association with the moisture content. That is, the modeling unit 12 creates a model formula that expresses the mass of the mass (density) and the pore water pressure as a function of the water content (step S16).
  • the modeling unit 12 constructs an adhesive force-water amount model and an internal friction angle-water amount model from the adhesive force and the internal friction angle acquired in association with the water amount. That is, the modeling unit 12 creates a model formula that expresses the adhesive force and the internal friction angle as a function of the water content (step S17).
  • the optimum state moisture amount estimation unit 13 estimates the moisture amount in the optimum state using soil parameters obtained in association with a plurality of moisture amounts. Specifically, the optimum state moisture amount estimation unit 13 acquires the slope length, the slope angle, and the slip layer depth in advance based on the investigation result on the monitoring target slope, and is obtained in association with a plurality of moisture amounts.
  • the safety factor is calculated based on the formula (1) from the adhesive strength, the internal friction angle, the mass of the clot (density), and the pore water pressure. Then, from the increase / decrease of the safety factor with respect to the moisture content, the moisture content when the safety factor becomes the highest is estimated and set as the optimum moisture content (step S18).
  • the modeling unit 12 stores the created adhesive strength-water content model, internal friction angle-water content model, clot weight (density) -water content model, pore water pressure-water content model in the storage unit 14, and the optimal state moisture
  • the amount estimation unit 13 stores the optimal amount of water and the optimal state safety factor in the storage unit 14 (step S19).
  • FIG. 6 is a flowchart showing the risk degree calculation operation of the first embodiment.
  • the moisture meter 15 measures the current moisture content mt on the slope to be monitored (step S21).
  • the current safety factor calculation unit 16 substitutes the moisture amount mt measured on the monitoring target slope into the four model formulas stored in the storage unit 14, so that four analytical formulas at the time of measuring the moisture amount on the monitoring target slope are obtained.
  • variables current soil parameters
  • that is, adhesive force, internal friction angle, mass of clot (density), and pore water pressure are estimated (step S22).
  • the current safety factor calculation unit 16 acquires the slope length l of the slope to be monitored, the slope slope angle ⁇ of the slope, and the slip layer depth d in advance, and the estimated soil parameters, that is, the adhesive force Ct and the internal friction angle.
  • the current safety factor Fs of the slope is calculated by Equation (1) using ⁇ t, pore water pressure ut, and lump weight Wt (step S23).
  • the optimum state safety factor calculation unit 17 substitutes the estimated amount of water in the optimum state into the four model formulas stored in the storage unit 14 to obtain four analytical equation variables (optimum in the optimum state of the slope to be monitored).
  • (Soil parameters) that is, values of adhesive force, internal friction angle, soil mass weight (density), and pore water pressure are estimated (step S24).
  • the optimum state safety factor calculation unit 17 obtains in advance the slope length l of the slope to be monitored, the slope slope angle ⁇ of the slope, and the slip layer depth d, and provides four analytical formula variables in the optimum state of the slope to be monitored. That is, the safety factor Fsopt of the optimum state of the slope is calculated by the equation (1) using the adhesive force, the internal friction angle, the pore water pressure, and the mass of the clot (step S25).
  • FIG. 7 is a diagram illustrating an example of the current risk level output based on the optimum state of the risk output unit of FIG.
  • the risk output unit 18 displays the current safety factor Fs together with the optimum safety factor Fsop on a display unit (not shown) as shown in FIG. 7, for example (step S26).
  • the risk output unit 18 determines whether the measurement is completed, and if it is determined that the measurement is not completed, the process returns to step S21. Thus, the process of step S21 to S26 is repeated until a measurement is complete
  • the current safety factor Fs calculated from the amount of water mt measured on the slope to be monitored is displayed together with the safety factor Fsopt in the optimum state, so the safety factor Fsopt in the optimum state is displayed.
  • the current safety factor Fs which changes according to the amount of moisture in the soil, can be grasped step by step, and step-by-step warning and evacuation can be issued.
  • the risk output unit 18 has been described as displaying the current safety factor Fs together with the safety factor Fsopt in the optimum state.
  • the present invention is not limited to this, and various methods for outputting the risk level are conceivable.
  • a plurality of risk levels may be set, and the risk level determined from the current safety factor Fs based on the safety factor Fsopt in the optimum state may be output.
  • FIG. 8 is a block diagram showing the configuration of the second embodiment.
  • the risk output unit 18 includes a level range setting unit 181, a risk level determination unit 182, and a display unit 183.
  • the level range setting unit 181 sets a predetermined number of stages, for example, five risk levels in advance.
  • the level range setting unit 181 sets the range of the current safety factor Fs corresponding to each risk level based on the safety factor Fsopt in the optimum state.
  • the risk level determination unit 182 determines which of the risk levels the current safety factor Fs calculated from the amount of water mt measured on the slope to be monitored corresponds.
  • the display unit 183 displays a risk level corresponding to the current safety factor Fs.
  • FIG. 9 is a diagram illustrating a first setting example of each risk level.
  • the risk level determination unit 182 calculates the risk level D from the current safety rate Fs based on the safety factor Fsopt in the optimum state, and the level range setting unit 181 sets the range of the risk level D for each risk level. May be.
  • the risk level determination unit 182 calculates the risk level from the ratio of the current safety factor Fs and the optimum safety factor Fsopt as shown in the following equation (3).
  • D (Fs-1) / (Fsopt-1) (3)
  • the level range setting unit 181 sets a predetermined number of levels, for example, five levels as the risk level, and sets the range of the risk D calculated by the above equation (3) for each risk level. Set.
  • the level range setting unit 181 sets a predetermined number of levels, for example, five levels as the risk level, and sets the range of the risk D calculated by the above equation (3) for each risk level. Set.
  • the level range setting unit 181 sets the risk D range of each risk level as follows.
  • the risk level determination unit 182 Is used to calculate the risk level D, and the corresponding risk level is determined based on the risk level range set by the level range setting unit 181 and displayed on the display unit 183.
  • the second embodiment based on the current safety factor Fs and the optimum safety factor Fopt, for example, it is determined which of the five risk levels is set. Since it is displayed on the display unit, it is possible to clearly grasp the level of the risk level of the slope to be monitored, and to perform step-by-step warning and evacuation.
  • FIG. 10 is a diagram illustrating a second setting example of each risk level. As shown in FIG. 10, the second example is an example in which the width of the safety factor range at the high risk level is set narrower than the low risk level.
  • FIG. 11 is a block diagram showing the configuration of a risk output unit that sets the width of each risk level as shown in FIG.
  • the risk output unit 19 of the present modified example sets the ratio of the width of the safety factor range of each risk level so that the width of the safety factor range at the high risk level becomes narrower than the low risk level.
  • a range ratio setting unit 191 to be set is provided, and the level range setting unit 192 is different from the configuration of FIG. 8 in that the width of the safety factor range of each risk level is set based on the set ratio.
  • the range ratio setting unit 191 has a safety level at each risk level so that the range of the safety factor range at the high risk level is narrower than the low risk level for the N risk levels.
  • the range ratio setting unit 191 sets, for example, the width of level N, the width of level N ⁇ 1,..., The width of level 2 and the width of level 1 of 1: 2:. : N ratio is set.
  • the range ratio setting unit 191 sets the ratio of the range from the level 5 with the highest risk to the level 1 to 1: 2: 3: 4: 5.
  • the level range setting unit 192 sets the range of the risk level D of each risk level as follows so that the range from the level 5 with the highest risk level to the level 1 becomes 1: 2: 3: 4: 5. .
  • the risk level determination unit 182 Is used to calculate the risk level D, and the corresponding risk level is determined based on the risk level range set by the level range setting unit 192 and displayed on the display unit 183.
  • the range of the risk level with a high risk level is set narrower than the width of the risk level with a low risk level, so the possibility of false alarms at the highest risk level is reduced.
  • FIG. 12 is a diagram illustrating a third setting example of each risk level.
  • the third example is an example in which a caution safety factor that is the upper limit of the highest risk level is set.
  • FIG. 13 is a block diagram showing a configuration of a risk output unit that sets the width of each risk level as shown in FIG.
  • the degree-of-risk output unit 20 of the present modification includes a caution safety factor setting unit 201 and a range ratio setting unit 202.
  • the caution safety factor setting unit 201 sets the caution safety factor that is the upper limit of the risk level with the highest risk.
  • the range ratio setting unit 202 sets the width of the safety factor range of each risk level so that the width of the safety factor range at the risk level other than the risk level with the highest risk level becomes narrower as the risk level with the higher risk level. Set the ratio.
  • the level range setting unit 203 sets the width of the safety factor range of each risk level based on the attention safety factor and the set ratio.
  • the risk output unit 20 of this modification is different from the configurations of FIGS. 8 and 11 in these respects.
  • the width of the safety factor range equal to or higher than the second highest risk level is an example in which the range of the high risk level is set narrower than the low risk level as in the second example.
  • the range from the risk level N-1 having the second highest risk level to the risk level 1 is 2: 3: ...: N-1: N It is set to become the ratio.
  • the level range setting unit 203 has the risk level D of the highest risk level D.
  • the level range setting unit 203 sets the risk level D of each risk level so that the range of the risk level 1 from the risk level 4 having the second highest risk level becomes a ratio of 2: 3: 4: 5. Set the range.
  • the level range setting unit 203 sets the range of the risk level D of each risk level as follows.
  • the range of the risk level with the highest risk can be set arbitrarily, appropriate warning and evacuation can be issued according to the region and weather conditions.

Abstract

In order to make it possible to grasp, in a stepwise manner, a safety factor and a degree of danger that change in accordance with the moisture content in soil and to enable the issuing of warnings and evacuation orders in stages, this slope monitoring system 1 comprises: a measurement unit 11 that measures soil parameters in association with a moisture content regarding a material layer constituting a slope to be monitored; a modeling unit 12 that generates a model formula on the basis of the measured soil parameters and moisture content; an optimal state moisture content estimation unit 13 that estimates an optimal state moisture content at which a maximum safety factor is achieved; a moisture meter 15 that measures the current moisture content in the slope to be monitored; a current safety factor calculation unit 16 that calculates a safety factor using the soil parameters estimated from the current moisture content; an optimal state safety factor calculation unit 17 that calculates a safety factor using soil parameters estimated from the optimal state moisture content; and a danger degree output unit 18 that outputs a current danger degree level in which the optimal state is used as a reference.

Description

斜面監視システム、斜面監視方法及び記録媒体Slope monitoring system, slope monitoring method and recording medium
　本発明は、山や谷などの地形における斜面を監視する斜面監視システム、斜面監視方法及び記録媒体に関する。 The present invention relates to a slope monitoring system, a slope monitoring method, and a recording medium for monitoring slopes on topography such as mountains and valleys.
　大雨のときに、山や谷などの地形における斜面が崩壊する危険性、又は、斜面の崩壊の恐れがない度合を示す安全性を評価する指標として安全率が用いられている。安全率は、斜面の安全性を評価する指標であって、斜面を滑落しようとする滑落力を分母とし、滑落を抑止しようとする抵抗力を分子とした比で表わされる。この値が１未満、すなわち滑落力が抵抗力よりも大きくなったときに、崩壊する可能性があると評価される。 The safety factor is used as an index for evaluating the safety of the risk of collapse of slopes in terrain such as mountains and valleys, or the degree of no risk of slope collapse during heavy rain. The safety factor is an index for evaluating the safety of a slope, and is represented by a ratio in which a sliding force for sliding down the slope is used as a denominator and a resistance force for preventing the sliding is used as a numerator. When this value is less than 1, that is, when the sliding force becomes larger than the resistance force, it is evaluated that there is a possibility of collapse.
　例えば特許文献１，２に、この種の斜面安全性監視技術が開示されている。特許文献１に開示される斜面監視システムは、監視対象斜面を構成している物質層と略同一の物質層である試験層を有する試験環境から計測される、試験層の水分量を変化させたときの、所定の解析式変数の各々の値を計測する。そして斜面監視システムは、解析式変数の各々の値と、水分量に基づいて、解析式変数の各々について、水分量から各解析式変数の値との関係を規定するモデルを構築する。そして斜面監視システムは、構築されたモデルを用いて監視対象斜面の水分量を計測したときの各解析式変数の値を算出し、算出された各解析式変数の値を基に、斜面安定解析式を用いて監視対象斜面の安全率を算出する。 For example, Patent Documents 1 and 2 disclose this type of slope safety monitoring technology. The slope monitoring system disclosed in Patent Document 1 changes the moisture content of the test layer measured from a test environment having a test layer that is substantially the same material layer as the material layer constituting the monitored slope. Measure each value of a predetermined analytical expression variable. Then, the slope monitoring system constructs a model that defines the relationship between the amount of water and the value of each analytical expression variable for each of the analytical expression variables based on the value of each analytical expression variable and the amount of water. The slope monitoring system calculates the value of each analytical expression variable when measuring the water content of the monitored slope using the constructed model, and based on the calculated value of each analytical expression variable, the slope stability analysis Calculate the safety factor of the slope to be monitored using the formula.
　特許文献２に開示される災害予測システムは、特定の地点における土中の水分量を取得し、特定の地点を含む一定の範囲における地表の水分量を取得する。そして災害予測システムは、特定の地点における土中の水分量と、一定の範囲における地表の水分量とに基づいて、一定の範囲に含まれる任意の地点における土中の水分量または一定の範囲に含まれる任意の地点における土壌の特性を表すパラメータを推定する。また災害予測システムは、斜面安定解析式を利用して算出した安全率が徐々に小さくなり１に近づいてきた時点で、当該地域に土砂災害の危険があると判定し、当該地点の周辺に住む住民に対し避難勧告や避難指示を出すことで、時機を逸しないタイムリーな警報を実現しようとするものである。 The disaster prediction system disclosed in Patent Document 2 acquires the amount of moisture in the soil at a specific point, and acquires the amount of water on the ground surface in a certain range including the specific point. And the disaster prediction system is based on the moisture content in the soil at a specific point and the moisture content on the ground surface in a certain range. Estimate the parameters representing the characteristics of the soil at any point included. The disaster prediction system determines that there is a risk of landslide disaster in the area when the safety factor calculated using the slope stability analysis formula gradually decreases and approaches 1, and lives in the vicinity of the point By issuing evacuation advisories and evacuation instructions to residents, it is intended to realize timely warnings that do not miss time.
国際公開第２０１６／０２７３９０号International Publication No. 2016/027390 国際公開第２０１７／０４７０６１号International Publication No. 2017/047061 国際公開第２０１６／０２７２９１号International Publication No. 2016/027291
　しかしながら特許文献１及び特許文献３の斜面監視システムは、構築されたモデルを用いて監視対象斜面の水分量を計測したときの各解析式変数の値を算出し、算出された各解析式変数の値を基に斜面安定解析式を用いて監視対象斜面の安全率を算出し、所定の閾値を下回っていれば警報を出すものである。特許文献１及び特許文献３は、安全率が所定の閾値以下か、それ以外かの２段階で危険度が判断され、それより多数の段階による段階的な評価が可能な構成は開示されていない。特許文献２にも同様に、安全率が１に近づいてきた時点で土砂災害の危険があると判定し避難勧告や避難指示を出す構成が開示されているが、特許文献２にも、崩壊に近い危険度か、否かの２段階より多数の段階による段階的な評価が可能な構成は開示されていない。 However, the slope monitoring systems of Patent Document 1 and Patent Document 3 calculate the value of each analytical expression variable when the moisture content of the monitored slope is measured using the constructed model, and the calculated analytical expression variable The safety factor of the slope to be monitored is calculated using the slope stability analysis formula based on the value, and an alarm is issued if it falls below a predetermined threshold. Patent Document 1 and Patent Document 3 do not disclose a configuration in which the degree of danger is determined in two stages, that is, the safety factor is equal to or less than a predetermined threshold value, and a gradual evaluation in more stages is possible. . Similarly, Patent Document 2 discloses a configuration in which it is determined that there is a risk of a landslide disaster when the safety factor approaches 1, and an evacuation recommendation or evacuation instruction is issued. There is no disclosure of a configuration that can perform stepwise evaluation in more stages than two stages of near risk or not.
　本発明は、土中水分量に応じて変化する安全率や危険度を段階的に把握でき、段階的な警戒や避難の発令ができる斜面監視システム、斜面監視方法及び記録媒体を提供することを主な目的としている。 It is an object of the present invention to provide a slope monitoring system, a slope monitoring method, and a recording medium capable of stepwise grasping the safety factor and the degree of danger that change in accordance with the amount of moisture in the soil, and making a stepwise warning and evacuation order. The main purpose.
　本発明の１つの側面による斜面監視システムは、監視対象斜面を構成している物質層について水分量と紐づけて土壌パラメータを測定する測定部と、測定された前記土壌パラメータと前記水分量に基づいてモデル式を生成するモデル化部と、前記土壌パラメータに基づいて安全率が最大となる最適状態の水分量を推定する最適状態水分量推定部と、前記監視対象の斜面において現状の水分量を計測する水分計と、前記モデル式に基づいて前記現状の水分量から推定される現状土壌パラメータを用いて現状の安全率を算出する現状安全率算出部と、前記モデル式に基づいて前記最適状態の水分量から推定される最適土壌パラメータを用いて前記最適状態の安全率を算出する最適状態安全率算出部と、前記現状の安全率と前記最適状態の安全率とに基づいて前記最適状態を基準とした現状の危険度レベルを出力する危険度出力部と、を備える。 A slope monitoring system according to one aspect of the present invention is based on a measurement unit that measures a soil parameter in association with a moisture content of a material layer that constitutes a monitored slope, and based on the measured soil parameter and the moisture content. A modeling unit that generates a model equation, an optimal state water amount estimation unit that estimates the optimal amount of water with the maximum safety factor based on the soil parameter, and a current water amount on the monitored slope. A moisture meter to be measured; a current safety factor calculation unit that calculates a current safety factor using a current soil parameter estimated from the current moisture content based on the model equation; and the optimum state based on the model equation An optimum state safety factor calculation unit that calculates the optimum factor safety factor using an optimum soil parameter estimated from the water content of the water, the current safety factor and the optimum factor safety factor And a risk output unit for outputting the risk level of the current relative to the said optimum state based on.
　本発明の他の側面による斜面監視方法は、監視対象斜面を構成している物質層について水分量と紐づけて土壌パラメータを測定し、測定された前記土壌パラメータと前記水分量に基づいてモデル式を生成し、前記土壌パラメータに基づいて安全率が最大となる最適状態の水分量を推定し、前記監視対象の斜面において現状の水分量を計測し、前記モデル式に基づいて前記現状の水分量から推定される現状土壌パラメータを用いて現状の安全率を算出し、前記モデル式に基づいて前記最適状態の水分量から推定される最適土壌パラメータを用いて前記最適状態の安全率を算出し、前記現状の安全率と前記最適状態の安全率とに基づいて前記最適状態を基準とした現状の危険度レベルを出力する。 In the slope monitoring method according to another aspect of the present invention, a soil layer is measured by associating a moisture content with a substance layer constituting a slope to be monitored, and a model formula is based on the measured soil parameter and the moisture content. Generating an optimal amount of water with a maximum safety factor based on the soil parameter, measuring the current amount of water on the slope to be monitored, and based on the model formula Calculate the current safety factor using the current soil parameter estimated from, calculate the optimal state safety factor using the optimal soil parameter estimated from the water content of the optimal state based on the model formula, Based on the current safety factor and the optimum safety factor, a current risk level based on the optimum state is output.
　本発明のさらに他の側面による記録媒体は、コンピュータに、監視対象斜面を構成している物質層について水分量と紐づけて測定された土壌パラメータと前記水分量に基づいてモデル式を生成する処理、前記土壌パラメータに基づいて安全率が最大となる最適状態の水分量を推定する処理、前記監視対象の斜面において現状の水分量を取得する処理、前記モデル式に基づいて前記現状の水分量から推定される現状土壌パラメータを用いて現状の安全率を算出する処理、前記モデル式に基づいて前記最適状態の水分量から推定される最適土壌パラメータを用いて前記最適状態の安全率を算出する処理、及び、前記現状の安全率と前記最適状態の安全率とに基づいて前記最適状態を基準とした現状の危険度レベルを出力する処理、を実行させる斜面監視プログラムを格納している。 According to still another aspect of the present invention, there is provided a recording medium that generates, on a computer, a model formula based on a soil parameter measured in association with a moisture content and a moisture content of a material layer constituting a monitoring target slope. , A process for estimating the optimum amount of water that maximizes the safety factor based on the soil parameter, a process for obtaining the current amount of water on the slope to be monitored, and the current amount of water based on the model formula Processing to calculate the current safety factor using the estimated current soil parameter, processing to calculate the safety factor of the optimal state using the optimal soil parameter estimated from the water content of the optimal state based on the model formula And a process for outputting a current risk level based on the optimum state based on the current safety factor and the optimum factor safety factor. Stores surface monitoring program.
　本発明の上記側面によれば、土中水分量に応じて変化する安全率や危険度を段階的に把握でき、段階的な警戒や避難の発令ができる。 According to the above aspect of the present invention, the safety factor and the degree of danger that change according to the amount of moisture in the soil can be grasped step by step, and step by step warning and evacuation can be issued.
図１は、第一の実施形態の構成の一例を示すブロック図である。FIG. 1 is a block diagram illustrating an example of the configuration of the first embodiment. 図２は、図１の測定部の斜面安定性に関連する土壌パラメータの取得方法の一例を示すフローチャートである。FIG. 2 is a flowchart illustrating an example of a method for acquiring soil parameters related to slope stability of the measurement unit in FIG. 図３は、図２のステップＳ１１における三軸圧縮試験（せん断試験）の詳細を示すフローチャートである。FIG. 3 is a flowchart showing details of the triaxial compression test (shear test) in step S11 of FIG. 図４は、図１の測定部の加水試験の例を示すフローチャートである。FIG. 4 is a flowchart illustrating an example of a water addition test of the measurement unit in FIG. 図５は、図１のモデル化の動作及び最適状態の水分量を推定する動作の一例を示すフローチャートである。FIG. 5 is a flowchart showing an example of the modeling operation of FIG. 1 and the operation of estimating the optimum amount of water. 図６は、第一の実施形態の安全率算出動作を示すフローチャートである。FIG. 6 is a flowchart showing the safety factor calculation operation of the first embodiment. 図７は、図１の危険度出力部の最適状態を基準とした現状の危険度レベルの出力の一例を示す図である。FIG. 7 is a diagram illustrating an example of the current risk level output based on the optimum state of the risk output unit of FIG. 図８は、第二の実施形態の構成の一例を示すブロック図である。FIG. 8 is a block diagram illustrating an example of the configuration of the second embodiment. 図９は、各危険度レベルの第１の設定例を示す図である。FIG. 9 is a diagram illustrating a first setting example of each risk level. 図１０は、各危険度レベルの第２の設定例を示す図である。FIG. 10 is a diagram illustrating a second setting example of each risk level. 図１１は、図１０のように各危険度レベルの幅を設定する危険度出力部の構成を示すブロック図である。FIG. 11 is a block diagram showing a configuration of a risk output unit that sets the width of each risk level as shown in FIG. 図２は、各危険度レベルの第３の設定例を示す図である。FIG. 2 is a diagram illustrating a third setting example of each risk level. 図１３は、図１２のように各危険度レベルの幅を設定する危険度出力部の構成を示すブロック図である。FIG. 13 is a block diagram showing a configuration of a risk output unit that sets the width of each risk level as shown in FIG. 図１４は、各実施形態の各部を実現するコンピュータの構成の一例を示す図である。FIG. 14 is a diagram illustrating an example of a configuration of a computer that implements each unit of each embodiment.
　次に例示的な第一の実施形態について図面を参照して説明する。本発明の各実施形態では、式（１）に示すような斜面安定解析式を用いるフェレニウス法により斜面の安全性を評価する例について説明する。
Figure JPOXMLDOC01-appb-I000001
Next, an exemplary first embodiment will be described with reference to the drawings. In each embodiment of the present invention, an example in which the safety of a slope is evaluated by the Ferrenius method using a slope stability analysis formula as shown in Formula (1) will be described.
Figure JPOXMLDOC01-appb-I000001
　ここで、Ｆｓは安全率、αは傾斜勾配角、Ｃ、Ｗ、ｕ、φは、それぞれ土壌の性質を表す土壌パラメータである粘着力、土塊重量、間隙水圧、内部摩擦角である。 Here, Fs is the safety factor, α is the slope angle, C, W, u, and φ are the soil parameters representing the properties of the soil, adhesive strength, mass weight, pore water pressure, and internal friction angle, respectively.
　フェレニウス法において、各分割片（土塊等）のせん断応力は、当該分割片の、当該分割片に加わる重力としての土塊重量Ｗと傾斜勾配角αとで表される（式（１）の分母参照）。一方、各分割片のせん断抵抗力は、分割片（土塊）の、粘着力Ｃと、垂直応力に基づく抵抗力（（Ｗ－ｕ）ｃｏｓα・ｔａｎφ）とで表される（式（１）の分子参照）。フェレニウス法においては、各分割片の斜面方向に働くせん断応力と、そのせん断応力による滑落を阻止するせん断抵抗力との比を用いて算出される安全率Ｆｓによって斜面の安全性が評価される。 In the Ferrenius method, the shear stress of each divided piece (such as a lump) is represented by the lump weight W as the gravity applied to the divided piece and the slope gradient angle α (see the denominator of equation (1)). ). On the other hand, the shear resistance of each divided piece is expressed by the adhesive force C of the divided piece (clump) and the resistance force ((Wu) cos α · tan φ) based on the vertical stress (of the equation (1)) See molecule). In the Ferrenius method, the safety of a slope is evaluated by a safety factor Fs calculated using a ratio of a shear stress acting in the slope direction of each divided piece and a shear resistance force that prevents sliding due to the shear stress.
　図１は、第一の実施形態の構成の一例を示すブロック図である。図１に示すように斜面監視システム１は、測定部１１と、モデル化部１２と、最適状態水分量推定部１３と、記憶部１４を備えている。 FIG. 1 is a block diagram showing an example of the configuration of the first embodiment. As shown in FIG. 1, the slope monitoring system 1 includes a measurement unit 11, a modeling unit 12, an optimum state moisture amount estimation unit 13, and a storage unit 14.
　測定部１１は、監視対象斜面を構成している物質層（土砂）を用いて、水分量と紐づけて予め斜面安定性に関連する土壌パラメータを測定する。すなわち測定部１１は、１以上の水分量ｍの土砂で予め斜面安定性に関連する土壌パラメータを測定する。斜面安定性に関連する土壌パラメータとは、具体的には、粘着力Ｃ、内部摩擦角φ、間隙水圧ｕ、土塊重量Ｗである。例えば、予め監視対象斜面から採取した物質層（土砂）を用いて作成された含水比が異なる１以上の水分量ｍ１、ｍ２、・・・ｍｍａｘの試験体（土塊）について土壌パラメータ、すなわち粘着力Ｃ１、Ｃ２、・・・Ｃｍａｘ、内部摩擦角φ１、φ２、・・・φｍａｘ、間隙水圧ｕ１、ｕ２、・・・ｕｍａｘ、土塊重量Ｗ１、Ｗ２、・・・Ｗｍａｘが測定される。本実施形態では、式（１）により算出される安全率が最大となる最適状態の含水比（水分量）を判断する必要があるため、安全率が最大となると予想される範囲の含水比、すなわち水分量が少ない範囲でも複数の水分量で試験体を作成し土壌パラメータの測定を行う。 The measurement part 11 measures the soil parameter relevant to slope stability previously linked | related with a moisture content using the substance layer (sediment) which comprises the monitoring object slope. That is, the measurement part 11 measures the soil parameter relevant to slope stability previously with the soil of 1 or more moisture content m. Specifically, the soil parameters related to the slope stability are the adhesive force C, the internal friction angle φ, the pore water pressure u, and the clot weight W. For example, soil parameters for a specimen (soil mass) of one or more water amounts m 1 , m 2 ,..., Max , which are created using a material layer (sediment) collected in advance from a slope to be monitored and have different water content ratios, That is, adhesive forces C 1 , C 2 ,... C max , internal friction angles φ 1 , φ 2 ,... Φ max , pore water pressures u 1 , u 2 , ... u max , clot weight W 1 , W 2 ... W max is measured. In this embodiment, since it is necessary to determine the water content ratio (water content) in the optimum state where the safety factor calculated by the equation (1) is maximum, the water content ratio in the range where the safety factor is expected to be maximum, That is, even in a range where the amount of water is small, a specimen is prepared with a plurality of water amounts and the soil parameters are measured.
　図２は、図１の測定部の斜面安定性に関連する土壌パラメータの取得方法の一例を示すフローチャートである。まず、測定部１１は、粘着力Ｃ、内部摩擦角φを算出するため三軸圧縮試験（せん断試験）を行う（ステップＳ１１）。 FIG. 2 is a flowchart showing an example of a method for acquiring soil parameters related to the slope stability of the measurement unit in FIG. First, the measuring unit 11 performs a triaxial compression test (shear test) to calculate the adhesive force C and the internal friction angle φ (step S11).
　図３は、図２のステップＳ１１における三軸圧縮試験（せん断試験）の詳細を示すフローチャートである。まず、監視対象斜面から採取した物質層（土砂）を用いて、含水比を調整した試験体（土塊）が作成される（ステップＳ１１１）。試験体の土は、実斜面の土と同質のものを用いる。ここで試験体は、実斜面の土と同一の種類、乾燥密度および締固め度の土からなる土塊を、含水比を変えて複数作成される。 FIG. 3 is a flowchart showing details of the triaxial compression test (shear test) in step S11 of FIG. First, using a material layer (sediment) collected from the slope to be monitored, a test body (soil mass) having an adjusted water content ratio is created (step S111). The soil of the test body is the same as the soil of the actual slope. Here, a plurality of test bodies are formed by changing the water content ratio of soil blocks made of soil having the same type, dry density and compaction as the soil on the actual slope.
　次に、測定部１１は、水分計を用いて、用意した土塊の水分量を計測する（ステップＳ１１２）。 Next, the measuring unit 11 measures the water content of the prepared earth clot using a moisture meter (step S112).
　次に、測定部１１は、用意された土塊を、測定部１１に含まれる、応力センサを備えた三軸圧縮試験装置にセットして圧縮を行い、圧縮時の垂直応力σとせん断応力τを計測する（ステップＳ１１３）。 Next, the measurement unit 11 performs compression by setting the prepared soil block in a triaxial compression test apparatus including a stress sensor included in the measurement unit 11, and calculates the vertical stress σ and shear stress τ during compression. Measurement is performed (step S113).
　必要回数に達するまで、ステップＳ１１２～Ｓ１１３の圧縮および応力測定を繰り返し実施する（ステップＳ１１４）。通常は最低３回圧縮および応力測定が実施される。これにより、１つの土塊に対して、少なくとも複数の垂直荷重に対応したせん断時の垂直応力データおよびせん断応力データが得られる。 Until the required number of times is reached, the compression and stress measurement in steps S112 to S113 is repeated (step S114). Usually at least three compression and stress measurements are performed. Thereby, the normal stress data and the shear stress data at the time of shearing corresponding to at least a plurality of vertical loads are obtained for one soil block.
　必要サンプル数に達するまで、含水比を変えた土塊に対して同様の動作がわれる（ステップＳ１１５）。これにより、測定部１１は、含水比の異なる土塊の各々に対して、水分量データと、複数の垂直荷重に対応したせん断時の垂直応力データおよびせん断応力データとを得る。 Until the required number of samples is reached, the same operation is performed on the soil block with the changed moisture content (step S115). As a result, the measurement unit 11 obtains moisture amount data, and normal stress data and shear stress data during shearing corresponding to a plurality of vertical loads, for each of the soil blocks having different moisture contents.
　せん断試験により、含水比の異なる土塊の各々に対して、水分量データと、複数の垂直荷重に対応したせん断時の垂直応力データおよびせん断応力データとを得ると、測定部１１は、得られた垂直応力データおよびせん断応力データに基づいて、粘着力Ｃおよび内部摩擦角φを算出する（図２のステップＳ１２）。 When the moisture amount data, the normal stress data during shearing and the shear stress data corresponding to a plurality of vertical loads are obtained for each of the soil blocks having different moisture contents by the shear test, the measuring unit 11 is obtained. Based on the normal stress data and the shear stress data, the adhesive force C and the internal friction angle φ are calculated (step S12 in FIG. 2).
　クーロンの式と呼ばれる以下の式（２）によれば、せん断強さｓは、土壌がもつ粘着力Ｃと、せん断面上に働く垂直応力σにもとづく抵抗力（σｔａｎφ）の和で表わされる。ここで、ｔａｎφは土壌の性質を表す土壌パラメータの１つである内部摩擦角φに基づく有効摩擦係数である。
ｓ＝Ｃ＋σｔａｎφ・・・（２）
　例えば、測定部１１は、一面せん断試験等によって、水分量ｍ１、ｍ２、・・・ｍｍａｘの土砂について試験体（土塊等）に加える垂直荷重を変化させながら垂直応力及びせん断応力を測定する。測定部１１は、水分量ｍ１、ｍ２、・・・ｍｍａｘの土砂の、破壊時のせん断応力をせん断強さｓ１、ｓ２、・・・ｓｍａｘとし、破壊時の垂直応力を、σ１、σ２、・・・σｍａｘとする。これらを、式（２）に当てはめることにより、水分量ｍ１、ｍ２、・・・ｍｍａｘに対応する、粘着力Ｃ１、Ｃ２、・・・Ｃｍａｘ、内部摩擦角φ１、φ２、・・・φｍａｘを算出することができる。 According to the following equation (2) called the Coulomb equation, the shear strength s is represented by the sum of the adhesive force C of the soil and the resistance force (σ tan φ) based on the normal stress σ acting on the shear surface. Here, tanφ is an effective friction coefficient based on the internal friction angle φ, which is one of the soil parameters representing the properties of the soil.
s = C + σtanφ (2)
For example, the measurement unit 11, the direct shear test, etc., measuring the water content m 1, m 2, vertical stress while changing the vertical load applied on sediment · · · m max to the test body (clod, etc.) and shear stress To do. The measuring unit 11 sets the shear stress at the time of fracture of the soils having moisture amounts m 1 , m 2 ,..., Max to the shear strength s 1 , s 2 ,. , Σ 1 , σ 2 ,... Σ max . These, by fitting the equation (2), the water content m 1, m 2, corresponds to · · · m max, adhesion C 1, C 2, ··· C max, internal friction angle phi 1, phi 2 ... Φ max can be calculated.
　次に、測定部１１は、ステップＳ１１のせん断試験で用いた土と同質、すなわち同一の種類、乾燥密度および締固め度の土からなる試験体（土塊）を用いて、加水試験を実施する（ステップＳ１３）。 Next, the measurement part 11 implements a hydration test using the test body (soil mass) which is the same as the soil used in the shear test in Step S11, that is, a soil (soil mass) made of soil of the same type, dry density and compaction degree ( Step S13).
　図４は、図１の測定部の加水試験の例を示すフローチャートである。図４に示す加水試験では、初めに、せん断試験で用いた土と同一の種類、乾燥密度および締固め度の土からなり、かつ含水比が相対的に少ない試験体（土塊）を用意する（ステップＳ１３１）。ここで試験体としては、せん断試験で用いられた試験体のうち最小の含水比の試験層を有する試験体よりも少ない含水比の試験層になるように調整された土塊が用いられる。 FIG. 4 is a flowchart showing an example of the water addition test of the measurement unit in FIG. In the hydration test shown in FIG. 4, first, a specimen (soil mass) made of soil of the same type, dry density and compaction as the soil used in the shear test and having a relatively low water content is prepared ( Step S131). Here, as the test body, a soil block adjusted so as to have a test layer with a lower water content ratio than a test body having a test layer with the minimum water content ratio among the test bodies used in the shear test is used.
　次に、測定部１１は、用意された土塊を、測定部１１に含まれる、水分計、間隙水圧計および重量計を備える試験機にセットして、水分量、間隙水圧および土塊重量を計測する（ステップＳ１３２～ステップＳ１３４）。これにより、少なくとも加水前の含水比が既知の状態における土塊の水分量、間隙水圧および土塊重量を得る。 Next, the measurement unit 11 sets the prepared clot on a test machine including the moisture meter, the pore water pressure meter, and the weight meter included in the measurement unit 11, and measures the moisture content, the pore water pressure, and the clot weight. (Steps S132 to S134). As a result, at least the water content, pore water pressure, and soil weight of the soil mass in a state where the water content ratio before the addition is known are obtained.
　次に、土が飽和するまで土塊に一定量ずつ加水して（ステップＳ１３５，ステップＳ１３６）、同様の計測を行う（ステップＳ１３２に戻る）。これにより、土が飽和するまでの加水過程における各状態（加水前および加水毎）の土塊の水分量データ、間隙水圧データ、土塊重量データを取得する。なお、「土が飽和する」とは、具体的には、土に水がしみ込まなくなる状態になることである。なお、土が飽和するまで加水を行う方法以外に、所定回数分加水を行う方法もある。 Next, a certain amount of water is added to the mass until the soil is saturated (step S135, step S136), and the same measurement is performed (return to step S132). Thereby, the moisture content data, pore water pressure data, and soil mass weight data of the soil mass in each state (before and after each addition) in the hydrolysis process until the soil is saturated are acquired. Note that “saturation of the soil” specifically means a state where water does not soak into the soil. In addition to the method of adding water until the soil is saturated, there is a method of adding water a predetermined number of times.
　このようにして測定部１１は、加水試験により、監視対象斜面から採取した物質層（土砂）を用いて作成された含水比が異なる１以上の水分量ｍ１、ｍ２、・・・ｍｍａｘの土塊（試験体）について、間隙水圧ｕ１、ｕ２、・・・ｕｍａｘ、土塊重量Ｗ１、Ｗ２、・・・Ｗｍａｘを取得する（ステップＳ１４）。なお、上記の例では、せん断試験を行った後に、加水試験を行っているが、試験の順序は特に問わない。 In this way, the measurement unit 11 has one or more water amounts m 1 , m 2 ,..., M max that differ in water content ratios created using the material layer (earth and sand) collected from the slope to be monitored by the water test. Pore water pressures u 1 , u 2 ,... U max , and clot weights W 1 , W 2 ,... W max are acquired (step S14). In the above example, the water test is performed after the shear test, but the order of the test is not particularly limited.
　なお測定部１１は、例えば、水分量ｍ１、ｍ２、・・・ｍｍａｘと紐づけて予め測定を行って得られた土壌パラメータ、すなわち粘着力、内部摩擦角、間隙水圧、及び、土塊重量と、複数の水分量ｍ１、ｍ２、・・・ｍｍａｘとを紐づけて図示しない記憶部に記憶してもよい。 Note that the measurement unit 11 is, for example, a soil parameter obtained by measuring in advance in association with the water content m 1 , m 2 ,... M max , that is, adhesive force, internal friction angle, pore water pressure, and soil mass. The weight and a plurality of moisture amounts m 1 , m 2 ,... M max may be associated with each other and stored in a storage unit (not shown).
　図１にもどり本実施形態の斜面監視システム１の構成についてさらに説明する。モデル化部１２は、例えば図示しない記憶部から水分量に紐づけて取得された粘着力、内部摩擦角、土塊重量、間隙水圧から、粘着力－水分量モデル、内部摩擦角－水分量モデル、土塊重量－水分量モデル、間隙水圧－水分量モデルを構築する。すなわちモデル化部１２は、水分量に紐づけて取得された各土壌パラメータから、土壌パラメータを水分量の関数として表すモデル式を作成する。 Referring back to FIG. 1, the configuration of the slope monitoring system 1 of this embodiment will be further described. The modeling unit 12 uses, for example, an adhesive force-moisture amount model, an internal friction angle-moisture amount model, based on an adhesive force, an internal friction angle, a clot weight, and a pore water pressure that are acquired from a storage unit (not shown). Build soil mass-water content model, pore water pressure-water content model. That is, the modeling unit 12 creates a model expression that represents the soil parameter as a function of the moisture content from each soil parameter acquired in association with the moisture content.
　また最適状態水分量推定部１３は、例えば図示しない記憶部から各水分量に紐づけて取得された粘着力、内部摩擦角、土塊重量、間隙水圧に基づいて各水分量における安全率を算出し、安全率が最大となる最適状態の水分量を推定する。 Further, the optimum state moisture amount estimation unit 13 calculates a safety factor for each moisture amount based on, for example, the adhesive force, the internal friction angle, the clot weight, and the pore water pressure obtained by linking each moisture amount from a storage unit (not shown). Estimate the optimal amount of water that maximizes the safety factor.
　記憶部１４は、モデル化部１２が生成したモデル式と、最適状態水分量推定部１３が推定した最適状態の水分量を記憶する。 The storage unit 14 stores the model formula generated by the modeling unit 12 and the optimal amount of water estimated by the optimal state water amount estimation unit 13.
　また、斜面監視システム１は、監視対象斜面に設置された水分計１５と、監視対象斜面において測定された現状の水分量ｍｔから現状の安全率を算出する現状安全率算出部１６を備えている。また斜面監視システム１は、最適状態の水分量から最適状態の安全率を算出する最適状態安全率算出部１７と、算出された現状の安全率と最適状態の安全率に基づいて監視対象斜面の危険度を判定する危険度出力部１８を備えている。 The slope monitoring system 1 also includes a moisture meter 15 installed on the monitored slope, and a current safety factor calculation unit 16 that calculates the current safety factor from the current moisture amount mt measured on the monitored slope. . In addition, the slope monitoring system 1 includes an optimum state safety factor calculating unit 17 that calculates the safety factor of the optimum state from the amount of moisture in the optimum state, and the current state of the safety factor and the safety factor of the optimum state calculated based on the calculated current safety factor. A risk output unit 18 for determining the risk is provided.
　現状安全率算出部１６及び最適状態安全率算出部１７は、予め監視対象の斜面の斜面長ｌ、斜面の傾斜勾配角α、すべり層深さｄを取得している。また現状安全率算出部１６は、監視対象斜面において計測した水分量ｍｔに対応する土壌パラメータ（現状土壌パラメータ）、すなわち粘着力Ｃｔ、内部摩擦角φｔ、間隙水圧ｕｔ、土塊重量Ｗｔを、記憶部１４に記憶されているモデル式に基づいて推定する。そして現状安全率算出部１６は、推定した土壌パラメータ、すなわち粘着力Ｃｔ、内部摩擦角φｔ、間隙水圧ｕｔ、土塊重量Ｗｔを用いて式（１）により斜面の現状の安全率を算出する。 The current safety factor calculation unit 16 and the optimum state safety factor calculation unit 17 obtain in advance the slope length l of the slope to be monitored, the slope inclination angle α of the slope, and the slip layer depth d. Further, the current safety factor calculation unit 16 stores a soil parameter (current soil parameter) corresponding to the moisture amount mt measured on the monitoring target slope, that is, the adhesive force Ct, the internal friction angle φt, the pore water pressure ut, and the clot weight Wt. 14 based on the model formula stored in FIG. Then, the current safety factor calculation unit 16 calculates the current safety factor of the slope according to the equation (1) using the estimated soil parameters, that is, the adhesive force Ct, the internal friction angle φt, the pore water pressure ut, and the clot weight Wt.
　最適状態安全率算出部１７は、記憶部１４に記憶されている最適状態の水分量に対応する土壌パラメータ（最適土壌パラメータ）、すなわち粘着力Ｃｔ、内部摩擦角φｔ、間隙水圧ｕｔ、土塊重量Ｗｔを、記憶部１４に記憶されているモデル式に基づいて推定する。そして最適状態安全率算出部１７は、推定した最適状態の水分量に対応する土壌パラメータ、すなわち粘着力Ｃｔ、内部摩擦角φｔ、間隙水圧ｕｔ、土塊重量Ｗｔを用いて式（１）により斜面の最適状態の安全率を算出する。 The optimum state safety factor calculation unit 17 is a soil parameter (optimum soil parameter) corresponding to the optimum amount of water stored in the storage unit 14, that is, adhesive force Ct, internal friction angle φt, pore water pressure ut, and lump weight Wt. Is estimated based on the model formula stored in the storage unit 14. Then, the optimum state safety factor calculation unit 17 uses the soil parameters corresponding to the estimated optimum amount of water, that is, the adhesive force Ct, the internal friction angle φt, the pore water pressure ut, and the mass of the soil mass Wt according to the equation (1). Calculate the optimal safety factor.
　危険度出力部１８は、算出された現状の安全率と最適状態の安全率に基づいて監視対象斜面の危険度を判定する。 The risk output unit 18 determines the risk of the slope to be monitored based on the calculated current safety factor and the optimum safety factor.
　なお図１に示す第一の実施形態及び後述の他の実施形態の斜面監視システムの各構成要素は、機能単位のブロックを示している。各実施形態の斜面監視システムの各構成要素の一部又は全部は、例えば図１４に示すようなコンピュータ５０とプログラムとの任意の組み合わせにより実現されてもよい。コンピュータ５０は、一例として、以下のような構成を含む。 In addition, each component of the slope monitoring system of 1st embodiment shown in FIG. 1 and other embodiment mentioned later has shown the block of the functional unit. Part or all of the components of the slope monitoring system of each embodiment may be realized by any combination of a computer 50 and a program as shown in FIG. 14, for example. The computer 50 includes the following configuration as an example.
　　・ＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）５１
　　・ＲＯＭ（Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）５２
　　・ＲＡＭ（Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）５３
　　・ＲＡＭ５３にロードされるプログラム５４
　　・プログラム５４を格納する記憶装置５５
　　・記録媒体５６の読み書きを行うドライブ装置５７
　　・通信ネットワーク５９と接続する通信インターフェース５８
　　・データの入出力を行う入出力インターフェース６０
　　・各構成要素を接続するバス６１
　各実施形態の各構成要素は、これらの機能を実現するプログラム５４をＣＰＵ５１が取得して実行することで実現される。例えば、図１の斜面監視システム１の例では、モデル化部１２は、プログラム５４を取得したＣＰＵ５１が、プログラム５４に基づき、水分量と紐づけて測定された土壌パラメータと水分量に基づいてモデル式を生成する処理を行うことで機能が実現されてもよい。 CPU (Central Processing Unit) 51
・ ROM (Read Only Memory) 52
-RAM (Random Access Memory) 53
A program 54 loaded into the RAM 53
A storage device 55 for storing the program 54
A drive device 57 that reads and writes the recording medium 56
A communication interface 58 connected to the communication network 59
-I / O interface 60 for data input / output
・ Bus 61 connecting each component
Each component of each embodiment is implement | achieved when CPU51 acquires and executes the program 54 which implement | achieves these functions. For example, in the example of the slope monitoring system 1 in FIG. 1, the modeling unit 12 uses the model based on the soil parameter and the water content measured by the CPU 51 that has acquired the program 54 in association with the water content based on the program 54. A function may be realized by performing processing for generating an expression.
　また最適状態水分量推定部１３は、プログラム５４を取得したＣＰＵ５１が、プログラム５４に基づき上記の土壌パラメータに基づいて安全率が最大となる最適状態の水分量を推定し、最適状態の水分量を記憶装置５５に記憶する処理を行うことで機能が実現されてもよい。 In addition, the optimum state water amount estimation unit 13 estimates the optimum amount of water with the maximum safety factor based on the above-mentioned soil parameters based on the program 54, and the CPU 51 that has acquired the program 54 calculates the optimum amount of water. The function may be realized by performing processing stored in the storage device 55.
　また現状安全率算出部１６については、プログラム５４を取得したＣＰＵ５１が、プログラム５４に基づき監視対象の斜面において測定される現状の水分量を取得する処理を行う。また、プログラム５４を取得したＣＰＵ５１が、プログラム５４に基づき記憶装置５５に記憶されている上記のモデル式に基づいて土壌パラメータ（現状土壌パラメータ）を推定する処理を行う。またプログラム５４を取得したＣＰＵ５１が、プログラム５４に基づき、推定される土壌パラメータを用いて現状の安全率を算出する処理を行う。これらの処理を行うことで現状安全率算出部１６の機能が実現されてもよい。 In addition, for the current safety factor calculation unit 16, the CPU 51 that has acquired the program 54 performs processing for acquiring the current water content measured on the slope to be monitored based on the program 54. Moreover, CPU51 which acquired the program 54 performs the process which estimates a soil parameter (present soil parameter) based on said model formula memorize | stored in the memory | storage device 55 based on the program54. Moreover, CPU51 which acquired the program 54 performs the process which calculates the present safety factor using the estimated soil parameter based on the program54. The function of the current safety factor calculation unit 16 may be realized by performing these processes.
　また最適状態安全率算出部１７については、プログラム５４を取得したＣＰＵ５１が、プログラム５４に基づき記憶装置５５に記憶されている上記のモデル式に基づいて記憶装置５５に記憶されている上記の最適状態の水分量から土壌パラメータ（最適土壌パラメータ）を推定する処理を行う。またプログラム５４を取得したＣＰＵ５１が、プログラム５４に基づき、推定される土壌パラメータを用いて最適状態の安全率を算出する処理を行う。これらの処理を行うことで最適状態安全率算出部１７の機能が実現されてもよい。 For the optimum state safety factor calculation unit 17, the CPU 51 that has acquired the program 54 stores the optimum state stored in the storage device 55 based on the model formula stored in the storage device 55 based on the program 54. The soil parameter (optimum soil parameter) is estimated from the water content of the soil. Moreover, CPU51 which acquired the program 54 performs the process which calculates the safety factor of an optimal state using the estimated soil parameter based on the program54. The function of the optimum state safety factor calculation unit 17 may be realized by performing these processes.
　また危険度出力部１８は、プログラム５４を取得したＣＰＵ５１が、プログラム５４に基づき上記のように算出された現状の安全率及び最適状態の安全率に基づいて最適状態を基準とした現状の危険度レベルを出力する処理を行うことで機能が実現されてもよい。 Further, the risk output unit 18 obtains the current risk level based on the optimum state based on the current safety factor and the optimum state safety factor calculated as described above based on the program 54 by the CPU 51 that has acquired the program 54. A function may be realized by performing a process of outputting a level.
　各実施形態の各構成要素の機能を実現するプログラム５４は、例えば、予め記憶装置５５やＲＯＭ５２やＲＡＭ５３に格納されており、必要に応じてＣＰＵ５１が読み出すように構成されてもよい。またプログラム５４は、通信ネットワーク５９を介してＣＰＵ５１に供給されてもよいし、予め記録媒体５６に格納されており、ドライブ装置５７が当該プログラムを読み出してＣＰＵ５１に供給してもよい。 The program 54 that realizes the function of each component of each embodiment is stored in advance in the storage device 55, the ROM 52, or the RAM 53, for example, and may be configured to be read by the CPU 51 as necessary. The program 54 may be supplied to the CPU 51 via the communication network 59, or may be stored in advance in the recording medium 56, and the drive device 57 may read the program and supply it to the CPU 51.
　次に本実施形態の動作について説明する。図５は、第一の実施形態の土壌パラメータのモデル化及び最適状態の判断動作を示すフローチャートである。まずモデル化部１２が、水分量に紐づけて取得された土塊重量、間隙水圧から、土塊重量－水分量モデル、間隙水圧－水分量モデルを構築する。すなわちモデル化部１２が、土塊重量（密度）、間隙水圧を水分量の関数として表すモデル式を作成する（ステップＳ１６）。またモデル化部１２は、水分量に紐づけて取得された粘着力、内部摩擦角から、粘着力－水分量モデル、内部摩擦角－水分量モデルを構築する。すなわちモデル化部１２が、粘着力、内部摩擦角を水分量の関数として表すモデル式を作成する（ステップＳ１７）。 Next, the operation of this embodiment will be described. FIG. 5 is a flowchart showing the soil parameter modeling and optimum state determination operation of the first embodiment. First, the modeling unit 12 constructs a soil mass-water content model and a pore water pressure-water content model from the soil mass weight and pore water pressure obtained in association with the moisture content. That is, the modeling unit 12 creates a model formula that expresses the mass of the mass (density) and the pore water pressure as a function of the water content (step S16). The modeling unit 12 constructs an adhesive force-water amount model and an internal friction angle-water amount model from the adhesive force and the internal friction angle acquired in association with the water amount. That is, the modeling unit 12 creates a model formula that expresses the adhesive force and the internal friction angle as a function of the water content (step S17).
　また最適状態水分量推定部１３は、複数の水分量に紐づけて取得された土壌パラメータを用いて最適状態の水分量を推定する。具体的には、最適状態水分量推定部１３は、監視対象斜面における調査結果に基づき、予め斜面長、斜面角度、すべり層深さを取得しており、複数の水分量に紐づけて取得された粘着力、内部摩擦角、土塊重量（密度）、間隙水圧から、式（１）に基づいて安全率を算出する。そして水分量に対する安全率の増減から、安全率が最も高くなるときの水分量を推定し最適状態の水分量とする（ステップＳ１８）。 Also, the optimum state moisture amount estimation unit 13 estimates the moisture amount in the optimum state using soil parameters obtained in association with a plurality of moisture amounts. Specifically, the optimum state moisture amount estimation unit 13 acquires the slope length, the slope angle, and the slip layer depth in advance based on the investigation result on the monitoring target slope, and is obtained in association with a plurality of moisture amounts. The safety factor is calculated based on the formula (1) from the adhesive strength, the internal friction angle, the mass of the clot (density), and the pore water pressure. Then, from the increase / decrease of the safety factor with respect to the moisture content, the moisture content when the safety factor becomes the highest is estimated and set as the optimum moisture content (step S18).
　モデル化部１２は、作成した粘着力－水分量モデル、内部摩擦角－水分量モデル、土塊重量（密度）－水分量モデル、間隙水圧－水分量モデルを記憶部１４に保存し、最適状態水分量推定部１３は、最適状態の水分量及び最適状態の安全率を記憶部１４に保存する（ステップＳ１９）。 The modeling unit 12 stores the created adhesive strength-water content model, internal friction angle-water content model, clot weight (density) -water content model, pore water pressure-water content model in the storage unit 14, and the optimal state moisture The amount estimation unit 13 stores the optimal amount of water and the optimal state safety factor in the storage unit 14 (step S19).
　図６は、第一の実施形態の危険度算出動作を示すフローチャートである。まず、水分計１５は、監視対象の斜面において現状の水分量ｍｔを計測する（ステップＳ２１）。 FIG. 6 is a flowchart showing the risk degree calculation operation of the first embodiment. First, the moisture meter 15 measures the current moisture content mt on the slope to be monitored (step S21).
　また現状安全率算出部１６は、監視対象斜面において計測した水分量ｍｔを、記憶部１４に記憶されている４つのモデル式に代入して、監視対象斜面の水分量計測時における４つの解析式変数（現状土壌パラメータ）、すなわち粘着力、内部摩擦角、土塊重量（密度）、間隙水圧の値を推定する（ステップＳ２２）。 Further, the current safety factor calculation unit 16 substitutes the moisture amount mt measured on the monitoring target slope into the four model formulas stored in the storage unit 14, so that four analytical formulas at the time of measuring the moisture amount on the monitoring target slope are obtained. The values of variables (current soil parameters), that is, adhesive force, internal friction angle, mass of clot (density), and pore water pressure are estimated (step S22).
　現状安全率算出部１６は、予め監視対象の斜面の斜面長ｌ、斜面の傾斜勾配角α、すべり層深さｄを取得しており、推定された土壌パラメータ、すなわち粘着力Ｃｔ、内部摩擦角φｔ、間隙水圧ｕｔ、土塊重量Ｗｔを用いて式（１）により斜面の現状の安全率Ｆｓを算出する（ステップＳ２３）。 The current safety factor calculation unit 16 acquires the slope length l of the slope to be monitored, the slope slope angle α of the slope, and the slip layer depth d in advance, and the estimated soil parameters, that is, the adhesive force Ct and the internal friction angle. The current safety factor Fs of the slope is calculated by Equation (1) using φt, pore water pressure ut, and lump weight Wt (step S23).
　最適状態安全率算出部１７は、推定された最適状態の水分量を、記憶部１４に記憶されている４つのモデル式に代入して、監視対象斜面の最適状態における４つの解析式変数（最適土壌パラメータ）、すなわち粘着力、内部摩擦角、土塊重量（密度）、間隙水圧の値を推定する（ステップＳ２４）。また最適状態安全率算出部１７は、予め監視対象の斜面の斜面長ｌ、斜面の傾斜勾配角α、すべり層深さｄを取得しており、監視対象斜面の最適状態における４つの解析式変数、すなわち粘着力、内部摩擦角、間隙水圧、土塊重量を用いて式（１）により斜面の最適状態の安全率Ｆｓｏｐｔを算出する（ステップＳ２５）。 The optimum state safety factor calculation unit 17 substitutes the estimated amount of water in the optimum state into the four model formulas stored in the storage unit 14 to obtain four analytical equation variables (optimum in the optimum state of the slope to be monitored). (Soil parameters), that is, values of adhesive force, internal friction angle, soil mass weight (density), and pore water pressure are estimated (step S24). The optimum state safety factor calculation unit 17 obtains in advance the slope length l of the slope to be monitored, the slope slope angle α of the slope, and the slip layer depth d, and provides four analytical formula variables in the optimum state of the slope to be monitored. That is, the safety factor Fsopt of the optimum state of the slope is calculated by the equation (1) using the adhesive force, the internal friction angle, the pore water pressure, and the mass of the clot (step S25).
　危険度出力部１８は、現状安全率算出部１６が算出した現状の安全率と、最適状態安全率算出部１７が算出した最適状態の安全率とに基づいて、最適状態を基準とした現状の危険度レベルを出力する。図７は、図１の危険度出力部の最適状態を基準とした現状の危険度レベルの出力の一例を示す図である。例えば危険度出力部１８は、図示しない表示部に、例えば図７に示すように、最適状態の安全率Ｆｓｏｐｔとともに現状の安全率Ｆｓを表示する（ステップＳ２６）。 Based on the current safety factor calculated by the current safety factor calculation unit 16 and the optimum state safety factor calculated by the optimum state safety factor calculation unit 17, the risk level output unit 18 Outputs the risk level. FIG. 7 is a diagram illustrating an example of the current risk level output based on the optimum state of the risk output unit of FIG. For example, the risk output unit 18 displays the current safety factor Fs together with the optimum safety factor Fsop on a display unit (not shown) as shown in FIG. 7, for example (step S26).
　危険度出力部１８は、計測終了か判断し、終了でないと判断するとステップＳ２１に戻る。このようにして計測が終了するまで、ステップＳ２１からＳ２６の処理が繰り返される。 The risk output unit 18 determines whether the measurement is completed, and if it is determined that the measurement is not completed, the process returns to step S21. Thus, the process of step S21 to S26 is repeated until a measurement is complete | finished.
　以上説明したように、本実施形態によれば、最適状態の安全率Ｆｓｏｐｔとともに監視対象斜面において計測した水分量ｍｔから算出された現状の安全率Ｆｓを表示するので、最適状態の安全率Ｆｓｏｐｔを基準として土中水分量に応じて変化する現状の安全率Ｆｓを段階的に把握でき、段階的な警戒や避難の発令ができる。 As described above, according to the present embodiment, the current safety factor Fs calculated from the amount of water mt measured on the slope to be monitored is displayed together with the safety factor Fsopt in the optimum state, so the safety factor Fsopt in the optimum state is displayed. As a standard, the current safety factor Fs, which changes according to the amount of moisture in the soil, can be grasped step by step, and step-by-step warning and evacuation can be issued.
　なお危険度出力部１８は、最適状態の安全率Ｆｓｏｐｔとともに現状の安全率Ｆｓを表示するとして説明したが、これに限らず、危険度レベルの出力方法は種々考えられる。例えば、複数段階の危険度レベルが設定され、最適状態の安全率Ｆｓｏｐｔを基準として現状の安全率Ｆｓから判定された危険度レベルが出力されてもよい。 The risk output unit 18 has been described as displaying the current safety factor Fs together with the safety factor Fsopt in the optimum state. However, the present invention is not limited to this, and various methods for outputting the risk level are conceivable. For example, a plurality of risk levels may be set, and the risk level determined from the current safety factor Fs based on the safety factor Fsopt in the optimum state may be output.
　図８は第二の実施形態の構成を示すブロック図である。本実施形態では、斜面監視システム２は、危険度出力部１８が、レベル範囲設定部１８１と、危険度レベル判定部１８２と、表示部１８３とを備えている。 FIG. 8 is a block diagram showing the configuration of the second embodiment. In the present embodiment, in the slope monitoring system 2, the risk output unit 18 includes a level range setting unit 181, a risk level determination unit 182, and a display unit 183.
　レベル範囲設定部１８１は、予め所定の段階数、例えば５段階の危険度レベルを設定する。レベル範囲設定部１８１は、最適状態の安全率Ｆｓｏｐｔを基準として各危険度レベルに対応する現状の安全率Ｆｓの範囲を設定する。 The level range setting unit 181 sets a predetermined number of stages, for example, five risk levels in advance. The level range setting unit 181 sets the range of the current safety factor Fs corresponding to each risk level based on the safety factor Fsopt in the optimum state.
　危険度レベル判定部１８２は、監視対象斜面において計測した水分量ｍｔから算出された現状の安全率Ｆｓが危険度レベルのどれに対応するかを判定する。 The risk level determination unit 182 determines which of the risk levels the current safety factor Fs calculated from the amount of water mt measured on the slope to be monitored corresponds.
　表示部１８３は、現状の安全率Ｆｓに対応する危険度レベルを表示する。 The display unit 183 displays a risk level corresponding to the current safety factor Fs.
　図９は、各危険度レベルの第１の設定例を示す図である。図９に示すように、第１の例は、最適状態の安全率Ｆｓｏｐｔから安全率＝１まで、各危険度レベルにおける安全率範囲の幅が均等になるように設定する例である。 FIG. 9 is a diagram illustrating a first setting example of each risk level. As shown in FIG. 9, the first example is an example in which the width of the safety factor range at each risk level is set to be uniform from the safety factor Fsopt in the optimum state to the safety factor = 1.
　なお危険度レベル判定部１８２は、最適状態の安全率Ｆｓｏｐｔを基準として現状の安全率Ｆｓから危険度Ｄを算出し、レベル範囲設定部１８１は、各危険度レベルの危険度Ｄの範囲を設定してもよい。 The risk level determination unit 182 calculates the risk level D from the current safety rate Fs based on the safety factor Fsopt in the optimum state, and the level range setting unit 181 sets the range of the risk level D for each risk level. May be.
　例えば危険度レベル判定部１８２は、以下の式（３）のように現状の安全率Ｆｓと最適状態の安全率Ｆｓｏｐｔの比から危険度を算出する。
Ｄ＝（Ｆｓ－１）／（Ｆｓｏｐｔ－１）・・・（３）
　またレベル範囲設定部１８１が、危険度レベルとして、所定の段階数、例えば５段階の危険度レベルを設定し、各危険度レベルについて上記の式（３）により算出された危険度Ｄの範囲を設定する。 For example, the risk level determination unit 182 calculates the risk level from the ratio of the current safety factor Fs and the optimum safety factor Fsopt as shown in the following equation (3).
D = (Fs-1) / (Fsopt-1) (3)
Further, the level range setting unit 181 sets a predetermined number of levels, for example, five levels as the risk level, and sets the range of the risk D calculated by the above equation (3) for each risk level. Set.
　またレベル範囲設定部１８１が、危険度レベルとして、所定の段階数、例えば５段階の危険度レベルを設定し、各危険度レベルについて上記の式（３）により算出された危険度Ｄの範囲を設定する。 Further, the level range setting unit 181 sets a predetermined number of levels, for example, five levels as the risk level, and sets the range of the risk D calculated by the above equation (3) for each risk level. Set.
　レベル範囲設定部１８１は、例えば危険度レベル数が５と設定され、最適状態の安全率が１０の場合、各危険度レベルの危険度Ｄの範囲を以下のように設定する。

Figure JPOXMLDOC01-appb-I000002
For example, when the risk level number is set to 5 and the safety factor in the optimal state is 10, the level range setting unit 181 sets the risk D range of each risk level as follows.

Figure JPOXMLDOC01-appb-I000002
　危険度レベル判定部１８２は、現状安全率算出部１６が算出した現状の安全率Ｆｓと、最適状態安全率算出部１７が算出した最適状態の安全率Ｆｏｐｔとに基づいて、上記の式（３）を用いて危険度Ｄを算出し、レベル範囲設定部１８１により設定された危険度レベルの範囲に基づいて対応する危険度レベルを判定して表示部１８３に表示する。 Based on the current safety factor Fs calculated by the current safety factor calculator 16 and the optimal state safety factor Fopt calculated by the optimum state safety factor calculator 17, the risk level determination unit 182 ) Is used to calculate the risk level D, and the corresponding risk level is determined based on the risk level range set by the level range setting unit 181 and displayed on the display unit 183.
　このように第二の実施形態によれば、現状の安全率Ｆｓと、最適状態の安全率Ｆｏｐｔとに基づいて、例えば５段階に設定される危険度レベルのどれに対応するかを判定して表示部に表示するので、監視対象斜面の危険度レベルの段階を明確に把握でき、段階的な警戒や避難の発令ができる。 Thus, according to the second embodiment, based on the current safety factor Fs and the optimum safety factor Fopt, for example, it is determined which of the five risk levels is set. Since it is displayed on the display unit, it is possible to clearly grasp the level of the risk level of the slope to be monitored, and to perform step-by-step warning and evacuation.
　次に各危険度レベルの安全率の幅の設定が異なる変形例について説明する。図１０は、各危険度レベルの第２の設定例を示す図である。第２の例は、図１０に示すように、危険度が高い危険度レベルにおける安全率範囲の幅が、危険度の低い危険度レベルより狭く設定される例である。 Next, a description will be given of modified examples in which the setting of the safety factor width for each risk level is different. FIG. 10 is a diagram illustrating a second setting example of each risk level. As shown in FIG. 10, the second example is an example in which the width of the safety factor range at the high risk level is set narrower than the low risk level.
　図１１は、図１０のように各危険度レベルの幅を設定する危険度出力部の構成を示すブロック図である。本変形例の危険度出力部１９は、危険度が高い危険度レベルにおける安全率範囲の幅が、危険度の低い危険度レベルより狭くなるよう各危険度レベルの安全率範囲の幅の比率を設定する範囲比率設定部１９１を備え、レベル範囲設定部１９２は、設定された比率に基づいて各危険度レベルの安全率範囲の幅を設定する点で図８の構成と異なっている。 FIG. 11 is a block diagram showing the configuration of a risk output unit that sets the width of each risk level as shown in FIG. The risk output unit 19 of the present modified example sets the ratio of the width of the safety factor range of each risk level so that the width of the safety factor range at the high risk level becomes narrower than the low risk level. A range ratio setting unit 191 to be set is provided, and the level range setting unit 192 is different from the configuration of FIG. 8 in that the width of the safety factor range of each risk level is set based on the set ratio.
　範囲比率設定部１９１は、例えば、Ｎ段階の危険度レベルに対し、危険度が高い危険度レベルにおける安全率範囲の幅が、危険度の低い危険度レベルより狭くなるよう各危険度レベルの安全率範囲の幅の比率を設定する。範囲比率設定部１９１は、例えば最も危険度が高いレベルＮの幅、レベルＮ－１の幅、・・・、レベル２の幅、レベル１の幅を１：２：・・・：Ｎ－１：Ｎの比率を設定する。例えば危険度レベル数が５、最適状態の安全率Ｆｓｏｐｔが１０の場合、範囲比率設定部１９１は、最も危険度が高いレベル５からレベル１の幅の比率を１：２：３：４：５に設定する。レベル範囲設定部１９２は、最も危険度が高いレベル５からレベル１の幅が１：２：３：４：５になるよう、各危険度レベルの危険度Ｄの範囲を以下のように設定する。

Figure JPOXMLDOC01-appb-I000003
For example, the range ratio setting unit 191 has a safety level at each risk level so that the range of the safety factor range at the high risk level is narrower than the low risk level for the N risk levels. Set the ratio of the width of the rate range. The range ratio setting unit 191 sets, for example, the width of level N, the width of level N−1,..., The width of level 2 and the width of level 1 of 1: 2:. : N ratio is set. For example, when the number of risk levels is 5 and the safety factor Fsopt in the optimum state is 10, the range ratio setting unit 191 sets the ratio of the range from the level 5 with the highest risk to the level 1 to 1: 2: 3: 4: 5. Set to. The level range setting unit 192 sets the range of the risk level D of each risk level as follows so that the range from the level 5 with the highest risk level to the level 1 becomes 1: 2: 3: 4: 5. .

Figure JPOXMLDOC01-appb-I000003
　危険度レベル判定部１８２は、現状安全率算出部１６が算出した現状の安全率Ｆｓと、最適状態安全率算出部１７が算出した最適状態の安全率Ｆｏｐｔとに基づいて、上記の式（３）を用いて危険度Ｄを算出し、レベル範囲設定部１９２により設定された危険度レベルの範囲に基づいて対応する危険度レベルを判定して表示部１８３に表示する。 Based on the current safety factor Fs calculated by the current safety factor calculator 16 and the optimal state safety factor Fopt calculated by the optimum state safety factor calculator 17, the risk level determination unit 182 ) Is used to calculate the risk level D, and the corresponding risk level is determined based on the risk level range set by the level range setting unit 192 and displayed on the display unit 183.
　このように第２の例では危険度が高い危険度レベルの幅は、危険度の低い危険度レベルの幅より狭く設定されるので、最も高い危険度レベルでの誤報の可能性は少なくなる。また比較的危険度が低い危険度レベルでは広い危険度範囲で住民に注意を促すことが可能となる。 In this way, in the second example, the range of the risk level with a high risk level is set narrower than the width of the risk level with a low risk level, so the possibility of false alarms at the highest risk level is reduced. In addition, it is possible to call attention to residents in a wide risk range at a risk level with a relatively low risk level.
　さらに各危険度レベルの安全率の幅の設定が図９、図１０と異なる変形例について説明する。図１２は、各危険度レベルの第３の設定例を示す図である。第３の例は、最も危険度が高い危険度レベルの上限となる注意安全率が設定される例である。 Furthermore, a modified example in which the setting of the width of the safety factor of each risk level is different from that in FIGS. 9 and 10 will be described. FIG. 12 is a diagram illustrating a third setting example of each risk level. The third example is an example in which a caution safety factor that is the upper limit of the highest risk level is set.
　図１３は、図１２のように各危険度レベルの幅を設定する危険度出力部の構成を示すブロック図である。本変形例の危険度出力部２０は、注意安全率設定部２０１と、範囲比率設定部２０２を備えている。注意安全率設定部２０１は、最も危険度が高い危険度レベルの上限となる注意安全率を設定する。範囲比率設定部２０２は、最も危険度が高い危険度レベル以外の危険度レベルにおける安全率範囲の幅が、危険度の高い危険度レベルほど狭くなるよう各危険度レベルの安全率範囲の幅の比率を設定する。レベル範囲設定部２０３は、注意安全率と、設定された比率に基づいて各危険度レベルの安全率範囲の幅を設定する。本変形例の危険度出力部２０は、これらの点で図８、図１１の構成と異なっている。 FIG. 13 is a block diagram showing a configuration of a risk output unit that sets the width of each risk level as shown in FIG. The degree-of-risk output unit 20 of the present modification includes a caution safety factor setting unit 201 and a range ratio setting unit 202. The caution safety factor setting unit 201 sets the caution safety factor that is the upper limit of the risk level with the highest risk. The range ratio setting unit 202 sets the width of the safety factor range of each risk level so that the width of the safety factor range at the risk level other than the risk level with the highest risk level becomes narrower as the risk level with the higher risk level. Set the ratio. The level range setting unit 203 sets the width of the safety factor range of each risk level based on the attention safety factor and the set ratio. The risk output unit 20 of this modification is different from the configurations of FIGS. 8 and 11 in these respects.
　また２番目に危険度が高い危険度レベル以上の安全率範囲の幅は、第２の例と同様、危険度の高いレベルの幅が危険度の低いレベルより狭く設定される例である。第３の例では、例えば危険度レベル数がＮの場合、２番目に危険度が高い危険度レベルＮ－１から危険度レベル１の幅が２：３：・・・：Ｎ－１：Ｎの比率になるよう設定される。 Also, the width of the safety factor range equal to or higher than the second highest risk level is an example in which the range of the high risk level is set narrower than the low risk level as in the second example. In the third example, for example, when the number of risk levels is N, the range from the risk level N-1 having the second highest risk level to the risk level 1 is 2: 3: ...: N-1: N It is set to become the ratio.
　レベル範囲設定部２０３は、例えば危険度レベル数が５と設定され、最適状態の安全率Ｆｓｏｐｔが１０、注意安全率Ｆｓｃが１．５の場合、最も危険度が高いレベル５の危険度Ｄの上限値は、注意安全率１．５に対応する危険度Ｄ＝（Ｆｓｃ－１）/（Ｆｓｏｐｔ－１）＝０．０５５５≒０．０６とする。またレベル範囲設定部２０３は、２番目に危険度が高い危険度レベル４から、危険度レベル１の幅が、２：３：４：５の比率となるよう各危険度レベルの危険度Ｄの範囲を設定する。レベル範囲設定部２０３は、各危険度レベルの危険度Ｄの範囲を以下のように設定する。

Figure JPOXMLDOC01-appb-I000004
For example, when the number of risk levels is set to 5 and the safety factor Fsopt in the optimal state is 10 and the caution safety factor Fsc is 1.5, the level range setting unit 203 has the risk level D of the highest risk level D. The upper limit value is a risk level D = (Fsc−1) / (Fsopt−1) = 0.0555≈0.06 corresponding to a safety factor of attention 1.5. Further, the level range setting unit 203 sets the risk level D of each risk level so that the range of the risk level 1 from the risk level 4 having the second highest risk level becomes a ratio of 2: 3: 4: 5. Set the range. The level range setting unit 203 sets the range of the risk level D of each risk level as follows.

Figure JPOXMLDOC01-appb-I000004
　このように第３の例では危険度が最も高い危険度レベルの範囲を任意に設定可能となるので、地域や天候の状況に応じて適切な警戒や避難の発令が可能となる。 Thus, in the third example, since the range of the risk level with the highest risk can be set arbitrarily, appropriate warning and evacuation can be issued according to the region and weather conditions.
　以上、実施形態を参照して本発明を説明したが、本発明は上記実施形態に限定されるものではない。本発明の構成や詳細には、本発明のスコープ内で当業者が理解し得る様々な変更をすることができる。 The present invention has been described above with reference to the embodiments, but the present invention is not limited to the above embodiments. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.
　この出願は、２０１８年３月１３日に出願された日本出願特願２０１８－０４４８５６を基礎とする優先権を主張し、その開示の全てをここに取り込む。 This application claims priority based on Japanese Patent Application No. 2018-044856 filed on Mar. 13, 2018, the entire disclosure of which is incorporated herein.
　１、２　　斜面監視システム
　１１　　測定部
　１２　　モデル化部
　１３　　最適状態水分量推定部
　１４　　記憶部
　１５　　水分計
　１６　　現状安全率算出部
　１７　　最適状態安全率算出部
　１８、１９、２０　　危険度出力部
　１８１、１９２、２０３　　レベル範囲設定部
　１８２　　危険度レベル判定部
　１８３　　表示部
　１９１、２０２　　範囲比率設定部
　２０１　　注意安全率設定部 DESCRIPTION OF SYMBOLS 1, 2 Slope monitoring system 11 Measuring part 12 Modeling part 13 Optimal state water content estimation part 14 Storage part 15 Moisture meter 16 Current safety factor calculation part 17 Optimal state safety factor calculation part 18, 19, 20 Risk level output part 181, 192, 203 Level range setting unit 182 Risk level determination unit 183 Display unit 191, 202 Range ratio setting unit 201 Caution safety factor setting unit

Claims (8)

  1. 　監視対象斜面を構成している物質層について水分量と紐づけて土壌パラメータを測定する測定手段と、
    　測定された前記土壌パラメータと前記水分量に基づいてモデル式を生成するモデル化手段と、
    　前記土壌パラメータに基づいて安全率が最大となる最適状態の水分量を推定する最適状態水分量推定手段と、
    　前記監視対象の斜面において現状の水分量を計測する水分計と、
    　前記モデル式に基づいて前記現状の水分量から推定される現状土壌パラメータを用いて現状の安全率を算出する現状安全率算出手段と、
    　前記モデル式に基づいて前記最適状態の水分量から推定される最適土壌パラメータを用いて前記最適状態の安全率を算出する最適状態安全率算出手段と、
    　前記現状の安全率と前記最適状態の安全率とに基づいて前記最適状態を基準とした現状の危険度レベルを出力する危険度出力手段と、
    　を有する斜面監視システム。     A measuring means for measuring a soil parameter in association with a moisture content of a material layer constituting a slope to be monitored;
    Modeling means for generating a model formula based on the measured soil parameter and the moisture content;
    Optimal state water content estimation means for estimating the optimal state water content that maximizes the safety factor based on the soil parameters;
    A moisture meter for measuring the current amount of moisture on the slope to be monitored;
    A current safety factor calculating means for calculating a current safety factor using a current soil parameter estimated from the current water content based on the model formula;
    An optimum state safety factor calculating means for calculating a safety factor of the optimum state using an optimum soil parameter estimated from the amount of water in the optimum state based on the model formula;
    A risk output means for outputting a current risk level based on the optimum state based on the current safety factor and the optimum state safety factor;
    Slope monitoring system with.
  2. 　前記危険度出力手段は、前記現状の危険度レベルとして設定される複数の危険度レベルに対応させて、前記最適状態の安全率を基準とした安全率の範囲をそれぞれ設定するレベル範囲設定手段を有する請求項１に記載の斜面監視システム。 The risk level output means includes level range setting means for setting a safety factor range based on a safety factor in the optimum state in correspondence with a plurality of risk levels set as the current risk level. The slope monitoring system according to claim 1.
  3. 　前記危険度出力手段は、前記現状の安全率から前記最適状態の安全率を基準として危険度を算出し、
    　前記レベル範囲設定手段は、前記複数の危険度レベルに対応させて前記危険度の範囲をそれぞれ設定することで前記安全率の範囲をそれぞれ設定する、請求項２に記載の斜面監視システム。     The risk output means calculates a risk based on the safety factor in the optimum state from the current safety factor,
    The slope monitoring system according to claim 2, wherein the level range setting unit sets the range of the safety factor by setting the range of the risk level corresponding to the plurality of risk level levels.
  4. 　前記レベル範囲設定手段は、
    　前記複数の危険度レベルに、前記最適状態の安全率から１までの間を均等にわった前記安全率の範囲をそれぞれ設定する、請求項２又は３に記載の斜面監視システム。     The level range setting means includes:
    The slope monitoring system according to claim 2 or 3, wherein a range of the safety factor that is evenly distributed between the safety factor of the optimum state and 1 is set for each of the plurality of risk levels.
  5. 　前記レベル範囲設定手段は、
    　危険度が高い前記危険度レベルほど、前記安全率の範囲を狭く設定する範囲比率設定手段を有する、
    　請求項２又は３に記載の斜面監視システム。     The level range setting means includes:
    The risk level having a higher risk level has range ratio setting means for setting the safety factor range narrower.
    The slope monitoring system according to claim 2 or 3.
  6. 　前記レベル範囲設定手段は、
    　前記複数の危険度レベルのうち最も高い前記危険度レベルの範囲の上限となる注意安全率を設定する注意安全率設定手段を有する、
    　請求項２又は３に記載の斜面監視システム。     The level range setting means includes:
    A caution safety factor setting means for setting a caution safety factor that is the upper limit of the range of the highest risk level among the plurality of risk levels;
    The slope monitoring system according to claim 2 or 3.
  7. 　監視対象斜面を構成している物質層について水分量と紐づけて土壌パラメータを測定し、
    　測定された前記土壌パラメータと前記水分量に基づいてモデル式を生成し、
    　前記土壌パラメータに基づいて安全率が最大となる最適状態の水分量を推定し、
    　前記監視対象の斜面において現状の水分量を計測し、
    　前記モデル式に基づいて前記現状の水分量から推定される現状土壌パラメータを用いて現状の安全率を算出し、
    　前記モデル式に基づいて前記最適状態の水分量から推定される最適土壌パラメータを用いて前記最適状態の安全率を算出し、
    　前記現状の安全率と前記最適状態の安全率とに基づいて前記最適状態を基準とした現状の危険度レベルを出力する、
    　斜面監視方法。     Measure soil parameters in relation to the amount of water for the material layer that constitutes the monitored slope,
    Generate a model formula based on the measured soil parameter and the moisture content,
    Estimating the optimal amount of water with the maximum safety factor based on the soil parameters,
    Measure the current amount of water on the monitored slope,
    Calculate the current safety factor using the current soil parameters estimated from the current water content based on the model formula,
    Using the optimal soil parameters estimated from the water content in the optimal state based on the model formula, calculate the safety factor in the optimal state,
    Outputting the current risk level based on the optimum state based on the current safety factor and the optimum state safety factor;
    Slope monitoring method.
  8. 　コンピュータに、
    　監視対象斜面を構成している物質層について水分量と紐づけて測定された土壌パラメータと前記水分量に基づいてモデル式を生成する処理、
    　前記土壌パラメータに基づいて安全率が最大となる最適状態の水分量を推定する処理、　前記監視対象の斜面において現状の水分量を取得する処理、
    　前記モデル式に基づいて前記現状の水分量から推定される現状パラメータを用いて現状の安全率を算出する処理、
    　前記モデル式に基づいて前記最適状態の水分量から推定される最適土壌パラメータを用いて前記最適状態の安全率を算出する処理、及び、
    　前記現状の安全率と前記最適状態の安全率とに基づいて前記最適状態を基準とした現状の危険度レベルを出力する処理、
    　を実行させる斜面監視プログラムを格納した記録媒体。     On the computer,
    A process for generating a model formula based on the soil parameter and the moisture content measured in association with the moisture content for the material layer constituting the monitored slope,
    A process for estimating the water content in an optimum state where the safety factor is maximized based on the soil parameter, a process for obtaining the current water content on the slope to be monitored,
    A process for calculating a current safety factor using a current parameter estimated from the current water content based on the model formula;
    A process for calculating a safety factor in the optimum state using an optimum soil parameter estimated from the amount of water in the optimum state based on the model formula; and
    A process for outputting a current risk level based on the optimum state based on the current safety factor and the optimum state safety factor;
    A recording medium that stores a slope monitoring program that executes
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