A method for calculating typhoon rainfall-induced landslide susceptibility based on root force and soil saturation

Abstract

The present invention relates to the technical field of landslide susceptibility assessment, and specifically discloses a method for calculating the susceptibility of typhoon rainfall-type landslides from root force and soil saturation. The susceptibility of typhoon rainfall-type landslides is evaluated by inverting the spatiotemporal changes of root force and soil saturation during typhoons. The method includes the following steps: collection of influencing factors and model data; inversion of vegetation root force; inversion of soil saturation; and prediction of landslide susceptibility. The method can accurately invert the vegetation root force, take into account the influence of root force and rainfall to invert the landslide susceptibility in the area under the typhoon image, and has better prediction accuracy than the existing landslide susceptibility map generated without considering the vegetation root force and the default value of the root force.

Description

Technical Field

[0001] The invention relates to the technical field of landslide susceptibility evaluation, in particular to a method for calculating typhoon rainfall type landslide susceptibility based on root force and soil saturation. Background Art

[0002] Landslide susceptibility assessment can predict the possibility of landslides and identify potential landslide hazard areas, thereby reducing the impact and losses caused by landslides.

[0003] The rapid development of remote sensing earth observation methods has facilitated the acquisition of a large amount of surface and remote sensing data.

[0004] The development of the research on slope stability and root force inversion of vegetation root forces has made it feasible to invert root forces at the landscape scale. The stability model based on infinite slopes combines a series of physical model parameters such as soil with environmental variables such as root forces and soil saturation.

[0005] However, the mechanism of landslides in vegetation-covered areas during typhoons and rainstorms is complex, and typhoon rainfall induces landslides quickly. Most typhoon landslide susceptibility evaluation models use a unified root force and total rainfall to evaluate after the typhoon ends, without accurately considering the impact of vegetation root force and temporal rainfall changes on landslide susceptibility evaluation.

[0006] Since the root force of vegetation has an important influence on slope stability, vegetation at different heights has different root force performance, and soil saturation changes during rainfall, both root force and rainfall have an important influence on the evaluation of landslide susceptibility. Summary of the invention

[0007] In view of the above problems in the prior art, the present invention provides a method for calculating the susceptibility of typhoon rainfall-type landslides based on root force and soil saturation, which can effectively evaluate the susceptibility of landslides during typhoon rainfall.

[0008] The technical solution adopted by the present invention is as follows:

[0009] A method for calculating the susceptibility of typhoon rainfall-induced landslides based on root force and soil saturation, comprising the following steps:

[0010] S1: Impact factor and model data collection;

[0011] S2: Inversion of vegetation root forces;

[0012] S3: soil saturation inversion;

[0013] S4: Landslide susceptibility prediction.

[0014] Preferably, S1 is specifically:

[0015] Determine the area to be studied and set the grid size, and obtain the landslides induced by typhoon rainfall in the study area;

[0016] The spatial distribution data of landslide susceptibility evaluation indicators are collected and preprocessed, the parameter indicators of the slope stability model are extracted, and the spatial data required for root force inversion and hydrological inversion are collected.

[0017] Preferably,

[0018] The spatial distribution data of the landslide susceptibility evaluation index include: digital elevation model DEM, soil thickness, aboveground biomass AGB, soil saturation, vegetation root force, soil similarity SOIL, soil cohesion, soil saturation weight, soil natural state weight, soil internal friction angle and slope;

[0019] The preprocessing includes: resampling, projection coordinate conversion, and mask clipping;

[0020] The parameter indicators of the slope stability model include: elevation, soil type, vegetation load, soil thickness, soil internal friction angle, and saturated soil unit weight;

[0021] The spatial data required for the root force inversion and hydrological inversion include: forest canopy height, aboveground biomass, slope, slope aspect, profile curvature, rainfall, evapotranspiration, and terrain humidity index.

[0022] Preferably, S2 is specifically:

[0023] A root force inversion model was constructed based on key forest parameters to obtain the regional root force distribution at the landscape scale.

[0024] Preferably, the root force inversion model is:

[0025]

[0026] Where K is a constant, set to 1.2; H is the forest canopy height, unit: m; BGB is the underground biomass, unit: kg / m 2 ρ r is the root density, unit: kg / m 3 ;z s is the soil thickness, unit: m; T r is the tensile strength of the root system, unit: N / m 2 ; A(z s ) is the vertical distribution of root area in the vegetation root system, unit: m; A0 is the vertical distribution of root area when the soil depth is 0, unit: m; e is the base of the natural logarithm, with a value of 2.71828; η is the shape parameter of the root, dimensionless.

[0027] Preferably, S3 is specifically:

[0028] Typhoon rainfall data and typhoon rainfall evapotranspiration data are combined with the regional digital elevation model DEM, flow direction FDR, flow FAC, terrain wetness index TWI, mask data MASK, soil type SOIL, and land cover LANDCOVER. After data preprocessing, the CREST hydrological model is used to input the pre-prepared data into the CREST hydrological model to invert the changes in soil saturation during typhoon rainfall.

[0029] Preferably, the inversion of soil saturation changes during typhoon rainfall is as follows: the prepared data is input into the CREST hydrological model, specific data is input into a folder specified by the hydrological model, and the code is run.

[0030] Preferably, S4 specifically comprises: implementing landslide susceptibility assessment by inputting landslide susceptibility assessment data into the model;

[0031] The inversion results of root force and soil saturation are combined with the landslide influencing factors such as digital elevation model DEM, soil thickness, aboveground biomass AGB, soil saturation, vegetation root force, soil similar SOIL, soil cohesion, soil saturated weight, soil natural state weight, soil internal friction angle and slope, and the landslide susceptibility evaluation model is used to predict the landslide susceptibility of the study area during typhoon rainfall.

[0032] Preferably, the landslide susceptibility assessment model is:

[0033]

[0034] Among them, C s is soil cohesion, unit: N / m 2 ; C r is the vegetation root force, unit: N / m 2 ; α is the slope, unit: °; φ is the soil internal friction angle, unit: °; AGB is the aboveground biomass, unit: kg / m 2 ; γ m Soil density in natural state, unit: N / m 3 ;z s is the soil thickness, unit: m; γ sat is the saturated soil density, unit: N / m 3 ; γ w is the density of water, unit: N / m 3 , value 9810N / m 3 ;h w is the soil saturation, dimensionless.

[0035] Preferably, the landslide susceptibility prediction for the study area during typhoon rainfall is:

[0036] The landslide susceptibility prediction results are obtained from the results of the landslide susceptibility evaluation model, and the results are classified to complete the landslide susceptibility evaluation in the area.

[0037] If the hazard coefficient is less than or equal to 1.25, it is judged as an extremely high-risk area; if the hazard coefficient is less than or equal to 1.5 and greater than 1.25, it is judged as a high-risk area; if the hazard coefficient is less than or equal to 1.75 and greater than 1.5, it is judged as a medium-risk area; if the hazard coefficient is less than or equal to 2 and greater than 1.75, it is judged as a low-risk area; if the hazard coefficient is greater than 2, it is judged as an extremely low-risk area.

[0038] The present invention has the following characteristics and advantages:

[0039] It can accurately invert the vegetation root force, take into account the influence of root force and rainfall to invert the landslide susceptibility in the area under the typhoon image, and has better prediction accuracy than the existing landslide susceptibility map generated without considering the vegetation root force and the default value of root force. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a flow chart of a method embodiment of the present invention;

[0041] Figure 2 is a schematic diagram of the location and elevation of a study area of ​​an embodiment of the method of the present invention;

[0042] FIG3 is a landslide susceptibility distribution map obtained by the method embodiment of the present invention and the default setting root force method, FIG3-a is a landslide susceptibility map generated without considering the vegetation root force, FIG3-b is a landslide susceptibility map generated by the default root force value, and FIG3-c is a landslide susceptibility map using the method of the embodiment of the present invention;

[0043] Figure 4 3 is a receiver operating characteristic (ROC) curve diagram of landslide susceptibility evaluation obtained under three conditions of the method embodiment of the present invention. DETAILED DESCRIPTION

[0044] The embodiments are described below in conjunction with the accompanying drawings and data.

[0045] This example selects a rectangular area in Sanming City as the research area. Figure 2 shown.

[0046] Reference Figure 1 The method for calculating the susceptibility of typhoon rainfall-induced landslides based on root force and soil saturation includes the following steps:

[0047] S1: Impact factor and model data collection;

[0048] S2: Inversion of vegetation root forces;

[0049] S3: soil saturation inversion;

[0050] S4: Landslide susceptibility prediction.

[0051] Preferably, S1 is specifically:

[0052] Determine the area to be studied and set the grid size, and obtain the landslides induced by typhoon rainfall in the study area;

[0053] The spatial distribution data of landslide susceptibility evaluation indicators are collected and preprocessed, the parameter indicators of the slope stability model are extracted, and the spatial data required for root force inversion and hydrological inversion are collected.

[0054] Preferably,

[0055] The spatial distribution data of the landslide susceptibility evaluation index include: digital elevation model DEM, soil thickness, aboveground biomass AGB, soil saturation, vegetation root force, soil similarity SOIL, soil cohesion, soil saturation weight, soil natural state weight, soil internal friction angle and slope;

[0056] The preprocessing includes: resampling, projection coordinate conversion, and mask clipping;

[0057] The parameter indicators of the slope stability model include: elevation, soil type, vegetation load, soil thickness, soil internal friction angle, and saturated soil unit weight;

[0058] The spatial data required for the root force inversion and hydrological inversion include: forest canopy height, aboveground biomass, slope, slope aspect, profile curvature, rainfall, evapotranspiration, and terrain humidity index.

[0059] Preferably, S2 is specifically:

[0060] A root force inversion model was constructed based on key forest parameters to obtain the regional root force distribution at the landscape scale.

[0061] Preferably, the root force inversion model is:

[0062]

[0063] Where K is a constant, set to 1.2; H is the forest canopy height, unit: m; BGB is the underground biomass, unit: kg / m 2 ρ r is the root density, unit: kg / m 3 ;z s is the soil thickness, unit: m; T r is the tensile strength of the root system, unit: N / m 2 ; A(z s) is the vertical distribution of root area in the vegetation root system, unit: m; A0 is the vertical distribution of root area when the soil depth is 0, unit: m; e is the base of the natural logarithm, with a value of 2.71828; η is the shape parameter of the root, dimensionless.

[0064] Preferably, S3 is specifically:

[0065] Typhoon rainfall data and typhoon rainfall evapotranspiration data are combined with the regional digital elevation model DEM, flow direction FDR, flow FAC, terrain wetness index TWI, mask data MASK, soil type SOIL, and land cover LANDCOVER. After data preprocessing, the CREST hydrological model is used to input the pre-prepared data into the CREST hydrological model to invert the changes in soil saturation during typhoon rainfall.

[0066] Preferably, the inversion of soil saturation changes during typhoon rainfall is as follows: the prepared data is input into the CREST hydrological model, specific data is input into a folder specified by the hydrological model, and the code is run.

[0067] Preferably, S4 specifically comprises: implementing landslide susceptibility assessment by inputting landslide susceptibility assessment data into the model;

[0068] The inversion results of root force and soil saturation are combined with the landslide influencing factors such as digital elevation model DEM, soil thickness, aboveground biomass AGB, soil saturation, vegetation root force, soil similar SOIL, soil cohesion, soil saturated weight, soil natural state weight, soil internal friction angle and slope, and the landslide susceptibility evaluation model is used to predict the landslide susceptibility of the study area during typhoon rainfall.

[0069] Preferably, the landslide susceptibility assessment model is:

[0070]

[0071] Among them, C s is soil cohesion, unit: N / m 2 ; C r is the vegetation root force, unit: N / m 2 ; α is the slope, unit: °; φ is the soil internal friction angle, unit: °; AGB is the aboveground biomass, unit: kg / m 2 ; γ m Soil density in natural state, unit: N / m 3 ;z s is the soil thickness, unit: m; γ sat is the saturated soil density, unit: N / m 3 ; γ w is the density of water, unit: N / m3 , value 9810N / m 3 ;h w is the soil saturation, dimensionless.

[0072] Preferably, the landslide susceptibility prediction for the study area during typhoon rainfall is:

[0073] The landslide susceptibility prediction results are obtained from the results of the landslide susceptibility evaluation model, and the results are classified to complete the landslide susceptibility evaluation in the area.

[0074] If the hazard coefficient is less than or equal to 1.25, it is judged as an extremely high-risk area; if the hazard coefficient is less than or equal to 1.5 and greater than 1.25, it is judged as a high-risk area; if the hazard coefficient is less than or equal to 1.75 and greater than 1.5, it is judged as a medium-risk area; if the hazard coefficient is less than or equal to 2 and greater than 1.75, it is judged as a low-risk area; if the hazard coefficient is greater than 2, it is judged as an extremely low-risk area.

[0075] From FIG. 3 , it can be seen from the comparative analysis that the method of this embodiment can accurately invert the root force of vegetation, and take into account the influence of the root force and rainfall to invert the landslide susceptibility in the area under the typhoon image.

[0076] Depend on Figure 4 It can be seen that adding the inverse root force into the landslide susceptibility prediction can obtain better prediction accuracy.

[0077] The embodiments described above are only descriptions of the preferred modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for calculating the susceptibility of typhoon rainfall-induced landslides from root forces and soil saturation, characterized in that: The following steps are involved: S1: Impact factor and model data collection; S2: Inversion of vegetation root forces; S3: soil saturation inversion; S4: Landslide susceptibility prediction; S1 is specifically: Determine the area to be studied and set the grid size, and obtain the landslides induced by typhoon rainfall in the study area; Collect and pre-process the spatial distribution data of landslide susceptibility evaluation indicators, extract parameter indicators of slope stability model, and collect spatial data required for root force inversion and hydrological inversion; The spatial distribution data of the landslide susceptibility evaluation index include: digital elevation model DEM, soil thickness, aboveground biomass AGB, soil saturation, vegetation root force, soil similarity SOIL, soil cohesion, soil saturation weight, soil natural state weight, soil internal friction angle and slope; The preprocessing includes: resampling, projection coordinate conversion, and mask clipping; The parameter indicators of the slope stability model include: elevation, soil type, vegetation load, soil thickness, soil internal friction angle, and saturated soil unit weight; The spatial data required for the root force inversion and hydrological inversion include: forest canopy height, aboveground biomass, slope, aspect, profile curvature, rainfall, evapotranspiration, and terrain humidity index; S4 is specifically: implementing landslide susceptibility assessment by inputting landslide susceptibility assessment data into the model; Combined with the root force inversion results and soil saturation inversion results, combined with the digital elevation model DEM, soil thickness, aboveground biomass AGB, soil saturation, vegetation root force, soil similar SOIL, soil cohesion, soil saturated weight, soil natural state weight, soil internal friction angle and slope, these landslide influencing factors, the landslide susceptibility evaluation model is used to predict the landslide susceptibility of the study area during typhoon rainfall. The landslide susceptibility evaluation model is: in, is soil cohesion, unit: N / m 2 ; is the vegetation root force, unit: N / m 2 ; is the slope, unit: °; is the soil internal friction angle, unit: °; is the aboveground biomass, unit: kg / m 2 ; Soil density in natural state, unit: N / m 3 ; is the soil thickness, unit: ; is the saturated soil density, unit: N / m 3 ; is the density of water, unit: N / m 3 , value 9810N / m 3 ; is the soil saturation, dimensionless.

2. The method according to claim 1, characterized in that: S2 is specifically: A root force inversion model was constructed based on key forest parameters to obtain the regional root force distribution at the landscape scale.

3. The method according to claim 2, characterized in that The root force inversion model is: in, is a constant, set to 1.2; is the forest canopy height, in m; BGB is the underground biomass, unit: kg / m 2 ; is the root density, unit: kg / m 3 ; is the soil thickness in: ; is the tensile strength of the root system, unit: ; It is the vertical distribution of the root area in the vegetation root system, unit: m; is the vertical distribution of root area when the soil depth is 0, unit: m; It is the base of natural logarithm, and its value is 2.71828; is the shape parameter of the root and is dimensionless.

4. The method according to claim 1, characterized in that: S3 is specifically: Typhoon rainfall data and typhoon rainfall evapotranspiration data are combined with the regional digital elevation model DEM, flow direction FDR, flow FAC, terrain wetness index TWI, mask data MASK, soil type SOIL, and land cover LANDCOVER. After data preprocessing, the CREST hydrological model is used to input the pre-prepared data into the CREST hydrological model to invert the changes in soil saturation during typhoon rainfall.

5. The method according to claim 4, characterized in that The inversion of soil saturation changes during typhoon rainfall is as follows: the prepared data is input into the CREST hydrological model, specific data is input into the folder specified by the hydrological model, and the code is run.

6. The method according to claim 1, characterized in that The landslide susceptibility prediction for the study area during typhoon rainfall is as follows: The landslide susceptibility prediction results are obtained from the results of the landslide susceptibility evaluation model, and the results are classified to complete the landslide susceptibility evaluation in the area.

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