CN113807740A - Risk assessment system for hydrological disasters of water burst runoff of mountain railway tunnel - Google Patents
Risk assessment system for hydrological disasters of water burst runoff of mountain railway tunnel Download PDFInfo
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Abstract
Mountain ridge railway tunnel gushing water runoff hydrogeology calamity risk evaluation system relates to geological disasters risk assessment technical field, the simulation result to runoff discharge simulation technique calculation among the prior art only is the table form, the analysis result degree of accuracy is low, and then influence the construction progress, threaten constructor's safety, still can be to the earth's surface, the problem of underground water system production disturbance, the trend after this application can systematic analysis gushing water and gush out from the tunnel portal, high accuracy reduction gushing water discharges the flow path, thereby all-round true deduction gushing water discharges the scene. In addition, the method for judging the hydrogeological disaster risk level is determined by constructing a star-shaped hierarchical structure-hydrogeological model simulation result superposition analysis function, and the range and the degree of the hydrogeological disaster risk in the tunnel site area caused by the emission event of the tunnel water burst runoff are visually displayed in the form of a runoff hydrogeological disaster risk level rendering map.
Description
Technical Field
The invention relates to the technical field of hydrological disaster risk assessment, in particular to a hydrological disaster risk assessment system for water burst runoff of a mountain railway tunnel.
Background
In china, mountain railways are the necessary traffic infrastructure to connect regions. The mountain railway not only needs to pass through the high mountain canyon, but also needs to continuously pass through the deep and large active fracture zone and the criss-cross underground water system, so that the mountain railway tunnel construction is provided with a great water inrush risk. Sudden water gushing not only can influence tunnel engineering construction and threaten the safety of constructors, but also can cause very big influence to surface water system and nearby ground thing especially after gushing out water from the tunnel portal, and the runoff of gushing water can lead to the tunnel site area to face calamity risks such as mud-rock flow, massif landslide. Therefore, the problem of simulating the discharge of the water burst runoff of the mountain railway tunnel and evaluating the risk of the hydrological disaster caused by the water burst runoff needs to be solved urgently, the discharge process of the water burst runoff needs to be simulated urgently, and the risk of the hydrological disaster caused by the runoff is judged, so that the risk of the water burst runoff discharge to the surrounding environment is effectively quantified.
Generally, the traditional technology is used for predicting, early warning, preventing and controlling the water inflow of the tunnel face in the tunnel, and the discharge process of water inflow runoff and the risk of the water inflow runoff to the hydrology in the tunnel site are rarely concerned. Aiming at the event that surface runoff is formed after the gushing water gushes out from the tunnel portal, the discharge process of the gushing water runoff is simulated, and the hydrological disaster risk caused by the gushing water runoff is judged.
Due to the continuity of water burst during tunnel face excavation and the discontinuity of water burst in different construction stages, the outflow data of a tunnel portal is difficult to obtain and is difficult to apply to hydrological scientific research; and, huge massif can produce massif effect, causes tunnel on the massif to have the risk such as rockburst, karst, height heat, and these disasters can directly lead to mountain ridge railway tunnel to gush out high temperature water and karst water in the work progress, and this not only can influence the construction progress, threatens constructor's safety, still can produce the disturbance to earth's surface, secret river system, gush out the back from the tunnel portal and also can cause very big influence to the hydrology situation in tunnel site area.
Disclosure of Invention
The purpose of the invention is: aiming at the problem of low accuracy of runoff discharge simulation analysis results in the prior art, the mountainous railway tunnel water burst runoff hydrology disaster risk assessment system is provided.
The technical scheme adopted by the invention to solve the technical problems is as follows:
the system for evaluating the risk of the hydrological disasters of water burst runoffs of the mountain railway tunnel comprises a runoff influence factor acquisition subsystem, a runoff discharge simulation subsystem and a hydrological disaster risk grade judgment subsystem;
the runoff influence factor acquisition subsystem is used for acquiring and correcting influence factors of a runoff discharge process;
the runoff discharge simulation subsystem is used for acquiring influence factors processed by the subsystem according to the runoff influence factors to simulate the discharge process of the water runoff and obtain a runoff discharge simulation result;
and the hydrological disaster risk grade judgment subsystem evaluates the hydrological disaster risk of the tunnel water burst runoff according to the runoff discharge simulation result.
Further, the influence factors include an elevation factor, a grade factor, and a slope factor.
Further, the runoff influence factor acquiring subsystem comprises a runoff basic data acquiring module and a runoff basic data processing module;
the runoff basic data acquisition module is used for acquiring basic data of tunnel water burst runoff discharge, the basic data comprises a tunnel site area remote sensing image, attribute data of water burst runoff in the tunnel site area and water quantity monitoring data,
the method comprises the following specific steps:
firstly, a sentinel second satellite is used for collecting a DEM elevation remote sensing image of a tunnel address area, the spatial resolution of the remote sensing image is 5 meters, the coverage rate of clouds is less than 10 percent,
then, acquiring an image of the water burst discharge runoff in the tunnel site area by using a digital aerial photography instrument DMC, and extracting attribute data of the water burst discharge runoff in the tunnel site area according to the acquired image of the water burst discharge runoff in the tunnel site area, wherein the attribute data of the water burst discharge runoff comprises a runoff cross section interval, a distance between a runoff center line and two banks, and a distance between a left bank, a center line and a right bank between an upstream cross section and a downstream cross section, the spatial resolution of the image of the water burst discharge runoff in the tunnel site area is 120 optical line pairs/mm, the spectral resolution is 48bit, and the cloud coverage rate is less than 1%;
finally, water quantity monitoring data is obtained by utilizing the water quantity monitoring points, the water quantity monitoring data comprises flow, flow rate and water level data,
the runoff basic data processing module is used for correcting and processing basic data of tunnel water burst runoff discharge, and the specific steps are as follows:
the method comprises the steps of utilizing a grid calculator to interpret a tunnel address area DEM elevation remote sensing image collected by a sentinel second satellite, then carrying out radiometric calibration on the interpreted image, namely converting the DN value of the interpreted image into a radiance value, then carrying out atmospheric correction, extracting reflection information of elevation, gradient and slope data of the tunnel address area from the atmosphere, and finally carrying out image cutting according to the reflection information of the elevation, gradient and slope data of the tunnel address area in the corrected image and the zone location characteristics to obtain the elevation, gradient and slope data of the tunnel address area, namely an elevation factor, a gradient factor and a slope factor.
Furthermore, the attribute data of the water burst runoff in the tunnel site area comprises runoff cross section distance and the distance between a runoff center line and two banks.
Further, the runoff discharge simulation subsystem comprises a runoff influence factor fusion module, a hydrological model building module and a runoff waterpower simulation module,
the runoff influence factor fusion module is used for fusing and identifying the treated runoff influence factors, and the specific steps are as follows:
firstly, filling depression in Arcgis software to calculate the flow direction of water-inrush runoff of a tunnel, simulating a runoff river network by using accumulated runoff calculation in the Arcgis software, extracting the runoff river network in the Arcgis software according to an elevation factor, a gradient factor and a slope factor to generate a runoff river channel, and then segmenting the runoff river channel at a water quantity monitoring point or at a runoff inflection point by using a space analysis method, so that at least one segment of cross-section bread water content monitoring data is assigned to the water quantity monitoring data of the water quantity monitoring point on a runoff cross section, and finally obtaining a runoff line;
the hydrological model building module is based on 1: 1000, establishing a hydrological model of the runoff line by utilizing an HEC-HMS surface runoff model,
the runoff water power simulation module carries out water quantity evolution operation according to the hydrological model of the runoff line, finally obtains the simulation result of the runoff discharge of gushing water, extracts the simulation result of the risk sensitive factor of the runoff line in the simulation result of the runoff discharge of gushing water, and the simulation result of the risk sensitive factor of the runoff line comprises runoff water surface elevation variation, runoff flow rate, runoff flow area, runoff water surface width and runoff water power acceleration rate.
Further, the HEC-HMS surface runoff model comprises a surface runoff model and a river water flow model.
Further, the hydrological disaster risk grade judgment subsystem comprises a judgment matrix construction module, a risk weight calculation module, a hydrological disaster risk grade classification module and a hydrological disaster risk grade judgment module,
the judgment matrix construction module is used for constructing a star-shaped hierarchical structure model by taking elevation variation of the runoff water surface, runoff flow velocity, runoff flow area, runoff water surface width and runoff hydraulic acceleration as primary indexes, and constructing a judgment matrix according to the relative importance construction of hydrological disaster risk sensitive factors caused by water gushing of a tunnel by adopting a comparison scale method and combining with an questionnaire according to the star-shaped hierarchical structure model, wherein the judgment matrix is as follows:
| A | B1 | B2 | B3 | B4 | B5 |
| B1 | 1 | 2 | 2 | 3 | 2 |
| B2 | 1/2 | 1 | 4 | 2 | 6 |
| B3 | 1/2 | 1/4 | 1 | 2 | 3 |
| B4 | 1/3 | 1/2 | 1/2 | 1 | 2 |
| B5 | 1/2 | 1/6 | 1/3 | 1/2 | 1 |
wherein, A represents a total target, and the number represents relative importance, and the elevation variation of the runoff water surface, the runoff flow velocity, the runoff flow area, the runoff water surface width and the runoff hydraulic acceleration rate respectively correspond to B1, B2, B3, B4 and B5;
the risk weight calculation module obtains the risk weight of the hydrological disaster risk sensitive factor based on the judgment matrix, and obtains a hydrological disaster risk weight coefficient by utilizing an analytic hierarchy process;
the hydrological disaster risk grading module is used for carrying out superposition analysis according to the simulation result of the risk sensitive factor of the radial flow line and the hydrological disaster risk weight coefficient to obtain a risk superposition parameter Qj；
The hydrological disaster risk grade evaluation module is used for superposing the parameter Q according to the riskjAnd (6) carrying out risk assessment.
Further, the hydrology disaster risk level evaluation module has the following judgment principle:
if hydrological disaster risk superposition parametersQjQ is not less than 58jIf the risk is less than 70, judging the risk to be high;
if hydrological disaster risk superposition parameter QjIs 46 or more than QjIf the number is less than 58, the risk is judged to be medium;
if hydrological disaster risk superposition parameter QjIs 34 or more than QjIf < 46, judging the risk to be low;
if hydrological disaster risk superposition parameter QjQ is not less than 22jIf < 34 >, judging the risk is extremely low;
if hydrological disaster risk superposition parameter QjQ is not less than 0jIf < 22 >, the judgment is no risk.
Further, the risk stacking parameter QjExpressed as:
Qj＝Bij·Mij＝-B1j×M1j+B2j×M2j+B3j×M3j+B4j×M4j+B5j×M5j
Qjsuperimposing the parameters for the risk; j represents each tunnel water burst runoff section; i is expressed as the ith risk sensitive factor; b isijThe hydrological model simulation result of the ith risk sensitive factor of the jth tunnel water inrush runoff section; mijAnd (4) the risk weight of the ith risk sensitive factor of the jth tunnel water inrush runoff section.
Furthermore, the hydrology disaster risk level judgment subsystem further comprises a consistency check module, and the consistency check module is used for performing consistency check on the judgment matrix.
The invention has the beneficial effects that:
aiming at the two specificities of the mountain railway tunnel (firstly, the continuity of water burst during tunnel face excavation and the discontinuity of water burst in different construction stages lead to the difficulty in obtaining the outflow data of the tunnel entrance and applying the outflow data in hydrological scientific research, secondly, the huge mountain body can generate mountain body effect, the tunnel on the mountain body has the risks of rock burst, karst, high and low heat and the like, and the disaster risks can directly lead to the high-temperature water and karst water burst in the construction process of the mountain railway tunnel, thereby not only influencing the construction progress and threatening the safety of constructors, but also disturbing the ground surface and underground water system, and further causing great influence on the hydrological condition of the tunnel site area after the water burst from the tunnel entrance), the application creatively integrates the elevation, gradient and slope elements of water burst into the runoff influence factor obtaining module of the water burst of the mountain railway tunnel, the purpose is for all-round true deduction gushing water discharges the scene, and the trend after gushing water from the tunnel portal is followed in comprehensive analysis, and the high accuracy restores gushing water and discharges the flow path, improves the degree of accuracy of gushing water runoff discharge process simulation. And the hydrological disaster risk level of the tunnel site area caused by the tunnel water runoff is calculated by constructing a star-shaped hierarchical structure-hydrological model simulation result superposition analysis function, so that the hydrological disaster risk can be judged more intuitively and accurately.
The trend after the analysis gushing water that this application can be systematic gushes water from the tunnel portal and discharges the flow path, and high accuracy reduction gushing water to all-round true deduction gushing water discharges the scene, even under the condition that lacks the relevant observation data of long-term high accuracy, also can establish a maintenance cost low and the succinct accurate mountain railway tunnel of output result gushes water and discharges hydrological model. In addition, the method for judging the hydrological disaster risk level is determined by constructing a star-shaped hierarchical structure-hydrological model simulation result superposition analysis function, and the range and the degree of the hydrological disaster risk in the tunnel site area caused by the tunnel water burst runoff discharge event are visually displayed in the form of a runoff hydrological disaster risk level rendering graph.
Drawings
FIG. 1 is a schematic overall flow diagram of the system architecture;
FIG. 2 is a star hierarchy model of the system;
FIG. 3 is a water runoff river channel of a large pillar mountain tunnel in an embodiment;
FIG. 4 is a generalized river for water runoff discharge in a hydrological model building block;
FIG. 5 shows the simulation results of the runoff discharge of the gushing water in the examples;
fig. 6 is a rendering diagram of risk levels of runoff hydrology disasters in an embodiment.
Detailed Description
It should be noted that, in the present invention, the embodiments disclosed in the present application may be combined with each other without conflict.
The first embodiment is as follows: specifically describing the embodiment with reference to fig. 1, the mountain railway tunnel water burst runoff hydrological disaster risk assessment system according to the embodiment includes: a runoff influence factor acquisition subsystem, a runoff discharge simulation subsystem and a hydrological disaster risk grade judgment subsystem,
the runoff influence factor acquiring subsystem is used for acquiring and processing various index parameters influencing the runoff discharging process and comprises a runoff influence factor acquiring module and a runoff influence factor processing module. The runoff influence factors are specific indexes of mountain tunnels added on the basis of conventional factors, and comprise elevations, slopes and slopes of a tunnel site area, remote sensing images of the tunnel site area, attribute data (runoff cross section distance, distance between a runoff center line and two banks and the like) of all water inrush runoff in the tunnel site area and water quantity monitoring data.
The runoff discharge simulation subsystem is used for simulating the discharge process of the water-inrush runoff and comprises a runoff influence factor fusion module, a hydrological model establishment module and a runoff waterpower simulation module, namely, the runoff discharge evolution process is simulated by using data integrated by the runoff influence factor acquisition subsystem, and a runoff discharge simulation calculation result is obtained.
The hydrological disaster risk grade judgment subsystem comprises a judgment matrix construction module, a risk weight measuring and calculating module, a hydrological disaster risk grade dividing module and a hydrological disaster risk grade judging module, namely a star-shaped hierarchical structure model is constructed according to risk sensitive factors in runoff discharge simulation calculation results, a risk sensitive factor judgment matrix is determined according to the star-shaped hierarchical structure model, and then the risk weight of the risk sensitive factors is obtained. And then determining a simulation result of the risk sensitive factors based on the hydrological model, comprehensively judging and constructing a star-shaped hierarchical structure-hydrological model simulation result superposition analysis function by combining the simulation result of the risk sensitive factors of each section of the tunnel and the risk weight, and calculating to obtain a hydrological disaster risk value. In determining the risk level of the hydrological disasterAfter the criterion is judged, the hydrological disaster risk superposition parameter Q of the tunnel water burst runoffjAnd (4) carrying out practical judgment to finally obtain the hydrological disaster risk grade, wherein the judgment principle is as follows:
if hydrological disaster risk superposition parameter QjIf Qj is more than or equal to 58 and less than 70, the risk is judged to be high;
if hydrological disaster risk superposition parameter QjIf Qj is more than or equal to 46 and less than 58, determining the risk is medium;
if hydrological disaster risk superposition parameter QjIf Qj is more than or equal to 34 and less than 46, the risk is judged to be low;
if hydrological disaster risk superposition parameter QjIf Qj is more than or equal to 22 and less than 34, the risk is judged to be extremely low;
if hydrological disaster risk superposition parameter Qj0Qj < 22, the result is judged to be risk-free.
The runoff basic data acquisition module is used for acquiring basic data of tunnel water burst runoff discharge, and acquiring related influence factors of mountain railway tunnel water burst runoff discharge under a complex background by using a multi-sensor (the integrated monitoring technology of air, space and ground) to obtain heterogeneous information.
The 'empty' is based on a traditional satellite observation data system, high-precision mountain railway tunnel site region DEM remote sensing image data are acquired by relying on a Sentinel 2 (Sentinel-2) earth observation satellite, a remote sensing image with high spatial resolution within a 2km distance range around a tunnel portal is imaged within 30 meters below, the cloud cover is less than 10%, the main monitoring region is covered, the image quality is good, the conditional region preferentially selects the remote sensing image with high spatial resolution below 10 meters, and the data format is an shp format;
the 'sky' means that a digital aerial photography instrument DMC is used for collecting images of water burst discharge runoff in a tunnel site area, and property data of the water burst discharge runoff in the tunnel site area are extracted according to the collected images of the water burst discharge runoff in the tunnel site area, wherein the property data of the water burst discharge runoff comprise runoff cross section distance, the distance between a runoff center line and two banks and the like. When the scale of the graph is 1: at 2000, the shooting navigation height is 1440m, the heading breadth is 1132m, the sidewise breadth is 1991m, the ground resolution is 0.144m, the image spatial resolution is 120 optical line pairs/mm, and the spectral resolution is 48 bit;
the 'ground' means that real-time water quantity monitoring data are obtained by using an actual water quantity monitoring point, the time interval of the water quantity data is 1 day, the data are station data, no spatial resolution exists, and the data format is a txt file.
The runoff basic data processing module is used for correcting and processing basic data of tunnel water burst runoff discharge, a grid calculator is used for interpreting a tunnel address area DEM elevation remote sensing image acquired by a Sentinel 2 (Sentinel-2) earth observation satellite, then the interpreted image is subjected to radiometric calibration, namely, a DN value of the interpreted image is converted into a radiance value, then reflection information of elevation, gradient and slope data of the tunnel address area is extracted from the atmosphere through atmospheric correction, and finally image cutting is carried out according to the reflection information of the elevation, gradient and slope data of the tunnel address area in the corrected image and according to location characteristics to obtain the elevation, gradient and slope data of the tunnel address area, namely an elevation factor, a gradient factor and a slope factor.
The runoff discharge simulation subsystem comprises a runoff influence factor fusion module, a hydrological model construction module and a runoff hydraulic simulation module.
And the runoff influence factor fusion module is used for fusing and identifying the processed runoff influence factors to obtain basic input data of the system, so that the accuracy and reliability of the data are improved. And (5) performing radial streamline drawing and radial cross section division on the corrected system basic data. Firstly, depression filling in Arcgis software is used for calculating the flow direction of water-inrush runoff of a tunnel, runoff accumulative calculation in the Arcgis software is used for simulating a runoff river network, then the runoff river network is extracted in the Arcgis software according to an elevation factor, a gradient factor and a slope factor to generate a runoff river channel, then the runoff river channel is segmented at a water quantity monitoring point or at a runoff inflection point by using a space analysis method, so that at least one segmented cross-section bread water content monitoring data is assigned to the water quantity monitoring data of the water quantity monitoring point, finally, a runoff line (the runoff river channel) is obtained, a plurality of runoff cross sections are marked, and the obtained runoff line is checked and identified by using a digital aerial photograph instrument DMC to reduce misjudgment.
The hydrological model building module is based on 1: 1000, and constructing a hydrological model of the runoff line by using the HEC-HMS surface runoff model.
The runoff waterpower simulation module adopts a dynamic wave model in the HEC-HMS hydrological model, performs water quantity evolution operation in HEC-RAS water surface line calculation software according to the hydrological model of the runoff line to finally obtain a simulation result of the runoff discharge, and extracts a simulation result of the risk sensitive factors of the runoff line in the simulation result of the runoff discharge, wherein the simulation result of the risk sensitive factors of the runoff line comprises runoff water surface elevation variation, runoff flow velocity, runoff flow area, runoff surface width and runoff waterpower acceleration.
The dynamic wave model is a conceptual model in an HEC-HMS surface runoff model, and describes the physical mechanism of surface water movement in the water collection area surface and a smaller water collection river channel as much as possible. Since the relevant observation data with high long-term accuracy cannot be obtained in mountain areas, the model parameters of the dynamic wave model are only related to the measured and observed water-collecting region characteristics. Therefore, in the case where it is not convenient to acquire field measurement data with high accuracy for a long period of time, the dynamic wave model is the best choice.
The dynamic wave model comprises a surface flow model and a river flow model:
(1) a surface flow model. The water flow on the plane is mainly one-dimensional flow. The momentum equation for the one-dimensional case is:
in the formula 1, SfIs an energy gradient; soIs a bottom slope; v is the runoff flow rate; y is hydraulic depth; x is the length along the flow path; t is time; g is the acceleration of gravity;
is a pressure gradient;
is convective acceleration;
is the local acceleration.
The solving equation for the energy gradient is:
in the formula 2, Q is the water inrush flow; r is a runoff hydraulic radius; a is the cross-sectional area of the runoff; and N is a resistance coefficient.
For shallow currents, the bottom slope and the energy gradient are approximately equal, the acceleration effect can be neglected, so the momentum equation can be simplified as:
Sf＝Soformula 3
The energy gradient equation can be simplified as:
Q＝αAmformula 4
In formula 4, α and m are parameters related to the water flow geometry and surface roughness.
The one-dimensional continuity equation in the surface flow is:
in the formula 5, B is the width of the runoff water surface; q is the inflow of the river channel in unit length;
the water storage capacity is prism;
the water storage capacity is wedge-shaped;
is the rate of rise.
The one-dimensional continuous equation is simplified into an equation suitable for plane shallow water flow, and the equation is as follows:
combining a one-dimensional momentum equation with a one-dimensional continuous equation to obtain a dynamic wave approximation equation:
the HEC-HMS represents the runoff of water gushing as a rectangular channel of unit width, where: alpha is 1.486S1/2N; and m is 5/3. N is the surface flow roughness coefficient (see Table 1)
TABLE 1 surface flow roughness coefficient for surface flow modeling (USACE, 1998)
(2) And (4) a water burst runoff model. The dynamic wave approximation equation of surface flow is also applicable to the river flow model. When the river channel flows, runoff inflow comes from a water collecting area plane or an upstream river channel. Wherein the values of α and m are shown in Table 2.
TABLE 2 dynamic wave parameters of runoff river channels of different shapes (USACE, 1998)
The hydrological disaster risk grade judgment subsystem comprises a judgment matrix construction module, a risk weight measuring and calculating module, a hydrological disaster risk grade classification module and a hydrological disaster risk grade judgment module. The idea of judging the risk of the hydrological disaster by adopting the star-shaped hierarchical structure-hydrological model simulation result superposition analysis function is as follows: the method comprises the steps of firstly calculating risk weight of risk sensitive factors through a star-type hierarchical structure model, then constructing a judgment matrix for risk judgment, determining hydrological disaster risk grade classification standards according to a maximum simulation result principle after obtaining the risk weight meeting consistency test, and further judging the grade of the hydrological disaster risk caused by water burst runoff of a certain tunnel.
The judgment matrix construction module determines that the elevation variation (Crit W.S), the runoff Flow Area (Flow Area) and the runoff Width (Top Width) of the runoff surface in the runoff discharge simulation result are direct influence factors of the runoff caused hydrological disaster on the basis of deeply analyzing various factors of the runoff caused hydrological disaster, and the runoff Flow rate (Vel Chnl) and the runoff hydraulic acceleration (E.G.slope) are indirect influence factors of the runoff caused hydrological disaster on the runoff. The larger the water surface elevation variation of the runoff is, the smaller the water amount flowing to the downstream along the runoff is, the more the water flows to the two sides of the runoff is, and the larger the disaster degree on the surrounding hydrological environment is. Conversely, the tunnel water burst runoff section with small water surface elevation variation of the runoff shows that the runoff flow of the section is large, and the hydrological disaster risk of the section to the tunnel site area is smaller. Therefore, a hydrological disaster risk sensitive factor caused by the tunnel water burst runoff is taken as a general target A, the elevation variation of the runoff water surface, the runoff flow rate, the runoff flow area, the runoff water surface width and the runoff hydraulic acceleration rate are respectively taken as B1, B2, B3, B4 and B5 as primary indexes, and a star-shaped hierarchical structure model is established as shown in FIG. 2. By constructing the star-shaped hierarchical structure model by using an analytic hierarchy process, the correlation among the risk sensitive factors can be more intuitively and accurately depicted.
According to the star-shaped hierarchical structure model, a comparative scaling method is adopted, 110 questionnaires are issued to scientific research experts, mountain railway tunnel construction technicians and government related management departments, 72 questionnaires are recovered, the recovery rate exceeds 65%, the relative importance of hydrological disaster risk sensitive factors caused by tunnel water burst is obtained through analysis and statistics, and a judgment matrix is constructed as shown in table 3.
TABLE 3A (B) judgment matrix
| A | B1 | B2 | B3 | | B5 |
| B1 | |||||
| 1 | 2 | 2 | 3 | 2 | |
| |
1/2 | 1 | 4 | 2 | 6 |
| |
1/2 | 1/4 | 1 | 2 | 3 |
| |
1/3 | 1/2 | 1/2 | 1 | 2 |
| |
1/2 | 1/6 | 1/3 | 1/2 | 1 |
And the risk weight measuring and calculating module is used for respectively calculating the risk weights of the risk sensitive factors of the hydrological disasters because the influence degrees of all factors on the hydrological disasters are different. Calculating the risk weight coefficient of the hydrological disaster by using an analytic hierarchy process, taking A (B) judgment matrix as an example, calculating the product W of each row of elements according to the formula 8i：
According to equation 9, calculate WiRoot of cubic (n times)
According to formula 10, pair
Carrying out normalization treatment to obtain a hydrological disaster risk weight coefficient Mi：
According to the formulas 8, 9 and 10, the judgment matrix A (B) is subjected to consistency check:
table 4 gives RI as 1.12, so the consistency check coefficient CR is:
TABLE 4 RI lookup Table for consistency index (TLSaaty, 1980)
| Number of factors (n) | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| Corresponding value | 0.00 | 0.00 | 0.58 | 0.90 | 1.12 | 1.24 | 1.32 | 1.41 | 1.45 |
As can be seen, the matrix meets the consistency check requirement, so the risk weight coefficients of the first-level indexes are M respectively1＝0.3231，M2＝0.3231，M3＝0.1615，M4＝0.1196，M50.0727, as shown in table 5.
TABLE 5 hydrologic disaster Risk weight coefficient Table
The hydrological disaster risk grading module is used for carrying out superposition analysis on the simulation result of the risk sensitive factor of the radial flow line and the hydrological disaster risk weight coefficient to obtain a risk superposition parameter Qj(formula 13), and determining the hydrological disaster risk grade classification standard caused by the water burst runoff of the tunnel by using an optimal segmentation method, see table 6. As a clustering method for analyzing data characteristics, an optimal segmentation method divides a data set into a plurality of types, so that the intra-type similarity is as large as possible and the inter-type similarity is as small as possible, and further, the difference between the grades is ensured to be large.
In formula 13, QjSuperimposing the parameters for the risk; j represents each tunnel water burst runoff section; i is expressed as item i risk sensitivityA sensory factor; b isijThe hydrological model simulation result of the ith risk sensitive factor of the jth tunnel water inrush runoff section; mijAnd (4) the risk weight of the ith risk sensitive factor of the jth tunnel water inrush runoff section.
TABLE 6 hydrologic disaster Risk ratings Standard
And the hydrological disaster risk grade evaluation module is used for truly evaluating the hydrological disaster risk of the water burst runoff of the specific tunnel according to the hydrological disaster risk grade division standard. By using formula 13, parameter Q is superimposed to hydrological disaster risk of water burst runoff of the specific tunneljCalculations are performed and risk rankings are performed by looking up a table 6. Dividing each section of the tunnel water inrush runoff into five grades of high risk, medium risk, low risk, extremely low risk and no risk according to a risk grade division standard, and representing the risk grade from high to no by using five colors of red, orange, yellow, light green and dark green. And performing risk grade continuous rendering on the hydrological disaster risk of the tunnel water burst runoff, and finally displaying the risk of the hydrological disaster in the tunnel site area caused by the drainage of the water burst runoff of the mountain railway tunnel in the form of a runoff hydrological disaster risk grade rendering graph.
Example (b):
according to the method, the large-column mountain railway tunnel is selected as an experimental object. The tunnel with the large pillar is located in Baoshan city of Yunnan province, traverses across the mountain, has a full length of 14484 meters, and has an average altitude of 4000 meters. The large-column mountain tunnel site area is rich in underground resources, dense in fault and high in karst development, and is a mountain railway tunnel with extremely high water burst risk.
Specifically describing the embodiment with reference to fig. 1, the system for evaluating the risk of hydrological disasters of water burst runoff in a mountain railway tunnel according to the embodiment includes: the system comprises a runoff influence factor acquisition subsystem, a runoff discharge simulation subsystem and a hydrological disaster risk grade judgment subsystem.
The runoff influence factor acquisition subsystem comprises a runoff basic data acquisition module and a runoff basic data processing module. The runoff influence factors are specific indexes of mountain tunnels added on the basis of conventional factors, and comprise elevation factors, gradient factors and slope factors of a tunnel site area, and the basic data comprise remote sensing images of the tunnel site area, attribute data (runoff cross section distance, distance between runoff center lines and two banks and the like) of all water inrush runoff in the tunnel site area and water quantity monitoring data.
The runoff basic data acquisition module is used for acquiring basic data of tunnel water burst runoff discharge and acquiring related influence factors of mountain railway tunnel water burst runoff discharge under a complex background by utilizing a multi-sensor (the 'air-space-ground' integrated monitoring technology) to obtain heterogeneous information.
Acquiring a tunnel address area DEM elevation remote sensing image of 2011 big prop mountain tunnel under construction by utilizing a Sentinel 2 (Sentinel-2) earth observation satellite, wherein the spatial resolution of the remote sensing image is 5 meters, and the cloud coverage rate is less than 10%; then, acquiring an image of the water burst discharge runoff in the tunnel site area by using a digital aerial photography instrument DMC, and extracting attribute data of the water burst discharge runoff in the tunnel site area according to the acquired image of the water burst discharge runoff in the tunnel site area, wherein the attribute data of the water burst discharge runoff comprises a runoff cross section interval, a distance between a runoff center line and two banks, and a distance between a left bank, a center line and a right bank between an upstream cross section and a downstream cross section, the spatial resolution of the image of the water burst discharge runoff in the tunnel site area is 120 optical line pairs/mm, the spectral resolution is 48bit, and the cloud coverage rate is less than 1%, and the image is stored in an Excel file form; and finally, acquiring water quantity monitoring data by using the water quantity monitoring point, wherein the water quantity monitoring data comprises flow, flow rate and water level data. The time resolution of the water quantity monitoring data is 1 day, and the water quantity monitoring data is stored in an Excel file form.
The runoff basic data processing module is used for correcting and processing basic data of tunnel water burst runoff discharge, a grid calculator is used for interpreting a tunnel address region DEM elevation remote sensing image acquired by a sentencel-2 earth observation satellite, then the interpreted image is subjected to radiometric calibration, namely, a DN value of the interpreted image is converted into a radiance value, then the reflected information of elevation, gradient and slope data of the tunnel address region is extracted from the atmosphere through atmospheric correction, finally, image cutting is carried out according to the reflected information of the elevation, gradient and slope data of the tunnel address region in the corrected image and according to location characteristics, and the elevation, gradient and slope data of the tunnel address region, namely, an elevation factor, a gradient factor and a slope factor, the data type is vector data, and the scale is 1: 2.5 ten thousand.
The runoff discharge simulation subsystem comprises a runoff influence factor fusion module, a hydrological model construction module and a runoff hydraulic simulation module.
The runoff influence factor fusion module is used for fusing and identifying the processed runoff influence factors, firstly, depression filling in Arcgis software is used for calculating the flow direction of water-inrush runoff of a tunnel, then runoff accumulation calculation in the Arcgis software is used for simulating a runoff river network, then the runoff river network is extracted in the Arcgis software according to an elevation factor, a gradient factor and a slope factor to generate a runoff river channel, then the runoff river channel is segmented at a water quantity monitoring point or at a runoff inflection point by using a space analysis method, so that at least one segmented cross section of bread water content monitoring data is obtained, the water quantity monitoring data of the water quantity monitoring point is assigned on the runoff cross section, finally, a runoff line (runoff river channel) is obtained, a plurality of runoff cross sections are marked, and the obtained runoff line is checked and identified by using a digital aerial photograph instrument DMC to reduce misjudgment. FIG. 3 is a water gushing streamline at the exit of a large pillar tunnel (25 ° 12 '59 "N, 99 ° 14' 06" E).
The hydrological model building module is based on 1: 1000, constructing a hydrological model of the water gushing radial flow line at the outlet of the large pillar mountain tunnel by using an HEC-HMS surface radial flow model. Processing the runoff DEM data through an expansion module HEC-GeoHMS 3.3 of Arcview3.3, extracting topographic parameters and river channel characteristic parameters of runoff, dividing the runoff into sub-basins (named as R10W10), and constructing an HEC-HMS project on the basis. Reading a river system graph net, runoff data (river system and river section names) and cross section data (section elevation, left bank distance and Mannesmia ratio of upstream and downstream sections, main deep groove distance and Mannesmia ratio of upstream and downstream sections, right bank distance and Mannesmia ratio of upstream and downstream sections, and contraction and expansion coefficients) and inputting the data into HEC-RAS software, and finally obtaining a generalized river channel for runoff discharge in the hydrological model of the runoff line as shown in figure 4.
The runoff waterpower simulation module adopts a dynamic wave model in an HEC-HMS hydrological model, performs water quantity evolution operation in HEC-RAS water surface line calculation software according to the hydrological model of the runoff line to finally obtain a simulation result of the runoff discharge of the water inrush (as shown in figure 5), and extracts a simulation result of risk sensitive factors of the runoff line in the simulation result of the runoff discharge of the water inrush (as shown in table 7), wherein the simulation result of the risk sensitive factors of the runoff line comprises runoff water surface elevation variation, runoff flow rate, runoff flow area, runoff surface width and runoff acceleration rate. The simulation result is verified by using the water quantity data measured by the actual water quantity monitoring point, and the result shows that the overall trend of the simulation result is basically consistent with that of the measured value, so that the reliability and the rationality of the method are verified.
TABLE 7 simulation results of risk sensitivity factors
The hydrological disaster risk grade judgment subsystem comprises a judgment matrix construction module, a risk weight measuring and calculating module, a hydrological disaster risk grade classification module and a hydrological disaster risk grade judgment module.
And the judgment matrix construction module is used for constructing a star-shaped hierarchical structure model by taking the elevation variation of the runoff water surface, the runoff flow velocity, the runoff flow area, the runoff water surface width and the runoff hydraulic acceleration as primary indexes, and constructing a judgment matrix (shown in a table 3) according to the relative importance construction of the hydrological disaster risk sensitive factors caused by the water burst of the tunnel by adopting a comparative scaling method and combining with an questionnaire according to the star-shaped hierarchical structure model.
And the risk weight measuring and calculating module is used for obtaining the risk weight of the hydrological disaster risk sensitive factor based on the judgment matrix and obtaining a hydrological disaster risk weight coefficient by utilizing an analytic hierarchy process (as shown in table 5).
A hydrological disaster risk grading module for grading the risk of the hydrological disaster according to the simulation result of the risk sensitive factor of the radial flow line and the hydrological disaster risk weight systemThe numbers are subjected to superposition analysis to obtain a risk superposition parameter Qj(formula 13), and determining a hydrological disaster risk grading standard caused by tunnel water burst runoff (as shown in table 6).
And the hydrological disaster risk grade evaluation module is used for truly evaluating the hydrological disaster risk of the water burst runoff of the specific tunnel according to the hydrological disaster risk grade division standard. By using formula 13, parameter Q is superimposed to hydrological disaster risk of water burst runoff of the specific tunneljCalculations are performed and risk rankings are performed by looking up a table 6. Dividing each section of the tunnel water inrush runoff into five grades of high risk, medium risk, low risk, extremely low risk and no risk according to a risk grade division standard, and representing the risk grade from high to no by using five colors of red, orange, yellow, light green and dark green. And continuously rendering the risk levels of the hydrological disaster risks of the tunnel water burst runoff, and finally displaying the risk level of the hydrological disaster in the tunnel site area caused by the drainage of the water burst runoff of the mountain railway tunnel in the form of a runoff hydrological disaster risk level rendering graph (as shown in fig. 6).
Q1＝Bi1·Mi1＝-B11×M11+B21×M21+B31×M31+B41×M41+B51×M51
＝-173.8×0.3231+18.04×0.3231+55.44×0.1615+5.57×0.1196
+944.13×0.0727＝27.932
Q2＝Bi2·Mi2＝-B12×M12+B22×M22+B32×M32+B42×M42+B52×M52
＝-78.8×0.3231+17.58×0.3231+56.87×0.1615+5.96×0.1196
+770.08×0.0727＝46.1019
Q3＝Bi3·Mi3＝-B13×M13+B23×M23+B33×M33+B43×M43+B53×M53
＝-73.06×0.3231+6.40×0.3231+156.19×0.1615+5.64×0.1196
+713.4×0.0727＝56.2255
Q4＝Bi4·Mi4＝-B14×M14+B24×M24+B34×M34+B44×M44+B54×M54
＝-88.12×0.3231+18.8×0.3231+53.18×0.1615+4.86×0.1196
+422.27×0.0727＝17.4716
Q5＝Bi5·Mi5＝-B15×M15+B25×M25+B35×M35+B45×M45+B55×M55
＝-8.49×0.3231+4.15×0.3231+240.71×0.1615+4.64×0.1196
+380.19×0.0727＝65.6672
Obtaining a hydrological disaster risk superposition parameter Q of the water burst runoff of the large pillar mountain tunnel after superposition analysis function calculation of the simulation result of the star-type hierarchical structure-hydrological modeljAnd looking up table 6 to perform risk classification, see table 8.
TABLE 8 hydrological disaster risk level of water burst runoff of large-pillar mountain tunnel
| Serial number | Tunnel water burst runoff section | Risk stack parameter Qj | Risk rating | Grade represents |
|
| 1 | DK111+960～DK112+230 | 27.932 | Extremely low | Light green | |
| 2 | DK113+280～DK113+660 | 46.1019 | Low risk | |
|
| 3 | DK114+900～DK117+900 | 56.2255 | Middle risk | |
|
| 4 | DK120+930～DK121+600 | 17.4716 | Without risk | Dark green | |
| 5 | DK122+500～DK123+720 | 65.6672 | High risk | Red colour |
It should be noted that the detailed description is only for explaining and explaining the technical solution of the present application, and the scope of protection of the claims is not limited thereby. All such modifications as fall within the scope of the application are intended to be included within the scope of the claims and the description.
Claims (10)
1. The mountainous railway tunnel water burst runoff hydrological disaster risk assessment system is characterized by comprising a runoff influence factor acquisition subsystem, a runoff discharge simulation subsystem and a hydrological disaster risk grade judgment subsystem;
the runoff influence factor acquisition subsystem is used for acquiring and correcting influence factors of a runoff discharge process;
the runoff discharge simulation subsystem is used for acquiring influence factors processed by the subsystem according to the runoff influence factors to simulate the discharge process of the water runoff and obtain a runoff discharge simulation result;
and the hydrological disaster risk grade judgment subsystem evaluates the hydrological disaster risk of the tunnel water burst runoff according to the runoff discharge simulation result.
2. The mountain railway tunnel water inrush runoff hydrological disaster risk assessment system of claim 1, wherein the impact factors include an elevation factor, a grade factor, and a slope factor.
3. The mountain ridge railway tunnel water burst runoff hydrological disaster risk assessment system according to claim 2, wherein the runoff influencing factor acquiring subsystem comprises a runoff basic data acquiring module and a runoff basic data processing module;
the runoff basic data acquisition module is used for acquiring basic data of tunnel water burst runoff discharge, the basic data comprises a tunnel site area remote sensing image, attribute data of water burst runoff in the tunnel site area and water quantity monitoring data,
the method comprises the following specific steps:
firstly, a sentinel second satellite is used for collecting a DEM elevation remote sensing image of a tunnel address area, the spatial resolution of the remote sensing image is 5 meters, the coverage rate of clouds is less than 10 percent,
then, acquiring an image of the water burst discharge runoff in the tunnel site area by using a digital aerial photography instrument DMC, and extracting attribute data of the water burst discharge runoff in the tunnel site area according to the acquired image of the water burst discharge runoff in the tunnel site area, wherein the attribute data of the water burst discharge runoff comprises a runoff cross section interval, a distance between a runoff center line and two banks, and a distance between a left bank, a center line and a right bank between an upstream cross section and a downstream cross section, the spatial resolution of the image of the water burst discharge runoff in the tunnel site area is 120 optical line pairs/mm, the spectral resolution is 48bit, and the cloud coverage rate is less than 1%;
finally, water quantity monitoring data is obtained by utilizing the water quantity monitoring points, the water quantity monitoring data comprises flow, flow rate and water level data,
the runoff basic data processing module is used for correcting and processing basic data of tunnel water burst runoff discharge, and the specific steps are as follows:
the method comprises the steps of utilizing a grid calculator to interpret a tunnel address area DEM elevation remote sensing image collected by a sentinel second satellite, then carrying out radiometric calibration on the interpreted image, namely converting the DN value of the interpreted image into a radiance value, then carrying out atmospheric correction, extracting reflection information of elevation, gradient and slope data of the tunnel address area from the atmosphere, and finally carrying out image cutting according to the reflection information of the elevation, gradient and slope data of the tunnel address area in the corrected image and the zone location characteristics to obtain the elevation, gradient and slope data of the tunnel address area, namely an elevation factor, a gradient factor and a slope factor.
4. The mountain railway tunnel water inrush runoff hydrological disaster risk assessment system of claim 3, wherein the property data of the water inrush runoff in the tunnel site area comprises runoff cross section distance and distance between a runoff center line and two banks.
5. The mountain railway tunnel water burst runoff hydrological disaster risk assessment system as claimed in claim 4, wherein the runoff drainage simulation subsystem comprises a runoff influencing factor fusion module, a hydrological model establishment module and a runoff waterpower simulation module,
the runoff influence factor fusion module is used for fusing and identifying the treated runoff influence factors, and the specific steps are as follows:
firstly, filling depression in Arcgis software to calculate the flow direction of water-inrush runoff of a tunnel, simulating a runoff river network by using accumulated runoff calculation in the Arcgis software, extracting the runoff river network in the Arcgis software according to an elevation factor, a gradient factor and a slope factor to generate a runoff river channel, and then segmenting the runoff river channel at a water quantity monitoring point or at a runoff inflection point by using a space analysis method, so that at least one segment of cross-section bread water content monitoring data is assigned to the water quantity monitoring data of the water quantity monitoring point on a runoff cross section, and finally obtaining a runoff line;
the hydrological model building module is based on 1: 1000, establishing a hydrological model of the runoff line by utilizing an HEC-HMS surface runoff model,
the runoff water power simulation module carries out water quantity evolution operation according to the hydrological model of the runoff line, finally obtains the simulation result of the runoff discharge of gushing water, extracts the simulation result of the risk sensitive factor of the runoff line in the simulation result of the runoff discharge of gushing water, and the simulation result of the risk sensitive factor of the runoff line comprises runoff water surface elevation variation, runoff flow rate, runoff flow area, runoff water surface width and runoff water power acceleration rate.
6. The mountain railway tunnel water inrush runoff hydrological disaster risk assessment system of claim 5, wherein the HEC-HMS surface runoff model comprises a surface runoff model and a river runoff model.
7. The mountain railway tunnel water inrush runoff hydrologic disaster risk assessment system of claim 5, wherein the hydrologic disaster risk level judgment subsystem comprises a judgment matrix construction module, a risk weight calculation module, a hydrologic disaster risk level classification module and a hydrologic disaster risk level judgment module,
the judgment matrix construction module is used for constructing a star-shaped hierarchical structure model by taking elevation variation of the runoff water surface, runoff flow velocity, runoff flow area, runoff water surface width and runoff hydraulic acceleration as primary indexes, and constructing a judgment matrix according to the relative importance construction of hydrological disaster risk sensitive factors caused by water gushing of a tunnel by adopting a comparison scale method and combining with an questionnaire according to the star-shaped hierarchical structure model, wherein the judgment matrix is as follows:
wherein, A represents a total target, and the number represents relative importance, and the elevation variation of the runoff water surface, the runoff flow velocity, the runoff flow area, the runoff water surface width and the runoff hydraulic acceleration rate respectively correspond to B1, B2, B3, B4 and B5;
the risk weight calculation module obtains the risk weight of the hydrological disaster risk sensitive factor based on the judgment matrix, and obtains a hydrological disaster risk weight coefficient by utilizing an analytic hierarchy process;
the hydrological disaster risk grading module is used for carrying out superposition analysis according to the simulation result of the risk sensitive factor of the radial flow line and the hydrological disaster risk weight coefficient to obtain a risk superposition parameter Qj；
The hydrological disaster risk grade evaluation module is used for superposing the parameter Q according to the riskjAnd (6) carrying out risk assessment.
8. The mountain ridge railway tunnel water inrush runoff hydrological disaster risk assessment system of claim 7, wherein the hydrological disaster risk level evaluation module has the determination principle of:
if hydrological disaster risk superposition parameter QjQ is not less than 58jIf the risk is less than 70, judging the risk to be high;
if hydrological disaster risk superposition parameter QjIs 46 or more than QjIf the number is less than 58, the risk is judged to be medium;
if hydrological disaster risk superposition parameter QjIs 34 or more than QjIf < 46, judging the risk to be low;
if hydrological disaster risk superposition parameter QjQ is not less than 22jIf < 34 >, judging the risk is extremely low;
if hydrological disaster risk superposition parameter QjQ is not less than 0jIf < 22 >, the judgment is no risk.
9. The mountain ridge railway tunnel water inrush runoff hydrological disaster risk assessment system of claim 8, wherein the risk stacking parameter QjExpressed as:
Qj＝Bij·Mij＝-B1j×M1j+B2j×M2j+B3j×M3j+B4j×M4j+B5j×M5j
Qjsuperimposing the parameters for the risk; j represents each tunnel water burst runoff section; i is expressed as the ith risk sensitive factor; b isijThe hydrological model simulation result of the ith risk sensitive factor of the jth tunnel water inrush runoff section; mijAnd (4) the risk weight of the ith risk sensitive factor of the jth tunnel water inrush runoff section.
10. The mountain ridge railway tunnel water inrush runoff hydrological disaster risk assessment system of claim 6, wherein the hydrological disaster risk level judgment subsystem further comprises a consistency check module for performing consistency check on the judgment matrix.
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| CN114297953A (en) * | 2021-12-24 | 2022-04-08 | 河北省气象灾害防御中心 | Mountain area gale disaster risk zoning method |
| CN114297953B (en) * | 2021-12-24 | 2024-04-30 | 河北省气象灾害防御中心 | Mountain area storm disaster risk division method |
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| CN113807740B (en) | 2022-09-23 |
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