CN116976679A - Dam break early warning method and device for barrier lake, electronic equipment and readable storage medium - Google Patents
Dam break early warning method and device for barrier lake, electronic equipment and readable storage medium Download PDFInfo
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Abstract
The invention provides a dam break early warning method, a device, electronic equipment and a readable storage medium for a barrier lake, which relate to the technical field of dam break early warning and comprise the following steps: acquiring a multi-source data set corresponding to a target monitoring area; constructing dam body formed elevation data corresponding to the target monitoring area based on unmanned aerial vehicle data; dam break simulation is carried out on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body, so that a dam break simulation result corresponding to the target monitoring area is obtained, and risk grade evaluation is carried out on the target monitoring area, so that a barrier lake risk grade corresponding to the target monitoring area is obtained; performing dam deformation monitoring on the target monitoring area according to the InSAR data to obtain a dam deformation monitoring result corresponding to the target monitoring area; and carrying out dam break early warning on the barrier lake in the target monitoring area based on the dam break simulation result, the barrier lake danger level and the dam deformation monitoring result. The dam-break early warning method and device can remarkably improve the early warning effect on dam-break risks of the barrier lake.
Description
Technical Field
The invention relates to the technical field of dam break early warning, in particular to a dam break early warning method and device of a barrier lake, electronic equipment and a readable storage medium.
Background
The dam break early warning problem of the barrier lake is mainly based on rainfall models, hydrologic models, hydrodynamic models, physical model experiments and some industry history empirical formulas, such as a famous formula of Xie Ren, and the like, and the physical process of the dam break is simulated by combining the traditional method of analyzing and numerical simulation of the sediment characteristic information data of the actual dam break stack when the barrier lake is formed, and the early warning is focused on the simulation prediction of the dam break type, the break forming time, the break width, the break peak flow, the leakage flow and the like. With the vigorous development of the aerospace satellite remote sensing industry in China, in recent years, some disaster prevention and reduction high-resolution satellites successfully transmit, and remote sensing monitoring is also gradually applied to dam break early warning of barrier lakes. However, both conventional methods and remote sensing have some drawbacks. The traditional numerical simulation method based on the model and dam-break pile feature information data firstly has the possibility that great deviation exists in numerical simulation based on past historical experience because the dam-break pile deposition feature of each barrier lake is different; secondly, the calibration of the model is time-consuming, the model is constructed and is not changed after calibration, and the real-time acquired internet of things perception data are difficult to fuse. The remote sensing monitoring is applied to dam break early warning of the barrier lake, the principle is that the area change of the barrier lake area and the tiny deformation of a dam break accumulation body are monitored for early warning, firstly, the satellite revisiting time is long, the rainfall flood peak impact causes instant occurrence of the dam break condition, and the frequency of the remote sensing monitoring is insufficient; secondly, the position of the barrier lake is generally in a mountain area, and the corresponding river basin in the same period can be accompanied by heavy rainfall, so that uncertainty exists in acquisition of effective monitoring data due to cloud layers and the like in remote sensing monitoring, and the early warning effect of the existing barrier lake dam break early warning method is poor.
Disclosure of Invention
Accordingly, the invention aims to provide a dam-break early warning method and device for a barrier lake, electronic equipment and a readable storage medium, which can remarkably improve the effect of early warning the risk of dam-break of the barrier lake.
In a first aspect, an embodiment of the present invention provides a dam break early warning method for a barrier lake, including:
acquiring a multi-source data set corresponding to a target monitoring area; the multi-source data set at least comprises drainage basin elevation data, unmanned aerial vehicle data and InSAR data before dam formation;
constructing dam body formed elevation data corresponding to the target monitoring area based on the unmanned aerial vehicle data;
performing dam break simulation on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body to obtain a dam break simulation result corresponding to the target monitoring area; according to the elevation data before forming the dam body and the elevation data after forming the dam body, carrying out risk level evaluation on the target monitoring area to obtain a barrier lake risk level corresponding to the target monitoring area;
performing dam deformation monitoring on the target monitoring area according to the InSAR data to obtain a dam deformation monitoring result corresponding to the target monitoring area;
And carrying out dam break early warning on the target monitoring area based on the dam break simulation result, the dam break risk level and the dam body deformation monitoring result.
In one embodiment, constructing dam formation post-elevation data corresponding to the target monitoring area based on the unmanned aerial vehicle data includes:
performing track and coordinate calculation on the point cloud data in the unmanned aerial vehicle data to obtain standard point cloud data;
removing noise points in the standard point cloud data to obtain target point cloud data;
and based on the target point cloud data, performing data embedding on the high and steep slope points in the target monitoring area to reconstruct elevation data after forming the dam body corresponding to the target monitoring area.
In one embodiment, the multi-source data set further comprises ground-based measurement data; performing dam break simulation on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body to obtain a dam break simulation result corresponding to the target monitoring area, wherein the dam break simulation result comprises the following steps:
respectively determining the flood peak flow, the final average width of the breach and the residual dam height after dam break of the barrier lake according to the elevation data before forming the dam, the elevation data after forming the dam and the ground foundation measurement data corresponding to the target monitoring area;
And performing dam break simulation on the target monitoring area based on the flood peak flow, the final average width of the breach and the residual dam height to obtain a dam break simulation result corresponding to the target monitoring area.
In one embodiment, the multi-source data set further comprises meteorological data; according to the elevation data before forming the dam body and the elevation data after forming the dam body, carrying out risk level evaluation on the target monitoring area to obtain the barrier lake risk level corresponding to the target monitoring area, wherein the method comprises the following steps:
determining target lake inflow corresponding to the target monitoring area according to the ground foundation measurement data, the meteorological data and the dam body formation elevation data;
determining the upstream water inflow corresponding to the target monitoring area based on the target lake inflow; determining the dam height and the river length of a barrier lake reservoir corresponding to the target monitoring area according to the elevation data after the formation of the dam;
respectively determining the upstream water inflow, the barrier lake reservoir capacity, the dam height and the danger grade score of the cis river length;
and weighting the risk grade scores to obtain target risk grade scores, and determining barrier lake risk grades matched with the target risk grade scores based on a preset threshold.
In one embodiment, determining the target lake inflow corresponding to the target monitoring area according to the ground foundation measurement data, the meteorological data and the dam formation front elevation data comprises:
determining initial lake inflow corresponding to the target monitoring area according to the ground foundation measurement data and the dam body formation front elevation data through an SWAT model;
determining a corrected runoff coefficient through the HEC-HMS model;
and correcting the initial lake inflow by using the corrected runoff coefficient to obtain the target lake inflow corresponding to the target monitoring area.
In one embodiment, performing dam deformation monitoring on the target monitoring area according to the InSAR data to obtain a dam deformation monitoring result corresponding to the target monitoring area, including:
determining position information of a barrier lake dam body in the target monitoring area based on the InSAR data through an SBAS-InSAR algorithm;
determining a first deformation rate of landslide movement at the barrier lake dam body along the radar sight direction, and converting the first deformation rate along the radar sight direction into a second deformation rate along the gradient direction and a second deformation rate along the vertical direction respectively;
Determining a ground surface displacement monitoring point according to the position information of the barrier lake dam body and the second deformation rate so as to acquire GNSS data at the ground surface displacement monitoring point;
and fusing the GNSS data and the InSAR data to monitor the deformation of the dam body of the target monitoring area based on the fused data, and obtaining a dam body deformation monitoring result corresponding to the target monitoring area.
In one embodiment, the method further comprises:
and generating a three-dimensional model corresponding to the target monitoring area based on the dam break simulation result, the barrier lake danger level and the dam body deformation monitoring result so as to visualize the target monitoring area through the three-dimensional model.
In a second aspect, an embodiment of the present invention further provides a dam break early warning device of a barrier lake, including:
the data acquisition module is used for acquiring a multi-source data set corresponding to the target monitoring area; the multi-source data set at least comprises drainage basin elevation data, unmanned aerial vehicle data and InSAR data before dam formation;
the elevation data construction module is used for constructing elevation data after forming the dam body corresponding to the target monitoring area based on the unmanned aerial vehicle data;
The simulation evaluation module is used for carrying out dam break simulation on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body to obtain a dam break simulation result corresponding to the target monitoring area; according to the elevation data before forming the dam body and the elevation data after forming the dam body, carrying out risk level evaluation on the target monitoring area to obtain a barrier lake risk level corresponding to the target monitoring area;
the deformation monitoring module is used for monitoring the deformation of the dam body of the target monitoring area according to the InSAR data to obtain a dam body deformation monitoring result corresponding to the target monitoring area;
and the dam break early warning module is used for carrying out dam break early warning on the target monitoring area based on the dam break simulation result, the dam break risk level and the dam body deformation monitoring result.
In a third aspect, an embodiment of the present invention further provides an electronic device comprising a processor and a memory storing computer-executable instructions executable by the processor to implement the method of any one of the first aspects.
In a fourth aspect, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions which, when invoked and executed by a processor, cause the processor to implement the method of any one of the first aspects.
The embodiment of the invention provides a dam break early warning method, a dam break early warning device, electronic equipment and a readable storage medium for a barrier lake, wherein a multisource data set corresponding to a target monitoring area is firstly obtained; the multi-source data set at least comprises drainage basin elevation data, unmanned aerial vehicle data and InSAR data before dam formation; then, based on unmanned aerial vehicle data, constructing dam body formed elevation data corresponding to the target monitoring area; performing dam break simulation on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body to obtain a dam break simulation result corresponding to the target monitoring area; according to the elevation data before forming the dam body and the elevation data after forming the dam body, carrying out risk grade assessment on the target monitoring area to obtain a barrier lake risk grade corresponding to the target monitoring area; meanwhile, dam deformation monitoring is carried out on the target monitoring area according to the InSAR data, and a dam deformation monitoring result corresponding to the target monitoring area is obtained; and finally, dam break early warning is carried out on the target monitoring area based on the dam break simulation result, the dam break risk level and the dam deformation monitoring result. The method mainly uses unmanned plane data to reconstruct high-precision dam body formed elevation data, combines the existing drainage basin elevation data to realize accurate estimation of the dam body of the barrier lake, monitors the characteristics of high precision, high resolution, flexibility and effectiveness through the unmanned plane, is easy to deploy when disasters occur, respectively determines a dam break simulation result, a barrier lake danger level and a dam body deformation monitoring result on the basis, predicts and early warns the dam break risk of the barrier lake with the result, and therefore, the effect of early warning the dam break risk of the barrier lake is remarkably improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a dam break early warning method of a barrier lake according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of another dam break early warning method of a barrier lake according to an embodiment of the present invention;
Fig. 3 is a schematic structural diagram of a dam break early warning device of a barrier lake according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described in conjunction with the embodiments, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, the existing dam break early warning method of the barrier lake is poor in early warning effect, and based on the method, the device, the electronic equipment and the readable storage medium for the dam break early warning method of the barrier lake are provided, so that the effect of early warning the risk of dam break of the barrier lake can be remarkably improved.
For the convenience of understanding the present embodiment, first, a method for early warning of dam break of a barrier lake disclosed in the present embodiment will be described in detail, referring to a schematic flow chart of the method for early warning of dam break of a barrier lake shown in fig. 1, the method mainly includes the following steps S102 to S110:
Step S102, a multi-source data set corresponding to a target monitoring area is obtained.
The target monitoring area can be a barrier lake generation position; the multi-source data set at least comprises river basin elevation (DEM) data, unmanned aerial vehicle data and InSAR (synthetic aperture radar) data before dam formation, and can also comprise ground base measurement data, meteorological data, GNSS (global navigation satellite system) data and the like.
In one embodiment, according to the position of the barrier lake, the area of the river basin is defined, and ground base measurement data such as land type data, soil type data, hydrological data, gradient data, elevation data and the like are defined, so that multi-stage hyperspectral remote sensing data (such as wind three D, high score 5B) and radar satellite image data (such as whistle one and high score three) before and after the barrier lake is formed, wherein the multi-stage hyperspectral remote sensing data is GNSS data, and the radar satellite image data is InSAR data.
Further, after the closed drainage basin area is defined in the target monitoring area, a database corresponding to the closed drainage basin area can be established, and ground basic measurement data corresponding to the target monitoring area and the like are collected in the database.
Step S104, constructing dam body elevation data corresponding to the target monitoring area based on the unmanned aerial vehicle data.
In one embodiment, track and coordinate calculation can be performed on LiDAR point cloud data in unmanned aerial vehicle data to generate standard point cloud, noise points are removed, high-precision data embedding is performed on high-steep slope points of a barrier lake region by combining DEM data, and high-precision DEM data around the barrier lake, namely dam body forming elevation data, are reconstructed.
Step S106, dam break simulation is carried out on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body, and a dam break simulation result corresponding to the target monitoring area is obtained; and evaluating the risk level of the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body to obtain the risk level of the barrier lake corresponding to the target monitoring area.
In one embodiment, the geometric parameters of the dam body are calculated according to the data of the pre-forming DEM, the high-precision DEM after forming, the water body range of the barrier lake, the water level height and the like, the dam body erosion degree is additionally set, and values are taken according to factors such as the type, compactness, gravity, soil particle size and the like of a soil body. And carrying out simulation calculation on the peak flow of the dam in the dam break of the barrier lake, the final average width of the break after the break and the residual dam height after the dam break by using the parameters to obtain a dam break simulation result.
In one embodiment, the lake inflow rate may be calculated based on a SWAT model, a HEC-RAS model, etc., and the required data include digital elevation data, soil data, land use data, meteorological data, water temperature data, and the calculated lake inflow rate is corrected to obtain a barrier lake risk level based on the corrected lake inflow rate.
And S108, performing dam deformation monitoring on the target monitoring area according to the InSAR data to obtain a dam deformation monitoring result corresponding to the target monitoring area.
In one embodiment, the deformation of the dam body can be monitored by using GNSS data and InSAR data, and the GNSS data and the InSAR data are fused by using a Kriging Kalman Filter model, so that the data monitoring precision is improved.
And step S110, dam break early warning is carried out on the target monitoring area based on the dam break simulation result, the dam break risk level and the dam deformation monitoring result.
The dam break early warning device for the barrier lake provided by the embodiment of the invention is mainly characterized in that the high-precision elevation data after the formation of the dam is rebuilt by using unmanned plane data, the accurate estimation of the dam of the barrier lake is realized by combining the existing drainage basin elevation data, the monitoring by using the unmanned plane has the characteristics of high precision, high resolution, flexibility and effectiveness, the dam break simulation result, the dam break risk level and the dam deformation monitoring result are respectively determined on the basis of the characteristics of easiness in deployment when disasters happen, and the dam break risk of the barrier lake is predicted and early warned by combining the results, so that the effect of early warning the dam break risk of the barrier lake is obviously improved.
For easy understanding, the embodiment of the invention provides a specific implementation mode of a dam break early warning method of a barrier lake.
For the step S102, the preparation of the basic data of the river basin is first performed, specifically, the data related to the area range of the river basin is defined according to the position of the barrier lake, such as the land type data, the soil type data, the hydrologic data, the gradient data, the elevation data, etc., and the multi-stage hyperspectral remote sensing data (such as wind three D, high score 5B) and the radar satellite image data (such as whistle one and high score three) before and after the barrier lake is formed are obtained.
Further, the steps of demarcating the area of the closed river basin of the barrier lake and acquiring data are executed, specifically, see the following steps a1 to a3:
step a1, establishing a river grid by DEM data, which comprises the following steps:
1) And (3) extracting a water system drainage basin by using an ArcGIS hydrologic analysis module, carding tributaries and river networks, and defining the related closed drainage basin area.
2) Determining a submerged area range: the dam location and approximate profile state are determined using WNDVI to extract the dam range.
Step a2, establishing a meteorological change database in a river basin, which comprises the following steps:
1) Collecting and processing meteorological rainfall data: and after the related closed river basin area is delimited, collecting weather rainfall data of weather stations arranged in the area. And (3) meshing and dividing the defined closed drainage basin area with certain precision, and performing Kriging interpolation processing on the grid area without precipitation data.
2) Precipitation data acquisition frequency: the rainfall data is acquired in real time, and rainfall forecast data of all grids in the future 1 hour, 2 hours, even 2 days and 3 days can be acquired based on weather stations and Kriging interpolation methods in the closed basin area.
Step a3, land type data, soil type data, hydrologic data, gradient data, including:
1) The land type data may be classified into agricultural land, woodland, grassland, wet land, water area, construction land, barren land, etc. according to the actual situation of the closed watershed area.
2) The soil type data may be classified into sand soil, swamp soil, loess, white slurry soil, peat soil, etc. according to the actual condition of the closed basin area and the division scale of the soil type.
3) The hydrologic data is obtained in real time according to hydrologic stations in the closed drainage basin area.
4) The gradient data are divided into a certain gradient according to the actual condition of the closed river basin area and the grid division precision. Elevation data is 30 m30 m DEM digital elevation data.
For the foregoing step S104, the embodiment of the present invention provides an implementation manner of constructing dam post-formation elevation data corresponding to a target monitoring area based on unmanned aerial vehicle data, see the following steps b1 to b3:
And b1, performing track and coordinate calculation on point cloud data in the unmanned aerial vehicle data to obtain standard point cloud data.
In one embodiment, unmanned airborne LiDAR can be used for multi-view image/LiDAR point cloud data acquisition of the surrounding area of the barrier lake, and the main points of the aerial flight are the barrier dam and the area with landslide risk; and performing track and coordinate calculation on the acquired unmanned airborne LiDAR point cloud data to generate standard point cloud data.
Step b2, eliminating noise points in the standard point cloud data to obtain target point cloud data;
and b3, performing data embedding on the high and steep slope points in the target monitoring area based on the target point cloud data so as to reconstruct elevation data after the dam body corresponding to the target monitoring area is formed.
In one embodiment, high-precision data embedding can be performed on high-steep slope points of the barrier lake region in combination with DEM data, and high-precision DEM around the barrier lake is reconstructed.
；
Wherein: pi is the point cloud to be registered (i.e., the target point cloud data with registration); qi is the nearest point of the corresponding Pi in the reference point cloud data; n is the number of nearest neighbor point pairs; r is a 3 x 3 rotation matrix; t is a 3 x 1 translation vector.
For the foregoing step S104, the embodiment of the present invention provides an implementation manner of performing dam break simulation on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body to obtain the dam break simulation result corresponding to the target monitoring area, which can be seen in the following steps c1 to c2:
And c1, respectively determining the flood peak flow, the final average width of the breach and the residual dam height after the dam body of the barrier lake is broken corresponding to the target monitoring area according to the elevation data before the formation of the dam body, the elevation data after the formation of the dam body and the ground foundation measurement data.
In one embodiment, the geometric parameters of the dam body, including the volume of the barrier lake, are calculated according to the data of the DEM before forming the barrier lake, the high-precision DEM after forming, the water body range of the barrier lake, the water level height and the like(m 3 ) Single wide volume V of damming dam saddle r (m 3 ) Dam length->(m) internal friction angle of damming dam->Degree of damming dam height H d (m) particle diameter d corresponding to a mass fraction of 90% smaller than a certain particle diameter 90 (m) additionally setting the erosion degree of the dam body +.>The soil particle size is determined according to the type, compactness, severity and the like of the soil body.
Using these parameters to determine peak flow rate at break of barrier lakePost-ulcer of ulcerFinal average width of mouth +.>(m) residual dam height after dam break>(m) performing a simulation calculation, the calculation formula being as follows:
1) Flood peak flow calculation：
；
2) Final average width of crumple：
；
3) Residual dam height after dam break：
。
And c2, dam break simulation is carried out on the target monitoring area based on the flood peak flow, the final average width of the breach and the residual dam height, and a dam break simulation result corresponding to the target monitoring area is obtained.
For the foregoing step S104, the embodiment of the present invention further provides an implementation manner of performing risk level assessment on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body to obtain the risk level of the barrier lake corresponding to the target monitoring area, which can be seen in the following steps d1 to d4:
step d1, determining a target lake inflow corresponding to a target monitoring area according to ground foundation measurement data, meteorological data and dam formation elevation data, wherein the method specifically comprises the following steps d1-1 to d1-3:
and d1-1, determining initial lake inflow corresponding to the target monitoring area according to ground foundation measurement data and dam body formation elevation data through the SWAT model. In one embodiment, the initial lake inflow corresponding to the target monitoring area may be determined as follows:
1) Calculating soil water: water quantity SW flowing out from saturated zone of soil ly,excess (mm); saturated Water conductivity of soil layer K sat (mm/h); total porosity of soil d The method comprises the steps of carrying out a first treatment on the surface of the Slope length L hill (m); slope drop slp, carry-in calculation of soil water Q lat ：
。
2) Calculating the vapor emission: latent heat of vaporization lambda (MJ/kg), rate of vaporization T t (mm/d), atmospheric pressure P (kPa), scale factor K 1 Temperature and saturated water vapor pressure slope fating, net radiation quantity H net (MJ/(m 2 d) Density ρ of air) air (kg/m 3 ) Saturated water vapor pressureSteam pressure e z Temperature count constant ϒ (Pa/DEGC), vegetation canopy impedance r c (s/m) air layer dispersion resistance r a (s/m), carried over into Penman-Monteth method:
。
3) Calculating underground water: base flow Q entering main river channel on ith day gw (mm/H 2 O) shallow groundwater hydraulic conductivity K sat Distance L from boundary of groundwater river to main river gw (m) carrying out simulation by taking the formula:
。
4) Calculating loss: adding the soil water, the evapotranspiration water yield and the groundwater yield, and calculating the surface runoff loss:
。
5) Calculating the daily flow rate of the barrier lake:
；
wherein the method comprises the steps ofPrecipitation (mm) on day i.
And d1-2, determining a corrected runoff coefficient through the HEC-HMS model. In one embodiment, when the flow rate Q is to be corrected, the set of runoff coefficients is corrected(/>，/>，…，/>) Wherein->The same proportion correction is carried out to obtain a corrected runoff coefficient set +.>(/>，/>，…，/>)。
Specifically, the main process of calculating the barrier lake water level and correcting the flow rate Q of the lake by the HEC-HMS model is as follows:
1) Calculating potential infiltration amount: the empirical value CN of the application site type (CN value lookup table listed in relevant manual can be used according to the topography condition of the barrier lake region) is carried into calculation, and the potential infiltration amount S is calculated:
。
2) Calculating rainfall loss: let P represent rainfall (mm), S be the potential infiltration (mm) before radial flow is generated, then the radial flow is:
。
and d1-3, correcting the initial lake inflow by using the corrected runoff coefficient to obtain the target lake inflow corresponding to the target monitoring area. In one embodiment, the initial lake inflow may be modified as follows:
1) And (3) calculating in real time: real-time calculation of barrier lake water level using SWAT model and lake-entering flow Q；
2) Budget: using HEC-RAS model and lake-in flowReal-time budget of barrier lake Water level>；
3) When the water level H of the barrier lake needs to be corrected, correcting the flow Q of the lake to obtain Q';
4) The model sets triggering conditions in real time: model real-time calibration triggering condition depends on calculated value of barrier lake water levelAnd measured value->The relative deviation of the (2) is determined by adopting the following calculation formula, and when the relative deviation is more than or equal to 5%, the triggering rate is determined under the condition that:
。
step d2, determining the upstream water inflow corresponding to the target monitoring area based on the target lake inflow; and determining the dam volume, the dam height and the river length of the barrier lake corresponding to the target monitoring area according to the elevation data after the dam is formed.
In one embodiment, the dam volume, dam height H, and river length L may be calculated from the high-precision DEM data, and the upstream inflow amount is calculated from the inflow amount Q, and after logarithmic and normalization processing, the dam risk assessment is performed using the dam risk classification index specified in the "dam risk classification and Emergency treatment Specification" (SL/T450-2021), such as the one shown in Table 1:
TABLE 1
And d3, respectively determining the upstream water inflow, the dam stock volume, the dam height and the danger grade scores of the river length. In one embodiment, the upstream water supply, dam stock volume, dam height, and risk level score for a river length may be determined according to Table 1 above.
And d4, weighting the risk grade scores to obtain target risk grade scores, and determining barrier lake risk grades matched with the target risk grade scores based on a preset threshold.
In one embodiment, the comprehensive discrimination formula is as follows:
；
wherein A is the score of comprehensive discrimination, a 1 、a 2 、a 3 、a 4 The weight values corresponding to the 4 indexes can be all 0.25, and can be properly adjusted according to the influence degree of the 4 indexes, but the sum is 1;
in one example, A 1 、A 2 、A 3 、A 4 The scores corresponding to the risk levels of the 4 indexes are respectively assigned as 4, 3, 2 and 1, and the extremely high risk, the medium risk and the low risk are respectively assigned.
In one example, the damming body is extremely dangerous when A is greater than or equal to 3.0, is highly dangerous when A is greater than or equal to 2.25 and less than or equal to 3.0, is moderately dangerous when A is greater than or equal to 1.5 and less than or equal to 2.25, and is low dangerous when A is less than or equal to 1.5.
Specifically, barrier lakes are classified according to the prediction result according to "low risk", "medium risk", "high risk" and "extremely high risk".
For the foregoing step S106, the embodiment of the present invention further provides an implementation manner of performing dam deformation monitoring on the target monitoring area according to the InSAR data to obtain a dam deformation monitoring result corresponding to the target monitoring area, which specifically refers to the following steps e1 to e4:
and e1, determining the position information of the barrier lake dam body in the target monitoring area based on InSAR data through an SBAS-InSAR algorithm.
In one embodiment, firstly, monitoring deformation of an SBAS-InSAR barrier lake dam body; then, carrying out interference pattern processing, track refining and re-flattening, atmosphere correction and obtaining radar image data according to the pixel points (x, r) (x is azimuth coordinate, r is distance coordinate) at t A And t B Phase phi (t) of two-time image generation A X, r) and phi (t) B The interference phase delta phi j (x, r) at the pixel point (x, r) can be obtained, and the deformation maximum position can be determined by acquiring the topographic deformation quantity in a long time.
In addition, in the process of monitoring the deformation of the SBAS-InSAR barrier lake dam body, the position information of the barrier lake dam body in the target monitoring area can be obtained.
And e2, determining a first deformation rate of landslide movement at the barrier lake dam body along the radar sight line direction, and converting the first deformation rate along the radar sight line direction into a second deformation rate along the gradient direction and a second deformation rate along the vertical direction respectively.
In one embodiment, monitoring of the deformation rate of landslide around the barrier lake may be performed, in particular: assuming landslide motion along unit vectorThe specified direction occurs, and the deformation rate of the line-of-sight direction is converted into the deformation rates of the gradient direction and the vertical direction by adopting the following formula:
(A) Calculating deformation rate V along gradient direction s ：
V s =/cosβ；
Wherein, the liquid crystal display device comprises a liquid crystal display device,cos β is a cos function of the included angle β of the view slope, which is the deformation rate along the radar line of sight.
(B) Calculating deformation rate in vertical direction：
Wherein:is an included angle between the azimuth direction and the north direction; />Is the azimuth direction and the sight direction; />Is the azimuth angle of landslide; />Is the angle of incidence.
And e3, determining the earth surface displacement monitoring point according to the position information of the barrier lake dam body and the second deformation rate so as to acquire GNSS data at the earth surface displacement monitoring point.
In one embodiment, a GNSS monitoring arrangement is performed, in particular: and arranging ground surface displacement monitoring points at the position with the maximum speed of the barrier lake and surrounding landslide according to the SBAS-InSAR monitoring, acquiring deformation data in a monitoring period, establishing a long-time-sequence deformation monitoring database, supplementing data of a missing time period of a remote sensing image and monitoring the high-risk barrier lake in real time.
And e4, fusing the GNSS data and the InSAR data to monitor the deformation of the dam body in the target monitoring area based on the fused data, and obtaining a dam body deformation monitoring result corresponding to the target monitoring area.
In one embodiment, the GNSS and InSAR data may be fused to improve the InSAR monitoring accuracy. Specific: and fusing GNSS and InSAR deformation data by using a Kriging Kalman Filter model, improving data monitoring precision, and fusing the data according to the following formula:
(A) Selecting a GNSS reference station to convert the InSAR relative deformation into absolute deformation;
(B) The state quantity a (t) is first calculated, and the equation is as follows:
；/>
wherein:is a state transition matrix; />And t is a state vector, which is a systematic error.
(C) Finally obtaining the observed value of GNSS or InSAR：
H(s)a(t)=/>；
Wherein: h(s) is the spatial field; a (t) is a state quantity;、/>spatial fields of GNSS and InSAR, respectively; />、/>The observed errors of GNSS and InSAR, respectively.
For the foregoing step S108, the embodiment of the present invention further provides an implementation manner for performing dam break early warning on the target monitoring area based on the dam break simulation result, the dam break risk level and the dam deformation monitoring result, and specifically: unmanned aerial vehicle monitoring is continuously carried out on a barrier lake, important information such as a high-precision DEM (digital elevation model), a water body range, a water level and the like is updated, lake entering flow calculation, dam monitoring and evaluation, dam break simulation calculation and the like are carried out by utilizing the model in combination with data such as an actual water level meter measured value and a drainage basin rainfall forecast, dam break early warning information is issued on the barrier lake, and level early warning is carried out on the barrier lake, wherein the dam break early warning information comprises a dangerous level, a rate of reaching a warning water level and the residual time of reaching the warning water level.
Further, the embodiment of the invention also provides an implementation mode for visualizing the target monitoring area, which can generate a three-dimensional model corresponding to the target monitoring area based on the dam break simulation result, the barrier lake danger level and the dam deformation monitoring result so as to visualize the target monitoring area through the three-dimensional model. Specific: based on the information obtained in the steps, dynamic simulation and three-dimensional visual presentation are carried out on the area and the water level of the barrier lake region by utilizing digital twin drainage basin visual tools. According to the contents such as the data structure, the data volume size and the geometric characteristics of the barrier lake object, the display precision is determined, the algorithm technology is optimized, the lake area and the water level are displayed in a split precision mode, and the smooth scheduling of the barrier lake water area and water level change information, the visual roaming of the three-dimensional scene and the high-fidelity scene rendering are realized. The visualization tool mainly comprises a light-weight tool, a data interface tool, a model integration tool, a three-dimensional interaction tool, a three-dimensional simulation tool and the like.
In summary, the dam break early warning method of the barrier lake provided by the embodiment of the invention has at least the following characteristics:
(1) The embodiment of the invention mainly reconstructs the high-precision DEM by using the unmanned aerial vehicle data, and combines the existing drainage basin high-precision DEM data to realize accurate estimation of the barrier lake dam body. The unmanned aerial vehicle monitoring has the characteristics of high precision, high resolution, flexibility and effectiveness, and is easy to deploy when disasters occur.
(2) Based on high-precision elevation data, the dam volume, the lake entering flow calculation, the dam break simulation analysis and other calculations are carried out by combining a related model, and the current situation of the barrier lake and the multi-scene simulation can be visually displayed through visual three-dimensional presentation, so that the prediction and early warning of the dam break risk of the barrier lake are realized.
(3) And the deformation of the dam body is monitored by using GNSS and InSAR, and the deformation data of the GNSS and the InSAR are fused by using a Kriging Kalman Filter model, so that the data monitoring precision is improved.
For easy understanding, the embodiment of the present invention further provides another implementation manner of a dam-break early warning method of a barrier lake, referring to a flow chart of another dam-break early warning method of a barrier lake shown in fig. 2, including: (1) Constructing a high-precision DEM (i.e. dam formation post elevation data) by using unmanned plane data, performing lake-entering flow calculation based on SWAT and other models on the basis of ground basic measurement data, historical DEM data (i.e. dam formation pre elevation data), meteorological data and the high-precision DEM (i.e. dam formation post elevation data), and further evaluating barrier lake risk level by combining the high-precision DEM (i.e. dam formation post elevation data); (2) Constructing a high-precision DEM (namely, elevation data after forming a dam body) by using unmanned aerial vehicle data, and performing dam break process simulation on the basis; (3) Performing dam deformation monitoring according to the radar data and the GNSS data; (4) And forecasting, early warning and visual display are carried out based on dam break process simulation and dam body deformation monitoring of the barrier lake danger level.
The embodiment of the invention realizes accurate estimation of the dam body of the barrier lake by reconstructing the high-precision DEM (namely, the elevation data after the formation of the dam body) with unmanned aerial vehicle data based on the high-precision DEM (namely, the elevation data before the formation of the dam body) of the river basin and other data. According to the embodiment of the invention, the deformation of the dam body is monitored by using the GNSS and the InSAR, the deformation data of the GNSS and the InSAR are fused by using the Kriging Kalman Filter model, and the data monitoring precision is improved. According to the embodiment of the invention, based on high-precision DEM data, the calculation of dam volume, lake-entering flow, dam break simulation analysis and the like are carried out by combining the related model, and the current situation of the barrier lake and multi-scene simulation can be intuitively displayed through visual three-dimensional presentation, so that the prediction and early warning of the dam break risk of the barrier lake are realized.
On the basis of the foregoing embodiment, the embodiment of the present invention provides a dam-break early warning device for a barrier lake, referring to a schematic structural diagram of the dam-break early warning device for a barrier lake shown in fig. 3, the device mainly includes the following parts:
the data acquisition module 302 is configured to acquire a multi-source data set corresponding to the target monitoring area; the multi-source data set at least comprises drainage basin elevation data, unmanned aerial vehicle data and InSAR data before dam formation;
The elevation data construction module 304 is configured to construct elevation data after forming a dam corresponding to the target monitoring area based on the unmanned aerial vehicle data;
the simulation evaluation module 306 is configured to perform dam break simulation on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body, so as to obtain a dam break simulation result corresponding to the target monitoring area; according to the elevation data before forming the dam body and the elevation data after forming the dam body, carrying out risk grade assessment on the target monitoring area to obtain a barrier lake risk grade corresponding to the target monitoring area;
the deformation monitoring module 308 is configured to monitor the deformation of the dam body in the target monitoring area according to the InSAR data, so as to obtain a dam body deformation monitoring result corresponding to the target monitoring area;
and the dam break early warning module 310 is used for carrying out dam break early warning on the target monitoring area based on the dam break simulation result, the dam break risk level and the dam deformation monitoring result.
The dam break early warning device for the barrier lake provided by the embodiment of the invention is mainly characterized in that the high-precision elevation data after the formation of the dam is rebuilt by using unmanned plane data, the accurate estimation of the dam of the barrier lake is realized by combining the existing drainage basin elevation data, the monitoring by using the unmanned plane has the characteristics of high precision, high resolution, flexibility and effectiveness, the dam break simulation result, the dam break risk level and the dam deformation monitoring result are respectively determined on the basis of the characteristics of easiness in deployment when disasters happen, and the dam break risk of the barrier lake is predicted and early warned by combining the results, so that the effect of early warning the dam break risk of the barrier lake is obviously improved.
In one embodiment, elevation data construction module 304 is further configured to:
performing track and coordinate calculation on point cloud data in the unmanned aerial vehicle data to obtain standard point cloud data;
removing noise points in the standard point cloud data to obtain target point cloud data;
and based on the cloud data of the target point, performing data embedding on the high and steep slope points in the target monitoring area so as to reconstruct elevation data after the dam body corresponding to the target monitoring area is formed.
In one embodiment, the multi-source data set further comprises ground-based measurement data; the simulation evaluation module 306 is also configured to:
respectively determining the flood peak flow, the final average width of the breach and the residual dam height after dam break of the barrier lake according to the elevation data before forming the dam, the elevation data after forming the dam and the ground foundation measurement data corresponding to the target monitoring area;
and carrying out dam break simulation on the target monitoring area based on the flood peak flow, the final average width of the breach and the residual dam height, and obtaining a dam break simulation result corresponding to the target monitoring area.
In one embodiment, the multi-source data set further comprises meteorological data; the simulation evaluation module 306 is also configured to:
determining target lake inflow corresponding to a target monitoring area according to ground foundation measurement data, meteorological data and dam body formation elevation data;
Determining the upstream water inflow corresponding to the target monitoring area based on the target lake inflow; determining the dam volume, dam height and river length of the barrier lake corresponding to the target monitoring area according to the elevation data after the formation of the dam;
respectively determining the upstream water inflow, the dam volume of the barrier lake, the dam height and the danger grade score of the river length;
and weighting the risk grade scores to obtain target risk grade scores, and determining barrier lake risk grades matched with the target risk grade scores based on a preset threshold.
In one embodiment, the simulation evaluation module 306 is further configured to:
determining initial lake inflow corresponding to a target monitoring area according to ground foundation measurement data and dam body formation elevation data through an SWAT model;
determining a corrected runoff coefficient through the HEC-HMS model;
and correcting the initial lake inflow flow by using the corrected runoff coefficient to obtain the target lake inflow flow corresponding to the target monitoring area.
In one embodiment, the deformation monitoring module 308 is further configured to:
determining position information of a barrier lake dam body in a target monitoring area based on InSAR data by an SBAS-InSAR algorithm;
determining a first deformation rate of landslide movement at a barrier lake dam body along the radar sight direction, and converting the first deformation rate along the radar sight direction into a second deformation rate along the gradient direction and a second deformation rate along the vertical direction respectively;
Determining earth surface displacement monitoring points according to the position information of the barrier lake dam body and the second deformation rate so as to acquire GNSS data at the earth surface displacement monitoring points;
and fusing the GNSS data and the InSAR data to monitor the deformation of the dam body in the target monitoring area based on the fused data, and obtaining a dam body deformation monitoring result corresponding to the target monitoring area.
In one embodiment, the method further comprises a visualization module for:
based on the dam break simulation result, the dam barrier lake danger level and the dam body deformation monitoring result, generating a three-dimensional model corresponding to the target monitoring area, and visualizing the target monitoring area through the three-dimensional model.
The device provided by the embodiment of the present invention has the same implementation principle and technical effects as those of the foregoing method embodiment, and for the sake of brevity, reference may be made to the corresponding content in the foregoing method embodiment where the device embodiment is not mentioned.
The embodiment of the invention provides electronic equipment, which comprises a processor and a storage device; the storage means has stored thereon a computer program which, when executed by the processor, performs the method of any of the embodiments described above.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where the electronic device 100 includes: a processor 40, a memory 41, a bus 42 and a communication interface 43, the processor 40, the communication interface 43 and the memory 41 being connected by the bus 42; the processor 40 is arranged to execute executable modules, such as computer programs, stored in the memory 41.
The memory 41 may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and the at least one other network element is achieved via at least one communication interface 43 (which may be wired or wireless), which may use the internet, a wide area network, a local network, a metropolitan area network, etc.
Bus 42 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 4, but not only one bus or type of bus.
The memory 41 is configured to store a program, and the processor 40 executes the program after receiving an execution instruction, and the method executed by the apparatus for flow defining disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 40 or implemented by the processor 40.
The processor 40 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in processor 40. The processor 40 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a digital signal processor (Digital Signal Processing, DSP for short), application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory 41 and the processor 40 reads the information in the memory 41 and in combination with its hardware performs the steps of the method described above.
The computer program product of the readable storage medium provided by the embodiment of the present invention includes a computer readable storage medium storing a program code, where the program code includes instructions for executing the method described in the foregoing method embodiment, and the specific implementation may refer to the foregoing method embodiment and will not be described herein.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. The dam break early warning method for the barrier lake is characterized by comprising the following steps of:
acquiring a multi-source data set corresponding to a target monitoring area; the multi-source data set at least comprises drainage basin elevation data, unmanned aerial vehicle data and InSAR data before dam formation;
Constructing dam body formed elevation data corresponding to the target monitoring area based on the unmanned aerial vehicle data;
performing dam break simulation on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body to obtain a dam break simulation result corresponding to the target monitoring area; according to the elevation data before forming the dam body and the elevation data after forming the dam body, carrying out risk level evaluation on the target monitoring area to obtain a barrier lake risk level corresponding to the target monitoring area;
performing dam deformation monitoring on the target monitoring area according to the InSAR data to obtain a dam deformation monitoring result corresponding to the target monitoring area;
and carrying out dam break early warning on the target monitoring area based on the dam break simulation result, the dam break risk level and the dam body deformation monitoring result.
2. The dam break early warning method of claim 1, wherein constructing dam formation post-elevation data corresponding to the target monitoring area based on the unmanned aerial vehicle data comprises:
performing track and coordinate calculation on the point cloud data in the unmanned aerial vehicle data to obtain standard point cloud data;
Removing noise points in the standard point cloud data to obtain target point cloud data;
and based on the target point cloud data, performing data embedding on the high and steep slope points in the target monitoring area to reconstruct elevation data after forming the dam body corresponding to the target monitoring area.
3. A barrier lake dam break early warning method according to claim 1, wherein the multi-source data set further comprises ground base measurement data; performing dam break simulation on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body to obtain a dam break simulation result corresponding to the target monitoring area, wherein the dam break simulation result comprises the following steps:
respectively determining the flood peak flow, the final average width of the breach and the residual dam height after dam break of the barrier lake according to the elevation data before forming the dam, the elevation data after forming the dam and the ground foundation measurement data corresponding to the target monitoring area;
and performing dam break simulation on the target monitoring area based on the flood peak flow, the final average width of the breach and the residual dam height to obtain a dam break simulation result corresponding to the target monitoring area.
4. A barrier lake dam break early warning method according to claim 3, wherein the multi-source data set further comprises meteorological data; according to the elevation data before forming the dam body and the elevation data after forming the dam body, carrying out risk level evaluation on the target monitoring area to obtain the barrier lake risk level corresponding to the target monitoring area, wherein the method comprises the following steps:
Determining target lake inflow corresponding to the target monitoring area according to the ground foundation measurement data, the meteorological data and the dam body formation elevation data;
determining the upstream water inflow corresponding to the target monitoring area based on the target lake inflow; determining the dam height and the river length of a barrier lake reservoir corresponding to the target monitoring area according to the elevation data after the formation of the dam;
respectively determining the upstream water inflow, the barrier lake reservoir capacity, the dam height and the danger grade score of the cis river length;
and weighting the risk grade scores to obtain target risk grade scores, and determining barrier lake risk grades matched with the target risk grade scores based on a preset threshold.
5. The method of claim 4, wherein determining the target lake intake flow corresponding to the target monitoring area based on the ground base measurement data, the meteorological data, and the dam formation front elevation data, comprises:
determining initial lake inflow corresponding to the target monitoring area according to the ground foundation measurement data and the dam body formation front elevation data through an SWAT model;
Determining a corrected runoff coefficient through the HEC-HMS model;
and correcting the initial lake inflow by using the corrected runoff coefficient to obtain the target lake inflow corresponding to the target monitoring area.
6. The dam break early warning method of claim 1, wherein the dam deformation monitoring is performed on the target monitoring area according to the InSAR data to obtain a dam deformation monitoring result corresponding to the target monitoring area, and the dam break early warning method comprises the following steps:
determining position information of a barrier lake dam body in the target monitoring area based on the InSAR data through an SBAS-InSAR algorithm;
determining a first deformation rate of landslide movement at the barrier lake dam body along the radar sight direction, and converting the first deformation rate along the radar sight direction into a second deformation rate along the gradient direction and a second deformation rate along the vertical direction respectively;
determining a ground surface displacement monitoring point according to the position information of the barrier lake dam body and the second deformation rate so as to acquire GNSS data at the ground surface displacement monitoring point;
and fusing the GNSS data and the InSAR data to monitor the deformation of the dam body of the target monitoring area based on the fused data, and obtaining a dam body deformation monitoring result corresponding to the target monitoring area.
7. A method of pre-warning a dam break in a barrier lake according to claim 1, further comprising:
and generating a three-dimensional model corresponding to the target monitoring area based on the dam break simulation result, the barrier lake danger level and the dam body deformation monitoring result so as to visualize the target monitoring area through the three-dimensional model.
8. The dam break early warning device of the barrier lake is characterized by comprising:
the data acquisition module is used for acquiring a multi-source data set corresponding to the target monitoring area; the multi-source data set at least comprises drainage basin elevation data, unmanned aerial vehicle data and InSAR data before dam formation;
the elevation data construction module is used for constructing elevation data after forming the dam body corresponding to the target monitoring area based on the unmanned aerial vehicle data;
the simulation evaluation module is used for carrying out dam break simulation on the target monitoring area according to the elevation data before forming the dam body and the elevation data after forming the dam body to obtain a dam break simulation result corresponding to the target monitoring area; according to the elevation data before forming the dam body and the elevation data after forming the dam body, carrying out risk level evaluation on the target monitoring area to obtain a barrier lake risk level corresponding to the target monitoring area;
The deformation monitoring module is used for monitoring the deformation of the dam body of the target monitoring area according to the InSAR data to obtain a dam body deformation monitoring result corresponding to the target monitoring area;
and the dam break early warning module is used for carrying out dam break early warning on the target monitoring area based on the dam break simulation result, the dam break risk level and the dam body deformation monitoring result.
9. An electronic device comprising a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the method of any one of claims 1 to 7.
10. A computer readable storage medium storing computer executable instructions which, when invoked and executed by a processor, cause the processor to implement the method of any one of claims 1 to 7.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105678984A (en) * | 2015-12-30 | 2016-06-15 | 四川大学 | Burst disaster warning system establishing method for barrier lake in data-lacking-area |
| DE102016111238A1 (en) * | 2016-06-20 | 2017-12-21 | Ocean Maps GmbH | Scanning device for scanning the bottom of waters and method for generating underwater maps |
| CN111311747A (en) * | 2020-01-17 | 2020-06-19 | 中国水利水电科学研究院 | Multi-sensor barrier lake region integrated three-dimensional model rapid construction method |
| CN112378386A (en) * | 2020-10-28 | 2021-02-19 | 浙江天禹信息科技有限公司 | Unmanned aerial vehicle water conservancy hydrological flow measurement method |
| JP2021125163A (en) * | 2020-02-10 | 2021-08-30 | 三菱電機株式会社 | River flood and damage prediction device |
| CN116561529A (en) * | 2023-05-18 | 2023-08-08 | 中国电建集团成都勘测设计研究院有限公司 | Dam break-up state prediction method based on case statistics and break-up process |
| CN116625329A (en) * | 2023-07-24 | 2023-08-22 | 新兴际华(北京)智能装备技术研究院有限公司 | Method, system, electronic equipment and storage medium for determining barrier lake information |
-
2023
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Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105678984A (en) * | 2015-12-30 | 2016-06-15 | 四川大学 | Burst disaster warning system establishing method for barrier lake in data-lacking-area |
| DE102016111238A1 (en) * | 2016-06-20 | 2017-12-21 | Ocean Maps GmbH | Scanning device for scanning the bottom of waters and method for generating underwater maps |
| CN111311747A (en) * | 2020-01-17 | 2020-06-19 | 中国水利水电科学研究院 | Multi-sensor barrier lake region integrated three-dimensional model rapid construction method |
| JP2021125163A (en) * | 2020-02-10 | 2021-08-30 | 三菱電機株式会社 | River flood and damage prediction device |
| CN112378386A (en) * | 2020-10-28 | 2021-02-19 | 浙江天禹信息科技有限公司 | Unmanned aerial vehicle water conservancy hydrological flow measurement method |
| CN116561529A (en) * | 2023-05-18 | 2023-08-08 | 中国电建集团成都勘测设计研究院有限公司 | Dam break-up state prediction method based on case statistics and break-up process |
| CN116625329A (en) * | 2023-07-24 | 2023-08-22 | 新兴际华(北京)智能装备技术研究院有限公司 | Method, system, electronic equipment and storage medium for determining barrier lake information |
Non-Patent Citations (2)
| Title |
|---|
| 蔡耀军等: "堰塞湖风险评估快速检测与应急抢险技术和装备研发", 岩土工程学报, vol. 44, no. 7, pages 1 - 4 * |
| 魏迎奇;孙黎明;傅中志;吴帅峰;蔡红;: "堰塞湖多源信息及其感知技术", 人民长江, no. 04 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117744535A (en) * | 2024-01-02 | 2024-03-22 | 昆明理工大学 | Method and system for predicting debris flow peak value of loose rock soil body dam |
| CN117744535B (en) * | 2024-01-02 | 2024-05-14 | 昆明理工大学 | Method and system for predicting debris flow peak value of loose rock soil body dam |
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