A construction method of a disaster mitigation dam system for flood disaster prevention

Abstract

The application provides a construction method of a disaster mitigation dam system for flood disaster prevention, comprising the following steps: step 1, configuring a dam system foundation to a target basin based on geographic information and hydrological information of the target basin; step 2, performing risk assessment based on flood information of the target basin, analyzing possible flood paths and influence sets, and determining key areas and high-risk areas that need to be prevented from flood; step 3, screening corresponding initial ecological dam system from a dam type database based on the dam system foundation; step 4, planning and adjusting the initial ecological dam system according to the regional determination result; and step 5, monitoring the surrounding environment of the dam system after planning and adjustment based on a constructed sensing system, and performing geological disaster early warning. The method improves the disaster prevention and mitigation capability, and ensures the feasibility and practicability of dam system construction.

Description

Technical Field

[0001] This invention relates to the field of flash flood disaster prevention and control technology in small and medium-sized watersheds, and in particular to a method for constructing a disaster reduction dam system for flash flood disaster prevention and control. Background Technology

[0002] Currently, flash floods are one of the main types of mountain disasters. Data shows that the number of deaths caused by flash floods accounts for about 70% of the total number of deaths caused by floods. This indicates that flash floods have become a natural disaster that seriously threatens public safety and severely restricts local socio-economic development. Therefore, the demand for flash flood management has become increasingly strong.

[0003] Flash floods in small and medium-sized watersheds are natural disasters that occur and develop rapidly within a short period of time, typically occurring in small to medium-scale watersheds. Their characteristics include: ① Rapid onset triggered by short-duration heavy rainfall: Flash floods in small and medium-sized watersheds are often triggered by short-duration heavy rainfall, which is often concentrated within a few hours, leading to a rapid increase in water volume and the formation of large amounts of runoff. ② Rapid development and rapid receding: Due to the short-duration heavy rainfall, flash floods develop rapidly, with peak flow and velocity increasing rapidly, but they usually recede quickly as well. This makes the disaster sudden and short-lived, but it can have a serious impact on downstream areas. ③ Uneven spatial distribution: Heavy rainfall is often concentrated in localized mountainous areas, leading to uneven spatial distribution of flash floods. Even if some areas within the watershed are drought-stricken, other areas may still be threatened by floods. ④ Increased risk of geological hazards: Flash floods in small and medium-sized watersheds usually occur in mountainous areas, easily triggering geological hazards such as landslides and debris flows, thereby increasing the risk to people and property. ⑤ Smaller impact area: Compared to large-scale floods, flash floods in small and medium-sized river basins have a smaller impact area, but they often severely affect local production, livelihoods, and infrastructure. ⑥ Greater difficulty in early warning: Due to their rapid development and uneven spatial and temporal distribution, early warning of flash floods in small and medium-sized river basins is more difficult, requiring accurate meteorological forecasts and watershed hydrological monitoring data.

[0004] Mountain torrent gullies are widely distributed in my country, exhibiting significant regional differences. A single management model is insufficient to address the unique characteristics of different gullies. The management standards for mountain torrent gullies are relatively low, making them inadequate to withstand floods triggered by torrential rains, and the mechanisms for responding to floods exceeding design standards are inadequate. The established mountain torrent disaster prevention and control system has played a crucial role in flood disaster prevention work across various regions, achieving remarkable results and demonstrating significant importance.

[0005] Therefore, this invention proposes a method for constructing a disaster reduction dam system for preventing mountain torrent disasters. Summary of the Invention

[0006] This invention provides a method for constructing a disaster reduction dam system for preventing mountain torrent disasters. Through multi-level flood regulation and mitigation, combined with the application of technological means, it can effectively reduce the harm of mountain torrent disasters in small and medium-sized watersheds to human society and the ecological environment, improve disaster prevention and mitigation capabilities, and ensure the feasibility and practicality of dam system construction.

[0007] This invention provides a method for constructing a disaster reduction dam system for flood prevention, comprising:

[0008] Step 1: Based on the geographic and hydrological information of the target watershed, configure dam system foundations for the target watershed, wherein the dam system foundations are related to the areas of potential flood disaster and potential treatment areas in the target watershed;

[0009] Step 2: Conduct a risk assessment based on the flood information of the target watershed, analyze possible flood paths and impact sets, and identify key areas and high-risk areas that require flash flood prevention.

[0010] Step 3: Based on the aforementioned dam system foundation, select the corresponding initial ecological dam system from the dam type database;

[0011] Step 4: Based on the regional determination results, plan and adjust the initial ecological dam system;

[0012] Step 5: Based on the constructed sensing system, monitor the surrounding environment of the dam system after the planning adjustment, and conduct geological disaster early warning.

[0013] Preferably, the geographic information is related to the geographic location, geographic boundaries, geographic area, geographic topography, and geographic terrain of the target area;

[0014] The water information mentioned is related to rainfall data, runoff data, and water level changes.

[0015] Preferably, key areas and high-risk areas requiring flash flood prevention are identified, including:

[0016] Based on the flood information and the water information, the probability of flood occurrence in the possible flood disaster area is determined, as well as the flood path and the set of impacts of each historical flood in the corresponding possible flood disaster area.

[0017] Based on all flood paths and corresponding impact sets of the same potential flood disaster area, assess the regional vulnerability of the corresponding potential flood disaster area;

[0018] Based on the probability of flooding and regional vulnerability in areas prone to flooding, potential risk values ​​are determined.

[0019] Based on the potential risk values, all areas with possible flood hazards are ranked to identify key areas and high-risk areas requiring flash flood prevention.

[0020] Preferably, the initial ecological dam system is planned and adjusted based on the regional determination results, including:

[0021] Determine the downstream flow rate after the formation of the single dam:

[0022]

[0023] Where Q′1 is the downstream flow after setting up a single dam, Q c Q represents the outflow capacity at the base of a single dam. i ΔW is the inflow rate in front of a single dam, ΔW is the available reservoir capacity of a single dam, and Δt is the time taken to reach ΔW.

[0024] Determine the downstream flow rate Q′2 after setting up a dam system consisting of n individual dams:

[0025] Q′2=F1(t)*F2(t)*…*F n (t)

[0026] Among them, F n (t2) represents the downstream flow of the nth single dam; t represents the peak time.

[0027] Based on the downstream flow Q′1 after the formation of the single dam and the downstream flow Q′2 after the dam system, and combined with the factor conditions of each region in the regional determination results, the number and form of the mountain flood control dam system are determined, and the initial ecological dam system is planned and adjusted.

[0028] Preferably, it also includes: constructing a sensing system, specifically including:

[0029] Based on the surrounding construction conditions of the dam system after the planning adjustment, the soil information, vegetation growth information, and construction structure of each construction location point of the dam system after the planning adjustment are determined to determine the overtopping warning line.

[0030] Based on soil growth information, vegetation growth information, and dam overflow warning lines, an early warning disaster database is constructed, and a corresponding sensing system is established based on the early warning disaster database to monitor and sense the dam system after the planning adjustment.

[0031] Preferably, assessing the regional vulnerability of areas potentially susceptible to flooding includes:

[0032] Construct an impact function Y0(H1, YJ) corresponding to the area of ​​possible flood disaster, where H1 is the flood path and YJ is the set of impacts corresponding to the flood path;

[0033] Break down the effective influencing factors, ineffective influencing factors, and marginal influencing factors in the impact set under each flood path;

[0034] The marginalized influencing factors and the effective influencing factors are subjected to a first attribute similarity analysis. At the same time, the marginalized influencing factors and the ineffective influencing factors are subjected to a second attribute similarity analysis. The attribute similarity analysis refers to a similarity comparison based on the code attribute description of each influencing factor.

[0035] Based on the similarity analysis results, a partitioning coefficient is assigned to each marginal influencing factor;

[0036] When the division coefficient is within the preset division range corresponding to the effective influencing factor, the corresponding marginal influencing factor is classified as an effective influencing factor;

[0037] When the division coefficient is within the preset division range corresponding to the invalid influencing factor, the corresponding marginal influencing factor is classified as an invalid influencing factor;

[0038] When the partitioning coefficient is involved between valid and invalid, a dynamic partitioning probability is set for the corresponding marginal influencing factor;

[0039] According to the dynamic partitioning probability, the corresponding marginal influencing factors are dynamically partitioned, and the influence function Y0 is partitioned based on the last existing effective influencing factor to obtain the first vulnerability analysis function Y1(H1, Y2), where Y2 represents the last existing effective influencing factor;

[0040] The paths are divided according to the path flow direction information of each flood path in the corresponding potentially flood-prone area, resulting in several path combinations;

[0041] For each path combination, all influence sets involved are subjected to set overlap processing to obtain fully overlapping factors, first half-overlapping factors with a preset overlap number or greater, and second half-overlapping factors with a preset overlap number or less.

[0042] Extract the first test function from the function database that matches the fully overlapping factors and the first half overlapping factors in the corresponding combination, perform the first vulnerability test on each flood path in the corresponding combination, and construct the first vector;

[0043] Extract a second test function from the function database that matches the fully overlapping factors, the first half-overlapping factors, and the second half-overlapping factors in the corresponding combination; perform a second vulnerability test on each flood path in the corresponding combination; and construct a second vector.

[0044] Comparatively analyzing the first vector and the second vector under the same combination, determining the dependency relationship between the factors based on the same flood path, and extracting auxiliary factors consistent with the corresponding flood path from the second half-overlapping factors;

[0045] According to the fully overlapping factors, the first half-overlapping factors and the auxiliary factors of the same flood path, constructing and obtaining the second vulnerability analysis function Y2(H1, Y3) of the corresponding flood path, wherein Y3 is the fully overlapping factors, the first half-overlapping factors and the auxiliary factors under the same flood path;

[0046] Acquiring a first evaluation function matching Y1(H1, Y2) and a second evaluation function matching Y2(H1, Y3) from a function database, and respectively performing vulnerability assessment to obtain regional vulnerability of corresponding potential flood disaster areas.

[0047] Preferably, when the division coefficient is between valid and invalid, setting a dynamic division probability for the corresponding edge influencing factor, comprising:

[0048]

[0049] Wherein, u01 represents the division coefficient; u03 represents a left boundary value based on a preset division range corresponding to valid influencing factors; u02 represents a right boundary value based on a preset division range corresponding to invalid influencing factors, and u02<u03; G01 represents the dynamic division probability.

[0050] Preferably, extracting auxiliary factors consistent with the corresponding flood path from the second half-overlapping factors comprises:

[0051] Determining the vulnerability difference of the same flood path according to the comparative analysis result;

[0052] Determining the required extraction quantity of corresponding second half-overlapping factors according to the vulnerability difference;

[0053]

[0054] Wherein, N3 is the required extraction quantity corresponding to the vulnerability difference C1; Δ1 is a unit difference variable corresponding to the weak difference C1; YN is a difference threshold corresponding to the weak difference C1; Δ2 is a correlation error variable matching the corresponding Δ1; [] is a rounding symbol;

[0055] Sorting the overlapping quantity of each factor and the set weight of each factor in the second half-overlapping factors according to sorted values;

[0056]

[0057] Where R1 is the ranking value of the corresponding factor in the corresponding second half-overlap factor; cr is the number of overlaps of the corresponding factor in the corresponding second half-overlap factor; cq j02 Zn represents the weight set for the corresponding factor in the second half-overlapping factor based on the j02-th flood path, and the number of overlaps for the same factor is consistent with the number of flood paths corresponding to that factor; rq is the sum of the weights set for the corresponding factors in the second half-overlapping factor under the matched flood path; Zn represents the total number of factors existing in the second half-overlapping factor; Zq j01 The maximum weight is set for the j01st overlapping factor obtained from the corresponding second half-overlap factor;

[0058] Based on the required extraction quantity, the first N3 factors are extracted to obtain auxiliary factors. Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention can be realized and obtained by means of the structures particularly pointed out in the written description and drawings.

[0059] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0060] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0061] In the attached diagram:

[0062] Figure 1 This is a flowchart illustrating a method for constructing a disaster reduction dam system for flood prevention in an embodiment of the present invention;

[0063] Figure 2 This is a schematic diagram of the ecological dam structure in an embodiment of the present invention;

[0064] Figure 3 The disaster mitigation ecological dam in this embodiment of the invention achieves the expected flood reduction effect.

[0065] Figure 4 This refers to the expected flood reduction effect of the ecological dam system in the embodiments of the present invention;

[0066] Figure 5 This is a schematic diagram of the ecological dam system planning and layout in an embodiment of the present invention;

[0067] Figure 6 This is a blueprint for the construction of an ecological dam in a specific implementation scheme of the present invention;

[0068] Figure 7This is a distribution map of the ecological dam system in the Heihe River Basin, as shown in a specific implementation scheme of this invention. Detailed Implementation

[0069] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0070] This invention provides a method for constructing a disaster reduction dam system for flood prevention, such as... Figure 1 As shown, it includes:

[0071] Step 1: Based on the geographic and hydrological information of the target watershed, configure dam system foundations for the target watershed, wherein the dam system foundations are related to the areas of potential flood disaster and potential treatment areas in the target watershed;

[0072] Step 2: Conduct a risk assessment based on the flood information of the target watershed, analyze possible flood paths and impact sets, and identify key areas and high-risk areas that require flash flood prevention.

[0073] Step 3: Based on the aforementioned dam system foundation, select the corresponding initial ecological dam system from the dam type database;

[0074] Step 4: Based on the regional determination results, plan and adjust the initial ecological dam system;

[0075] Step 5: Based on the constructed sensing system, monitor the surrounding environment of the dam system after the planning adjustment, and conduct geological disaster early warning.

[0076] Preferably, the geographic information is related to the geographic location, geographic boundaries, geographic area, geographic topography, and geographic terrain of the target area;

[0077] The water information mentioned is related to rainfall data, runoff data, and water level changes.

[0078] Preferably, key areas and high-risk areas requiring flash flood prevention are identified, including:

[0079] Based on the flood information and the water information, the probability of flood occurrence in the possible flood disaster area is determined, as well as the flood path and the set of impacts of each historical flood in the corresponding possible flood disaster area.

[0080] Based on all flood paths and corresponding impact sets of the same potential flood disaster area, assess the regional vulnerability of the corresponding potential flood disaster area;

[0081] Based on the probability of flooding and regional vulnerability in areas prone to flooding, potential risk values ​​are determined.

[0082] Based on the potential risk values, all areas with possible flood hazards are ranked to identify key areas and high-risk areas requiring flash flood prevention.

[0083] Preferably, the initial ecological dam system is planned and adjusted based on the regional determination results, including:

[0084] Determine the downstream flow rate after the formation of the single dam:

[0085]

[0086] Where Q′1 is the downstream flow after setting up a single dam, Q c Q represents the outflow capacity at the base of a single dam. i ΔW is the inflow rate in front of a single dam, ΔW is the available reservoir capacity of a single dam, and Δt is the time taken to reach ΔW.

[0087] Determine the downstream flow rate Q′2 after setting up a dam system consisting of n individual dams:

[0088] Q′2=F1(t)*F2(t)*…*F n (t)

[0089] Among them, F n (t2) represents the downstream flow of the nth single dam; t represents the peak time.

[0090] Based on the downstream flow Q′1 after the formation of the single dam and the downstream flow Q′2 after the dam system, and combined with the factor conditions of each region in the regional determination results, the number and form of the mountain flood control dam system are determined, and the initial ecological dam system is planned and adjusted.

[0091] Preferably, it also includes: constructing a sensing system, specifically including:

[0092] Based on the surrounding construction conditions of the dam system after the planning adjustment, the soil information, vegetation growth information, and construction structure of each construction location point of the dam system after the planning adjustment are determined to determine the overtopping warning line.

[0093] Based on soil growth information, vegetation growth information, and dam overflow warning lines, an early warning disaster database is constructed, and a corresponding sensing system is established based on the early warning disaster database to monitor and sense the dam system after the planning adjustment.

[0094] Regarding step 1: the steps for calculating the peak flow rate with design frequency P using the inference formula are as follows:

[0095] ① Determine the rainstorm reduction index n and the maximum 1-hour rainfall intensity;

[0096] The rainfall reduction index n can be obtained by analyzing measured rainfall data or by looking up information in the hydrological manual of the basin area.

[0097] The maximum hourly rainfall intensity is generally calculated using the rainstorm formula based on the 24-hour design rainstorm, or it can be directly calculated from the maximum 24-hour design rainstorm distribution map of the same frequency in the rainstorm map set.

[0098] ② Determination of watershed loss parameter μ and confluence parameter m;

[0099] ③ Determine the design peak flow rate;

[0100] For step 2: Using Manning's formula, the peak flood level at the cross-section is calculated.

[0101] Since the frictional losses in unsteady flow are not significantly different from those in steady flow, the Manning formula is often used to calculate frictional losses in mountain flood calculations. The formula for mountain flood discharge is as follows:

[0102]

[0103] Where Q is the flow rate, n is the roughness coefficient, A is the cross-sectional area, R is the hydraulic radius of the cross-section, and S0 is the bottom slope at the cross-section. Both the cross-sectional areas A and R are functions of the water depth, and their functional relationships differ for different cross-sectional shapes.

[0104] For step 2: Based on DEM data, analyze the flooding extent and conduct a risk assessment:

[0105] Simulating and displaying flood inundation extent based on DEM data has become a research hotspot in the field of flood risk analysis. This paper utilizes high-precision DEM to estimate the inundation extent from the peak flood level of a small watershed, as detailed below.

[0106] First, based on the peak flood level at the cross section, extend along the cross section direction (i.e., the direction perpendicular to the channel) to both banks to find the peak flood level line at that cross section.

[0107] Within the same small watershed, take several (at least two) cross sections and linearly interpolate a water level surface from the flood peak water level lines of two adjacent cross sections.

[0108] The inundation range is obtained by subtracting the flood peak water level from the DEM data.

[0109] For step 3: For the Heihe River, a flood control ecological dam will be constructed using riprap concrete, with a dam height of 15m to 20m. A flow channel will be left at the bottom of the dam to avoid obstructing the river and affecting fish migration. When the upstream water flow does not exceed the flow capacity of the bottom channel, the water will flow through the bottom channel; when the upstream water flow exceeds the flow capacity of the bottom channel, the dam will impound the floodwater; when the impounded water level exceeds the dam crest elevation, the floodwater will be discharged through the dam crest overflow.

[0110] For step 4: Analyze areas frequently affected by flash floods and areas that may impact surrounding areas. Determine the length of the main channel of the Heihe River and the data and morphological distribution characteristics of its first-order tributaries to determine the number and location of dam systems. Based on the geographical environment, land use, and engineering construction conditions of the Heihe River basin, determine the specific number and form of dam systems. Simultaneously, during the planning of flash flood control dam systems, an environmental impact assessment is required. This includes assessing the impact of dam construction on the local ecological environment, hydrological environment, and land use, and taking corresponding measures for mitigation and restoration. Based on the above comprehensive analysis results of the Heihe River basin, a construction distribution map of the flash flood control dam system in the Heihe River basin has been developed, with the specific layout as follows: Figure 7 As shown.

[0111] In the analysis of specific implementation plans for flood reduction, the peak flow Q and peak occurrence time t of the ecological dam system for regulating mountain floods are two important hydrological elements. The specific expressions are the downstream flow after setting up a single dam and the downstream flow after setting up a dam system, as mentioned above.

[0112] Peak flow rate Q refers to the maximum flow rate during a flood event and is a crucial indicator of flood disaster risk. The peak flow rate is regulated by the flood mitigation dam system. When the upstream inflow exceeds the discharge flow rate through the culvert at the dam's base, the water level in front of the dam gradually rises. When the water level exceeds the dam crest, the floodwaters begin to overflow. During the discharge process, the flow rate gradually increases, and the peak flow rate is the point at which the flow rate reaches its maximum value.

[0113] Peak time t refers to the time required from the start of rainfall runoff to the formation of the flood with maximum flow. The peak time t can be delayed by the presence of flood control dam systems. Furthermore, the peak time t can vary during flood propagation due to factors such as river channel topography and water flow velocity.

[0114] The flood reduction benefits of disaster reduction dams and dam systems are as follows: Figure 3 and 4 As shown, the relationship between peak flow Q and peak time t can be described by the propagation speed of the flood wave. The propagation speed of the flood wave depends on factors such as river topography, water flow velocity, and the location of flood mitigation dams. In this case, there is an inverse relationship between peak flow Q and peak time t. That is, when the propagation speed of the flood wave increases, the peak time t shortens, leading to a rapid rise and fall of the floodwaters, and the peak flow Q arrives downstream earlier. Conversely, when the propagation speed of the flood wave slows down, the peak time t lengthens, and the peak flow Q arrives downstream later, resulting in a reduction in the peak flow Q. Increasing the peak time t is the flood control benefit of flood mitigation dams.

[0115] Regarding step 5: An ecological dam system will be constructed in the Heihe River basin. Sensors will be installed in front of each dam to monitor the water level. When the water level reaches a certain threshold, an early warning will be issued via SMS, gong, or other means. Sensors will also be deployed around the dam system to monitor the surrounding terrain and vegetation, providing early warnings of potential landslides, debris flows, and other geological disasters. When a potential geological disaster is detected, an early warning will be issued via SMS. An early warning system will be established around the dam system, classifying warning levels according to the severity of potential floods and geological disasters, issuing timely warnings, and guiding people to take appropriate measures based on the different warning levels, including timely evacuation if necessary. Figure 2 As shown.

[0116] In this embodiment, the determined quantity and form of dam systems with a tiered sequential order are called "series" dam systems, dam systems in adjacent tributaries are called "parallel" dam systems, and dam systems that simultaneously exhibit both series and parallel configurations are called "mixed" dam systems. Figure 5 , 6 As shown in Figures 7 and 8.

[0117] The flood control and mitigation dam system for small and medium-sized watersheds of this invention includes components such as a main dam, branch dams, and flood discharge channels. The main dam is located upstream of the small and medium-sized watershed to intercept floodwaters and form a water storage area, thereby mitigating and regulating floodwater flow. The branch dams are located downstream of the main dam upstream to further regulate peak flow and reduce flood impact. The flood discharge channels are located on the main dam and release water from the water storage area by controlling the opening and closing of the floodgates, ensuring the safety of the dam system.

[0118] This invention combines the main dam, branch dams, and spillway channels to achieve multi-level and multi-stage flood regulation and mitigation, adapting to the geographical characteristics and flood conditions of small and medium-sized river basins. Furthermore, this invention applies modern technologies such as sensor networks and remote sensing to the dam system's monitoring and early warning system, enabling real-time monitoring of flood dynamics and providing early warnings, thereby improving disaster prevention and mitigation effectiveness.

[0119] The application method of the dam system for flood prevention and mitigation in small and medium-sized watersheds of the present invention includes the following steps:

[0120] In the upper reaches of small and medium-sized river basins, select an appropriate location to construct a main dam and form a water storage area.

[0121] A sensor network is installed within the main dam's reservoir area to monitor rainfall and water level changes.

[0122] Based on monitoring data, the opening and closing of flood discharge channels should be controlled reasonably to release an appropriate amount of water and prevent dam failure.

[0123] A secondary dam is set up behind the main dam to further regulate the peak flow.

[0124] By using modern remote sensing technology, we can monitor the topography and vegetation around the dam system and provide early warnings of potential geological disasters such as landslides and debris flows.

[0125] Establish an early warning system around the dam system to issue timely flood warnings and guide people to take countermeasures.

[0126] The beneficial effects of the above technical solution are: the flood prevention and mitigation dam system of the present invention, through multi-level flood regulation and slow release, combined with the application of scientific and technological means, can effectively reduce the harm of floods in small and medium-sized watersheds to human society and the ecological environment, improve disaster prevention and mitigation capabilities, and ensure the feasibility and practicality of dam system construction.

[0127] This invention provides a method for constructing a disaster reduction dam system for flash flood disaster prevention, which assesses the regional vulnerability of areas prone to flooding, including:

[0128] Construct an impact function Y0(H1, YJ) corresponding to the area of ​​possible flood disaster, where H1 is the flood path and YJ is the set of impacts corresponding to the flood path;

[0129] Break down the effective influencing factors, ineffective influencing factors, and marginal influencing factors in the impact set under each flood path;

[0130] The marginalized influencing factors and the effective influencing factors are subjected to a first attribute similarity analysis. At the same time, the marginalized influencing factors and the ineffective influencing factors are subjected to a second attribute similarity analysis. The attribute similarity analysis refers to a similarity comparison based on the code attribute description of each influencing factor.

[0131] Based on the similarity analysis results, a partitioning coefficient is assigned to each marginal influencing factor;

[0132] When the division coefficient is within the preset division range corresponding to the effective influencing factor, the corresponding marginal influencing factor is classified as an effective influencing factor;

[0133] When the division coefficient is within the preset division range corresponding to the invalid influencing factor, the corresponding marginal influencing factor is classified as an invalid influencing factor;

[0134] When the partitioning coefficient is involved between valid and invalid, a dynamic partitioning probability is set for the corresponding marginal influencing factor;

[0135] According to the dynamic partitioning probability, the corresponding marginal influencing factors are dynamically partitioned, and the influence function Y0 is partitioned based on the last existing effective influencing factor to obtain the first vulnerability analysis function Y1(H1, Y2), where Y2 represents the last existing effective influencing factor;

[0136] The paths are divided according to the path flow direction information of each flood path in the corresponding potentially flood-prone area, resulting in several path combinations;

[0137] For each path combination, all influence sets involved are subjected to set overlap processing to obtain fully overlapping factors, first half-overlapping factors with a preset overlap number or greater, and second half-overlapping factors with a preset overlap number or less.

[0138] Extract the first test function from the function database that matches the fully overlapping factors and the first half overlapping factors in the corresponding combination, perform the first vulnerability test on each flood path in the corresponding combination, and construct the first vector;

[0139] Extract a second test function from the function database that matches the fully overlapping factors, the first half-overlapping factors, and the second half-overlapping factors in the corresponding combination; perform a second vulnerability test on each flood path in the corresponding combination; and construct a second vector.

[0140] By comparing and analyzing the first and second vectors under the same combination, the dependency relationship between the factors based on the same flood path is determined, and auxiliary factors consistent with the corresponding flood path are extracted from the second semi-overlapping factors.

[0141] Based on the complete overlap factors, the first half overlap factors, and auxiliary factors of the same flood path, a second vulnerability analysis function Y2(H1, Y3) is constructed for the corresponding flood path, where Y3 represents the complete overlap factors, the first half overlap factors, and the auxiliary factors under the same flood path.

[0142] The first evaluation function matching Y1(H1, Y2) and the second evaluation function matching Y2(H1, Y3) are obtained from the function database, and vulnerability assessments are performed on them to obtain the regional vulnerability of the corresponding possible flood disaster areas.

[0143] In this embodiment, the influence function is constructed to establish the relationship between the flood path and the influence set. This is mainly to facilitate the direct retrieval of the influence set based on the flood path, or the direct retrieval of the flood path based on the influence set. For example, flood path 1 corresponds to influence set A1, which contains a1, a2, a3, a4, a5, a6, and a7.

[0144] In this embodiment, the splitting of the impact set is achieved based on the impact splitting model, which is based on the annotation of different flood paths and possible impacts by experts, as well as the determination of the effectiveness, ineffectiveness, and steps of the impacts, thereby enabling the training of a neural network model.

[0145] In this embodiment, after analyzing the influence set based on the influence splitting model, we can directly obtain the effective influences a1, a2, a3, and a4, the ineffective influences a6 and a7, and the marginal influence a5.

[0146] In this embodiment, the attribute similarity analysis is code attribute description analysis, and it is obtained by matching from the factor-code description mapping table. This mapping table consists of different influencing factors and their corresponding code descriptions. For example, the code description corresponding to factor a1 is &&8899&&. At this time, the similarity analysis of the two can be achieved by performing similarity analysis on the code description through a similarity function.

[0147] In this embodiment, The effective similarity threshold is set at 0.7, and the invalid similarity threshold is set at 0.8.

[0148] In this embodiment, the preset division range corresponding to the effective influencing factors is (u03, u04), and the preset division range corresponding to the ineffective influencing factors is (u05, u02), and u02 is less than u03. The middle region is (u02, u03).

[0149] In this embodiment, the purpose of setting dynamic probabilities is to assign probabilities to edge influencing factors in order to determine whether the factor is classified as a valid or invalid random case.

[0150] In this embodiment, Y1 includes Y2.

[0151] In this embodiment, the set of path 1 in combination 1 is: a1, a2, a3, a4, a5, a6, a7;

[0152] The set of path 2 is: a1, a2, a3, a4, a5, a6;

[0153] The set for path 3 is: a1, a2;

[0154] The set of paths 4 is: a2, a3, a4;

[0155] Assuming the preset overlap is 2, then the fully overlapping factor is a2, the first half-overlapping factors are a1, a3, and a4, and the second half-overlapping factors are a5 and a6.

[0156] In this embodiment, the function database contains different combinations of factors and various vulnerability test functions that match the combinations of factors, which facilitates subsequent analysis. The vulnerability function is determined based on the damage caused by the influencing factors to the region. Generally, the greater the damage caused by the combination of factors, the greater the corresponding vulnerability.

[0157] In this embodiment, the first vector: {vulnerability of path 1, vulnerability of path 2, vulnerability of path 3, vulnerability of path 4}.

[0158] The second vector: {vulnerability of path 1, vulnerability of path 2, vulnerability of path 3, vulnerability of path 4}. The difference between the two vectors lies in that the basic factors may be different, that is, the second vector has more basic factors than the first vector, and the extra basic factors are the second half overlapping factors.

[0159] In this embodiment, the evaluation function is also obtained by matching from a database based on a set, which facilitates analysis of existing factors.

[0160] In this embodiment, regional vulnerability = the average value of evaluation values corresponding to the two evaluation functions.

[0161] The beneficial effect of the above technical solution is: by constructing a function and splitting a set, attribute similarity analysis is performed on edge influencing factors, then dynamic division probability is determined to realize the first vulnerability analysis, and subsequently factor overlap analysis is performed by dividing paths to realize the second vulnerability analysis, which ensures the reliability of obtaining regional vulnerability and provides a basis for subsequent construction of disaster reduction dam systems.

[0162] The present invention provides a construction method of a disaster reduction dam system for mountain flood disaster prevention, when the division coefficient is between effective and ineffective, setting a dynamic division probability for the corresponding edge influencing factors, comprising:

[0163]

[0164] Wherein, u01 represents the division coefficient; u03 represents the left boundary value based on the preset division range corresponding to effective influencing factors; u02 represents the right boundary value based on the preset division range corresponding to ineffective influencing factors, and u02<u03; G01 represents the dynamic division probability.

[0165] The beneficial effect of the above technical solution is: through the comparative analysis of boundary values, probability setting is performed for factors under different conditions, which facilitates effective allocation of edge influencing factors.

[0166] The present invention provides a construction method of a disaster reduction dam system for mountain flood disaster prevention, extracting auxiliary factors consistent with corresponding flood paths from the second half overlapping factors, comprising:

[0167] determining the vulnerability difference of the same flood path according to the comparative analysis result;

[0168] determining the required extraction quantity of corresponding second half overlapping factors according to the vulnerability difference;

[0169]

[0170] Where N3 is the number of variables to be extracted corresponding to fragile difference C1; Δ1 is the unit difference variable corresponding to weak difference C1; YN is the difference threshold corresponding to weak difference C1; Δ2 is the relevant error variable matched with the corresponding Δ1; [] is the rounding symbol;

[0171] The overlap of each factor in the second half of the overlapping factors and the weights assigned to the factors are sorted according to the ranking value.

[0172]

[0173] Where R1 is the ranking value of the corresponding factor in the corresponding second half-overlap factor; cr is the number of overlaps of the corresponding factor in the corresponding second half-overlap factor; cq j02 Zn represents the weight set for the corresponding factor in the second half-overlapping factor based on the j02-th flood path, and the number of overlaps for the same factor is consistent with the number of flood paths corresponding to that factor; rq is the sum of the weights set for the corresponding factors in the second half-overlapping factor under the matched flood path; Zn represents the total number of factors existing in the second half-overlapping factor; Zq j01 The maximum weight is set for the j01st overlapping factor obtained from the corresponding second half-overlap factor;

[0174] Based on the required number of factors, the first N3 factors are extracted to obtain auxiliary factors.

[0175] The beneficial effects of the above technical solution are: by conducting vulnerability analysis of the same flood path to determine the required number of extractions and by calculating the sorting value, it is easy to effectively extract auxiliary factors and provide a basis for obtaining vulnerability.

[0176] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for constructing a disaster reduction dam system for flood prevention, characterized in that, include: Step 1: Based on the geographic and hydrological information of the target watershed, configure dam system foundations for the target watershed, wherein the dam system foundations are related to the areas of potential flood disaster and potential treatment areas in the target watershed; Step 2: Conduct a risk assessment based on the flood information of the target watershed, analyze possible flood paths and impact sets, and identify key areas and high-risk areas that require flash flood prevention. Step 3: Based on the aforementioned dam system foundation, select the corresponding initial ecological dam system from the dam type database; Step 4: Based on the regional determination results, plan and adjust the initial ecological dam system; Step 5: Based on the constructed sensing system, monitor the surrounding environment of the dam system after the planning adjustment, and conduct geological disaster early warning; Step 2 includes: Based on the flood information and hydrological information, the probability of flood occurrence in areas prone to flood disasters is determined, as well as the flood paths existing in the corresponding areas prone to flood disasters for each historical flood and the set of impacts based on each flood path; Based on all flood paths and corresponding impact sets of the same potential flood disaster area, assess the regional vulnerability of the corresponding potential flood disaster area; Based on the probability of flooding and regional vulnerability in areas prone to flooding, potential risk values ​​are determined. Based on the potential risk values, all areas with possible flood hazards are ranked to determine the key areas and high-risk areas that require flash flood prevention. The assessment of regional vulnerability in areas prone to flooding includes: Construct an impact function Y0(H1, YJ) corresponding to the area of ​​possible flood disaster, where H1 is the flood path and YJ is the set of impacts corresponding to the flood path; Break down the effective influencing factors, ineffective influencing factors, and marginal influencing factors in the impact set under each flood path; The marginal influencing factors and the effective influencing factors are subjected to a first attribute similarity analysis. At the same time, the marginal influencing factors and the ineffective influencing factors are subjected to a second attribute similarity analysis. The attribute similarity analysis refers to a similarity comparison based on the code attribute description of each influencing factor. Based on the similarity analysis results, a partitioning coefficient is assigned to each marginal influencing factor; When the division coefficient is within the preset division range corresponding to the effective influencing factor, the corresponding marginal influencing factor is classified as an effective influencing factor; When the division coefficient is within the preset division range corresponding to the invalid influencing factor, the corresponding marginal influencing factor is classified as an invalid influencing factor; When the partitioning coefficient is between valid and invalid, a dynamic partitioning probability is set for the corresponding edge influencing factor; The corresponding marginal influencing factors are dynamically divided according to the dynamic division probability, and the influence function Y0 is divided based on the last existing effective influencing factor to obtain the first vulnerability analysis function Y1(H1, Y2), where Y2 represents the last existing effective influencing factor; The paths are divided according to the path flow direction information of each flood path in the corresponding potentially flood-prone area, resulting in several path combinations; Set overlapping processing is performed on all influence sets involved in each path combination respectively, to obtain completely overlapping factors, first half-overlapping factors whose number of overlaps is greater than or equal to a preset number of overlaps, and second half-overlapping factors whose number of overlaps is less than the preset number of overlaps; Extract first test functions matching the completely overlapping factors and the first half-overlapping factors in the corresponding combination from a function database, perform a first vulnerability test on each flood path in the corresponding combination, and construct a first vector; Extract second test functions matching the completely overlapping factors, the first half-overlapping factors and the second half-overlapping factors in the corresponding combination from the function database, perform a second vulnerability test on each flood path in the corresponding combination, and construct a second vector; Perform comparative analysis on the first vector and the second vector under the same combination, determine the dependency relationship between factors based on the same flood path, and extract auxiliary factors consistent with the corresponding flood path from the second half-overlapping factors; According to the completely overlapping factors, the first half-overlapping factors and the auxiliary factors of the same flood path, construct and obtain a second vulnerability analysis function Y2(H1, Y3) of the corresponding flood path, wherein Y3 is the completely overlapping factors, the first half-overlapping factors and the auxiliary factors under the same flood path; Acquire a first evaluation function matching Y1(H1, Y2) and a second evaluation function matching Y2(H1, Y3) from the function database, and perform vulnerability assessment respectively to obtain the regional vulnerability of the corresponding possible flood disaster area.

2. The construction method of a disaster reduction dam system for mountain flood disaster prevention according to claim 1, characterized in that, the geographic information is related to the geographical location, geographical boundary, geographical area, geographical terrain and geographical topography of the target watershed; the hydrological information is related to rainfall data, runoff data and water level changes.

3. The construction method of the disaster reduction dam system for flood prevention and control according to claim 1, characterized in that, further comprising: constructing a sensing system, specifically comprising: based on the surrounding construction conditions of the dam system after planning adjustment, determining the soil information and vegetation growth information of each construction position point, and determining an overtopping warning line according to the construction structure of each construction position point of the dam system after planning adjustment; constructing a warning disaster database according to the soil information, the vegetation growth information and the overtopping warning line, and establishing a corresponding sensing system according to the warning disaster database to perform monitoring and sensing on the dam system after planning adjustment.

4. The construction method of the disaster reduction dam system for flood prevention and control according to claim 1, characterized in that, when the division coefficient is between valid and invalid, setting a dynamic division probability for the corresponding edge influence factor, comprising: wherein u01 represents the division coefficient; u03 represents the left boundary value of the preset division range corresponding to valid influence factors; u02 represents the right boundary value of the preset division range corresponding to invalid influence factors, and u02 < u03; G01 represents the dynamic division probability.

5. The construction method of the disaster reduction dam system for flood prevention and control according to claim 1, characterized in that, extracting auxiliary factors consistent with the corresponding flood path from the second half-overlapping factors, comprising: determining the vulnerability difference of the same flood path according to the comparative analysis result; determining the required extraction quantity of the corresponding second half-overlapping factors according to the vulnerability difference; Where N3 is the number of samples that need to be extracted corresponding to the fragile difference C1; YN represents the unit difference variable corresponding to the fragile difference C1; YN represents the difference threshold corresponding to the fragile difference C1. For correspondence The matched relevant error variables; [ ] is the rounding symbol; sorting the overlapping number of each factor in the second half-overlapping factors and the set weight of the factor according to sorting values; Where R1 is the ranking value of the corresponding factor in the corresponding second half-overlapping factor; cr is the number of overlaps of the corresponding factor in the corresponding second half-overlapping factor; The corresponding factor in the second half-overlapping factor is assigned a weight based on the j02th flood path, and the number of overlaps of the same factor is consistent with the number of flood paths corresponding to that factor. This indicates the total number of factors present in the second overlapping factor; The maximum weight is set for the j01st overlapping factor obtained from the corresponding second half-overlap factor; Based on the required number of factors, the first N3 factors are extracted to obtain auxiliary factors.

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