DEM (Digital Elevation Model)-based reservoir return water submerging range analysis method, device, equipment and medium

Abstract

The invention provides a DEM-based reservoir return water inundation range analysis method, device and equipment and a medium, and relates to the technical field of water conservancy projects. Historical water level data of a plurality of test points in a reservoir are obtained, linear fitting is carried out according to a preset direction, a corresponding water level distribution curve is obtained, and a reservoir model corresponding to the reservoir is divided into a plurality of reservoir model sections with water level equal difference distribution according to a water level equal difference principle and a preset fixed value. Calculating a water level elevation value of a central point of each reservoir model section, constructing a corresponding digital elevation model (DEM), determining a boundary contour of a submerged area, and performing smooth connection processing to obtain a reservoir backwater submerged model, namely a reservoir backwater submerged range; the water level change can be quickly responded, the inundation prediction result can be updated in real time, the abnormal data recognition rate is increased, the inundation analysis accuracy is improved, the high-resolution DEM data is combined, meter-scale-precision inundation range delimitation is achieved, and the method is suitable for the reservoir area with the complex terrain.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water conservancy engineering, in particular to a reservoir backwater inundation range analysis method, device, equipment and medium based on DEM. BACKGROUND

[0002] Reservoir backwater refers to the phenomenon that the water level in the reservoir area is raised after the river channel is built with a dam to form a reservoir. When a flood occurs, the reservoir backwater may inundate some farmland, roads or houses along the reservoir bank, so it is often necessary to analyze the reservoir backwater inundation range.

[0003] In the prior art, the analysis of the reservoir backwater inundation range is commonly performed in the following ways: 1. A water level test point (such as a dam) is set in the reservoir, and the reservoir backwater inundation range is estimated based on the water level height of the water level test point. However, in actual situations, the water level heights of the upstream and downstream of the reservoir are not the same, and the water level difference between the upstream and downstream varies significantly under different situations (such as when the water flow is smooth and when the water flow is turbulent under heavy rain), resulting in a certain difference between the analyzed reservoir backwater inundation range and the actual situation. 2. A one-dimensional hydrodynamic model is used, which is suitable for long river section backwater calculation, but the depiction of the lateral inundation range is rough and it is difficult to reflect the influence of local topography. 3. A multi-dimensional hydrodynamic model: can accurately simulate the water flow diffusion process, but the calculation amount is large, depends on high-precision topographic data, and has high requirements for the completeness and accuracy of the measured hydrological data, and the application cost is high in actual engineering.

[0004] At present, the development of digital elevation model (DEM) provides high-precision topographic data support for inundation analysis, but how to combine dynamic water level data to realize fine simulation of the inundation range still faces challenges, and there is an urgent need for a reservoir backwater inundation analysis method that takes into account the calculation efficiency and accuracy to improve the scientificity and reliability of flood control decision-making. SUMMARY

[0005] The main purpose of the present application is to provide a reservoir backwater inundation range analysis method, device, equipment and medium based on DEM, to solve at least one of the above technical problems existing in the prior art.

[0006] To solve the above technical problems, the technical solution adopted by the present application is: a reservoir backwater inundation range analysis method based on DEM, comprising: S1: obtaining historical water level data of multiple test points in the reservoir and performing data preprocessing; S2: linearly fitting the data preprocessed water level data according to a preset direction to obtain a corresponding water level distribution curve, the preset direction being from the upstream to the downstream of the reservoir or from the downstream to the upstream of the reservoir; S3: According to the water level distribution curve and the water level equal difference principle, the reservoir model corresponding to the reservoir is divided into a plurality of water level equal difference distribution reservoir model sections, wherein the water level difference value of adjacent model sections is a preset fixed value; S4: Based on the water level distribution curve, the water level elevation value of the center point of each reservoir model section is calculated; S5: Based on the water level elevation value of each reservoir model section and the corresponding digital elevation model DEM, the boundary contour of the submerged area corresponding to each reservoir model section is determined; S6: The boundary contour of the submerged area of adjacent model sections is smoothly connected to obtain a reservoir backwater submerged model.

[0007] In the preferred scheme, the data preprocessing in S1 includes: The historical water level data of the plurality of test points is subjected to outlier rejection processing and missing value filling processing to obtain the once-processed historical water level data of the plurality of test points; The once-processed historical water level data of the plurality of test points is fitted by Huber regression to obtain the data-preprocessed water level data of the plurality of test points, specifically: S11. Initialize the regression coefficient; S12. Calculate the residual of the once-processed historical water level data of each test point; S13. Based on the residual of the once-processed historical water level data of each test point and a pre-set threshold value, the weight of the once-processed historical water level data of each test point is calculated; S14. Based on the weight of the once-processed historical water level data of each test point, the once-processed historical water level data of each test point is fitted by a weighted least squares algorithm to obtain an updated regression coefficient; S15. Repeat the steps S12-S14 until the latest regression coefficient is lower than the pre-set regression coefficient threshold value, and the latest once-processed historical water level data of each test point is taken as the data-preprocessed water level data of the corresponding test point.

[0008] In the preferred scheme, the water level equal difference principle in S3 is specifically: The reservoir model is divided into a plurality of sections, and the water level average value or intermediate value of each section is arranged in an equal difference sequence. The water level difference value of adjacent model sections is set to a fixed value in the range of 0.1-0.5 meters.

[0009] In the preferred scheme, the smooth connection processing of the boundary contour of the submerged area of adjacent model sections in S6 includes: For any two adjacent submerged area contours, the distance between the two contour edges of the first submerged area contour and the two contour edges of the second submerged area contour is calculated; The distance between the two profile edges of the first flooded area profile and the two profile edges of the second flooded area profile is determined to obtain two groups of adjacent profile edges between the first flooded area profile and the second flooded area profile, one of the profile edges in any group of profile edges is the profile edge of the first flooded area profile, and the other profile edge is the profile edge of the second flooded area profile. The middle point between the two closest points in each group of profile edges is determined. The two profile edges corresponding to each group of profile edges are subjected to smooth transition processing by taking the middle point between the two closest points in each group of profile edges as the end point of the two profile edges.

[0010] In the preferred embodiment, the distance between the two profile edges of the first flooded area profile and the two profile edges of the second flooded area profile is determined to obtain two groups of adjacent profile edges between the first flooded area profile and the second flooded area profile, comprising: The two groups of profile edges with the shortest distance are selected as the two groups of adjacent profile edges between the first flooded area profile and the second flooded area profile based on the distance between the two profile edges of the first flooded area profile and the two profile edges of the second flooded area profile.

[0011] In the preferred embodiment, in S2, the linear fitting is performed in a preset direction to obtain the corresponding water level distribution curve, comprising: The linear fitting is performed by linear regression, nonlinear regression or spline interpolation based on the water level data of each test point in the reservoir to obtain the water level distribution curve corresponding to the reservoir.

[0012] In the preferred embodiment, in S5, the corresponding flooded area boundary profile of each segment is determined, comprising: The DEM elevation data of the corresponding area of each model segment is extracted; The central point water level elevation is compared with the surrounding DEM elevation point by point; All areas with an elevation value less than the central point water level are marked as flooded areas; The closed boundary profile of the flooded area is extracted by using an edge detection algorithm.

[0013] In a second aspect, the present application provides a DEM-based reservoir backwater flooded area analysis device, comprising: An acquisition unit is configured to acquire historical water level data of a plurality of test points in a reservoir and perform data preprocessing; A fitting unit is configured to perform linear fitting on the water level data after data preprocessing in a preset direction to obtain a corresponding water level distribution curve, wherein the preset direction is from the upstream to the downstream of the reservoir or from the downstream to the upstream of the reservoir. The dividing unit is used for dividing the reservoir model corresponding to the reservoir into a plurality of reservoir model sections with equal water level distribution according to the water level distribution curve and the water level equal difference principle, wherein the water level difference between adjacent model sections is a preset fixed value. The calculating unit is used for calculating the water level elevation value of the center point of each reservoir model section based on the water level distribution curve. The determining unit is used for determining the submerged area boundary contour corresponding to each reservoir model section based on the water level elevation value of each reservoir model section and the corresponding digital elevation model (DEM). The predicting unit is used for performing smooth connection processing on the submerged area boundary contour of adjacent model sections to obtain the reservoir backwater submergence model.

[0014] In a third aspect, the present application provides an electronic device, comprising a memory and a processor; The memory is used for storing a computer program. The processor is used for implementing the DEM-based reservoir backwater submergence range analysis method as described in the first aspect or any possible design of the first aspect when executing the computer program.

[0015] In a fourth aspect, the present application provides a computer readable storage medium, characterized in that the storage medium stores a computer program, and the computer program, when executed by a processor, implements the DEM-based reservoir backwater submergence range analysis method as described in the first aspect or any possible design of the first aspect.

[0016] In the process of analyzing the reservoir backwater submergence range, the present application fits the water level distribution curve according to the water level data of each test point in the reservoir, and divides the reservoir model corresponding to the reservoir into a plurality of sections based on the water level equal difference principle, so that the upstream and downstream water level difference of each reservoir model section is maintained within a small numerical range. Therefore, when the submerged area contour is determined in combination with the digital elevation model, the difference between the submerged area contour and the actual submerged area contour is reduced due to the small upstream and downstream water level difference of each reservoir model section, the reservoir backwater submergence range is accurately analyzed, and the accuracy of the reservoir backwater submergence range analysis is improved, thereby providing guidance for flood disaster assessment, flood control and disaster relief management, etc. BRIEF DESCRIPTION OF DRAWINGS

[0017] The present application will be further described below in combination with the drawings and embodiments: Figure 1 is a flow chart of the reservoir submergence range analysis method of the present application; Figure 2 is a historical water level data distribution graph of a plurality of test points in a reservoir; Figure 3 is a block diagram of the reservoir submergence range analysis device of the present application. DETAILED DESCRIPTION

[0018] Embodiment 1 As Figures 1-2 shown, it is the flow chart of the DEM-based reservoir backwater inundation range analysis method provided by the first aspect of the embodiment of the application. The DEM-based reservoir backwater inundation range analysis method can but is not limited to include the following steps S1-S6, specifically: S1: Obtain historical water level data of a plurality of test points in the reservoir, and perform data preprocessing.

[0019] S2: Linearly fit the water level data after data preprocessing according to a preset direction to obtain a corresponding water level distribution curve. The preset direction is from the upstream to the downstream of the reservoir or from the downstream to the upstream of the reservoir.

[0020] S3: According to the water level distribution curve and the water level difference principle, divide the reservoir model corresponding to the reservoir into a plurality of water level difference distribution reservoir model segments, wherein the water level difference value of adjacent model segments is a preset fixed value.

[0021] S4: Based on the water level distribution curve, calculate the water level elevation value of the center point of each reservoir model segment.

[0022] S5: Based on the water level elevation value of each reservoir model segment and the corresponding digital elevation model DEM, determine the inundation area boundary contour corresponding to each reservoir model segment.

[0023] S6: Smoothly connect the inundation area boundary contour of adjacent model segments to obtain a reservoir backwater inundation model.

[0024] In this embodiment, by obtaining historical water level data of a plurality of test points in the reservoir, linearly fitting according to a preset direction to obtain a corresponding water level distribution curve, and according to the water level difference principle, dividing the reservoir model corresponding to the reservoir into a plurality of water level difference distribution reservoir model segments with a preset fixed value, calculating the water level elevation value of the center point of each reservoir model segment, constructing the corresponding digital elevation model DEM, determining the inundation area boundary contour, and performing smooth connection processing to obtain a reservoir backwater inundation model, the reservoir backwater inundation range is obtained. It can quickly respond to water level changes, update the inundation prediction results in real time, improve the abnormal data recognition rate, improve the accuracy of inundation analysis, combine high-resolution DEM data, realize meter-level precision inundation range demarcation, and is suitable for complex terrain reservoir areas.

[0025] Further, a three-dimensional model of the inundation range with elevation information is generated to intuitively display the inundation situation under different water levels; hierarchical display and dynamic simulation of inundation depth are supported to facilitate analysis of the inundation development trend. Through multi-source data fusion, intelligent segmented modeling and three-dimensional visualization, the reservoir backwater inundation range is improved from macro prediction to micro analysis.

[0026] In step S1, water level data of each test point in the reservoir is acquired.

[0027] In the embodiments of the present application, a plurality of test points can be arranged in the reservoir from upstream to downstream, and each test point is provided with a water level testing device for acquiring water level data of each test point.

[0028] The water level refers to the elevation of the free water surface relative to a certain base surface. The base surface used to calculate the water level can be a characteristic sea level elevation as a zero point leveling base surface, referred to as an absolute base surface, and the commonly used one is the Yellow Sea base surface. A specific point elevation can also be used as a reference to calculate the water level zero point, referred to as a station base surface. For example, Figure 2 As shown in FIG. 1, it is a historical water level data distribution diagram of a plurality of test points in a reservoir.

[0029] In addition, it should be noted that the water level data of each test point should be kept in time synchronization to ensure the accuracy of subsequent analysis.

[0030] In the preferred scheme, the data preprocessing in step S1 includes: performing outlier rejection processing and missing value filling processing on the historical water level data of the plurality of test points to obtain the once-processed historical water level data of the plurality of test points; performing fitting on the once-processed historical water level data of the plurality of test points through Huber regression to obtain the data-preprocessed water level data of the plurality of test points, specifically including: S11: initializing the regression coefficient.

[0031] S12: calculating the residual of the once-processed historical water level data of each test point.

[0032] S13: based on the residual of the once-processed historical water level data of each test point and a pre-set threshold, calculating the weight of the once-processed historical water level data of each test point.

[0033] S14: based on the weight of the once-processed historical water level data of each test point, performing fitting on the once-processed historical water level data of each test point through a weighted least squares algorithm to obtain an updated regression coefficient.

[0034] S15: repeating the above steps S12-S14 until the latest regression coefficient is lower than a pre-set regression coefficient threshold, and taking the latest once-processed historical water level data of each test point as the data-preprocessed water level data of the corresponding test point.

[0035] In the preferred scheme, in step S2, linear fitting is performed in a pre-set direction to obtain a corresponding water level distribution curve, including: Based on the water level data of each test point in the reservoir, the water level distribution curve of the reservoir is obtained by linear fitting through linear regression method, nonlinear regression method or spline interpolation method.

[0036] In this embodiment, step S2 is to obtain the water level distribution curve by linear fitting using the water level data. The water level distribution curve from upstream to downstream of the reservoir can be obtained by linear fitting through linear regression method, nonlinear regression method or spline interpolation method based on the water level data of each test point in the reservoir.

[0037] In the preferred embodiment, the water level arithmetic progression principle in step S3 is as follows: The reservoir model is divided into several segments, and the average or intermediate water level of each segment is distributed in an arithmetic progression. The water level difference between adjacent segments is set to a fixed value in the range of 0.1-0.5 meters.

[0038] In this embodiment, a reservoir model of the reservoir can be established in advance. When the reservoir model corresponding to the reservoir is divided into multiple reservoir model segments, the reservoir model corresponding to the reservoir can be divided into multiple reservoir model segments with average water level or water level intermediate value in arithmetic distribution according to the water level distribution curve and the preset water level arithmetic progression principle.

[0039] For example, the water level height (i.e. water level data) of the uppermost upstream of the reservoir is 148.20m, and the water level height of the lowermost downstream of the reservoir is 146.00m, with a difference of 2.2m between the upstream and downstream. According to the water level arithmetic progression principle, the model corresponding to the reservoir can be divided into 11 reservoir model segments, and the average water level or water level intermediate value (which can be calculated by the water level distribution curve) between adjacent two reservoir model segments is 0.2m.

[0040] By dividing the reservoir model corresponding to the reservoir into multiple reservoir model segments, the upstream and downstream water level difference of each reservoir model segment is maintained within a small range, so that when the digital elevation model (DEM) is used to determine the contour of the flooded area, the difference between the determined contour of each segment and the actual contour of the flooded area is small, thereby avoiding the difference between the determined contour of the flooded area and the actual contour of the flooded area due to the large upstream and downstream water level difference.

[0041] In the preferred embodiment, in step S5, the determination of the boundary contour of the flooded area corresponding to each segment includes: Extracting DEM elevation data of the area corresponding to each model segment.

[0042] Comparing the center point water level elevation with the surrounding DEM elevation point by point.

[0043] The area marked with all elevation values ​​below the center point water level is the flood zone.

[0044] An edge detection algorithm is used to extract the closed boundary contour of the flooded area.

[0045] Steps S4-S5 involve using water level distribution curves to calculate the center water level data of each reservoir model segment and the corresponding digital elevation model (DEM) for each reservoir model segment, thereby determining the outline of the inundation area corresponding to each reservoir model segment.

[0046] In this embodiment, a digital elevation model of the area where the reservoir is located is pre-established. This digital elevation model can be based on the reservoir during the dry season, so that the digital elevation model can clearly record the elevation data of the edges of the two banks of the reservoir.

[0047] After obtaining the water level data at the center of each reservoir model section, the water level data at the center of each reservoir model section can be used as its water level height, and the water level height of each reservoir model section can be used as its elevation data, or its elevation data can be calculated based on the water level height of each reservoir model section.

[0048] Then, by combining the digital elevation model, the area around each reservoir model segment whose elevation data is lower than its own elevation data can be taken as the corresponding inundation area of ​​each reservoir model segment, thereby determining the outline of the inundation area corresponding to each reservoir model segment.

[0049] In the preferred embodiment, step S6 involves smoothing the boundary contours of the flooded areas of adjacent model segments, including: Step S601: For any two adjacent flooded area contours, calculate the distance between the two contour lines of the first flooded area contour and the two contour lines of the second flooded area contour.

[0050] Step S602: Based on the distance between the two contour lines of the first submerged area contour and the two contour lines of the second submerged area contour, determine the two sets of adjacent contour lines between the first submerged area contour and the second submerged area contour.

[0051] In this case, one of the contour lines in any set of contour lines is the contour line of the first submerged area, and the other contour line is the contour line of the second submerged area.

[0052] Specifically, based on the distance between the two contour lines of the first submerged area contour and the two contour lines of the second submerged area contour, the two sets of contour lines with the shortest corresponding distance can be selected as the two sets of adjacent contour lines between the first submerged area contour and the second submerged area contour.

[0053] Step S603: Determine the middle point between the nearest two points in each group of contour lines.

[0054] Step S604: Smoothly transition the two corresponding contour lines in each group of contour lines by taking the middle point between the nearest two points in each group of contour lines as the end point of the two corresponding contour lines in each group of contour lines.

[0055] By smoothly transitioning the adjacent submerged area contours, a smooth transition is formed between the adjacent submerged area contours, making the final reservoir backwater inundation model more natural.

[0056] In one or more embodiments, after obtaining the reservoir backwater inundation model, the reservoir backwater inundation model can be visualized and displayed by a display unit.

[0057] Embodiment 2 As shown in Figure 3 The embodiment provides a DEM-based reservoir backwater inundation range analysis device, which comprises: An acquisition unit is configured to acquire historical water level data of a plurality of test points in a reservoir and perform data preprocessing.

[0058] A fitting unit is configured to linearly fit the water level data after data preprocessing according to a preset direction to obtain a corresponding water level distribution curve.

[0059] A division unit is configured to divide a reservoir model corresponding to the reservoir into a plurality of reservoir model segments with equidifferent water level distribution according to the water level distribution curve and the water level equidifferent principle, wherein a water level difference between adjacent model segments is a preset fixed value.

[0060] A calculation unit is configured to calculate water level elevation values of center points of the reservoir model segments based on the water level distribution curve.

[0061] A determination unit is configured to determine submerged area boundary contours corresponding to the reservoir model segments based on the water level elevation values of the reservoir model segments and a corresponding digital elevation model (DEM).

[0062] A prediction unit is configured to smoothly connect the submerged area boundary contours of adjacent model segments to obtain a reservoir backwater inundation model.

[0063] The working process, working details and technical effects of the DEM-based reservoir backwater inundation range analysis device provided by the embodiment can be referred to Embodiment 1, and will not be repeated here.

[0064] Embodiment 3 The embodiment of the present application provides an electronic device, comprising a memory and a processor. The memory is configured to store a computer program.

[0065] A processor for implementing the DEM-based reservoir backwater inundation range analysis method of embodiment 1 when executing a computer program, wherein the computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0066] For example, the memory can include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out memory (FIFO), and / or first-in-last-out memory (FILO), etc.; the processor can be, but is not limited to, a microprocessor of STM32F105 series, an ARM (Advanced RISC Machines) processor, an X86 architecture processor, or a processor integrated with NPU (neural-network processing units).

[0067] Embodiment 4 The embodiment of the present application provides a computer readable storage medium, and the computer readable storage medium stores a computer program. When the computer program is executed by a processor, the DEM-based reservoir backwater inundation range analysis method of embodiment 1 is implemented.

[0068] In the embodiment, the computer readable storage medium, that is, the computer readable storage medium stores instructions, and when the instructions run on the computer, the DEM-based reservoir backwater inundation range analysis method of the first aspect is executed. The computer readable storage medium is a carrier for storing data, and can include, but is not limited to, a floppy disk, an optical disc, a hard disk, a flash memory, a USB flash disk, and / or a memory stick, etc. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0069] The above-mentioned embodiments are only preferred technical solutions of the present application, and should not be regarded as limitations of the present application. The protection scope of the present application should be the technical solutions recited in the claims, including equivalent replacement solutions of the technical features recited in the claims. That is, equivalent replacement improvements within this range are also within the protection scope of the present application.

Claims

1. A DEM-based reservoir backwater inundation area analysis method, characterized in that, The method comprises the following steps: S1: obtaining historical water level data of multiple test points in a reservoir and performing data preprocessing; S2: linearly fitting the water level data after data preprocessing according to a preset direction to obtain a corresponding water level distribution curve, wherein the preset direction is from an upstream to a downstream of the reservoir or from a downstream to an upstream of the reservoir; S3: dividing a reservoir model corresponding to the reservoir into a plurality of reservoir model segments with equal-difference water level distribution according to the water level distribution curve and the water level equal-difference principle, wherein a water level difference value of adjacent model segments is a preset fixed value; S4: calculating water level elevation values of center points of the reservoir model segments based on the water level distribution curve; S5: determining a corresponding submergence area boundary contour of each reservoir model segment based on the water level elevation values of the reservoir model segments and a corresponding digital elevation model (DEM); S6: performing smooth connection processing on the submergence area boundary contours of adjacent model segments to obtain a reservoir backwater submergence model.

2. The DEM-based reservoir backwater inundation area analysis method of claim 1, wherein, The data preprocessing in S1 comprises: performing outlier rejection processing and missing value filling processing on the historical water level data of the multiple test points to obtain once-processed historical water level data of the multiple test points; performing fitting on the once-processed historical water level data of the multiple test points by Huber regression to obtain water level data after data preprocessing of the multiple test points, specifically comprising: S11: initializing a regression coefficient; S12: calculating a residual of the once-processed historical water level data of each test point; S13: calculating a weight of the once-processed historical water level data of each test point based on the residual of the once-processed historical water level data of each test point and a preset threshold value; S14: performing fitting on the once-processed historical water level data of each test point by a weighted least square algorithm based on the weight of the once-processed historical water level data of each test point to obtain an updated regression coefficient; S15: repeating the steps S12-S14 until the latest regression coefficient is lower than a preset regression coefficient threshold value, and taking the latest once-processed historical water level data of each test point as the water level data after data preprocessing of the corresponding test point.

3. The DEM-based reservoir backwater inundation area analysis method of claim 1, wherein, The water level equal-difference principle in S3 comprises: dividing the reservoir model into a plurality of segments so that an average value or a middle value of water level of each segment is in an equal-difference sequence; and the water level difference value of adjacent model segments is a fixed value in a range of 0.1-0.5 meters.

4. The DEM-based reservoir backwater inundation area analysis method of claim 1, wherein, The smooth connection processing on the submergence area boundary contours of adjacent model segments in S6 comprises: for any two adjacent submergence area contours, calculating distances between two contour edges of a first submergence area contour and two contour edges of a second submergence area contour; based on the distances between the two contour edges of the first submergence area contour and the two contour edges of the second submergence area contour, determining two adjacent groups of contour edges between the first submergence area contour and the second submergence area contour, wherein one contour edge in any group of contour edges is a contour edge of the first submergence area contour, and the other contour edge is a contour edge of the second submergence area contour; determining a middle point between the nearest two points in each group of contour edges; The middle point between the two closest points in each group of contour lines is taken as the end point of the two corresponding contour lines in each group of contour lines, and the two corresponding contour lines in each group of contour lines are subjected to smooth transition processing.

5. The DEM-based reservoir backwater inundation extent analysis method of claim 4, wherein, The distance between the two contour lines of the first submerged area contour and the two contour lines of the second submerged area contour determines two groups of adjacent contour lines between the first submerged area contour and the second submerged area contour, including: Based on the distance between the two contour lines of the first submerged area contour and the two contour lines of the second submerged area contour, the two groups of contour lines with the shortest distance are selected as the two groups of adjacent contour lines between the first submerged area contour and the second submerged area contour. 6.The DEM-based reservoir backwater inundation area analysis method of claim 1, wherein, In S2, linear fitting is performed in a preset direction to obtain a corresponding water level distribution curve, including: Based on the water level data of each test point in the reservoir, linear fitting is performed by linear regression method, nonlinear regression method or spline interpolation method to obtain the water level distribution curve corresponding to the reservoir.

7. The DEM-based reservoir backwater inundation extent analysis method of claim 1, wherein, In S5, the corresponding submerged area boundary contour of each section is determined, including: Extracting DEM elevation data of the corresponding area of each model section; Comparing the center point water level elevation with the surrounding DEM elevation point by point; Marking all areas with an elevation value less than the center point water level as submerged areas; Using an edge detection algorithm to extract the closed boundary contour of the submerged area.

8. A DEM-based reservoir backwater inundation area analysis device, characterized by, Including: An acquisition unit is configured to acquire historical water level data of a plurality of test points in a reservoir and perform data preprocessing; A fitting unit is configured to perform linear fitting on the water level data after data preprocessing in a preset direction to obtain a corresponding water level distribution curve, wherein the preset direction is from the upstream to the downstream of the reservoir or from the downstream to the upstream of the reservoir; A division unit is configured to divide a reservoir model corresponding to the reservoir into a plurality of reservoir model sections with equal water level differences according to the water level distribution curve and the water level difference principle, wherein the water level difference between adjacent model sections is a preset fixed value; A calculation unit is configured to calculate the water level elevation of the center point of each reservoir model section based on the water level distribution curve; A determination unit is configured to determine the submerged area boundary contour corresponding to each reservoir model section based on the water level elevation of each reservoir model section and the corresponding digital elevation model (DEM); A prediction unit is configured to perform smooth connection processing on the submerged area boundary contours of adjacent model sections to obtain a reservoir backwater submerged model.

9. An electronic device, comprising: Including a memory and a processor; The memory is configured to store a computer program; The processor is configured to implement the DEM-based reservoir backwater submerged range analysis method of any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The storage medium has a computer program stored thereon, and when the computer program is executed by the processor, the DEM-based reservoir backwater submerged range analysis method of any one of claims 1 to 7 is implemented.

Images