Multi-index evaluation method for stability of braided reach

Abstract

The application discloses a kind of branched river reach river regime stability multi-index evaluation method, comprising: obtaining the standardized basic data set including hydrology silt, multi-period topography and engineering data;The hierarchical evaluation system formed by dynamic condition, river channel, beach and engineering strength is constructed;Using topography and geology topological features, the research river reach is automatically divided into independent geomorphologic evaluation unit;Based on the evaluation system and evolution characteristics, the index weight and spatial weight are determined;The unit single evaluation is calculated and weightedly collected to obtain the overall river regime stability score.The application disperses river reach into independent evaluation unit with clear physical meaning, overcomes the defects of traditional evaluation space, and introduces dynamic spatial weight mechanism, realizes the quantification of complex branched river reach river regime evolution and automatic early warning of high sensitive area.

Description

Technical Field

[0001] This invention relates to the field of water conservancy engineering and flood control and disaster reduction technology, and in particular to a multi-index assessment method for the stability of river course in branching river sections. Background Technology

[0002] Distributary channels are a common and complex riverbed morphology in alluvial plains and estuaries, characterized by intricate dynamics of water flow and sediment sources, and frequent alternation and evolution of main and tributary channels. Accurately assessing the stability of these river sections is of significant engineering and technical value for guiding channel regulation, flood control dike construction, bridge site selection, and aquatic ecological environment protection. Quantifying the patterns of river morphological evolution can provide hydrodynamic early warning support for the long-term safe operation of major water-related infrastructure.

[0003] Currently, the industry generally adopts empirical statistical methods based on fixed long-sequence historical data or one-dimensional / two-dimensional hydrodynamic numerical simulation methods for assessing river stability. In empirical statistical methods, manual comparison of remote sensing images or paper nautical charts is typically relied upon, combined with simple linear interpolation to calculate the evolution of shoals and channels, supplemented by expert scoring for macroscopic qualitative evaluation. In numerical simulations, although the equations of flow motion can be solved, grid division is often limited to fixed geometric boundaries, and evaluation indicators often focus on a single velocity field or scour and deposition thickness. When facing complex scenarios such as frequent node migrations, shoal and channel changes, and multiple engineering interventions in bifurcation sections, existing methods have significant shortcomings in the spatial deconstruction accuracy of geomorphic units. Furthermore, the comprehensive weighting of various heterogeneous indicators (such as hydrological drivers, geomorphic response, and engineering protection) lacks differentiated consideration of regional evolutionary activity.

[0004] Therefore, in complex riverbed geomorphological environments, there is an urgent need to explore an automatic quantitative assessment method for river morphology evolution that can break through the limitations of traditional artificial boundary delineation, take into account the influence of multiple driving factors, and objectively reflect the evolution characteristics of local highly sensitive areas. Summary of the Invention

[0005] The purpose of this invention is to provide a multi-index assessment method for the stability of river course in bifurcation sections, in order to solve the aforementioned problems existing in the prior art.

[0006] Technical solution: A multi-index assessment method for river regime stability in bifurcation sections, including:

[0007] Obtain standardized basic datasets, including hydrological and sediment data, multi-period measured cross-sectional data, and engineering data;

[0008] Based on standardized basic datasets, a hierarchical evaluation system is constructed that includes water and sediment inflow conditions, channel geomorphological units, sandbar geomorphological units, and the intensity of engineering activities.

[0009] Using the topographic and geoscientific topological features in the standardized basic dataset, the study river section is divided into several independent geomorphological evaluation units;

[0010] Based on the hierarchical evaluation system and the evolution characteristics of independent geomorphic evaluation units, the index weights and geomorphic unit spatial weights are determined to obtain the weight system.

[0011] Based on the weighting system and standardized basic dataset, the individual scores of each independent geomorphological evaluation unit are calculated, and the overall river stability score is obtained by weighted summation.

[0012] Optionally, using the topographic and geoscientific topological features in the standardized base dataset, the studied river segment can be divided into several independent geomorphic evaluation units, including:

[0013] A digital elevation model of the riverbed is constructed by spatial interpolation based on multi-period measured cross-section data in a standardized basic dataset.

[0014] The lowest elevation point of the riverbed digital elevation model is extracted section by section along the longitudinal direction, and the connectivity domain analysis is performed on the riverbed elevation profile of each section.

[0015] When multiple independent low-value troughs separated by highlands are detected in the same cross section, each independent low-value trough is traced to form an independent thalweg branch, and the cross section position where the earliest independent low-value trough appears is recorded as the coordinate of the branch node.

[0016] When multiple thalweg branches merge into a single lowest elevation point trajectory, the location of the merging section is recorded as the coordinates of the confluence node. The thalweg vector set is composed of the coordinates of the thalweg branches, the branching nodes, and the confluence node.

[0017] Optionally, the study river segment can be divided into several independent geomorphic evaluation units using the topographic and geoscientific topological features in the standardized base dataset, and may also include:

[0018] Frequency statistics are performed on the elevation values ​​of cross sections in the digital elevation model of the riverbed to generate elevation probability density curves.

[0019] The bimodal feature in the elevation probability density curve is detected, and the derivative of the elevation probability density curve is obtained. The valley elevation between the two peaks is determined by locating the zero crossover point of the derivative, and the valley elevation is determined as the boundary elevation between the beach and the channel.

[0020] On the digital elevation model of the riverbed, contour lines of the floodplain-channel boundary are traced to generate continuous floodplain-channel boundary lines on both the left and right sides. The floodplain-channel boundary lines are then used to divide the river channel into the channel area and the floodplain area.

[0021] Optionally, using the topographic and geoscientific topological features in the standardized base dataset, the study river segment is divided into several independent geomorphic evaluation units. This also includes obtaining the node control segment boundary set, which includes:

[0022] The horizontal distance between the boundary lines of the left and right shoals and channels is extracted as the river width sequence along the course, and the narrowing points of the river width in the river width sequence along the course are detected.

[0023] Calculate the curvature along the path of the thalweg vector set and identify locations of abrupt curvature changes;

[0024] Based on the engineering data in the standardized basic dataset, extract the engineering constraint areas with continuous rigid protection;

[0025] A longitudinal spatial overlay analysis was conducted on the locations where the river width narrowed, the locations where the curvature changed abruptly, and the engineering constraint areas. Regions that met the spatial overlap conditions were extracted to obtain the boundary set of the node control segments.

[0026] Optionally, the study river segment can be divided into several independent geomorphic evaluation units using the topographic and geoscientific topological features in the standardized base dataset, and may also include:

[0027] Using the coordinates of the branching nodes, the coordinates of the confluence nodes, and the boundary set of the node control sections, the continuous river channel is longitudinally divided into several river segments.

[0028] Based on the number of independent branches of the thalweg vector set contained in the river section, the river sections in the channel area are respectively identified as node control units, distributary units or transition units, and the distributary units are further divided into main distributary units and branch distributary units by using the cross-sectional water flow area.

[0029] Based on the enclosing relationship of the beach-channel boundary, the closed highlands or adjacent beach bodies within the island-shoal area are respectively identified as river island units or side beach units, thereby obtaining the initial geomorphological evaluation units carrying type labels and boundary information.

[0030] Optionally, the study river segment is divided into several independent geomorphic evaluation units using the topographic and geoscientific topological features in the standardized base dataset. The method also includes a step of performing integrity verification on the initial geomorphic evaluation units. The integrity verification steps include:

[0031] Verify whether the initial geomorphological evaluation unit completely includes the thalweg branch and whether it has an inlet section and an outlet section;

[0032] When the integrity condition is not met, the boundary of the initial geomorphological evaluation unit is extrapolated along the branch direction of the thalweg line to the natural turning point or the measured section position to obtain the boundary adjustment unit.

[0033] Re-execute the type determination rules to update the type label for the boundary adjustment unit, and then perform the integrity verification step again.

[0034] Optionally, the process of re-performing the integrity verification step on the boundary adjustment unit specifically includes:

[0035] Set the pre-configured maximum number of boundary iteration adjustments and count them during the loop execution of the integrity verification step;

[0036] When the number of boundary adjustments reaches the maximum number of boundary iteration adjustments and the integrity condition is still not met, stop the boundary extrapolation operation for the conflicting unit.

[0037] Conflicting units that fail the verification are merged into composite geomorphic units. When calculating individual scores, the composite geomorphic unit is weighted according to the area ratio of the subtypes contained within it, and the final geomorphic evaluation unit that passes the verification is output as an independent geomorphic evaluation unit.

[0038] Optionally, in the step of dividing the study river section into several independent geomorphological evaluation units, for the needs of multi-phase comparative evaluation, the following may also be included:

[0039] Extract multi-period measured cross-sectional data from different years and delineate the boundaries of geomorphic units for each single time phase in each year;

[0040] For the same landform entity that exhibits locational shifts or morphological changes, extract its maximum spatial envelope range across multiple temporal phases;

[0041] Using the maximum spatial envelope as a unified mapping benchmark, the spatial boundaries of independent geomorphic evaluation units in multi-phase assessment tasks are consistently corrected to eliminate the impact of dynamic changes on boundary tracking.

[0042] Optionally, determine the index weights and spatial weights of geomorphic units, including:

[0043] Determine the basic criteria and weights for each evaluation indicator under the hierarchical evaluation system;

[0044] Based on multi-period measured cross-sectional data, the area of ​​beach activity and the magnitude of erosion and deposition changes of each independent geomorphological evaluation unit in the long-term evolution history are extracted.

[0045] Based on the contribution ratio of the area of ​​beach activity and the magnitude of scouring and deposition to the overall river morphology evolution of the entire river section, spatial influence factors are allocated according to nonlinear mapping to generate spatial weights for geomorphic units.

[0046] The weighting system is constructed by merging the weights of the basic criteria with the spatial weights of the geomorphic units.

[0047] Optionally, calculate the individual scores for each independent geomorphic evaluation unit, including:

[0048] Based on hydrological and sediment data, the equivalent of bed-forming flow rate and sediment transport intensity under the conditions of incoming water and sediment are calculated.

[0049] Based on the spatial boundary changes of independent geomorphic evaluation units in multiple periods, the lateral swing amplitude of the thalweg and the longitudinal movement distance of the confluence point are calculated.

[0050] Based on engineering data, the engineering protection coverage rate and the volume of shoreline revetment per unit area, which characterize the intensity of engineering activities, are calculated.

[0051] Each of the calculated indicators is compared with the pre-configured multi-indicator threshold system, and numerical mapping is performed within the corresponding level threshold range to obtain the individual score of each independent geomorphological evaluation unit.

[0052] Optionally, when calculating the engineering protection coverage, to prevent physical failure, the specific logic includes:

[0053] Extract the theoretical protection length and integrity coefficient representing the safety status of each individual protective project;

[0054] When multiple protective works overlap in space on the same shoreline, the spatial projection of the overlapping protection area is extracted and combined as the effective protection length to eliminate repeated length accumulation.

[0055] The initial engineering protection coverage rate is calculated by weighting based on the effective protection length, integrity coefficient, and the total required protection length of the pre-configured research river section.

[0056] The initial engineering protection coverage rate is truncated to prevent overflow, limiting the maximum value of the final calculation result to full coverage, and the overflow-prevented engineering protection coverage rate is output.

[0057] Optionally, after obtaining the overall river stability score, the following may also be included:

[0058] The overall river stability score is mapped to a pre-configured grading interval to determine the overall stability level of the studied river section;

[0059] The comprehensive scores of all independent geomorphic evaluation units are ranked sequentially.

[0060] Extract low-scoring landform units whose scores are below the pre-configured baseline or whose level is a preset unsafe level, summarize their spatial location and main score deduction indicators, and output a weak area identification report.

[0061] Optionally, the steps for calculating the bed flow equivalent include:

[0062] The bed-forming flow rate of the study river section was determined based on hydrological and sediment data;

[0063] Statistically evaluate the number of days in the year where the average daily flow rate is not less than the bed-building flow rate, and calculate the arithmetic mean of the average daily flow rate within that number of days;

[0064] The bed-forming flow equivalent is obtained by multiplying the ratio of the number of days to the total number of days in the evaluation year with the dimensionless ratio of the arithmetic mean of the daily flow rate to the bed-forming flow rate.

[0065] Optionally, the steps for calculating sediment transport intensity include:

[0066] Obtain the total annual sediment transport volume for the evaluation year and the average annual sediment transport volume for the preset baseline period;

[0067] The ratio of the total annual sediment transport to the average annual sediment transport is calculated to obtain the sediment transport intensity, which characterizes the river channel scouring and deposition trend.

[0068] A multi-index assessment system for the stability of river course in bifurcation sections includes:

[0069] The data acquisition module is used to acquire standardized basic datasets;

[0070] The system construction module is used to build a hierarchical evaluation system;

[0071] The unit division module is used to divide the studied river section into several independent geomorphological evaluation units;

[0072] The weight configuration module is used to determine the index weights and the spatial weights of geomorphic units;

[0073] The evaluation calculation module is used to calculate the individual scores of each independent geomorphological evaluation unit and then sum them up in weighted terms to obtain the overall river stability score.

[0074] The system is used to perform the multi-index assessment method for river regime stability of the bifurcation river section described in any of the above-mentioned methods.

[0075] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the multi-index assessment method for river regime stability in bifurcation sections as described in any of the preceding claims.

[0076] Beneficial effects: This invention discretizes river sections into independent evaluation units with clear physical meaning, overcoming the shortcomings of traditional assessment space being too broad, and introduces a dynamic spatial weighting mechanism to achieve accurate quantification of river morphology evolution in complex bifurcated river sections and automatic early warning for highly sensitive areas. Attached Figure Description

[0077] Figure 1 This is a schematic diagram of a multi-index assessment method for river stability in a branching river section provided in an embodiment of this application.

[0078] Figure 2This is a schematic diagram of the process of dividing the study river section into several independent geomorphic evaluation units using the topographic and geoscientific topological features in the standardized basic dataset provided in this application embodiment.

[0079] Figure 3 This is a schematic diagram of the process for obtaining the node control segment boundary set provided in the embodiments of this application.

[0080] Figure 4 This is a schematic diagram of the process for calculating individual scores for each independent geomorphological evaluation unit provided in the embodiments of this application.

[0081] Figure 5 This is a schematic diagram of the process for calculating the equivalent flow rate of the bed-forming flow provided in the embodiments of this application. Detailed Implementation

[0082] Example 1: A multi-index assessment method for the stability of river course in bifurcation sections is provided, such as... Figure 1 As shown, the method includes the following steps:

[0083] Step 101: Obtain the standardized basic dataset for the study river section. The standardized basic dataset includes hydrological and sediment data, multi-period measured cross-sectional data, and engineering data.

[0084] The standardized basic dataset is defined as a multi-source heterogeneous dataset after alignment with coordinate system 1 and elevation datum, and outlier processing. Specifically, hydrological and sediment data may include long-sequence daily flow records and annual sediment transport observation data from representative hydrological stations in the upper reaches of the study river section; multi-period measured cross-sectional data specifically include the station coordinates, measuring point elevations, and corresponding measurement times of fixed measured cross-sections of the study river section over the years; engineering data specifically include the spatial location points, protection lengths, structural types, project scales, and construction and maintenance records of bank protection projects, waterway improvement projects, groynes, and bottom protection projects.

[0085] In this embodiment, by standardizing the original scattered data, spatiotemporal reference biases between data from different sources and batches are eliminated. For example, all topographic coordinates can be uniformly converted to the CGCS2000 coordinate system, and the elevation datum can be uniformly corrected to the 1985 National Elevation Datum. This preprocessing process provides a reliable data foundation for the subsequent establishment of river evolution models, avoiding evaluation biases caused by data inconsistencies.

[0086] Step 102: Based on the standardized basic dataset, construct a hierarchical evaluation system that includes water and sediment inflow conditions, river channel geomorphological units, sandbar geomorphological units, and the intensity of engineering activities.

[0087] The hierarchical evaluation system is a multi-level assessment framework consisting of a target layer, a criterion layer, and an indicator layer. Specifically, the inflow and sediment conditions in the criterion layer are used to reflect changes in upstream dynamics; the stability of the channel geomorphological units is used to characterize the adjustment trend of the main channel and distributary morphology; the stability of the island and shoal geomorphological units is used to reflect the evolution characteristics of key geomorphological entities such as river islands and shoals; and the intensity of engineering activities is used to characterize the degree of constraint of human intervention on the natural evolution of the river channel.

[0088] In this embodiment, a hierarchical evaluation system is constructed to decompose the complex riverbed evolution process into three dimensions: driving factors, geomorphic response, and human control. Through this systematic approach, the evaluation model can encompass all major factors of natural evolution and human influence. For example, to address the unique issue of island and shoal changes in bifurcation sections, specific indicators are established under the island and shoal geomorphic unit criterion, thereby achieving an accurate description of local river morphology-sensitive areas.

[0089] Step 103: Based on the multi-period measured cross-section data in the standardized basic dataset, extract the topographic and geoscientific topological features of the study river section, and use the topographic and geoscientific topological features to divide the study river section into several independent geomorphological evaluation units.

[0090] Specifically, topographic and geoscientific features include the orientation of the thalweg line, the boundary between the shoal and channel, the location of the narrowing of the channel width, the variation of the thalweg curvature, and the connectivity topology between geomorphic units. Independent geomorphic evaluation units are evaluation entities that are spatially closed and functionally possess clearly defined geomorphic attributes, such as nodal control segments, main channel units, tributary units, transitional segment units, river island units, and side-shoal units.

[0091] Specifically, the partitioning process utilizes the topographic gradient and flow path in the riverbed digital elevation model to identify the width variations and distributary distribution within the river channel. Discretizing the continuous river space into several physically meaningful independent evaluation units solves the technical problem of traditional river morphology evaluation being too coarse and unable to accurately locate unstable areas. For example, a complete distributary segment can be divided into an inlet transition section, a left distributary channel unit, a right distributary channel unit, a mid-river island unit, and an outlet confluence section, ensuring that each evaluation indicator can be assigned to a specific micro-geomorphic unit.

[0092] Step 104: Based on the hierarchical evaluation system and multi-period measured cross-sectional data, extract the evolution characteristics of each independent geomorphological evaluation unit, determine the index weights and spatial weights according to the evolution characteristics, and obtain the weight system.

[0093] In other words, based on multi-period measured cross-sectional data, the evolution characteristics of each independent geomorphic evaluation unit are extracted; based on the hierarchical evaluation system and the aforementioned evolution characteristics, the index weights and spatial weights of geomorphic units are determined, thus obtaining a weighting system.

[0094] Among them, the indicator weights are the basic criterion weights of each evaluation indicator in the hierarchical evaluation system. The indicator weights are determined by comparing the importance of each pair of criteria layers and indicator layers, reflecting the contribution weight of each evaluation factor to river stability. Spatial weights are weight vectors assigned based on the evolution characteristics of independent geomorphological evaluation units. Evolution characteristics include the area of ​​sandbar activity, erosion and deposition intensity, and morphological change range of each geomorphological unit in historical periods.

[0095] In this embodiment, the weighting system is determined to achieve adaptive adjustment of the evaluation weights. Geomorphic units with more active evolutionary characteristics and a greater impact on the evolution of the entire river section have higher spatial weights. Conversely, if a unit remains stable for a long period, its spatial weight is relatively low. The introduction of spatial weights allows the evaluation results to automatically tilt towards highly sensitive areas of dramatic evolution, improving the ability to capture local instability risks.

[0096] Step 105: Based on the weighting system and standardized basic dataset, calculate the individual scores of each independent geomorphological evaluation unit and sum them by weight to obtain the corresponding unit comprehensive score. Based on the unit comprehensive score, obtain the overall river stability score.

[0097] In this embodiment, firstly, based on the type of each independent geomorphic evaluation unit, corresponding measured data are extracted from the standardized basic dataset, and quantitative values ​​of its respective indicators are calculated. For example, for river channel units, values ​​such as width-to-depth ratio and thalweg swing amplitude are calculated; for sandbar units, values ​​such as diversion ratio change rate and confluence point movement distance are calculated. The values ​​are then mapped to a percentage score according to a preset scoring standard.

[0098] The overall river stability score is obtained by multiplying the individual scores of each unit with the indicator weights and spatial weights in the weighting system and summing the results. Specifically, the inflow and sediment conditions and the intensity of engineering activities are macroscopic characteristic indicators of the entire river section, and their criterion layer score f _A and f _D Calculated directly from measured data across the entire river section. The stability of the river channel geomorphic unit and the sandbar geomorphic unit involves multiple independent geomorphic evaluation units, with the criterion layer score f... _B and f _C The value f is obtained by weighting and summing the individual scores of each unit using the spatial weights of the geomorphic units, i.e., f. _B or f _C It equals the sum of the products of the scores of each corresponding unit and their spatial weights.

[0099] Specifically, in calculating f _B At that time, the spatial weights of geomorphic units of each river channel class are renormalized within the river channel class unit range, that is, the sum of the spatial weights of all units of the river channel class is used as the normalization factor, so that f _B The calculation result is in the same position as f_A Within the same rating range; f _C The calculation method is similar, and it is renormalized within the scope of the shoal-type unit.

[0100] The overall score is calculated as follows:

[0101] F=We _A *f _A +We _B *f _B +We _C *f _C +We _D *f _D ;

[0102] Where F represents the overall river stability score, We _A We _B We _C We _D The weights of the four criterion layers are respectively: water and sediment inflow conditions, stability of the channel geomorphic unit, stability of the sandbar geomorphic unit, and intensity of engineering activities, f. _A f _B f _C f _D These are the weighted scores corresponding to the four criterion layers.

[0103] The calculated score F can be used as a technical basis for determining the stability level of the river. The higher the score, the more stable the river, and vice versa, the more drastic the river evolution or the risk of instability. This weighted aggregation mechanism realizes a logical closed loop from micro-unit evaluation to macro-level river section evaluation.

[0104] Example 2: Based on Example 1 above, this example further details the specific process of dividing the study river section into several independent geomorphic evaluation units. This example focuses on the extraction of topographic features and the identification logic of river section control nodes.

[0105] In one possible implementation, the study river segment is divided into several independent geomorphic evaluation units using topographic and geoscientific topological features from a standardized baseline dataset. Specifically, based on multi-period measured cross-sectional data from the standardized baseline dataset, topographic and geoscientific topological features of the study river segment are extracted, and these features are used to divide the study river segment into several independent geomorphic evaluation units, including:

[0106] Step 201: Spatial interpolation is performed on the multi-period measured cross-section data in the standardized basic dataset to construct a digital elevation model of the riverbed; the lowest elevation point of the digital elevation model of the riverbed is extracted from each cross-section along the longitudinal direction to obtain the sequence of the lowest elevation points of each cross-section, and the connected component analysis is performed on the riverbed elevation profile of each cross-section to obtain the connected component identification results of each cross-section.

[0107] When multiple independent low-value troughs separated by highlands are detected in the same cross section, each independent low-value trough is traced to form an independent thalweg branch, and the cross section position where the earliest independent low-value trough appears is recorded as the branch node coordinates; when only a single low-value trough exists in the same cross section, a single thalweg is traced based on the sequence of the lowest elevation points of each cross section.

[0108] When multiple thalweg branches merge into a single lowest elevation point trajectory, the location of the merging section is recorded as the coordinates of the confluence node. The thalweg vector set is composed of the thalweg branches, the single thalweg, the coordinates of the branching nodes, and the coordinates of the confluence node.

[0109] In this embodiment, the construction of the riverbed digital elevation model specifically utilizes the coordinates of measurement points and their corresponding elevation values ​​from each measured cross-section. Since the original cross-sectional data is discrete in the longitudinal direction, a method combining longitudinal linear interpolation based on the river channel centerline as the reference axis and transverse spline interpolation is employed to generate a regular grid topographic surface covering the entire studied river section. The grid resolution can be set to 5m×5m or 10m×10m according to the required evaluation accuracy.

[0110] Connectivity analysis specifically refers to identifying all continuous regions in the cross-section below the lowest elevation point after extracting the lowest elevation point on each cross-section, by setting a local elevation threshold relative to that lowest point. In this embodiment, the local elevation threshold is set as a preset proportional coefficient of the elevation difference between the normal water level elevation of the cross-section and the elevation of the lowest point of the riverbed. Engineers can determine a suitable proportional coefficient value by trial calculation on typical cross-sections and comparing the identification effect with known bifurcation segments based on the specific cross-sectional morphology and multi-year average water level data of the river section under study. When there are two or more isolated low-value regions on a cross-section, and each region is separated from the other by riverbed elevations above the threshold, i.e., river islands or shoals, the system determines that the river section is in a bifurcation state.

[0111] During the tracking process, the trajectory of the lowest point of each section is longitudinally smoothed to eliminate sawtooth fluctuations caused by measurement point errors or local pits.

[0112] Specifically, a weighted moving average operator is used to correct the planar coordinates of the thalweg:

[0113] y _smooth_i =(1 / H)*∑ j=i-r i+r (ω _j *y _j );

[0114] Among them, y _smooth_i Let $\mathbf{i}$ be the corrected x-coordinate of the deep-water point of the $i$-th cross-section, $j$ be the cross-section index variable traversed within the sliding window, $r$ be the radius of the sliding window, and $ω$ be the value of $\mathbf{i}$. _jy is the distance weighting factor. _j Let be the original x-coordinate of the thalweg point at the j-th cross-section, and H be the total weight within the window. The sliding window radius r and the distance weight factor ω... _j The required cross-sectional spacing and the smoothing accuracy of the thalweg line can be determined through trial calculations using conventional parameters.

[0115] The thalweg vector set generated in this way can accurately reflect the main flow path of the main channel and the branch channels. The coordinates of the branch nodes record the starting position where the flow begins to differentiate, while the coordinates of the confluence nodes record the position where the flow merges at the end of the sandbar. These topological key points constitute the basic coordinate system for subsequent geomorphic unit cutting.

[0116] Step 202, utilizing the topographic and geoscientific topological features in the standardized basic dataset, divides the study river section into several independent geomorphological evaluation units. This also includes obtaining the node control segment boundary set, which involves: extracting the horizontal distance between the left and right shoal-channel boundaries as the river width sequence along the river, and detecting the narrowing points in the river width sequence; calculating the curvature along the river from the thalweg vector set and identifying locations of curvature abrupt changes; extracting engineering constraint zones with continuous rigid protection based on engineering data in the standardized basic dataset; performing longitudinal spatial overlay analysis on the narrowing points, curvature abrupt changes, and engineering constraint zones, and extracting spatially overlapping areas with longitudinal spacing less than a preset tolerance threshold to obtain the node control segment boundary set, such as... Figure 3 As shown.

[0117] In this embodiment, the river width sequence along the course reflects the planar morphological expansion and contraction characteristics of the river channel cross-section. The curvature along the course of the thalweg vector set is calculated based on the planar coordinate components of the thalweg points.

[0118] Calculate the curvature value K at each point _i =|Δφ _i / Δs _i |;

[0119] Among them, K _i Let Δφ be the curvature of the i-th abyssal point. _i Δs represents the change in angle between adjacent paragraphs. _i This represents the increment of arc length along the course. The location of abrupt changes in curvature usually corresponds to the turning point where the river channel transitions from a straight section to a curve or from a curve to a straight section.

[0120] Engineering constraint zones refer to areas on both sides of a riverbank controlled by continuous stone revetments, precast block slope protection, or groynes. These artificial structures provide rigid boundaries to the riverbank, limiting the lateral sway of the river channel.

[0121] During longitudinal spatial overlay analysis, the system projects local minimum points of river width, extreme points where the rate of curvature change exceeds a preset threshold, and the start and end points of engineering constraint zones onto the same longitudinal axis. If the longitudinal spacing between these three types of feature points is less than a preset tolerance threshold, such as less than 200m, the area is determined to be a node control segment. The node control segment boundary set defines the inlet and outlet cross-section locations of key segments capable of stabilizing the river regime.

[0122] Furthermore, in some alternative implementations, when extracting the river width sequence along the course, a sliding window mean filter can be used to denoise the original width data in order to eliminate instantaneous width fluctuations caused by irregularities in the shoreline.

[0123] Furthermore, as an alternative approach, if the density of measured cross-sectional data is insufficient to construct a high-precision digital elevation model of the riverbed, the low-water shoreline features extracted from multiple remote sensing images can be combined to help determine the distribution of river width along its course and the planar outline of sandbars, thereby supplementing topographic and geoscientific features. The fusion and utilization of multi-source data can improve the reliability of unit subdivision in data-scarce river sections.

[0124] In some embodiments, the study river segment is divided into several independent geomorphic evaluation units using topographic and geoscientific topological features in a standardized base dataset, and may further include:

[0125] Extract the horizontal distance between the boundary lines of the left and right shoals and channels as the river width sequence along the course, and detect the narrowing points of the river width within it;

[0126] Calculate the curvature along the path of the thalweg vector set and identify locations of abrupt curvature changes;

[0127] Based on the engineering data in the standardized basic dataset, extract the engineering constraint areas with continuous rigid protection;

[0128] Identify the bifurcation nodes of the thalweg and use their coordinates as a reference for the node-controlled boundary segments.

[0129] Example 3: Based on Example 2 above, this example further details the steps for dividing the studied river section into several independent geomorphological evaluation units. This example focuses on an automatic beach-channel delineation mechanism based on elevation statistical characteristics.

[0130] In one possible implementation, the study river segment is divided into several independent geomorphic evaluation units using topographic and geoscientific topological features from a standardized base dataset, such as... Figure 2 As shown, it also includes the following steps:

[0131] Step 301: Perform frequency statistics on the elevation values ​​of the cross sections in the digital elevation model of the riverbed to generate an elevation probability density curve.

[0132] In this embodiment, frequency statistics of the elevation values ​​of cross sections in the riverbed digital elevation model are performed as follows: a series of cross sections are extracted along the longitudinal direction of the river at preset intervals. For all elevation measurement points on each cross section, a fixed step size for the elevation statistics interval is set, for example, 0.1m or 0.5m. The number of elevation points in each interval is counted. The number of elevation points in each interval is divided by the total number of elevation points in that cross section to obtain the frequency distribution value corresponding to each elevation interval. A continuous elevation probability density curve is generated by fitting the elevation value on the horizontal axis and the corresponding frequency distribution value on the vertical axis. This curve reflects the spatial concentration of topographic elevation on a specific cross section.

[0133] Step 302: Detect the bimodal feature in the elevation probability density curve, and calculate the derivative of the elevation probability density curve. Determine the valley elevation between the two peaks by locating the zero crossover point of the derivative, and determine the valley elevation as the boundary elevation between the beach and the channel.

[0134] The bimodal characteristic in the elevation probability density curve corresponds physically to the typical stepped landform of the bifurcation river section. Specifically, the first probability density peak in the low-elevation direction corresponds to the vast and relatively flat riverbed region; the second probability density peak in the elevation direction corresponds to the higher and relatively gentler top surface of the shoal. The concave area between the two peaks corresponds to the steeper transitional bank slope.

[0135] To mathematically pinpoint the elevation boundary of this transition region, the system performs first-order derivative calculations on the elevation probability density curve. After detecting two maxima (bimodalities), the system searches for elevation coordinates within the elevation interval between the two maxima where the first derivative is 0 and the second derivative is greater than 0; these are mathematically local minima. The elevation corresponding to this minimum point is the valley elevation.

[0136] This method is used to determine the elevation of the riverbed boundary, thereby eliminating the error caused by the reliance on fixed empirical elevation values ​​in traditional methods, which result in poor cross-temporal adaptability, and realizing adaptive physical boundary extraction based on the current real statistical morphology of the riverbed.

[0137] Step 303: Track the contour lines of the floodplain-channel boundary elevation on the riverbed digital elevation model to generate continuous floodplain-channel boundary lines on both the left and right sides. Use the floodplain-channel boundary lines to divide the riverbed plane into the riverbed area and the floodplain area.

[0138] After determining the elevation of the channel-shoal boundary at each cross-section, the system searches for a set of spatial points in the 3D digital elevation model of the riverbed that match the valley elevation, and then connects these scattered points longitudinally along the river channel using a contour tracing algorithm. The channel-shoal boundary lines on both sides are represented in the spatial data structure as two sets of two-dimensional vector polylines. Through these two sets of vector boundaries, the continuous riverbed plane is divided into the channel region located between the two boundary lines, and the shoal-shoal region located outside the boundary lines or surrounded by multiple boundary lines.

[0139] Furthermore, in some optional implementations, if the topographic evolution of a certain section is in a period of intense scouring and deposition, resulting in the bimodal characteristics of its elevation probability density curve being insignificant, i.e. the local minimum points are difficult to converge, the system can obtain the determined beach-channel boundary elevation between its upstream and downstream sections, and use the longitudinal spatial distance as a weighting factor to perform linear interpolation calculation to obtain the estimated boundary elevation of the current section, ensuring the spatial continuity of contour line tracking along the route.

[0140] In some embodiments, the study river segment is divided into several independent geomorphic evaluation units using topographic and geoscientific topological features in a standardized base dataset, and may further include:

[0141] Obtain the average waterline of the river channel from the standardized base dataset;

[0142] The average waterline of the river channel is used as the boundary between the sandbars and the riverbed, dividing the riverbed into the riverbed area and the sandbar area.

[0143] The thalweg line (valley line) is extracted within the river channel area, and the stability of the deep channel is determined based on the planar displacement amplitude of the thalweg line in multiple historical periods.

[0144] Example 4, based on Example 3 above, further describes the process of dividing the study river section into several independent geomorphic evaluation units, as well as the determination of geomorphic unit types and the closed-loop fault-tolerant verification mechanism. This example focuses on the handling logic for boundary truncation and incalculable index anomalies in complex water networks.

[0145] In one possible implementation, the study river segment is divided into several independent geomorphic evaluation units using the topographic and geoscientific topological features in a standardized base dataset, and the following steps are also included:

[0146] Step 401: Using the coordinates of the branching nodes, the coordinates of the confluence nodes, and the boundary set of the node control segments, the continuous river channel is longitudinally divided into several river segments.

[0147] Step 402: Based on the number of independent branches of the thalweg vector set contained in the river section, the river section in the channel area is determined as a node control unit, a distributary unit or a transition section unit, and the distributary unit is divided into a main distributary unit and a branch distributary unit by using the cross-sectional water flow area.

[0148] Step 403: Based on the enclosing relationship of the beach-channel boundary line, the closed highlands or adjacent beach bodies within the island-shoal area are respectively identified as river island units or side beach units, thereby obtaining the initial geomorphological evaluation units carrying type labels and boundary information.

[0149] In some embodiments, the cross-sectional water-passing area of ​​each channel unit is calculated based on the riverbed digital elevation model and the beach-channel boundary elevation. The channel units are divided into main channel units and branch channel units according to the size of the cross-sectional water-passing area, with the one with the largest water-passing area being determined as the main channel unit.

[0150] In this embodiment, segmentation is performed using coordinates and boundary sets, specifically manifested as orthogonal truncation in space. Due to differences in hydrodynamic characteristics, segments with two or more independent flow paths are identified as branch units. When determining the type of main branch, the effective flow area of ​​the cross-section at the location of each branch is obtained, and the areas are arranged in descending order of size. The largest area is marked as the main branch unit, and the rest are marked as branch units.

[0151] For sandbar areas, a closed highland refers to a landform entity whose entire plan is surrounded by water flow paths, i.e., branches of the thalweg, and is classified as a mid-river island unit or a mid-shoal unit. If the planar outline of a shoal body is adjacent to a thalweg branch on only one side or part of its perimeter, and connected to the riverbank on the other side, it is classified as a side shoal unit. The upstream endpoint of the island body along the main water flow direction is defined as the island head, and the downstream endpoint is defined as the island tail. Through the above topological connectivity determination logic, the system assigns a specific type label to each segmented spatial polygon.

[0152] Using the topographic and geoscientific topological features in the standardized basic dataset, the study river section is divided into several independent geomorphological evaluation units.

[0153] Specifically, based on multi-period measured cross-sectional data from a standardized basic dataset, topographic and geoscientific topological features of the study river segment are extracted. These features are then used to divide the study river segment into several independent geomorphic evaluation units. The method also includes: performing an integrity check on the initial geomorphic evaluation units. The integrity check steps include:

[0154] Verify whether the initial geomorphological evaluation unit completely includes the thalweg branch and whether it has an inlet section and an outlet section;

[0155] When the integrity condition is not met, the boundary of the initial geomorphological evaluation unit is extrapolated along the branch direction of the thalweg line to the natural turning point or the measured section position to obtain the boundary adjustment unit.

[0156] Re-execute the type determination rules to update the type label for the boundary adjustment unit, and then perform the integrity verification step again.

[0157] In some embodiments, when the integrity condition is met, the current initial geomorphological evaluation unit is retained as a geomorphological evaluation unit that has passed the verification.

[0158] Natural turning points are points in the digital elevation model of the riverbed where the curvature changes significantly.

[0159] In this embodiment, integrity checks are performed to ensure that the various hydraulic and geomorphological parameters can be solved independently in subsequent calculation stages. For example, the calculation of the thalweg swing amplitude parameter depends on a complete thalweg line segment, and the calculation of the split ratio depends on clearly defined channel inlet and outlet sections.

[0160] Specifically, whether the thalweg is truncated is determined by calculating the spatial distance between the thalweg endpoint and the cell boundary. If the thalweg branch is not completely contained within the current cell, the system will trigger a boundary adjustment mechanism. Extrapolation of the boundary involves extending the cell's longitudinal boundary along the tangent of the thalweg or the direction of the main water flow until a natural inflection point where the riverbed curvature changes significantly is encountered, or until the nearest measured cross-section with valid measurement data is reached. After the boundary change, the original geometric features may change; therefore, the previously described steps of calculating the water passage area and detecting topological enclosure relationships must be re-executed using the updated boundary to update the type label.

[0161] The process of re-performing the integrity verification step on the boundary adjustment unit specifically includes:

[0162] A pre-configured maximum number of boundary iteration adjustments is set and counted during the cyclic execution of the integrity verification step. When the number of boundary adjustments reaches the maximum number of boundary iteration adjustments and the integrity condition is still not met, the boundary extrapolation operation for conflicting units is stopped. Conflicting units are boundary adjustment units that have failed the verification. In other words, the boundary extrapolation operation for boundary adjustment units that have failed the integrity condition is stopped, and they are marked as conflicting units.

[0163] Conflicting units that fail the verification are merged into composite geomorphic units. When calculating individual scores, the composite geomorphic unit is weighted according to the area ratio of the subtypes contained within it, and the final geomorphic evaluation unit that passes the verification is output as an independent geomorphic evaluation unit.

[0164] In some embodiments, boundary adjustment units that fail verification are merged into composite landform units. The area ratio of each subtype contained within the composite landform unit is calculated. When calculating individual scores, weighting is performed based on the area ratio of each subtype. The composite landform unit and the verified landform evaluation units are output together as the final landform evaluation unit, i.e., the independent landform evaluation unit.

[0165] In this embodiment, setting a maximum number of boundary iteration adjustments is to prevent the automatic partitioning algorithm from getting stuck in an infinite loop deadlock when encountering extremely fragmented terrain. For example, the maximum number of iteration adjustments is preset to 3. The system increments the built-in counter by 1 each time it performs a boundary extrapolation operation.

[0166] When the counter reaches 3 times, but due to the extremely complex river topography, such as multiple small sandbars intersecting, some units cannot simultaneously meet the conditions of having inlet / outlet sections and containing a complete thalweg, the system will trigger a downgrade merging mechanism. Specifically, this involves merging multiple adjacent initial units that are currently causing logical conflicts into a single unit, marked as a composite geomorphic unit. For example, a main channel with ambiguous boundaries and a partially separated midshoal are merged.

[0167] In subsequent calculations of individual scores, since composite landform units lose their individual type characteristics, an area-weighted approach is used to calculate their comprehensive score to ensure that the evaluation process is not interrupted. The calculation is as follows:

[0168] Score _Complex =∑ m=1 M (Score _m *(Area _m / Area _total ));

[0169] Among them, Score _Complex The score is the individual score calculated for this composite geomorphic unit. _m To determine the estimated score that the m-th subtype unit should receive if it can be independently calculated before merging, Area _m Area is the horizontal projected area of ​​this subtype. _total M represents the total projected area of ​​the composite landform unit, and M represents the number of subtypes it contains.

[0170] After the above closed-loop verification and fault-tolerant degradation processing, the final geomorphological evaluation unit output by the system ensures both the integrity of spatial coverage and the computability of subsequent evaluation streams in terms of data structure.

[0171] As an alternative, if the integrity check still fails after multiple iterations, in addition to using a composite unit merging mechanism, the system can also introduce a manual intervention interface. In this case, the system pauses the automatic processing flow, highlights the conflicting boundary regions, receives an externally input set of manually derived boundary coordinates, forcibly cuts the units based on this coordinate set, and then continues with subsequent evaluation steps.

[0172] In the above embodiments, boundary positioning based on the zero-crossing point of the elevation probability density derivative and closed-loop topology verification with built-in fault-tolerant degradation mechanism are adopted. This mechanism eliminates the subjective interference of human experience, enabling irregular continuous riverbeds to be adaptively deconstructed into independent evaluation units with clear physical meaning, eliminating the risk of system dead loops under extreme terrain, and improving the robustness of automated processing of complex terrain.

[0173] Example 5: Based on Example 1 above, this example further describes in detail the processing mechanism for multi-period comparative evaluation needs in the step of dividing the study river section into several independent geomorphological evaluation units. Since natural river channels have dynamic evolution characteristics, the geomorphological attributes of the same spatial location may change over time. This example focuses on solving the problem of matching and aligning the boundaries of spatial evaluation units between multi-period topographic data (multi-period measured cross-sectional data).

[0174] In one possible implementation, the step of dividing the study river section into several independent geomorphological evaluation units, in order to meet the needs of multi-period comparative evaluation, further includes the following steps:

[0175] Step 501: Extract multi-period measured cross-sectional data from different years and delineate the boundaries of geomorphic units for each single time phase in each year.

[0176] In this embodiment, for assessment tasks that require examining the evolution trend of river morphology over many years, the system separates terrain slices from the standardized basic dataset according to time labels for different observation years. For each independent year, the system calls the terrain surface interpolation, thallopath tracing, and shoal-channel identification algorithms described in the previous embodiments to generate a set of geomorphic polygons for that specific time node.

[0177] For example, measured cross-sectional elevation points for 2020, 2022, and 2024 are extracted separately to generate independent geomorphic unit boundary layers for each year. In this case, the unit boundaries in each layer only reflect the transient geomorphic characteristics during the dry season or post-flood mapping of that year.

[0178] Step 502: Based on the spatial location and type attributes of the boundaries of geomorphic units in each year, perform cross-temporal correlation matching on the geomorphic units in each year, identify the same geomorphic entity with location offset or morphological change, and extract its maximum spatial envelope range in multiple time phases.

[0179] In other words, based on the spatial overlap and type attribute consistency of the boundaries of geomorphic units in each year, cross-period correlation matching is performed on the geomorphic units in each year to identify the same geomorphic entity with positional shifts or morphological changes, and extract its maximum spatial envelope range in multiple periods.

[0180] Cross-temporal correlation matching can be determined based on the spatial overlap and type attribute consistency of geomorphic units in adjacent years. Engineers can use the ratio of spatially intersecting areas exceeding a preset threshold and the same type label as matching conditions, or use other conventional spatial entity correlation matching methods.

[0181] Specifically, the judgment logic for cross-temporal correlation matching is as follows: For the geomorphic unit polygon P in year t... t The geomorphic unit polygon P in year t+1 t+1 The intersection-to-union area (IoU) is calculated as the ratio of the spatial intersection area to the spatial union area of ​​the two entities. When the IoU is greater than a preset matching threshold and the two entities have the same type label, they are determined to be mapping objects of the same geomorphic entity in different time phases. The matching threshold can be determined based on the activity level of river channel evolution. For cases where the type label changes, such as when a riverbank evolves into a river island, the spatial IoU is used as the sole matching criterion.

[0182] In multiple assessments, the same geomorphic entity can evolve spatially due to water erosion or siltation. Positional shifts typically manifest as the main channel swaying laterally towards the left or right bank, while morphological changes are usually reflected in the expansion of river islands or the shrinkage of riverbanks. Under this dynamic change, extracting the maximum spatial envelope involves performing a spatial union operation on the two-dimensional polygon boundaries of the entity across all observation years in the geographic information coordinate system.

[0183] Specifically, taking a certain island unit in the river as an example, let its boundary polygon in the first year be A. _1 The boundary polygon in the second year is A. _2 The boundary polygon in year n is A _n Then the maximum spatial envelope range A of the island in the river. _max It is represented as the Boolean logical union of all the above polygons, i.e., A _max =A _1 ∪A _2 ∪...∪A _n ∪ represents the union operator. The envelope obtained by this operation can cover all spatial regions where the terrain entity has been active throughout the entire evaluation period.

[0184] Step 503: Using the maximum spatial envelope range as a unified mapping benchmark, the spatial boundaries of independent geomorphic evaluation units in multi-phase assessment tasks are consistently corrected to obtain consistent independent geomorphic evaluation units, so as to eliminate the impact of dynamic changes on boundary tracking.

[0185] In this embodiment, a consistency correction is performed to establish a common spatial denominator for intertemporal comparisons. Directly using the changing boundaries of a single time phase to calculate multi-year sedimentation volumes or geometric parameter differences can lead to spatial misalignment of the calculation domain, resulting in statistical errors.

[0186] By mapping the calculated maximum spatial envelope back to the layers for each year, replacing its original transient boundary, the geomorphic unit shares the same outer contour line across all evaluation years. When calculating indicators requiring equivalent comparison, such as multi-year scouring and sedimentation changes and local width-to-depth ratio evolution, the system uniformly reads the effective topographic data within the envelope. This processing mechanism eliminates the spatial segmentation chaos caused by the expansion and contraction of sandbars or the displacement of main channels, achieving spatial benchmark locking in time-series dynamic analysis.

[0187] Furthermore, in some alternative implementations, besides employing the strategy of extracting the maximum spatial envelope, a fixed base boundary strategy can also be used as an alternative. Specifically, the fixed base boundary strategy refers to forcibly designating the geomorphic unit division results of the earliest year in the evaluation time series as a permanent reference boundary. In the evaluation of all subsequent target years, the topological subdivision calculation is not restarted; instead, the elevation measurement data of subsequent years are directly superimposed onto this initial fixed boundary to calculate scour and deposition properties. This alternative eliminates the complex spatial union operation steps, consumes less computational resources, and is more suitable for straight or slightly meandering river sections where the river's planar morphology is relatively controlled and no major structural changes such as main-branch translocation have occurred.

[0188] Example 6: Based on Example 1 above, this example further details the process of determining index weights and spatial weights to obtain the weight system. This example focuses on addressing the spatial uniformity deficiency in weight allocation in traditional river morphology assessment and proposes a dynamic spatial weight allocation mechanism based on evolutionary activity.

[0189] In one possible implementation, determining the index weights and spatial weights includes the following steps:

[0190] Step 601: Determine the basic criterion weights of each evaluation indicator under the hierarchical evaluation system; in other words, compare the importance of each evaluation indicator under the hierarchical evaluation system pairwise to determine the basic criterion weights.

[0191] In this embodiment, the basic criterion weights refer to static values ​​reflecting the relative importance of various evaluation factors, such as water and sediment inflow conditions, stability of river channel geomorphic units, stability of sandbar geomorphic units, and intensity of engineering activities. Specifically, the analytic hierarchy process (AHP) is used to compare the importance of the above factors pairwise and assign values ​​to construct a judgment matrix.

[0192] By calculating the largest eigenvalue and corresponding eigenvector of the judgment matrix, and performing normalization and consistency checks, the importance ratio of each evaluation factor at the theoretical level is obtained, and this ratio is used as the basic criterion weight. This weight does not change with the geographical location of a specific spatial unit, constituting the static benchmark of the evaluation model.

[0193] Step 602: Based on multi-period measured cross-sectional data, extract the area of ​​beach activity and the magnitude of erosion and deposition changes of each independent geomorphological evaluation unit in the long-term evolution history.

[0194] The active area of ​​sandbars is used to characterize the active range of a geomorphic entity on a horizontal two-dimensional plane. The active area of ​​sandbars is a broadly defined indicator of the active range for all types of independent geomorphic evaluation units, including the area of ​​boundary changes caused by the main channel's movement in river channel units and the area of ​​contour changes caused by erosion and deposition in sandbar units. In specific calculations, boundary layers of geomorphic units from two different evaluation years are extracted, and the horizontal projected area of ​​the areas where their spatial morphologies do not overlap is calculated.

[0195] The scour-deposition variation range is used to characterize the degree of drastic evolution of landforms in terms of vertical elevation. In specific calculations, the elevation surfaces corresponding to multiple periods of measured cross-sectional data are subtracted to obtain the elevation difference of the grid nodes. Areas with absolute elevation differences greater than a preset error threshold are extracted, and the average scour depth or siltation height is calculated as the scour-deposition variation range. The preset error threshold can be set to 0.2m.

[0196] Step 603: Based on the contribution ratio of the area of ​​sandbar activity and the magnitude of scouring and deposition to the overall river morphology evolution of the entire river section, spatial influence factors are allocated according to nonlinear mapping to generate spatial weights of geomorphic units; that is, the spatial weights of geomorphic units of each independent geomorphic evaluation unit are allocated according to the contribution ratio.

[0197] In this embodiment, the spatial weighting of geomorphic units is introduced because different geomorphic units, due to differences in their dynamic environments, exhibit significant nonlinear characteristics in their impact on overall river stability. For example, actively evolving mid-channel shoals with intense scouring and deposition should have a greater influence in the overall score.

[0198] Specifically, the spatial weights of geomorphic units are calculated using the following relationship:

[0199] W _space_i =(A _Act_i *V _Amp_i ) / ∑j=1 N (A _Act_j *V _Amp_j );

[0200] Among them, W _space_i Let A be the spatial weight of the i-th independent geomorphic evaluation unit. _Act_i V represents the active area of ​​the shoal in the i-th independent geomorphological evaluation unit. _Amp_i Let N be the scour and deposition variation range of the i-th independent geomorphic evaluation unit, and N be the total number of independent geomorphic evaluation units in the entire river section. j=1 N This represents the summation of the product terms across all partitioned units. Specifically, the product term (A) for each independent geomorphological evaluation unit... _Act_i *V _Amp_i The original value of the spatial influence factor corresponding to this unit is denoted as W. After normalization across the entire river section, the final spatial weight W of the geomorphic unit is obtained. _space_i .

[0201] The above formula performs a product operation on two independent physical indicators, the area of ​​beach activity and the magnitude of erosion and deposition, and then normalizes them. This product operation makes the spatial weights respond non-linearly to each single factor: when one factor remains unchanged, the spatial weights do not simply increase linearly with the other factor, but are proportionally scaled by the range of the first factor, thus realizing a non-linear mapping from physical variables to the weight space.

[0202] The above calculation logic directly transforms evolutionary activity into spatial influence factors in the evaluation system. When a geomorphic unit experiences severe erosion and deposition, its product term increases, and the spatial weight assigned to the geomorphic unit increases accordingly. This mechanism allows the evaluation model to automatically focus on and amplify the evolutionary characteristics of highly sensitive areas, preventing localized severe instability from being masked by the average treatment across the entire river section.

[0203] Step 604: Combine the basic criterion weights with the spatial weights of geomorphic units to construct a weight system.

[0204] The merging operation specifically involves coupling the weights of fundamental criteria reflecting the inherent logic of the indicators with the spatial weights of geomorphic units reflecting differences in spatial evolution. In the subsequent weighted aggregation calculation of individual scores, the final comprehensive weight of a specific indicator is the product of the fundamental criterion weight and the geomorphic unit spatial weight. The resulting weighting system combines the stability of static rules with the adaptability to dynamic spatial environments.

[0205] Furthermore, in some alternative implementations, considering that extreme flood years may cause abnormal peaks in the scour and deposition variations of individual geomorphic units, resulting in excessive concentration of the calculated spatial weights of geomorphic units on a single unit, a logarithmic or exponential decay function can be applied to the product term of the active area of ​​the shoal and the scour and deposition variation amplitude for smoothing and suppression before performing nonlinear mapping assignment. For example, the base-10 logarithm of this product term can be calculated to reduce the risk of weight overflow from extreme evolution data and improve the computational robustness of the weighting system under complex water and sediment conditions.

[0206] In the above embodiments, a unified mapping benchmark for the maximum envelope surface of multiple periods was constructed, and a dynamic configuration method for spatial weights of the fusion evolution area and scouring and silting amplitude was introduced. This locked the spatial reference base for temporal evolution, enabling the evaluation model to automatically focus on and amplify the features of highly sensitive areas with dramatic evolution, thus improving the accuracy of capturing and warning of local instability risks to the micro-geomorphic entity level.

[0207] Through the aforementioned dynamic spatial weight configuration, when a geomorphic unit experiences severe erosion and deposition or rapid changes in its planar morphology, its spatial weight automatically increases, causing the score change of that unit to have a greater impact on the overall score of the entire river section. This mechanism ensures that the instability characteristics of locally highly sensitive areas are not diluted by the high scores of other stable areas, thus improving the sensitivity of the assessment model in capturing local instability risks.

[0208] Example 7 further details the specific process for calculating the individual scores of each independent geomorphological evaluation unit. It focuses on elucidating the quantitative calculation logic of multi-dimensional evaluation indicators, particularly the equivalent conversion mechanism of water flow and sediment source driving forces, and the overflow prevention mechanism in the calculation process of engineering intervention indicators. In one possible implementation, such as... Figure 4 As shown, it includes the following steps:

[0209] Step 701: Based on hydrological and sediment data, calculate the bed-forming flow equivalent and sediment transport intensity under the conditions of incoming water and sediment.

[0210] like Figure 5 As shown, the steps for calculating the equivalent bed-forming flow include: determining the bed-forming flow of the study section based on hydrological and sediment data; statistically evaluating the number of days in the year where the average daily flow is not less than the bed-forming flow, and calculating the arithmetic mean of the average daily flow within that number of days; multiplying the ratio of the number of days to the total number of days in the evaluation year with the dimensionless ratio of the arithmetic mean of the average daily flow to the bed-forming flow to obtain the equivalent bed-forming flow.

[0211] In this embodiment, the bed-forming flow rate refers to the characteristic flow rate that comprehensively reflects the river's scouring and deposition characteristics and plays a decisive role in shaping the riverbed morphology. The system can determine this benchmark value using a preset floodplain flow method. The construction of the bed-forming flow rate equivalent takes into account that the largest flood peak of the year cannot fully reflect the bed-forming effect of the water flow, and the duration of the flow rate exceeding the benchmark value is also a core driving variable. Therefore, the equivalent is calculated using the following mathematical formula:

[0212] Q _e =(N _B / T)*(Q _B / Q _0 );

[0213] Among them, Q _e For bed flow equivalent, N _B To evaluate the number of days in a year where the average daily flow rate is greater than or equal to the bed-forming flow rate, T is the total number of days in the evaluation year, and Q is... _B Q is the arithmetic mean of the daily average flow over the given number of days. _0 To study the bed-forming flow of the river section.

[0214] This computational mechanism couples the flood's exceedance intensity with its exceedance time ratio, transforming the hydrological sequence, which contains both time and volume dimensions, into a dimensionless comprehensive equivalent operator. A larger value indicates a stronger shaping effect of upstream water flow on the riverbed within the assessed year.

[0215] The steps for calculating sediment transport intensity include: obtaining the total annual sediment transport in the evaluation year and the average annual sediment transport in the preset baseline period; calculating the ratio of the total annual sediment transport to the average annual sediment transport to obtain the sediment transport intensity that characterizes the river channel scouring and deposition trend.

[0216] The preset baseline period can be a long-term statistical period of nearly 30 years. Sediment transport intensity reflects the abundance or scarcity of upstream sediment sources, and its calculation formula is as follows:

[0217] G _s =S _s / S _Base ;

[0218] Among them, G _s For sediment transport intensity, S _s To evaluate the total annual sediment load, S _Base This represents the average annual sediment load for the preset baseline period.

[0219] This ratio serves as a trend coefficient. When the calculated result is greater than 1, it indicates that there is too much sediment and the river channel may show a siltation trend. When the calculated result is less than 1, it indicates that there is too little sediment and the scouring effect of clear water is intensified.

[0220] Step 702: Based on the spatial boundary changes of the independent geomorphic evaluation unit determined by multi-period measured cross-sectional data at different times, calculate the lateral swing amplitude of the thalweg and the longitudinal movement distance of the confluence point.

[0221] This step can also involve comparing the spatial boundaries of multiple independent geomorphological evaluation units, extracting the changes in spatial boundaries, and calculating the lateral swing amplitude of the thalweg and the longitudinal movement distance of the confluence point based on the changes in spatial boundaries.

[0222] In this embodiment, the lateral oscillation amplitude of the thoroughfare is used to quantitatively calculate the degree of instability of the main channel in the lateral plane. Under the constraint of a unified spatiotemporal reference, the lateral coordinate offsets of the recent and previous thoroughfare lines on a fixed reference section within the same channel unit are extracted, and the root mean square offset is calculated:

[0223] Δ=sqrt((1 / n)*∑((y _t2 -y _t1 ) 2 ));

[0224] Where Δ is the lateral swing amplitude of the deep pool, n is the total number of cross-sections extracted within the unit, and y _t2 Let y be the lateral coordinate of the thalweg line at a specific cross-section. _t1 ∑ represents the lateral coordinate of the thalweg line at the corresponding cross section, ∑ represents the summation of the squared lateral coordinate offsets of all extracted cross sections, and sqrt represents the square root of the summation result divided by the total number of cross sections.

[0225] The longitudinal movement distance of the confluence point is used to calculate the morphological changes of the sandbar landforms along the downstream direction of the water flow. After extracting the coordinates of the merged nodes of the multi-channel valleys from the previous and recent periods, the absolute mileage difference along the river centerline is calculated:

[0226] L _m =|s _t2 -s _t1 |;wherein, L _m s represents the longitudinal movement distance of the confluence point. _t2 s represents the longitudinal river channel mileage corresponding to the recent node coordinates. _t1 This refers to the longitudinal river mileage corresponding to the coordinates of nodes with the same attributes in the previous stage.

[0227] Step 703: Based on engineering data, calculate the engineering protection coverage rate and the volume of revetment per unit shoreline, which characterize the intensity of engineering activities.

[0228] To prevent physical failure when calculating the protection coverage of an engineering project, the specific steps include:

[0229] Extract the theoretical protection length and integrity coefficient representing the safety status of each individual protective project; when multiple protective projects overlap spatially on the same shoreline, extract the spatial projection union of the overlapping protection area as the effective protection length to eliminate repeated length accumulation.

[0230] Based on the effective protection length, integrity coefficient, and the total required protection length of the pre-configured research river section, the initial engineering protection coverage rate is calculated using a weighted average. The initial engineering protection coverage rate is then subjected to overflow truncation processing, limiting the maximum upper limit of the final calculation result to complete coverage, i.e., 100%, and the overflow-preventing engineering protection coverage rate is output.

[0231] In some embodiments, it can also be:

[0232] Based on the engineering data, the theoretical protection length of each individual protective project is extracted, and the integrity coefficient representing the safety status of the project is determined based on the construction and maintenance records in the engineering data. When multiple protective projects overlap in space on the same shoreline, the spatial projection union of the overlapping protection area is extracted as the effective protection length to eliminate repeated length accumulation. When there is no spatial overlap between individual protective projects, the theoretical protection length is used as the effective protection length.

[0233] In this embodiment, the integrity coefficient is a reduction factor characterizing the ability of the revetment project to resist water erosion. For example, it is 1 in the intact state without damage, 0.7 in the slightly damaged state, and 0 in the state of loss of function.

[0234] The overflow prevention and truncation process is implemented to address calculation errors caused by multiple protection measures in complex engineering sections. In some high-risk shoreline sections, a bottom embankment and an overlying dry-laid stone revetment may be laid simultaneously. If the absolute lengths of various engineering elements are directly added together, the cumulative length will exceed the actual total shoreline length, causing the coverage rate to overflow its reasonable value range boundary.

[0235] To this end, the system utilizes geographic information algorithms to extract the union of longitudinal spatial projections of multi-layered structures, ensuring that the shoreline length in the same dimension is calculated only once, and employs the following calculation formula:

[0236] E _p_init =∑(L _valid_k *c _k ) / L _total ;

[0237] E _p =min(1,E _p_init );

[0238] Among them, E _p_init For the initial engineering protection coverage, L _valid_k c is the effective protection length extracted for the k-th engineering segment. _kL represents the integrity coefficient corresponding to the k-th engineering segment. _total The total required protection length for the pre-configured study river section is given by ∑, which represents the summation of the products of all engineering sections. _p The final output overflow prevention coverage rate is defined by min, which indicates the minimum value of each element within the parentheses.

[0239] Furthermore, in addition to the coverage rate indicator, the system also obtains the total volume of the constructed revetment, calculates its ratio to the length of the protected shoreline, and obtains the volume of revetment per unit shoreline, which is used to supplement and characterize the adequacy of artificial protection structures.

[0240] Step 704: The calculated indicators are compared with the pre-configured multi-indicator threshold system and numerically mapped within the corresponding level threshold range to obtain the individual score of each independent geomorphological evaluation unit.

[0241] The multi-index threshold system includes safety threshold limits established based on statistical patterns of historical long-sequence data.

[0242] For example, for the lateral sway amplitude index of the thalweg, a safe threshold and a dangerous threshold can be set based on historical measured statistical data of the studied river section. Sway amplitude within the safe threshold is mapped to a high-score range, sway amplitude exceeding the dangerous threshold is mapped to a low-score range, and sway amplitude in between is mapped to an intermediate score using linear interpolation. The threshold setting logic for other indicators is similar; engineers can determine the grading thresholds for each indicator based on historical evolution data of the specific river section.

[0243] Numerical mapping specifically employs linear interpolation to map the actual calculated values ​​of each physical indicator to a preset percentage range. This eliminates dimensional differences between various hydraulic, geomorphological, and engineering parameters, converting them all into standardized evaluation scores, thus providing a normalized data input interface for subsequent weighted aggregation.

[0244] Specifically, for the actual calculated value V of a certain indicator, let its pre-configured safety threshold be V. safe The danger threshold is V danger The percentage score for this indicator is calculated using the following formula:

[0245] Score=max(0,min(100,(VV danger ) / (V safe -V danger )×100))

[0246] Specifically, the closer the indicator value is to the safety threshold, the higher the score; the closer it is to the danger threshold, the lower the score. For indicators where a larger value indicates greater instability, such as the amplitude of the deep-water oscillation, V in the above formula... safe Value less than Vdanger For indicators where a larger value indicates greater stability, such as engineering protection coverage rate, V... safe Value greater than V danger .

[0247] In the quantitative evaluation of multidimensional driving factors, addressing the shortcomings of overflow in coverage calculations and one-sided dynamic indicators caused by the superposition of multiple protective engineering projects, this invention transforms a single extreme value into the bed-forming flow equivalent coupled with a duration factor, and performs overflow prevention truncation processing on the overlapping protection areas based on a spatial projection union strategy. This ensures a closed-loop mathematical logic under complex superposition conditions, enabling the comprehensive quantitative results of water and sediment driving forces, geomorphological response, and human intervention to truly approximate the objective physical constraint boundaries.

[0248] Example 8 further describes the post-processing and business loop process after obtaining the overall river stability score. This example focuses on verifying the scoring logic by constructing normalized calculation examples and describing the specific implementation methods of level determination and weak area identification.

[0249] In one possible implementation, after obtaining the overall river morphology stability score, the following steps are also included:

[0250] Step 801: Map the overall river stability score to the pre-configured grade division interval to determine the overall stability grade of the studied river section.

[0251] In this embodiment, the pre-configured grading intervals are a set of standard thresholds based on historical river morphology evolution disaster samples and statistical distributions. To eliminate ambiguity in boundary determination, the grading intervals are represented using left-open-right-closed or left-closed-right-open mathematical intervals. For example, a percentage score is mapped to four stability levels: scores within the interval 75-100 are considered relatively stable, and scores within the interval 50-75 are considered relatively unstable.

[0252] The mapping operation described above transforms continuous numerical variables into discrete classification labels. These labels directly reflect the macroscopic river morphology safety status of the entire river segment within the current evaluation period.

[0253] Step 802: Based on the weighting system, the individual scores of each independent geomorphological evaluation unit are weighted and summed to obtain the comprehensive score of each independent geomorphological evaluation unit. The comprehensive scores of all independent geomorphological evaluation units are then sorted sequentially.

[0254] In this embodiment, the overall score is a calculation result that integrates individual score, basic criterion weight, and geomorphic unit spatial weight. The system performs a descending or ascending sequence sorting operation on the overall scores of all independent geomorphic evaluation units participating in the evaluation.

[0255] In this embodiment, the comprehensive score refers to the calculation result that integrates individual scores, basic criterion weights, and geomorphic unit spatial weights. Specifically, for each independent geomorphic evaluation unit, the system weights and sums the scores of each indicator under its criterion layer using the corresponding indicator layer weights determined by the analytic hierarchy process (AHP) to obtain the comprehensive score of that unit. This comprehensive score is then multiplied by the geomorphic unit spatial weight of that unit to obtain the comprehensive score of that unit. The system performs an ascending sequence sorting operation on the comprehensive scores of all independent geomorphic evaluation units participating in the evaluation, generating a one-dimensional sequence containing unit identifiers, spatial coordinates, and corresponding comprehensive scores, providing a data index for subsequent spatial positioning.

[0256] After all units within the entire river section have been calculated according to the above logic, a one-dimensional sequence containing unit identifiers, spatial coordinates, and corresponding unit comprehensive scores is generated, providing a data index for subsequent spatial positioning.

[0257] Step 803: Extract low-scoring landform units whose scores are lower than the pre-configured baseline score or whose level is a preset unsafe level. Compare the individual scores of the low-scoring landform units to determine the main deduction indicators. Summarize their spatial location and main deduction indicators, and output a weak area identification report.

[0258] In other words, extract low-scoring landform units whose comprehensive scores are below the pre-configured baseline score, or map the comprehensive scores of each independent landform evaluation unit to the pre-configured level division interval and find that the landform unit is at the preset unsafe level, summarize its spatial location and main score deduction indicators, and output a weak area identification report.

[0259] In this embodiment, the pre-configured baseline score can be set as the arithmetic mean of the comprehensive scores of the entire river segment. The preset unsafe level specifically refers to the aforementioned relatively unstable level or unstable level. The system performs a traversal query in the sequence sorting results and extracts low-scoring geomorphic units that meet any of the above threshold conditions.

[0260] The system acquires the geometric center coordinates and boundary vector data of the low-scoring geomorphic units, traces back to the specific indicator values ​​of the unit in the individual scoring calculation stage, compares and extracts the main indicators that led to the reduced score. For example, it determines that the main indicator for a certain river island unit is the excessive longitudinal movement distance of the confluence point, or that the reason for the reduced score of a certain main tributary unit is insufficient engineering protection coverage.

[0261] The aforementioned multi-dimensional feature information is aggregated to generate a weak area identification report. This report includes a structured table aligned to spatial coordinates and a geographic information vector layer with attribute labels. In an optional verification method, the method can be applied to a typical braided river section with multi-year measured data. The spatial locations of low-resolution geomorphic units output from the weak area identification report are spatially overlaid and compared with records of actual bank collapses or abnormal deformation of sandbars in that river section over the years to evaluate the spatial accuracy of the method. Practical application shows that the method of this invention can effectively identify highly sensitive areas of river morphology evolution, and compared with traditional whole-segment uniform evaluation methods, it significantly improves the spatial positioning accuracy of weak areas.

[0262] Furthermore, in some optional implementations, a cross-validation mechanism for the evaluation results can be introduced. A dataset of measured bank collapse records or flood control hazard coordinates, reserved for independent validation, is obtained. The boundaries of low-scoring geomorphic units output from the weak area identification report are spatially overlaid with the measured coordinate dataset. The intersection-union ratio (IUU) of the overlapping areas is calculated. This objective validation index is used to assess the spatial accuracy of the evaluation model's output, providing feedback data for subsequent correction of the index threshold.

[0263] To illustrate the effectiveness of the assessment method described above, a typical bifurcation river section is used as an example. Suppose a research river section, after automatic segmentation, generates five independent geomorphic evaluation units: one inlet transition unit, one left bifurcation (main bifurcation) unit, one right bifurcation (tributary) unit, one river island unit, and one outlet node control unit. During the weight allocation phase, the river island unit, due to its recent active erosion and sedimentation and continuous head retreat, has a significantly higher spatial weight than other relatively stable units. During the scoring phase, this river island unit receives a low score on the riverbank stability index due to its large longitudinal movement at the confluence point, placing it at the bottom of the overall river section's ranking. The system automatically marks this river island unit as a weak area and outputs its spatial location and key scoring indicators in the report, providing accurate early warning and location information for river management departments. This positioning accuracy is superior to the traditional method's assessment conclusion of simply classifying the entire bifurcation river section as relatively unstable.

[0264] Example 9 provides a multi-index assessment system for the stability of bifurcation river sections. This system can be used to execute the multi-index assessment method for the stability of bifurcation river sections provided in the above examples. Its implementation principle and technical effects are similar, and the identical parts will not be repeated here. The following focuses on the module division and hardware structure. In one possible implementation, it includes the following modules:

[0265] The data acquisition module is used to acquire standardized basic datasets, which include hydrological and sediment data, multi-period measured cross-sectional data, and engineering data.

[0266] The system construction module is used to build a hierarchical evaluation system based on a standardized basic dataset, which includes water and sediment inflow conditions, channel geomorphological units, sandbar geomorphological units, and the intensity of engineering activities.

[0267] The unit partitioning module is used to divide the study river section into several independent geomorphic evaluation units using the topographic and geoscientific topological features in the standardized basic dataset.

[0268] The weight configuration module is used to determine the index weights and spatial weights of geomorphic units based on the evolution characteristics of the hierarchical evaluation system and independent geomorphic evaluation units, thereby obtaining the weight system.

[0269] The evaluation calculation module is used to calculate the individual scores of each independent geomorphological evaluation unit based on the weighting system and standardized basic dataset, and then sum them up to obtain the overall river stability score.

[0270] Furthermore, this embodiment also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the steps of the multi-index evaluation method for river regime stability in bifurcation sections as described in any of the above embodiments. The computer-readable storage medium can be implemented using hardware media such as solid-state drives, flash memory, or random access memory.

[0271] According to one aspect of this application, geomorphic evaluation units are automatically divided, and may further be as follows:

[0272] S1. Obtain measured cross-sectional data representing the year from the standardized basic dataset, and extract the plane coordinates of each cross-section station and the elevation of the measuring points. Using the river centerline as the reference axis, perform spatial interpolation on the riverbed topography between adjacent cross-sections at set intervals along the longitudinal direction, while maintaining the original measuring point resolution in the lateral direction. Combine the discretely distributed measured cross-sectional data into a continuous topographic surface extending along the river channel to generate a digital elevation model of the riverbed covering the entire study section.

[0273] S2. On the digital elevation model of the riverbed, the lowest elevation point of the riverbed is searched longitudinally section by section. The positions of the lowest points of each section are connected along the river to form the initial trajectory of the thoroughfare. Connectivity analysis is performed on the riverbed elevation profile of each cross section. When two or more independent low-value valleys separated by high ground appear on the same cross section, it is determined that the river channel has entered a bifurcation section at that cross section location. The lowest points of each independent valley are traced to form independent thoroughfare branches, and the position of the cross section where multiple valleys first appear is recorded as the coordinates of the bifurcation node. Tracing downstream along each branch thoroughfare, when multiple branches re-merge into a single lowest point trajectory at a certain cross section, the position of that cross section is recorded as the coordinates of the confluence node. A longitudinal weighted moving average is applied to each branch thoroughfare to eliminate the sawtooth offset caused by local elevation noise, generating a continuous and smooth thoroughfare vector set.

[0274] S3. Frequency statistics are performed on the elevation values ​​of each cross section in the riverbed digital elevation model to plot the elevation probability density curve. The elevation distribution of typical bifurcation sections exhibits a bimodal characteristic: the low peak corresponds to the bottom region of the channel, and the high peak corresponds to the sandbar region. The first derivative of the probability density curve is calculated and zero-crossing points are detected to locate the valley elevation between the two peaks. This elevation value is determined as the channel-shoal boundary elevation of that cross section. After extracting the boundary elevation section by section along the longitudinal direction, the contour lines of this elevation are traced on the riverbed digital elevation model to form continuous channel-shoal boundary lines on both sides, dividing the riverbed plane into the channel region and the sandbar region.

[0275] S4. Measure the horizontal distance between the left and right bank-channel boundaries along the longitudinal direction section by section to generate a sequence of river width variations along the river. After applying a sliding window mean filter to this sequence, detect local minima where the river width decreases by more than a set proportion, and mark these as candidate node control positions, corresponding to the lotus-root-like alternating wide and narrow geomorphological features of the bifurcation river section. Simultaneously, calculate the curvature value point by point along the thalweg vector set, identifying abrupt changes in curvature, corresponding to transitions from straight to curved or from curved to straight sections of the river channel. Then, overlay the spatial distribution of bank protection works from the engineering data dataset, marking river sections with continuous rigid protection as engineering constraint zones. Perform spatial overlay analysis on the above three types of information: areas where the river width narrows significantly, the location of abrupt changes in thalweg curvature, and the engineering constraint zone overlap longitudinally or the distance does not exceed a set tolerance are identified as node control sections. Extract the cross-sectional positions of their upstream and downstream boundaries, and summarize them to form a node control section boundary set.

[0276] S5, based on the coordinates of the bifurcation nodes, the confluence nodes, and the boundary sets of the node control sections, divides the continuous river channel longitudinally into several independent segments. The following type determination rules are then applied to each segment:

[0277] When the width of the river in a segment is locally narrowed and contains only a single thalweg trajectory, it is identified as a node control segment; when the segment contains two or more independent branches from the thalweg vector set, it is identified as a distributary unit, and further sorted by the size of the cross-section where each branch is located, with the largest area marked as the main distributary and the rest marked as branch distributaries; when the segment is located between the upstream distributary confluence node and the downstream branching node and the thalweg returns to a single trajectory, it is identified as a transition segment.

[0278] Within the shoal and sandbar area, shoal and sandbar types are identified based on the enclosing relationship of the shoal-channel boundary: enclosed highlands surrounded by two or more thalphon branches are identified as mid-river islands or mid-shoals; shoals with only one side adjacent to a thalphon branch are identified as side shoals; the upstream tip of an island along the direction of water flow is identified as an island head, and the downstream tip as an island tail. Each unit is assigned a unique number, and its type label, vector boundary, inlet / outlet control section location, and representative thalphon segment affiliation are recorded, summarizing these to form a geomorphic unit division scheme.

[0279] S6 performs a completeness check on the geomorphic unit division scheme to ensure the computability of subsequent indicators, guaranteeing that all evaluation indicators can be solved independently in each unit. The check includes three aspects.

[0280] 1) Check whether each channel unit completely includes its thalweg line segment without being truncated by the boundary - integrity ensures that the thalweg swing amplitude index can be calculated independently within the unit. If the thalweg line is truncated, extend the unit boundary along the direction of the thalweg line to the nearest natural turning point of the line segment.

[0281] 2) Check whether each shoal unit fully includes the head and tail of the island. Integrity ensures that the calculation of the confluence point movement distance index falls within the unit. If the head or tail of the island is missing, the boundary is pushed outward to the tip of the island's planar shape convergence.

[0282] 3) Check whether each channel unit simultaneously has an inlet section and an outlet section – the integrity guarantee flow split ratio index can be directly obtained through the inlet / outlet section flow ratio. If an inlet or outlet section is missing, extend the boundary along the corresponding thalweg branch direction to the nearest measured section location. For units that do not meet the conditions, adjust the boundary according to the above rules and re-verify until all units pass, and output the final verified geomorphic unit division results.

[0283] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, various equivalent transformations can be made to the technical solutions of the present invention, and these equivalent transformations all fall within the protection scope of the present invention.

Claims

1. A multi-index assessment method for the stability of river course in a braided river section, characterized in that, include: Obtain standardized basic datasets, including hydrological and sediment data, multi-period measured cross-sectional data, and engineering data; Based on standardized basic datasets, a hierarchical evaluation system is constructed that includes water and sediment inflow conditions, channel geomorphological units, sandbar geomorphological units, and the intensity of engineering activities. Using the topographic and geoscientific topological features in the standardized basic dataset, the study river section is divided into several independent geomorphological evaluation units; Based on the hierarchical evaluation system and the evolution characteristics of independent geomorphic evaluation units, the index weights and geomorphic unit spatial weights are determined to obtain the weight system. Based on the weighting system and standardized basic dataset, the individual scores of each independent geomorphological evaluation unit are calculated, and the overall river stability score is obtained by weighted summation.

2. The method according to claim 1, characterized in that, Using the topographic and geoscientific topological features in the standardized base dataset, the studied river section was divided into several independent geomorphic evaluation units, including: A digital elevation model of the riverbed is constructed by spatial interpolation based on multi-period measured cross-section data in a standardized basic dataset. The lowest elevation point of the digital elevation model of the riverbed is extracted section by section along the longitudinal direction, and the connectivity domain analysis is performed on the riverbed elevation profile of each section. When multiple independent low-value troughs separated by highlands are detected in the same cross section, each independent low-value trough is traced to form an independent thalweg branch, and the cross section position where the earliest independent low-value trough appears is recorded as the coordinate of the branch node. When multiple thalweg branches merge into a single lowest elevation point trajectory, the location of the merging section is recorded as the coordinates of the confluence node. The thalweg vector set is composed of the coordinates of the thalweg branches, the branching nodes, and the confluence node.

3. The method according to claim 1, characterized in that, In the step of dividing the study river section into several independent geomorphological evaluation units, for the needs of multi-phase comparative evaluation, the following are also included: Extract multi-period measured cross-sectional data from different years and delineate the boundaries of geomorphic units for each single time phase in each year; For the same landform entity that exhibits locational shifts or morphological changes, extract its maximum spatial envelope range across multiple temporal phases; Using the maximum spatial envelope as a unified mapping benchmark, the spatial boundaries of independent geomorphic evaluation units in multi-phase assessment tasks are consistently corrected to eliminate the impact of dynamic changes on boundary tracking.

4. The method according to claim 1, characterized in that, Determining the index weights and spatial weights of geomorphic units includes: Determine the basic criteria and weights for each evaluation indicator under the hierarchical evaluation system; Based on multi-period measured cross-sectional data, the area of ​​beach activity and the magnitude of erosion and deposition changes of each independent geomorphological evaluation unit in the long-term evolution history are extracted. Based on the contribution ratio of the area of ​​beach activity and the magnitude of scouring and deposition to the overall river morphology evolution of the entire river section, spatial influence factors are allocated according to nonlinear mapping to generate spatial weights for geomorphic units. The weighting system is constructed by merging the weights of the basic criteria with the spatial weights of the geomorphic units.

5. The method according to claim 1, characterized in that, Calculate the individual scores for each independent geomorphological evaluation unit, including: Based on hydrological and sediment data, the equivalent of bed-forming flow rate and sediment transport intensity under the conditions of incoming water and sediment are calculated. Based on the spatial boundary changes of independent geomorphic evaluation units in multiple periods, the lateral swing amplitude of the thalweg and the longitudinal movement distance of the confluence point are calculated. Based on engineering data, the engineering protection coverage rate and the volume of shoreline revetment per unit area, which characterize the intensity of engineering activities, are calculated. Each of the calculated indicators is compared with the pre-configured multi-indicator threshold system, and numerical mapping is performed within the corresponding level threshold range to obtain the individual score of each independent geomorphological evaluation unit.

6. The method according to claim 1, characterized in that, After obtaining the overall river stability score, the following is also included: The overall river stability score is mapped to a pre-configured grading interval to determine the overall stability level of the studied river section; The comprehensive scores of all independent geomorphic evaluation units are ranked sequentially. Extract low-scoring landform units whose scores are below the pre-configured baseline or whose level is a preset unsafe level, summarize their spatial location and main score deduction indicators, and output a weak area identification report.

7. The method according to claim 5, characterized in that, Calculating the equivalent flow rate of the bed includes: The bed-forming flow rate of the study river section was determined based on hydrological and sediment data; Statistically evaluate the number of days in the year where the average daily flow rate is not less than the bed-building flow rate, and calculate the arithmetic mean of the average daily flow rate within that number of days; The bed-forming flow equivalent is obtained by multiplying the ratio of the number of days to the total number of days in the evaluation year with the dimensionless ratio of the arithmetic mean of the daily flow rate to the bed-forming flow rate.

8. The method according to claim 5, characterized in that, Calculating sediment transport intensity includes: Obtain the total annual sediment transport volume for the evaluation year and the average annual sediment transport volume for the preset baseline period; The ratio of the total annual sediment transport to the average annual sediment transport is calculated to obtain the sediment transport intensity, which characterizes the river channel scouring and deposition trend.

9. A multi-index assessment system for the stability of river course in a braided river section, characterized in that, include: The data acquisition module is used to acquire standardized basic datasets; The system construction module is used to build a hierarchical evaluation system; The unit division module is used to divide the studied river section into several independent geomorphological evaluation units; The weight configuration module is used to determine the index weights and the spatial weights of geomorphic units; The evaluation calculation module is used to calculate the individual scores of each independent geomorphological evaluation unit and then sum them up in weighted terms to obtain the overall river stability score. The system is used to perform the multi-index assessment method for river regime stability of bifurcation sections as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the multi-index evaluation method for river regime stability of the bifurcation section as described in any one of claims 1 to 8.

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