A method for evaluating suitability of artificial sand beach engineering on bedrock coast

Abstract

This invention relates to a suitability assessment method for artificial beach projects on bedrock coastlines. The method divides assessment units based on coastline curvature, the width of available land behind the beach, and natural segmentation characteristics. It constructs an evaluation factor system covering sixteen core indicators across five categories: geomorphology, hydrodynamics, sediment, engineering, and ecology. Standardization and weighting are used to calculate the comprehensive suitability score for each unit. Suitability levels are classified and spatially expressed through a GIS platform. Dynamic response simulations of key shoreline sections are conducted using wave models and beach evolution numerical models to achieve correction and feedback optimization of suitability levels. This invention provides a complete assessment process from static suitability judgment to dynamic response trend prediction, offering reliable technical support for the scientific site selection, risk control, and long-term operation of artificial beach projects. It has good engineering applicability and promising prospects for widespread application.

Description

Technical Field

[0001] This invention relates to a suitability assessment method for artificial beach projects on bedrock coasts, belonging to the technical field of coastal engineering and coastal zone resource evaluation. Background Technology

[0002] Artificial beaches, as a form of coastal utilization that combines landscape, ecological, and economic value, have been widely adopted in many parts of the world. Especially in the southeastern coastal region of my country, due to the uneven distribution of natural beach resources, urbanization encroachment, and shoreline hardening, artificial beach projects have been extensively introduced to enhance shoreline functions, expand waterfront space, and restore ecological landscapes. Currently, the construction of artificial beaches can achieve a certain degree of long-term maintenance through comprehensive engineering measures such as "beach backfilling + structural stabilization + regular sand replenishment." However, with increasingly scarce coastal land resources, more and more beach construction demand is being driven towards bedrock coastlines. These sections naturally lack sediment supply, have complex topography, and strong hydrodynamics, posing greater challenges and uncertainties to the construction and maintenance of artificial beaches.

[0003] The aforementioned bedrock coasts are mainly distributed along the seaward edges of mountains or hills, characterized by steep slopes, exposed rock masses, scarce sand sources, and often situated in high-wave-energy environments. Compared to sedimentary coasts, bedrock coasts lack tidal flats, experience intense erosion, and typically lack the geomorphological conditions for naturally forming beaches. Therefore, artificial beach projects in such areas require comprehensive consideration of multiple aspects, including the feasibility of shoreline modification, the maintenance of sand stability, the technical challenges of integrating structures with bedrock, and the impact on the ecosystem. Currently, in practical engineering, artificial beaches on bedrock sections often rely heavily on extensive backfilling and structural facilities for maintenance. However, these projects are costly, have short maintenance cycles, and suffer from insufficient risk assessment, making them highly susceptible to beach erosion, structural damage, and even functional failure in the short term. Furthermore, due to the limited space and ecological sensitivity of bedrock sections, inappropriate engineering plans can also trigger new shoreline erosion and ecological disturbances.

[0004] To address the aforementioned issues concerning bedrock coastlines, methods such as expert scoring, remote sensing layer overlay, and fuzzy comprehensive evaluation are commonly used to qualitatively or semi-quantitatively assess suitability. While these methods are feasible to some extent, they suffer from significant limitations, including incomplete evaluation index systems, a lack of hydrodynamic process constraints, and a bias towards static geographical attributes. This is particularly problematic in the context of bedrock coastlines characterized by strong hydrodynamics, complex topography, and difficulty in maintaining sand sources, where existing methods struggle to accurately characterize practical construction feasibility. Furthermore, most existing studies lack numerical models to simulate physical processes, failing to assess the response and evolution of the beach body under the influence of waves, tides, and other dynamic forces. Consequently, they lack scientific support and predictive capabilities in guiding engineering site selection and design. Especially in high-risk or ecologically constrained coastlines, inappropriate site selection can lead to extremely high financial costs and environmental consequences.

[0005] Therefore, there is an urgent need for a method to conduct a suitability assessment of artificial beach construction for bedrock coasts that integrates multiple factors, constrains physical processes, and provides quantifiable and graded results. Summary of the Invention

[0006] This invention provides a suitability assessment method for artificial beach projects on bedrock coasts, which has a full-process assessment from static condition suitability judgment to dynamic response trend prediction. It provides reliable technical support for the scientific site selection, risk control and long-term operation of artificial beach projects, and has good engineering applicability and promotion prospects.

[0007] The technical solution adopted by this invention to solve its technical problem is: A suitability assessment method for artificial beach projects on bedrock coasts, specifically including the following steps: Step S1: Identify coastal segments with bedrock landform features and obtain vector data of the identified coastal segments. Divide the coastal segments into units based on the vector data and evaluate them to obtain coastal segments that meet the requirements. Step S2: Construct a suitability evaluation index system, in which the evaluation index includes five types of factors: geomorphological factors, hydrodynamic factors, sediment factors, engineering factors, and ecological factors. Step S3: Dimensionless processing is performed on each evaluation index within the system, and the index weights are assigned values. Step S4: Combine the individual evaluation index processing completed in step S3 to obtain the total suitability score for each unit, and perform preliminary classification of the coastal section based on the scores of each unit. Step S5: Based on the completed static comprehensive scoring, use a numerical model to simulate the dynamic response of the sand body in the coastal section after preliminary classification. Step S6: Spatialize the simulation results obtained in step S5 and automatically update the evaluation results for dynamic correction. Furthermore, in step S1, the method for identifying coastal sections with bedrock landform features includes remote sensing images, digital elevation models, or shoreline databases, wherein the bedrock landform features include cliff shores, rocky beaches, and rocky platform shores. Furthermore, in step S1, the step of obtaining the coastal section that meets the requirements is as follows: Step S11: Interpolate the acquired vector data into an equidistant point set, and estimate the discrete curvature using the three-point method. The calculation formula is as follows: (1) In formula (1), For curvature, For the first An angle is formed by three points, with point A as the vertex. The distance between points; Step S12: Set the curvature threshold as the basis for dividing natural segments, define the concave bank or the boundary of the concave bank as the segmentation node, divide the coastline into units, and form several initial shore segments. Step S13: Construct a buffer zone on the landward side of each initial shoreline segment, obtain the width of the construction land within the buffer zone, define it as W, and set a width threshold W. th If W>W th If W ≤ W, then the conditions for constructing an artificial beach are met. th If the conditions for the construction of an artificial beach are not met, this initial section of the shoreline will be excluded. Step S14: Assign numbers, start and end point coordinates, and attribute labels to the coastal sections that meet the requirements; Furthermore, in step S2, the geomorphic factors include bank slope, bedrock exposure rate, and coastline curvature; the hydrodynamic factors include significant wave height, nearshore current velocity, wave height reduction rate, and wave energy flux; the sediment factors include sediment transport flux, suspended sediment concentration, and siltation potential; the engineering factors include backshore land use, accessibility, and construction difficulty; and the ecological factors include overlap of ecologically sensitive areas and habitat disturbance index. Furthermore, in step S3, the step of dimensionless processing for each evaluation index is as follows: Step S311: If the evaluation indicator is a positive indicator, then the evaluation indicator is standardized using range. The calculation formula for each evaluation indicator is as follows: (2) In formula (2), The normalized value. These are the original indicator values. The maximum value of the evaluation index within the unit. The minimum value of the evaluation index within the unit; Step S312: If the evaluation indicator is a negative indicator, then reverse normalization is applied to the evaluation indicator. The formula for processing each evaluation indicator is: (3) In formula (3), The normalized value. These are the original indicator values. The maximum value of the evaluation index within the unit. The minimum value of the evaluation index within the unit; The steps for assigning values ​​to indicator weights are as follows: Step S321: Perform information entropy processing on the normalized values. The processing formula is as follows: (4) In formula (4), For information entropy, For the sample size, Numbering assigned to eligible coastal sections. For the first Within the first coastal section One evaluation indicator; Step S322, calculate the first... The weighting coefficients of the evaluation indicators within each coastal segment are calculated using the following formula: (5) In formula (5), These are the weighting coefficients. For the first Information utility value within each coastal segment, and d j = 1 – e j ; Furthermore, in step S4, the preliminary classification of the coastal section is performed as follows: Step S41: Calculate the overall suitability score for each assessment unit using the weighted linear superposition method. The calculation formula is as follows: (6) In formula (6), For the first j The overall suitability score for each coastal segment For the first i The weight of each indicator, This represents the total number of indicators; Step S42: Based on the comprehensive suitability score of the evaluation unit in Step S41, classify the areas into levels. If R ≥ 0.75, it is determined to be a highly suitable area, indicating that the coastal section has excellent conditions and is ready for direct construction, and is given priority recommendation; if 0.60 ≤ R < 0.75, it is determined to be a suitable area, indicating that the coastal section has construction conditions, but some factors are slightly weaker, and it is suitable to combine local optimization; if 0.40 ≤ R < 0.60, it is determined to be a low-suitability area, indicating that the conditions are limited and require supporting protection or ecological engineering; if R < 0.40, it is determined to be an unsuitable area, indicating that the terrain, wave, or ecological conditions are obviously unfavorable, and it is recommended not to build. Furthermore, in step S5, the steps for simulating the dynamic response of the sand body are as follows: Step S51: Set the core parameters of the numerical model, including the initial topography of the beach, sand body parameters, and boundary structure; Step S52: SWAN outputs boundary conditions, which include wave height, period, and direction; Step S53: Set up a simulation scenario for simulation, the scenario including typical tidal conditions and extreme conditions; Step S54: Simulate and output the results indicators, which include changes in beach profile, erosion and sedimentation, and beach shoulder migration. Determine the stability and erosion risk of the artificial beach during its operation cycle. If severe sand loss or frequent structural maintenance is found, the system will lower the original grade of the coastal section and mark it as requiring structural protection or a low suitability zone. If the sand backfilling potential and engineering response capability are good, the grade will be maintained or raised. Furthermore, in step S6, the evaluation results are spatially represented on the GIS platform. The evaluation results include: a four-color partitioning of the comprehensive suitability level map, a spatial distribution map of five types of factors, an output layer for simulating a simulated scenario, a level change layer of the simulated output result indicators, and a list of recommended construction sections and priority ranking.

[0008] By employing the above technical solutions, the present invention has the following beneficial effects compared to the prior art: 1. The suitability assessment method for artificial beach projects on bedrock coasts provided by this invention constructs a comprehensive assessment system covering five major categories of factors and establishes a multi-physics field correlation model of bedrock coast dynamics-sedimentation-ecology-engineering. Compared with traditional bedrock coast assessments that usually focus on a single or a few factors (such as only analyzing geomorphology or hydrodynamic conditions), this method avoids the lack of systematic correlation analysis of geomorphology, hydrodynamics, sediment movement, engineering construction and ecological environment due to a single factor. It incorporates multiple factors into a unified framework, realizes multi-element coupling analysis, and balances engineering benefits and ecological protection needs. 2. The suitability assessment method for artificial beach projects on bedrock coasts provided by this invention integrates the SWAN (hydrodynamic model) and EBEACH (sediment transport model) dual models. By coupling wave propagation, water flow, and sediment erosion and deposition processes, it realizes the whole-process analysis from static suitability determination to dynamic beach evolution prediction. This solves the problem that existing technologies mainly focus on static suitability evaluation and lack analysis of the time dimension of coastal dynamic processes and beach evolution. It significantly improves the accuracy of long-term coastal evolution prediction and avoids the distortion of results caused by "simplification assumptions". 3. The suitability assessment method for artificial beach projects on bedrock coastlines provided by this invention deeply integrates the assessment results with a GIS platform to achieve spatial expression (such as displaying the distribution of feasibility levels through color blocks and contour lines) and dynamic correction (such as the system automatically updating the assessment results after inputting real-time monitoring data), supporting the sustainable utilization of coastal resources and climate change adaptation management. Attached Figure Description

[0009] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0010] Figure 1 This is a schematic diagram of the suitability assessment method for artificial beach projects on bedrock coastlines provided by the present invention. Detailed Implementation

[0011] The present invention will now be described in further detail with reference to the accompanying drawings. In the description of this application, it should be understood that the terms "left side," "right side," "upper part," "lower part," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. "First," "second," etc., do not indicate the importance of the components, and therefore should not be construed as a limitation of the present invention. The specific dimensions used in this embodiment are only for illustrating the technical solution and do not limit the scope of protection of the present invention.

[0012] In the background, traditional assessment methods for bedrock coastlines have the following problems: they usually focus on a single or a few factors, lacking a systematic correlation analysis of geomorphology, hydrodynamics, sediment transport, engineering construction, and the ecological environment; they are mainly based on static suitability assessments, lacking time-dimensional analysis of coastal dynamic processes and beach evolution; model results are mostly presented in numerical or graphical form, lacking spatial visualization and dynamic correction capabilities; and assessment conclusions are biased towards theoretical feasibility, lacking quantitative analysis of engineering risks, and are difficult to directly guide construction design and shoreline management.

[0013] To address the aforementioned challenges, this application provides a suitability assessment method for artificial beach projects on bedrock coasts, building upon traditional technologies. It systematically constructs an assessment factor system covering five dimensions: geomorphology, hydrodynamics, sediment, engineering, and ecology. By combining the SWAN and EBEACH models to couple and simulate wave propagation and beach evolution, it achieves a comprehensive assessment from static suitability judgment to dynamic response trend prediction. Through spatial gridding, standardized processing, and multi-method weighting, this invention can not only quantitatively score and classify the suitability of different shorelines but also predict sand stability and dynamically correct suitability levels for specific shorelines, providing reliable technical support for the scientific site selection, risk control, and long-term operation of artificial beach projects.

[0014] The entire evaluation method is as follows Figure 1 As shown, it includes the following steps: Step S1: Identify coastal segments with bedrock landform features and obtain vector data of the identified coastal segments. Divide the coastal segments into units based on the vector data and evaluate them to obtain coastal segments that meet the requirements. In this step, the methods used to identify coastal features include remote sensing imagery (such as Landsat and Sentinel-2), digital elevation models (DEMs), and shoreline databases. The bedrock geomorphological features include cliff shores, rocky beaches, and rocky plateau shores. Remote sensing imagery offers wide-area, high-time-sensitivity spatial coverage, while digital elevation models provide high-precision topographic characterization. Combining the spectral characteristics of remote sensing imagery (differences in reflectance between bedrock and sand / vegetation), the topographic profiles of DEMs, and historical change data from shoreline databases can eliminate the limitations of single data sources and improve identification accuracy.

[0015] High-precision coastline vector data is obtained through remote sensing imagery or existing coastline databases. Subsequent steps to obtain suitable coastline segments include: Step S11: Interpolate the coastline into an equidistant point set (the spacing is generally 5-10 meters), calculate the local curvature value for each point, and estimate the discrete curvature using the three-point method. The calculation formula is as follows: (1) In formula (1), For curvature, For the first An angle is formed by three points, with point A as the vertex. The distance between points; Step S12: A larger curvature value indicates a more curved shape. Set a curvature threshold (e.g., |). kUsing ∣>0.002) as the basis for dividing natural segments, the point of abrupt change in curvature, i.e. the concave bank or the boundary between concave banks, is the segmentation node. The coastline is divided into units and cut into initial shore segments with coherent shape and controllable length (e.g., 200–1000 meters). Step S13: Construct a buffer zone (recommended width 200–300 meters) on the landward side of each initial shoreline segment. Obtain land use information within the buffer zone (such as a LUCC layer or a planning map), primarily the width of construction land. Urban land, bare land, and saline-alkali land can be considered "developable land," defined as W. Simultaneously, set a width threshold W. th If W>W th If W ≤ W, then the conditions for constructing an artificial beach are met. th If the conditions for artificial beach construction are not met, this initial shoreline will be excluded; preferably, the width threshold is set to 50 meters. Step S14 involves further identifying abrupt changes in engineering features within eligible coastal sections, such as road crossings, drainage outlets, natural headlands, or port boundaries, as functional boundary points. If an initial coastal section exceeds 1 kilometer in length, it can be further subdivided according to equal lengths (e.g., every 300 meters) or secondary variations in coastal curvature to ensure that the assessment units have controllable length and structural continuity. Each unit should ultimately have a clear number, start and end point coordinates, and attribute labels (e.g., administrative region, mean curvature, available land width, etc.) to provide spatial units for subsequent indicator assignment and model input.

[0016] Step S2 involves constructing a suitability evaluation index system based on a thorough consideration of the natural conditions and engineering requirements for constructing artificial beaches on bedrock coasts. The evaluation index includes five categories of factors, each selected according to the principle of "engineering feasibility + geomorphic stability + hydrodynamic adaptability + sediment supply capacity + ecological harmony," and combined with available spatial data or simulation outputs to ensure regional adaptability and practical operability. Specifically, geomorphic factors (such as shoreline slope, bedrock exposure rate, and coastline curvature) reflect the topographical foundation and natural beach shaping potential of the shoreline; hydrodynamic factors (such as significant wave height, nearshore current velocity, wave height reduction rate simulated by SWAN, and wave energy flux) measure the impact of waves and currents on sand body stability; sediment factors (such as sediment transport flux, suspended sediment concentration, and siltation potential) are used to assess the sand source guarantee and replenishment capacity; engineering factors (such as backshore land use, transportation accessibility, and structural construction difficulty) evaluate the practical feasibility of construction; and ecological factors (such as overlap of ecologically sensitive areas and habitat disturbance index) are used to control the potential disturbance of engineering activities to the coastal ecosystem.

[0017] These five categories of factors comprise a total of 16 core factors, with specific indicators shown in Table 1: Table 1. Suitability Assessment Indicators for Artificial Beaches

[0018] As one of the innovative aspects of this application, the aforementioned comprehensive evaluation system covers five major categories of factors, enabling coupled analysis of multiple elements and balancing engineering benefits with ecological protection needs.

[0019] Step S3 involves constructing the factor system and then applying a standardized and weighted comprehensive evaluation method for unified processing. This process includes two key steps: dimensionless processing of each evaluation indicator within the system and assigning weights to the indicators. First, all indicators are dimensionless. This is because the data types, numerical ranges, and units of each evaluation indicator are different, and to avoid distortion of the evaluation results due to differences in dimensions, the steps for dimensionless processing are as follows: Step S311: If the evaluation index is a positive index (the larger the value, the higher the suitability, such as wave height reduction rate, potential sediment transport flux, width of usable land on the back bank, etc.), then the evaluation index is processed using range standardization. The calculation formula for each evaluation indicator is as follows: (2) In formula (2), The normalized value. These are the original indicator values. The maximum value of the evaluation index within the unit. The minimum value of the evaluation index within the unit; Step S312: If the evaluation index is a negative index (the larger the value, the lower the suitability, such as annual maximum wave height, overlap of ecologically sensitive areas, and structural construction difficulty level), then the evaluation index is subjected to reverse normalization. The processing formula for each evaluation indicator is as follows: (3) In formula (3), The normalized value. These are the original indicator values. The maximum value of the evaluation index within the unit. The minimum value of the evaluation index within the unit; After this processing, the normalized results of all indicators are in the range of [0,1], and the larger the value, the higher the suitability, which facilitates unified weighted evaluation.

[0020] To reflect the varying degrees of influence of different indicators on the suitability of artificial beaches, it is necessary to assign weights to these indicators. This application preferably provides two methods for determining these weights. The first is the Analytic Hierarchy Process (AHP): This method is suitable for weight setting in expert-led, multi-objective decision-making. The specific process includes constructing a pairwise comparison matrix of factors, using consistency checks to confirm the rationality of the matrix, and calculating the normalized eigenvector as the weight vector. This method reflects expert knowledge and experience and is suitable for project decisions with clear engineering objectives.

[0021] Another method is the entropy weight method, which determines the weight based on the information entropy of each indicator, reflecting its degree of variation. The specific steps are as follows: Step S321: Perform information entropy processing on the normalized values. The processing formula is as follows: (4) In formula (4), For information entropy, For the sample size, Numbering assigned to eligible coastal sections. For the first Within the first coastal segment (unit) One evaluation indicator; Step S322, calculate the first... The weighting coefficients of the evaluation indicators within each coastal segment are calculated using the following formula: (5) In formula (5), These are the weighting coefficients. It is the information utility value, and d j = 1 – e j .

[0022] Entropy weight method is suitable for setting weights when evaluation index data is highly volatile and subjective information is insufficient, and can avoid human bias.

[0023] Step S4: After completing the standardization and weight allocation of each evaluation indicator, the individual evaluation indicator processing completed in Step S3 is combined to obtain the total suitability score of each unit, and the coastal section is initially classified according to the scores of each unit. Obviously, this step aims to combine the normalized values ​​of multiple factors with weights to calculate the comprehensive suitability score (R) of each evaluation unit, and classify it into different suitability levels accordingly, so as to achieve quantitative zoning evaluation.

[0024] The following describes the specific steps for the initial classification of the coastal section: Step S41: Calculate the overall suitability score for each assessment unit using the weighted linear superposition method. The calculation formula is as follows: (6) In formula (6), For the first j The overall suitability score of each assessment unit, For the first i The weight of each indicator, This represents the total number of indicators.

[0025] Step S42: Based on the comprehensive suitability score of the evaluation unit in Step S41, classify the areas into levels. If R ≥ 0.75, it is determined to be a highly suitable area, indicating that the coastal section has excellent conditions and is ready for direct construction, and is given priority recommendation. If 0.60 ≤ R < 0.75, it is determined to be a suitable area, indicating that the coastal section has construction conditions, but some factors are slightly weaker, and it is suitable to combine local optimization. If 0.40 ≤ R < 0.60, it is determined to be a low-suitability area, indicating that the conditions are limited and that it needs to be used with supporting protection or ecological engineering. If R < 0.40, it is determined to be an unsuitable area, indicating that the terrain, wave, or ecological conditions are obviously unfavorable, and it is recommended not to build.

[0026] Step S5, to overcome the inadequacy of static suitability assessment in reflecting the evolution trend of the sand body under actual hydrodynamic action after sand replenishment, based on the completed static comprehensive scoring, uses a numerical model (mainly referring to the introduced EBEACH numerical model) to simulate the dynamic response of the sand body in the coastal section after preliminary classification. This step overcomes the problem that traditional models can only simulate the beach morphology under current conditions. By coupling wave propagation, water flow, and sediment erosion and deposition processes, it realizes the whole process analysis from static suitability judgment to dynamic beach evolution prediction. It can identify the "short-term feasibility" and "long-term risk" of artificial beaches on bedrock coasts and quantify the risk level. Compared with a single model (such as using only a hydrodynamic model to predict beach morphology), the dual-model coupling significantly improves the prediction accuracy.

[0027] The steps for conducting dynamic response simulation of sand bodies are as follows: Step S51: Based on the completed static comprehensive scoring, select some high-potential or disputed areas and set the core parameters of the numerical model, including the initial topography of the beach, sand body parameters and boundary structure (such as submerged dikes and groynes). Step S52: SWAN outputs boundary conditions, which include wave height, period, and direction; Step S53: Set up a simulation scenario for simulation, the scenario including typical tidal conditions and extreme conditions; Step S54: Simulate and output the results indicators, including changes in beach profile, erosion and sedimentation, and beach shoulder migration, to determine the stability and erosion risk of the artificial beach during its operation cycle. If severe sand loss or frequent structural maintenance is found, the system will lower the original grade of the coastal section and mark it as requiring structural protection or a low suitability zone; if the sand backfilling potential and engineering response capability are good, the grade will be maintained or raised.

[0028] Step S6, another innovation of this application, involves spatially integrating and layering all suitability analysis results with the simulation results obtained in step S5 on a GIS platform. This outputs intuitive and operable auxiliary decision-making results and automatically updates the evaluation results for dynamic correction, which can shorten the evaluation cycle and reduce the cost of design changes.

[0029] The assessment results described here include: a comprehensive suitability rating map (four-color zoning), spatial distribution maps of key factors (such as wave height, slope, and sediment), simulation output layers (such as beach evolution profiles and erosion / deposition distribution), rating change layers (representing the rating differences before and after EBEACH correction), and a list of recommended construction shorelines with priority ranking. All results support the overlay of multi-source data such as land use, ecological protection red lines, and transportation corridors, assisting coastal management departments, planning units, or engineering designers in conducting multi-objective decision-making processes such as shoreline selection, engineering scheme comparison, ecological conflict avoidance, and long-term maintenance planning. The outputs of this invention can also be integrated with smart coastal platforms and digital twin systems to achieve full-process data-driven and dynamic control support for subsequent coastal engineering projects.

[0030] To verify the feasibility of the evaluation method provided in this application, two simulated embodiments are provided here.

[0031] Example 1: Suitability assessment of a semi-enclosed concave bank section in a tourism development zone of a certain province Within a planned coastal tourism development zone in a certain province, a typical semi-enclosed concave bay section was selected for suitability assessment. Through remote sensing interpretation and high-precision DEM analysis, the slope of this bay section is less than 5°, with a gentle construction terrace exceeding 80 m behind it, and a bedrock exposure rate of less than 20%, indicating preliminary suitability for artificial beach construction. Hydrodynamic factors, simulated using the SWAN model, show a wave height reduction rate of 64% and energy flux significantly lower than adjacent sections, indicating good natural shielding. Among sediment factors, the coastal sediment transport flux is high (approximately 12,000 tons / year). EBEACH simulation results show that after sand replenishment, the beach profile remains stable under typical wind and wave conditions, with only local shoulder displacement of 2–3 meters. The overall evaluation score is 0.82, classifying it as a "highly suitable area," recommending direct construction of an artificial beach, supplemented by ecological revetment and the construction of a marine leisure wharf.

[0032] Example 2: Assessment and Limitations of an Open Bedrock Section at the Ecological Red Line Boundary in a Certain Province A preliminary suitability screening for artificial beach construction was conducted on an open, straight bedrock section near the ecological protection red line boundary in the central part of a province. The shoreline has a steep slope (average 13°), with over 60% bedrock exposure. The backshore land is narrow and constrained by ecological red line planning, leading to an unfavorable initial assessment. SWAN model simulations show that this shoreline faces the northeast main wave direction, with a wave energy flux of 6.5 kW / m and a wave height reduction rate of less than 20%, classifying it as a typical high-energy open shoreline. EBEACH dynamic simulations further indicate that with 30,000 cubic meters of sand replenishment, the beach profile experiences large-scale leading-edge erosion under 24-hour strong wind and wave conditions, resulting in a beach loss rate of 46%. The maintenance cycle is too short, and the engineering cost is too high. The overall score is only 0.37, classifying it as a "low suitability zone." It is recommended that artificial beach construction not be carried out, and that an ecological buffer zone combined with a bedrock protection structure be adopted as the preferred shoreline remediation solution.

[0033] In summary, the suitability assessment method for artificial beach projects on bedrock coasts provided in this application divides assessment units based on coastline curvature, the width of available land behind the shoreline, and natural segmentation characteristics; constructs an evaluation factor system covering sixteen core indicators across five categories: geomorphology, hydrodynamics, sediment, engineering, and ecology; calculates the comprehensive suitability score for each unit using standardized processing and weighted assignment; classifies suitability levels and spatially expresses them through a GIS platform; and combines the SWAN wave model and the EBEACH beach evolution numerical model to conduct dynamic response simulations of key shoreline sections, enabling correction and feedback optimization of suitability levels. This application is specifically tailored to the "high complexity and high risk" characteristics of bedrock coasts, providing scientific and comprehensive assessment results that combine static geographical suitability analysis with dynamic physical process prediction. It offers a "quantifiable, visualized, and correctable" decision-making tool for the preliminary site selection, scheme comparison, and risk control of artificial beach projects on bedrock coasts in coastal cities, demonstrating good engineering applicability and promotional value.

[0034] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0035] The meaning of "and / or" as used in this application includes situations where each exists alone or both exist simultaneously.

[0036] The term "connection" as used in this application can mean a direct connection between components or an indirect connection between components through other components.

[0037] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A suitability assessment method for artificial beach projects on bedrock coastlines, characterized in that: Specifically, the following steps are included: Step S1: Identify coastal segments with bedrock landform features and obtain vector data of the identified coastal segments. Divide the coastal segments into units based on the vector data and evaluate them to obtain coastal segments that meet the requirements. The steps to obtain a suitable coastline are as follows: Step S11: Interpolate the acquired vector data into an equidistant point set, and estimate the discrete curvature using the three-point method. The calculation formula is as follows: （1） In formula (1), For curvature, For the first An angle is formed by three points, with point A as the vertex. The distance between points; Step S12: Set the curvature threshold as the basis for dividing natural segments, define the concave bank or the boundary of the concave bank as the segmentation node, divide the coastline into units, and form several initial shore segments. Step S13: Construct a buffer zone on the landward side of each initial shoreline segment, obtain the width of the construction land within the buffer zone, define it as W, and set a width threshold W. th If W>W th If W ≤ W, then the conditions for constructing an artificial beach are met. th If the conditions for the construction of an artificial beach are not met, this initial section of the shoreline will be excluded. Step S14: Assign numbers, start and end point coordinates, and attribute labels to the coastal sections that meet the requirements; Step S2: Construct a suitability evaluation index system, in which the evaluation index includes five types of factors: geomorphological factors, hydrodynamic factors, sediment factors, engineering factors, and ecological factors. Step S3: Dimensionless processing is performed on each evaluation index within the system, and the index weights are assigned values. Step S4: Combine the individual evaluation index processing completed in step S3 to obtain the total suitability score for each unit, and perform preliminary classification of the coastal section based on the scores of each unit. Step S5: Based on the completed static comprehensive scoring, use a numerical model to simulate the dynamic response of the sand body in the coastal section after preliminary classification. The steps for conducting dynamic response simulation of sand bodies are as follows: Step S51: Set the core parameters of the numerical model, including the initial topography of the beach, sand body parameters, and boundary structure; Step S52: SWAN outputs boundary conditions, which include wave height, period, and direction; Step S53: Set up a simulation scenario for simulation, the scenario including typical tidal conditions and extreme conditions; Step S54: Simulate and output the results indicators, which include changes in beach profile, erosion and sedimentation, and beach shoulder migration. Determine the stability and erosion risk of the artificial beach during its operation cycle. If severe sand loss or frequent structural maintenance is found, the system will lower the original grade of the coastal section and mark it as requiring structural protection or a low suitability zone. If the sand backfilling potential and engineering response capability are good, the grade will be maintained or raised. Step S6: Spatialize the simulation results obtained in step S5 and automatically update the evaluation results for dynamic correction.

2. The suitability assessment method for artificial beach projects on bedrock coasts according to claim 1, characterized in that: In step S1, the method for identifying coastal sections with bedrock landform features includes remote sensing images, digital elevation models, or shoreline databases. The bedrock landform features include cliff shores, rocky beaches, and rocky platform shores.

3. The suitability assessment method for artificial beach projects on bedrock coasts according to claim 1, characterized in that: In step S2, the geomorphic factors include bank slope, bedrock exposure rate, and coastline curvature; the hydrodynamic factors include significant wave height, nearshore current velocity, wave height reduction rate, and wave energy flux; the sediment factors include sediment transport flux, suspended sediment concentration, and siltation potential; the engineering factors include backshore land use, accessibility, and construction difficulty; and the ecological factors include overlap of ecologically sensitive areas and habitat disturbance index.

4. The suitability assessment method for artificial beach projects on bedrock coasts according to claim 1, characterized in that: In step S3, the step of dimensionless processing for each evaluation index is as follows: Step S311: If the evaluation index is a positive index, then the evaluation index is standardized using range. The calculation formula for each evaluation indicator is as follows: （2） In formula (2), The normalized value. These are the original indicator values. The maximum value of the evaluation index within the unit. The minimum value of the evaluation index within the unit; Step S312: If the evaluation indicator is a negative indicator, then reverse normalization is applied to the evaluation indicator. The formula for processing each evaluation indicator is: （3） In formula (3), The normalized value. These are the original indicator values. The maximum value of the evaluation index within the unit. The minimum value of the evaluation index within the unit; The steps for assigning values ​​to indicator weights are as follows: Step S321: Perform information entropy processing on the normalized values. The processing formula is as follows: （4） In formula (4), For information entropy, For the sample size, Numbering assigned to eligible coastal sections. For the first Within the first coastal section One evaluation indicator; Step S322, calculate the first... The weighting coefficients of the evaluation indicators within each coastal segment are calculated using the following formula: （5） In formula (5), These are the weighting coefficients. For the first Information utility value within each coastal segment, and d j = 1 – e j .

5. The suitability assessment method for artificial beach projects on bedrock coasts according to claim 1, characterized in that: In step S4, the preliminary classification of the coastal section is performed as follows: Step S41: Calculate the overall suitability score for each assessment unit using the weighted linear superposition method. The calculation formula is as follows: （6） In formula (6), For the first j The overall suitability score for each coastal segment For the first i The weight of each indicator, This represents the total number of indicators; Step S42: Based on the comprehensive suitability score of the evaluation unit in Step S41, classify the areas into levels. If R ≥ 0.75, it is determined to be a highly suitable area, indicating that the coastal section has excellent conditions and is ready for direct construction, and is given priority recommendation. If 0.60 ≤ R < 0.75, it is determined to be a suitable area, indicating that the coastal section has construction conditions, but some factors are slightly weaker, and it is suitable to combine local optimization. If 0.40 ≤ R < 0.60, it is determined to be a low-suitability area, indicating that the conditions are limited and require supporting protection or ecological engineering. If R < 0.40, it is determined to be an unsuitable area, indicating that the terrain, wave, or ecological conditions are obviously unfavorable, and it is recommended not to build.

6. The suitability assessment method for artificial beach projects on bedrock coasts according to claim 1, characterized in that: In step S6, the evaluation results are spatially represented on the GIS platform. The evaluation results include: a four-color partitioning of the comprehensive suitability level map, a spatial distribution map of five types of factors, an output layer for simulating a simulated scenario, a level change layer of the simulated output result indicators, and a list of recommended construction sections and priority ranking.

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