Bay ecosystem health evaluation zoning method based on tidal range

Abstract

The invention provides a bay ecosystem health evaluation zoning method based on tidal range, belongs to the field of marine ecological environment management and evaluation, and mainly aims at typical bays, especially closed and semi-closed bays. On the basis of long-time series tidal range data, a threshold determination method coupled with'spatial hierarchical clustering + natural discontinuity point + contour coefficient 'multistage correction is adopted, different management requirements are served by utilizing multistage clustering, the requirements of simplicity and fineness of management are considered, the visualization of a partitioning result is realized, and a typical bay partitioning scheme is finally obtained; according to the scheme, the zoning method based on the tidal range is established to reflect the difference characteristics of the water body in the typical bay, and a stable and repeatable zoning boundary is obtained, so that a health evaluation result is more reasonably obtained, and the method has important guiding significance for scientific evaluation and management of the health condition of an ecological system.

Description

Technical Field

[0001] This invention belongs to the field of marine ecological environment management and evaluation, and specifically relates to a zoning method for evaluating the health of bay ecosystems based on tidal range. Background Technology

[0002] Bays are marine waters where the coastline curves into the land, creating distinct watercourses. They possess unique geographical environments, and due to their encirclement by land and complex topography, the spatial heterogeneity of bay ecosystems is significantly higher than that of open seas. Bays are semi-enclosed, with significantly weaker water exchange capacity than open seas, leading to the easy accumulation of nutrients, pollutants, and other substances within the bay, forming unique biogeochemical cycling patterns (Wu, 2011; Zhang, 2014; HE, 2016). These characteristics make bay ecosystems particularly vulnerable and at high risk of degradation within the marine ecosystem, under the dual pressures of natural changes and human activities.

[0003] Ecosystem health assessment is an important tool for ecological management, comprehensively considering the structure, function, and services of ecosystems to measure their health status (Costanza et al., 1992), providing a scientific basis for protecting marine ecosystems and achieving sustainable development. Marine ecological zoning is a widely used spatial tool for marine management (Yael, 2025). In 1992, the United States initiated the development of the Coastal and Marine Ecological Classification Standard (CMECS), systematically integrating elements such as topography, substrate, and organisms to provide a scientific framework for zoning. However, current zoning methods do not involve bays, and their purpose is not to serve marine ecosystem health assessment, making them difficult to directly apply to bay ecological management.

[0004] Currently, there are numerous methods for assessing ecosystem health, such as the Ecological Quality Ratio (EQR index). This index is obtained by calculating the ratio of the standard value to the actual value or the actual value to the standard value to assess the health status of the ecosystem. However, it often has a major limitation: it considers all types of water bodies (estuaries, bays, open water bodies, etc.) in a unified manner. Existing methods do not adequately consider the differences between different types of water bodies, ignoring the significant ecological differences and spatial heterogeneity between different types of water bodies. This makes it difficult to accurately reflect the true ecological state of special water bodies such as bays, resulting in assessment results that deviate from reality and fail to provide effective support for precise governance.

[0005] From a technical perspective, existing zoning methods face three main challenges in their application to bays: First, bays are surrounded by land, have complex topography, and are semi-enclosed, exhibiting significant spatial heterogeneity and small-scale differences, lacking stable indicators suitable for zoning within the bay; second, hydrodynamic conditions are complex and variable, often lacking stable and universal physical or chemical parameters as zoning references; and third, bay ecosystems are heavily disturbed by human activities, with pollutants and nutrients easily accumulating, and biogeochemical processes exhibiting high spatiotemporal variability, leaving researchers often at a loss when zoning. Therefore, existing zoning frameworks mostly remain at the large-scale nearshore or open sea level, and systematic zoning studies for bays have not yet been conducted.

[0006] In today's rapidly developing society, phenomena such as water quality deterioration and ecological function degradation are gradually emerging. Under the dual pressures of natural changes and human activities, bays have become one of the most vulnerable areas for marine ecosystems. The key innovation and direction of this invention lies in overcoming the limitations of existing zoning methods in parameter selection and scale adaptation, and proposing a zoning scheme that truly reflects the characteristics of bays, thereby supporting the scientific evaluation and management of ecosystem health. Summary of the Invention

[0007] To address the shortcomings of existing ecosystem health assessment methods, such as neglecting spatial heterogeneity and the inapplicability of zoning methods to bays, this invention proposes a zoning method for bay ecosystem health assessment based on tidal range. By utilizing tidal range data for correlation analysis, the zoning results based on tidal range are visualized, and a typical bay zoning scheme is ultimately obtained.

[0008] This invention is achieved using the following technical solution: a zoning method for assessing the health of a bay ecosystem based on tidal range, comprising: Daily tidal data from various tide gauge stations in the nearshore waters were collected and organized to obtain long-term series of average tidal range data for each station. Spatial hierarchical clustering is used to classify the tidal range of each station based on its numerical and spatial characteristics, so that the clustering results have both mathematical and spatial characteristics. The natural discontinuity method is used to perform boundary correction on the spatial hierarchical clustering results, thereby reducing the error of the tidal zone threshold. Calculate the silhouette coefficient to verify the rationality of the partition threshold; Spatial analysis software was used to visualize the zoning results based on tidal range, forming a schematic diagram of nearshore sea area zoning. Based on management needs and zoning results, a typical bay zoning scheme was obtained.

[0009] Compared with the prior art, the advantages and positive effects of the present invention are as follows: This scheme, based on the obtained average tidal range data, reduces the error of the tidal range zoning threshold through spatial hierarchical clustering and boundary correction. It also verifies the rationality of the zoning threshold using the silhouette coefficient, thereby visualizing the tidal range-based zoning results and ultimately obtaining a typical bay zoning scheme. This achieves "stable and repeatable" zoning boundaries within bays with highly spatiotemporal variations, while balancing the "simplicity" required for administrative management with the inherent "precision" of ecological processes. It accurately reflects the characteristics of the bay and provides technical support for the scientific evaluation and management of ecosystem health. Attached Figure Description

[0010] Figure 1 This is a schematic diagram of the process for the zoning method for assessing the health of a bay ecosystem, as described in an embodiment of the present invention. Detailed Implementation

[0011] To better understand the above-described objects, features, and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments. Many specific details are set forth in the following description to provide a thorough understanding of the present invention; however, the present invention may be practiced in other ways than those described herein, and therefore, the present invention is not limited to the specific embodiments disclosed below. This embodiment proposes a zoning method for assessing the health of bay ecosystems based on tidal range, which is particularly suitable for enclosed and semi-enclosed bays, such as... Figure 1 The above includes the following steps: Step A: Determine the target sea area and obtain tidal range data; Step B: Preprocess the tidal range data: Step B1: Classify the obtained tidal range data based on its numerical and spatial characteristics using spatial hierarchical clustering; Step B2: Determine the tidal range classification discontinuity points based on the natural discontinuity method, and determine the discontinuity results; Step B3: Use the breakpoint results obtained in step B2 to perform boundary correction on the spatial hierarchical clustering results in step B1 to obtain the tidal range zoning threshold. Step C: Verify the rationality of the tidal range zoning threshold. If it is not rational, repeat step B. If it is rational, proceed to step D. Step D: Combine the tidal range zoning threshold to obtain the target sea area zoning results, use spatial analysis software to visualize the zoning results, and finally determine the target bay zoning scheme.

[0012] Specifically, to better understand the solution of this invention, the following detailed explanation is provided with reference to specific examples: Step A: Determine the target sea area and acquire and process large-scale, long-term tidal range monitoring data from tide gauge stations. Based on the geographical location of the target bay, the sea area where it is located is selected as the zoning object to ensure the continuity and rationality of the subsequent interpolation results and avoid the problem of inaccurate results caused by small-scale tidal range zoning. After determining the zoning sea area, daily tidal data from each tide gauge station within the range are collected as much as possible, and the average value is calculated to obtain long-term station average tidal range data. Tidal range, as a macroscopic steady-state factor that integrates the topography, hydrology and dynamic conditions of the bay, can effectively overcome the high-frequency fluctuation defects of conventional water quality indicators and provide a stable and reliable data foundation for zoning. Tidal range = high tide level of a single tidal cycle - low tide level of a single tidal cycle.

[0013] This embodiment specifically takes the nearshore waters of the Bohai Sea and the northern Yellow Sea as an example to determine the ecosystem health assessment zones of typical bays such as Liaodong Bay, Bohai Bay, and Laizhou Bay. In this embodiment, tidal data from 40 tide gauge stations, including Bayuquan, Beidaihe, and Beihuangcheng, from 2017 to 2022 were collected and their average values ​​were calculated.

[0014] Step B: Preprocess the tidal range data Step B1: Spatial Constraint Hierarchical Clustering Spatial hierarchical clustering is used to classify the tidal ranges of each station based on their numerical and spatial characteristics, giving the clustering results both mathematical and spatial features. This embodiment utilizes spatial analysis software for spatial hierarchical clustering. Spatial hierarchical clustering is a clustering method that integrates geographic spatial proximity and attribute similarity. Its core principle is to gradually merge spatial units by constructing a tree-like structure to form a multi-level cluster structure, ensuring that the results take into account both geographic coherence and attribute homogeneity. It is suitable for related studies of spatially continuous areas with similar ecological characteristics. During clustering, the number of clusters is adjusted according to the data characteristics and zoning requirements.

[0015] Specifically, software such as GeoDa can be used to perform the operation, setting 3, 4, or 5 categories to start clustering. The clustering results are then displayed in ArcGIS software.

[0016] Step B2, Data-driven classification of natural discontinuities By combining spatial analysis software and employing the Jenks Natural Breaks Optimization method, tidal range classification breakpoints are determined. The number of breakpoint classifications is the same as the number of clusters. Iterative optimization is used to find natural cluster boundaries in the data, minimizing the sum of intra-cluster variances while maximizing inter-cluster differences. This effectively avoids the subjectivity of manually set thresholds, highlights abrupt changes in spatial heterogeneity, and is suitable for geospatial analysis. This embodiment determines the optimal arrangement of tidal range values ​​within a group by iteratively comparing the sum of squared differences between the mean and observed values ​​of each group and the mean of elements within that group. The calculated optimal classification identifies breakpoints in the ordered distribution of tidal range values, minimizing the sum of intra-group squared differences.

[0017] In this embodiment, corresponding to the number of clustering categories in step B1, 3, 4, and 5 discontinuous categories are set respectively, and the breakpoint values ​​are determined. The breakpoint values ​​are as follows: Level 3 classification boundary: 89-189-268-365; Level 4 classification boundary: 89-156-207-274-365; Level 5 classification boundary: 89-151-194-230-284-365.

[0018] Step B3: Perform bidirectional boundary correction The breakpoint results (results in step B2) are used to correct the clustering results (results in step B1). The clustering results are offset and rounded towards the breakpoint results to optimize boundary values ​​and ensure minimal intra-cluster differences. Spatial hierarchical clustering combined with natural discontinuities determines the boundaries of tidal zones, integrating geographical proximity constraints and the identification of inherent data structures. This avoids spatial fragmentation caused by using only natural discontinuities to determine thresholds, maintaining spatial adjacency, and also prevents single spatial hierarchical clustering from ignoring inherent data features.

[0019] In this embodiment, the numerical breakpoint in step B2 is used to correct the clustering boundary in step B1, and the classification thresholds of each scale of the tidal zone are finally obtained, as shown in Table 1.

[0020] Table 1 Thresholds for Nearshore Tidal Range Zones Step C: Calculate the contour coefficient to verify the rationality of the partition threshold; Calculate the silhouette coefficients between the components of each partition after correction (results in step B3) to verify the rationality of the partitioning. The silhouette coefficient is an indicator that measures the clustering effect, assessing the similarity within the same cluster and between different clusters in the samples. Its value ranges from [-1, 1], and the closer it is to 1, the better the cohesion and separation are.

[0021] The silhouette coefficient represents a specific sample. Indicates sample The average distance to other samples within the same cluster; Indicates sample The average distance to all samples in the nearest other cluster; This represents the average silhouette coefficient of all samples within the nth category; This represents the number of samples within the nth category; This indicates the total number of samples.

[0022] Table 2. Calculation results of contour coefficients for three types of zones. Partition Category Profile coefficient Third-level partition 0.637 Level 4 partitions 0.628 Five-level partition 0.588 As shown in Table 2, all contour coefficients are positive and the values ​​are between 0.5 and 0.7, indicating that the grouping structure is reasonable.

[0023] Step D: Use spatial analysis software to visualize the zoning results based on tidal range, forming a schematic diagram of nearshore sea area zoning, and obtain a typical bay zoning scheme based on management needs and zoning results.

[0024] Then, based on the tidal range zoning threshold, a nearshore sea area zoning diagram is obtained, along with a target bay zoning scheme. Specifically, grading colors can be set according to the tidal range threshold to obtain a nearshore sea area zoning diagram, and the bay tidal range zoning result can be obtained based on the target bay boundary.

[0025] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments for application in other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A zoning method for assessing the health of a bay ecosystem based on tidal range, characterized in that, Includes the following steps: Step A: Determine the target sea area and obtain tidal range data; Step B: Preprocess the tidal range data: Step B1: Classify the obtained tidal range data based on its numerical and spatial characteristics using spatial hierarchical clustering; Step B2: Determine the tidal range classification discontinuity points based on the natural discontinuity method, and determine the discontinuity results; Step B3: Use the breakpoint results obtained in step B2 to perform boundary correction on the spatial hierarchical clustering results in step B1 to obtain the tidal range zoning threshold. Step C: Verify the rationality of the tidal range zoning threshold. If it is not rational, repeat step B. If it is rational, proceed to step D. Step D: Combine the tidal range zoning thresholds to obtain the target sea area zoning results, use spatial analysis software to visualize the zoning results, and finally determine the bay zoning scheme.

2. The zoning method for assessing the health of a bay ecosystem based on tidal range according to claim 1, characterized in that: In step A, daily tidal data from various tide gauge stations in the nearshore waters are collected and organized to obtain long-term series station average tidal range data.

3. The zoning method for assessing the health of a bay ecosystem based on tidal range according to claim 1, characterized in that: In step B1, spatial hierarchical clustering is performed using spatial analysis software. By constructing a tree structure, spatial units are gradually merged to form a multi-level clustering structure.

4. The zoning method for assessing the health of a bay ecosystem based on tidal range according to claim 1, characterized in that: In step B2, the number of tidal range classification breaks is the same as the number of cluster categories. The optimal arrangement of tidal range values ​​in the group is determined by iteratively comparing the sum of squared differences between the mean and the observed values ​​of each group and the mean of the elements in the group. The calculated optimal classification can determine the breakpoint of the tidal range values ​​in the ordered distribution.

5. The zoning method for assessing the health of a bay ecosystem based on tidal range according to claim 1, characterized in that: In step B3, spatial hierarchical clustering is combined with natural discontinuities to determine the tidal zone boundaries. The discontinuities are used to correct the cluster boundaries to obtain the threshold values ​​for each scale based on tidal range.

6. The zoning method for assessing the health of a bay ecosystem based on tidal range according to claim 1, characterized in that: In step C, the rationality of the tidal range zoning threshold is verified by calculating the profile coefficient. Specifically, the profile coefficient result is in the range of [-1, 1]. The closer it is to 1, the better the clustering effect and the more reasonable the zoning.

7. The zoning method for assessing the health of a bay ecosystem based on tidal range according to claim 1, characterized in that: In step D, when performing visualization, the graded colors are set according to the tidal range zoning threshold to obtain a schematic diagram of the nearshore sea area zoning, and the bay tidal range zoning result is obtained according to the target bay boundary.

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