Method and system for assessing ecological impact of waterway engineering construction on wetland along waterway

Abstract

The present application relates to the technical field of wetland ecological impact assessment, and particularly relates to a water transportation engineering construction method and system for assessing ecological impact on wetland areas along the line; the present application improves a mapping function of ecological index change rate mapping to a 0-1 interval, so as to offset the problem of possible asymmetric threshold response of ecological index change caused by the original tanh function, so that the overall mapping performance of the improved mapping function is significantly improved; when data cleaning is performed on ground monitoring data, according to the characteristics that the ground monitoring data in the wetland field investigation data are greatly affected by environmental factors, the tidal phase, rainfall intensity and monitoring parameters are triply associated, fine data cleaning of wetland natural fluctuation is realized, natural noise in the wetland monitoring data is effectively inhibited, and the ecological impact signal related to engineering activities is accurately extracted.

Description

Technical Field

[0001] This invention relates to the field of wetland ecological impact assessment technology, specifically a method and system for assessing the ecological impact of waterway engineering construction on wetland areas along the route. Background Technology

[0002] Water transport projects, such as canal dredging, channel dredging, and lock construction, are important infrastructure for regional economic development. However, their construction often involves human activities such as earthwork excavation, water disturbance, and pollutant discharge, which directly or indirectly affect the ecological functions of wetlands along the route. Wetlands, known as the "kidneys of the earth," have key ecological service functions such as water conservation, biodiversity maintenance, and water purification. Their ecosystems are sensitive and have long recovery cycles.

[0003] Because wetland field survey data contains a large amount of data with multiple parameters, especially ground monitoring data which is greatly affected by environmental factors, conventional data cleaning methods such as fixed threshold method and simple moving average filtering in existing technologies cannot provide good data preprocessing results for ground monitoring data in wetland ecological assessment. At the same time, when mapping evaluation indicators to the 0-1 interval, the Sigmoid function is generally used. However, the tanh in the Sigmoid function is an S-shaped curve symmetric about the origin, while the changes in indicators may have asymmetric threshold responses, resulting in low mapping accuracy and affecting the accurate assessment of the ecological impact of waterway construction on wetland areas along the route. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method and system for assessing the ecological impact of waterway engineering construction on wetland areas along the route, thereby resolving the issues existing in the prior art.

[0005] This invention provides a method for assessing the ecological impact of waterway engineering construction on wetland areas along the route, including the following steps: S1: Obtaining multi-source data for assessing the ecological impact of waterway engineering construction on wetland areas along the route;

[0006] S2: Perform data preprocessing operations on the multi-source data;

[0007] S3: Construct a multi-dimensional ecological impact indicator system;

[0008] S4: Calculate the standardized impact score for the ecological impact indicators;

[0009] Specifically, S4 consists of: S4.1: Calculating the relative change rate ΔR of each secondary indicator before and after the construction of the waterway project; S4.2: Mapping the relative change rate ΔR of each secondary indicator before and after the construction of the waterway project to a value in the range of 0-1; the mapping function is:

[0010] ;

[0011] Where: k is the linear adjustment coefficient; m is the quadratic adjustment coefficient; T func The threshold value is tanh; tanh is the hyperbolic tangent function.

[0012] S4.3: Perform orientation correction on the values ​​mapped to the 0-1 interval to obtain the standardized impact score corresponding to each indicator;

[0013] S5: Calculate the comprehensive impact index based on the standardized impact score and corresponding weight of each indicator;

[0014] S6: Assess the ecological impact of waterway construction on wetland areas along the route based on the comprehensive impact index.

[0015] Preferably, the preprocessing operation includes cleaning the ground monitoring data based on a tidal rainfall coupling processing method; specifically:

[0016] Sa: Feature extraction of tidal data; extracted features include: tidal cycle type, tidal phase, and tidal intensity; wherein, the detection of tidal cycle type based on tidal data specifically involves: performing Hilbert-Huang transform on the tidal data to extract multiple intrinsic mode functions (IMFs) of the tidal data; based on preset rules, selecting components reflecting the tidal cycle from the multiple IMFs of the tidal data; performing Fourier transform on the components reflecting the tidal cycle to determine the cycle type of the tidal data; Sb: Grading of rainfall intensity according to rainfall data; Sc: Determining the normal fluctuation range of the ground monitoring data; Sd: Data cleaning of the ground monitoring data according to the normal fluctuation range of the ground monitoring data.

[0017] Preferably, in step S2, the data preprocessing operation includes spatiotemporal alignment of multi-source data and enhancement of biological survey data.

[0018] Preferably, in the Sa, performing a Fourier transform on the components reflecting the tidal cycle to determine the cycle type of the tidal data specifically involves: performing a Fourier transform (FFT) on the selected components reflecting the tidal cycle, calculating their spectral distribution and extracting the cycle corresponding to the main frequency, and determining the tidal type as a semi-diurnal tide or a diurnal tide based on the cycle corresponding to the main frequency.

[0019] Determining the tidal phase based on the tidal data specifically involves dividing the tidal data into three tidal phases: high tide, low tide, and slack tide, according to the water level change trend and extreme points of the tidal data.

[0020] The quantification of tidal intensity based on the tidal data specifically involves: calculating the tidal range for each tidal cycle, and classifying tidal intensity into three levels: weak tide, moderate tide, and strong tide, reflecting the degree of influence of tides on wetland hydrological exchange; the tidal range of the weak tide is <1m; the tidal range of the moderate tide is 1-2m; and the tidal range of the strong tide is >2m.

[0021] Preferably, Sd specifically involves: for each monitoring time t, extracting the corresponding tidal phase, rainfall intensity, and monitoring parameter values; determining the normal range of each parameter of the ground monitoring data based on the tidal phase and rainfall intensity at time t; if the value of each parameter of the ground monitoring data is within the normal range corresponding to the parameter: marking it as natural fluctuation and retaining it; if the value of each parameter of the ground monitoring data exceeds the normal range corresponding to the parameter: further checking whether there are engineering activities, if so, marking it as engineering-related anomalies and retaining it; if not, marking it as natural noise and discarding it.

[0022] Preferably, the multi-dimensional ecological impact indicator system includes four primary indicators: habitat physical structure, biological community structure, environmental quality factors, and ecological function services. Each primary indicator includes multiple secondary indicators. Specifically, the habitat physical structure includes four secondary indicators: vegetation cover, soil sand / clay ratio, surface elevation change, and water level fluctuation. The biological community structure includes four secondary indicators: Shannon-Wiener index, benthic abundance, number of bird species, and survival rate of fish larvae. The environmental quality factors include eight secondary indicators: COD content, ammonia nitrogen content, total phosphorus content, heavy metal content, petroleum hydrocarbon content, organic matter content, soil electrical conductivity, and soil pH. The ecological function services include four secondary indicators: water evapotranspiration, groundwater recharge rate, soil organic carbon content, and pollution purification efficiency.

[0023] Preferably, the weighted summation model is used to calculate the comprehensive impact index EII; the calculation formula is as follows:

[0024] ;

[0025] In the formula, i is the i-th indicator, n is the number of indicators, and w i The weight of the i-th indicator is determined by AHP in step S3, S i Score represents the standardized impact score of the i-th indicator.

[0026] Preferably, the assessment results are categorized into four levels: minor, moderate, severe, and extremely severe. The comprehensive impact index (EII) range for the minor assessment result is 0 ≤ EII < 0.2; for the moderate assessment result, it is 0.2 ≤ EII < 0.5; for the severe assessment result, it is 0.5 ≤ EII < 0.8; and for the extremely severe assessment result, it is EII ≥ 0.8.

[0027] According to another aspect of the present invention, a method and system for assessing the ecological impact of waterway engineering construction on wetland areas along the route is provided. The system employs the aforementioned method for assessing the ecological impact of waterway engineering construction on wetland areas along the route, and the system includes:

[0028] The data acquisition module is used to acquire multi-source data for assessing the ecological impact of waterway engineering construction on wetland areas along the route;

[0029] The preprocessing module is used to perform data preprocessing operations on the multi-source data;

[0030] The indicator system construction module is used to construct a multi-dimensional ecological impact indicator system;

[0031] The indicator score calculation module is used to calculate the standardized impact score of the ecological impact indicator.

[0032] The comprehensive impact index calculation module is used to calculate the comprehensive impact index based on the standardized impact score and corresponding weight of each indicator.

[0033] The assessment module is used to assess the ecological impact of waterway construction on wetland areas along the route based on the comprehensive impact index.

[0034] The embodiments of the present invention have the following technical effects:

[0035] This invention improves the mapping function that maps the rate of change of ecological indicators to the 0-1 interval, thereby offsetting the problem of asymmetric threshold response that may exist in the changes of ecological indicators caused by the original tanh function. This significantly improves the overall mapping performance of the improved mapping function. When cleaning ground monitoring data, this invention takes into account the fact that ground monitoring data in wetland field survey data is greatly affected by environmental factors. It establishes a ternary correlation between tidal phase, rainfall intensity and monitoring parameters to achieve refined data cleaning of natural fluctuations in wetlands. This effectively suppresses natural noise in wetland monitoring data and accurately extracts ecological impact signals related to engineering activities. Attached Figure Description

[0036] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0037] Figure 1 This is a flowchart of the method for assessing the ecological impact of waterway engineering construction on wetland areas along the route, provided in an embodiment of the present invention.

[0038] Figure 2 This is a flowchart of the ground monitoring data cleaning operation based on tidal rainfall coupling processing provided in an embodiment of the present invention;

[0039] Figure 3 This is a flowchart for calculating the standardized impact score of the ecological impact index provided in an embodiment of the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0041] Example 1, Appendix Figure 1 A flowchart illustrating the method for assessing the ecological impact of waterway construction on wetland areas along the route is shown in the attached diagram. Figure 1 As shown, the method for assessing the ecological impact of waterway construction on wetland areas along the route includes the following steps:

[0042] S1: Obtain multi-source data for assessing the ecological impact of waterway engineering construction on wetland areas along the route;

[0043] In this step, the multi-source data includes remote sensing data, UAV aerial survey data, and ground monitoring data.

[0044] The remote sensing data is used to acquire macroscopic information such as wetland spatial distribution, vegetation cover dynamics, land use change, and hydrological connectivity. This remote sensing data mainly includes vegetation index data, water body index data, and land use / cover classification data. The UAV aerial survey data is used to supplement the shortcomings of the remote sensing data in terms of spatial resolution and timeliness, focusing on monitoring local habitat details within a 500-2000 meter radius around the waterway engineering area. This UAV aerial survey data mainly includes vegetation canopy height data, topographic relief data, and microhabitat structure data. The ground monitoring data is used to provide real-time dynamic data on key environmental factors such as water quality, soil, and meteorology, compensating for the deficiencies of the static snapshots of remote sensing data and UAV aerial survey data. The ground monitoring data mainly includes: water level data, water quality data, soil data, and meteorological data. The water level data includes tidal data detected by water level gauges. The water quality data includes data on water temperature, pH, dissolved oxygen (DO), conductivity, chemical oxygen demand (COD), ammonia nitrogen (NH3-N), total phosphorus (TP), and heavy metals (lead Pb, cadmium Cd) collected in real time by automatic monitoring stations or portable sensors. The soil data includes data on water content, conductivity, pH value, and organic matter content in the 0-30cm soil layer monitored by in-situ sensors. The meteorological data includes data on temperature, rainfall, wind speed, and relative humidity recorded by automatic weather stations.

[0045] S2: Perform data preprocessing operations on the multi-source data;

[0046] The data preprocessing operations include spatiotemporal alignment of multi-source data, data cleaning, and biological survey data enhancement.

[0047] It is worth emphasizing that when performing data cleaning and preprocessing on ground monitoring data used for assessing the ecological impact of waterway engineering construction on wetland areas along the route, wetlands are affected by natural processes such as tides and rainfall. Existing conventional data cleaning methods (fixed threshold method, simple moving average filtering, etc.) are not effective for cleaning ground monitoring data used in wetland ecological assessments. Therefore, if... Figure 2 As shown in the figure, this embodiment proposes a ground monitoring data cleaning operation based on tidal rainfall coupling processing; specifically:

[0048] Sa: Feature extraction from tidal data;

[0049] The extracted features include: tidal cycle type, tidal phase, and tidal intensity.

[0050] The specific steps for detecting the tidal cycle type based on tidal data are as follows: performing Hilbert-Huang transform (HHT) on the tidal data to extract multiple intrinsic mode functions (IMFs) of the tidal data; selecting components reflecting the tidal cycle from the multiple IMFs of the tidal data based on preset rules; and performing Fourier transform on the components reflecting the tidal cycle to determine the cycle type of the tidal data.

[0051] The core of the Hilbert-Huang transform is to decompose a non-stationary signal into a series of intrinsic mode functions (IMFs). Each IMF satisfies two conditions: the number of extrema is equal to or differs from the number of zero-crossings by no more than 1; and the mean of the upper and lower envelopes is zero.

[0052] The preset rules are specifically as follows:

[0053] Period range matching: The theoretical period range of tides is semi-diurnal or diurnal, and the period of the inherent mode function reflecting the tidal period should fall within this range;

[0054] Energy percentage priority: Calculate the energy of each intrinsic mode function, with the tidal period component having the highest energy;

[0055] Physical significance verification: In the time series diagram of the inherent mode function of the tidal cycle, it should show an alternating peak-trough pattern, and the waveform symmetry should conform to the physical law of tides.

[0056] Specifically, the process of performing a Fourier transform on the components reflecting the tidal cycle to determine the cycle type of the tidal data involves: performing a Fourier transform (FFT) on the selected components reflecting the tidal cycle, calculating their spectral distribution, extracting the cycle corresponding to the main frequency, and determining whether the tidal type is a semi-diurnal tide or a diurnal tide based on the cycle corresponding to the main frequency.

[0057] In this step, the tidal cycle detection method based on Hilbert-Huang transform (HHT) and Fourier transform effectively solves the problem of non-stationarity and nonlinear noise interference in wetland water level time series and accurately identifies the tidal cycle.

[0058] Determining the tidal phase based on the tidal data specifically involves dividing the tidal data into three tidal phases: high tide, low tide, and slack tide, according to the water level change trend and extreme points of the tidal data.

[0059] The quantification of tidal intensity based on the tidal data specifically involves: calculating the tidal range for each tidal cycle, and classifying tidal intensity into three levels: weak tide, moderate tide, and strong tide, reflecting the degree of influence of tides on wetland hydrological exchange; the tidal range of the weak tide is <1m; the tidal range of the moderate tide is 1-2m; and the tidal range of the strong tide is >2m.

[0060] Sb: Classify rainfall intensity based on rainfall data;

[0061] Rainfall affects monitoring parameters by altering processes such as surface runoff and soil infiltration. This step classifies rainfall intensity into four levels based on hourly rainfall; Table 1 is the rainfall intensity classification table.

[0062] Table 1 Rainfall Intensity Classification Table

[0063] ;

[0064] Sc: Determine the normal fluctuation range of the ground monitoring data;

[0065] Based on data from the year prior to construction without engineering interference, and combined with the conditions of tidal characteristics and rainfall intensity, the normal fluctuation range of each monitoring parameter under different tidal characteristics and rainfall intensity conditions was calculated:

[0066] For example, taking the calculation of the normal fluctuation range of COD monitoring data under high tide and light rain conditions as an example, all samples that meet the conditions of "tidal phase = high tide" and "rainfall intensity = light rain" are extracted from the data of one year before construction to form a subset; the mean (μ) and standard deviation (σ) of COD data in the subset are calculated; and a 95% confidence interval is calculated based on the mean and standard deviation as the normal fluctuation range of COD under high tide and light rain conditions.

[0067] Sd: Clean the ground monitoring data according to the normal fluctuation range of the ground monitoring data;

[0068] For each monitoring time t, the corresponding tidal phase, rainfall intensity, and monitoring parameter values ​​are extracted. Based on the tidal phase and rainfall intensity at time t, the normal range of each parameter of the ground monitoring data is determined. If the value of each parameter of the ground monitoring data is within the normal range corresponding to the parameter, it is marked as natural fluctuation and retained. If the value of each parameter of the ground monitoring data exceeds the normal range corresponding to the parameter, further checks are conducted to determine if there are any engineering activities. If so, it is marked as engineering-related anomaly and retained; otherwise, it is marked as natural noise and discarded.

[0069] This step breaks through the traditional single-parameter threshold method and for the first time establishes a ternary correlation between tidal phase, rainfall intensity and monitoring parameters, thereby achieving refined data cleaning of natural fluctuations in wetlands, effectively suppressing natural noise in wetland monitoring data, and accurately extracting ecological impact signals related to engineering activities.

[0070] S3: Construct a multi-dimensional ecological impact indicator system;

[0071] The multi-dimensional ecological impact indicator system includes four primary indicators: habitat physical structure, biological community structure, environmental quality factors, and ecological function services. Each primary indicator includes multiple secondary indicators. Specifically, the habitat physical structure includes four secondary indicators: vegetation cover, soil sand / clay ratio, surface elevation change, and water level fluctuation. The biological community structure includes four secondary indicators: Shannon-Wiener index, benthic abundance, number of bird species, and fish larval survival rate. The environmental quality factors include eight secondary indicators: COD content, ammonia nitrogen content, total phosphorus content, heavy metal content, petroleum hydrocarbon content, organic matter content, soil electrical conductivity, and soil pH. The ecological function services include four secondary indicators: water evapotranspiration, groundwater recharge rate, soil organic carbon content, and pollution purification efficiency.

[0072] The weight of each secondary indicator is determined by the Analytic Hierarchy Process (AHP). The method of determining weights using AHP is a prior art and will not be discussed in detail in this embodiment.

[0073] S4: Calculate the standardized impact score for the ecological impact indicators;

[0074] In the ecological impact assessment of wetlands in waterway engineering, the various ecological impact indicators have different dimensions. In order to achieve comparability and comprehensive analysis of multiple indicators, each indicator needs to be quantified into a standardized impact score within the range of 0-1. It is worth emphasizing that the indicators mentioned are secondary indicators.

[0075] Among them, such as Figure 3 As shown, S4 specifically includes:

[0076] S4.1: Calculate the relative rate of change of each secondary indicator before and after the construction of the waterway project;

[0077] Among them, the indicator value before the construction of the waterway project is the average value of the indicator obtained from the historical data of the indicator within the preset time range; the indicator value after the construction of the waterway project is the average value of the monitored value of the indicator within the preset time range.

[0078] S4.2: Map the relative rate of change of each of the secondary indicators before and after the construction of the waterway project to a value in the range of 0-1;

[0079] In existing technologies, the relative change rate ΔR of the secondary index before and after the construction of waterway engineering is used as input, and the Sigmoid function is used to map ΔR to the 0-1 interval, where ΔR=0 corresponds to a score of 0.5, and ΔR>0 or ΔR<0 (favorable change) corresponds to a score shifting towards 1 or 0.

[0080] The expression for the mapping function is:

[0081] ;

[0082] Where: k is the adjustment coefficient for the first-order term, used to control the steepness of the function, usually taken as 2-5, determined based on historical data fitting; T func is the preset threshold; tanh is the hyperbolic tangent function with an output range of [-1, 1], ensuring that the output is in the 0-1 interval.

[0083] However, when the above scheme is used for mapping, tanh is an S-shaped curve symmetric about the origin. When the tanh function is applied to the ecological and environmental impact assessment, the change in the index ΔR may have an asymmetric threshold response. When ΔR is too high, there will be an accelerated deterioration effect. That is, the relationship between ΔR and functional loss has a non-linear interaction characteristic. Therefore, applying the original tanh function to the ecological and environmental impact assessment will lead to a significant reduction in the accuracy of the mapping.

[0084] This embodiment addresses the aforementioned problems by improving the mapping function to counteract the asymmetric threshold response. Specifically, the mapping function that maps the relative rate of change of each of the secondary indicators before and after the construction of the waterway project to a value in the 0-1 range is as follows:

[0085] ;

[0086] Where: k is the linear term adjustment coefficient, used to control the steepness of the function, usually taken as 2-5, determined based on historical data fitting; m is the quadratic term adjustment coefficient, used to control the influence of the quadratic term; T func is the preset threshold; tanh is the hyperbolic tangent function with an output range of [-1, 1], ensuring that the output is in the 0-1 interval.

[0087] This embodiment improves the mapping function of the relative rate of change to counteract the problem of asymmetric threshold response that may exist in the change of ΔR caused by the original tanh function, thereby significantly improving the overall mapping performance of the improved mapping function.

[0088] S4.3: Perform orientation correction on the values ​​mapped to the 0-1 interval to obtain the standardized impact score corresponding to each indicator;

[0089] The formula for direction correction is as follows:

[0090] ;

[0091] In the formula, Score is the standardized impact score;

[0092] In the above formula, adverse effects refer to behaviors / factors that have a negative impact on wetland ecology, such as environmental pollution; favorable effects refer to behaviors / factors that bring positive effects to wetland ecology, such as environmental improvement; positive indicators refer to indicators whose larger values ​​represent better and more positive outcomes, such as an increase in the value corresponding to green coverage rate, which means a better wetland ecology; negative indicators refer to indicators whose larger values ​​represent worse and more negative outcomes, such as an increase in the value corresponding to pollutant emissions, which means increased pressure on wetland ecology.

[0093] S5: Calculate the comprehensive impact index based on the standardized impact score and corresponding weight of each indicator;

[0094] The weighted summation model is used to calculate the comprehensive impact index EII; the calculation formula is as follows:

[0095] ;

[0096] In the formula, i is the i-th indicator, n is the number of indicators, and w i The weight of the i-th indicator is determined by AHP in step S3, S i Score represents the standardized impact score of the i-th indicator.

[0097] S6: Assess the ecological impact of waterway construction on wetland areas along the route based on the comprehensive impact index;

[0098] The assessment results are categorized into four levels: minor, moderate, severe, and extremely severe. The EII (Economic Impact Index) range for the minor assessment result is 0 ≤ EII < 0.2; for the moderate assessment result, it is 0.2 ≤ EII < 0.5; for the severe assessment result, it is 0.5 ≤ EII < 0.8; and for the extremely severe assessment result, it is EII ≥ 0.8.

[0099] Example 2: This invention also provides a system for assessing the ecological impact of waterway engineering construction on wetland areas along the route. The system employs the method described in Example 1 for assessing the ecological impact of waterway engineering construction on wetland areas along the route. The system includes:

[0100] The data acquisition module is used to acquire multi-source data for assessing the ecological impact of waterway engineering construction on wetland areas along the route;

[0101] The preprocessing module is used to perform data preprocessing operations on the multi-source data;

[0102] The indicator system construction module is used to construct a multi-dimensional ecological impact indicator system;

[0103] The indicator score calculation module is used to calculate the standardized impact score of the ecological impact indicator.

[0104] The comprehensive impact index calculation module is used to calculate the comprehensive impact index based on the standardized impact score and corresponding weight of each indicator.

[0105] The assessment module is used to assess the ecological impact of waterway construction on wetland areas along the route based on the comprehensive impact index.

[0106] Example 3: The present invention also provides an electronic device, including one or more processors and a memory.

[0107] A processor can be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and can control other components in an electronic device to perform desired functions.

[0108] The memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and a processor may execute the program instructions to implement the method for assessing the ecological impact of waterway engineering construction on wetland areas along the route, as described above in any embodiment of this application, and / or other desired functions. Various contents such as initial extrinsic parameters and thresholds may also be stored in the computer-readable storage medium.

[0109] In one example, the electronic device may also include input and output devices, which are interconnected via a bus system and / or other forms of connection (not shown). The input device may include, for example, a keyboard, a mouse, etc. The output device may output various information to the outside, including warning messages, braking force, etc. The output device may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0110] Of course, for simplicity, components such as buses and input / output interfaces have been omitted. In addition, depending on the specific application, the electronic device may include any other appropriate components.

[0111] In addition to the methods and devices described above, embodiments of this application may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the function of a method for assessing the ecological impact of waterway engineering construction on wetland areas along the route, as provided in any embodiment of this application.

[0112] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0113] Furthermore, embodiments of this application may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to implement a method for assessing the ecological impact of waterway engineering construction on wetland areas along the route, as provided in any embodiment of this application.

[0114] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for assessing the ecological impact of waterway construction on wetland areas along the waterway, characterized in that, The method comprises the following steps: S1: acquiring multi-source data for ecological impact assessment of water transportation engineering construction on wetland areas along the line; S2: performing data preprocessing operation on the multi-source data; S3: constructing a multi-dimensional ecological impact index system; S4: calculating the standardized impact score of the ecological impact index; S4 is specifically: S4.1: calculating the relative change rate AR of each secondary index before and after the construction of the water transportation engineering; S4.2: mapping the relative change rate AR of each secondary index before and after the construction of the water transportation engineering to a value in the interval of 0-1; the mapping function is: ； Wherein: k is the adjustment coefficient of the first order term; m is the adjustment coefficient of the second order term; T func is a preset threshold; tanh is the hyperbolic tangent function; S4.3: direction correction is performed on the value mapped to the 0-1 interval to obtain a standardized influence score corresponding to each index. S5: calculating the comprehensive impact index according to the standardized impact score of each index and the corresponding weight; S6: assessing the ecological impact of water transportation engineering construction on wetland areas along the line according to the comprehensive impact index.

2. The method for assessing the ecological impact of waterway construction on the wetland area along the waterway according to claim 1, characterized in that: Wherein, The preprocessing operation includes ground monitoring data cleaning operation based on a tidal rainfall coupling processing method; Specifically: Sa: feature extraction is performed on tidal data; the extracted features include: tidal cycle type, tidal phase, and tidal intensity; wherein, the tidal cycle type is detected based on the tidal data, specifically: Hilbert-Huang transform is performed on the tidal data to extract multiple intrinsic mode functions of the tidal data; based on a preset rule, the components reflecting the tidal cycle are screened out from the multiple intrinsic mode functions of the tidal data; Fourier transform is performed on the components reflecting the tidal cycle to determine the cycle type of the tidal data; Sb: rainfall intensity is classified according to rainfall data; Sc: the normal fluctuation range of the ground monitoring data is determined; Sd: the ground monitoring data is cleaned according to the normal fluctuation range of the ground monitoring data.

3. The method for assessing the ecological impact of water transportation engineering construction on wetland areas along the line according to claim 1, characterized in that: In S2, the data preprocessing operation includes multi-source data spatio-temporal alignment and biological survey data enhancement.

4. The method for assessing the ecological impact of water transportation engineering construction on wetland areas along the line according to claim 2, characterized in that: In Sa, the Fourier transform is performed on the components reflecting the tidal cycle to determine the cycle type of the tidal data, specifically: the Fourier transform (FFT) is performed on the screened components reflecting the tidal cycle, the frequency spectrum distribution is calculated and the main frequency corresponding period is extracted, and the main frequency corresponding period is determined to be a semidiurnal tide or a diurnal tide according to the main frequency corresponding period; The tidal phase is determined based on the tidal data, specifically: the tidal data is divided into three tidal phases of rising tide period, falling tide period and flat tide according to the water level change trend and extreme points of the tidal data; The tidal intensity is quantified according to the tidal data, specifically: the tidal range of each tidal cycle is calculated, the tidal intensity is divided into three levels of weak tide, medium tide and strong tide, and the influence degree of the tide on the hydrological exchange of the wetland is reflected; the tidal range of the weak tide is <1m; the tidal range of the medium tide is 1-2m; the tidal range of the strong tide is >2m.

5. The method for assessing the ecological impact of water transportation engineering construction on wetland areas along the line according to claim 2, characterized in that: The Sd is specifically: for each monitoring time t, the corresponding tidal phase, rainfall intensity and monitoring parameter value are extracted; according to the tidal phase and rainfall intensity at t, the normal range of each parameter of the ground monitoring data is determined; if the value of each parameter of the ground monitoring data is within the corresponding normal range of the parameter: it is marked as natural fluctuation and retained; if the value of each parameter of the ground monitoring data is beyond the corresponding normal range of the parameter: further check whether there is engineering activity, if yes, it is marked as engineering related anomaly and retained; if not, it is marked as natural noise and eliminated.

6. The method according to claim 1, wherein the multi-dimensional ecological impact index system comprises four first-level indexes of habitat physical structure, biological community structure, environmental quality factor and ecological function service, each first-level index comprises multiple second-level indexes, wherein the habitat physical structure comprises four second-level indexes of vegetation coverage, soil sand / clay ratio, surface elevation change and water level fluctuation amplitude; the biological community structure comprises four second-level indexes of Shannon-Wiener index, benthic organism abundance, bird species number and fish larvae survival rate; the environmental quality factor comprises eight second-level indexes of COD content, ammonia nitrogen content, total phosphorus content, heavy metal content, petroleum content, organic matter content, soil conductivity and soil pH value; and the ecological function service comprises four second-level indexes of water evaporation amount, groundwater recharge rate, soil organic carbon content and pollution purification efficiency.

7. The method according to claim 1, wherein in the S5, a weighted summation model is used to calculate the comprehensive impact index EII, and the calculation formula is:

8. The method according to claim 1, wherein in the S6, the evaluation results are four types of slight, moderate, severe and extremely severe, the comprehensive impact index EII of the slight evaluation result ranges from 0 to less than 0.2, the comprehensive impact index EII of the moderate evaluation result ranges from 0.2 to less than 0.5, the comprehensive impact index EII of the severe evaluation result ranges from 0.5 to less than 0.8, and the comprehensive impact index EII of the extremely severe evaluation result is equal to or greater than 0.

8.

9. A method system for evaluating ecological impact of water transportation engineering construction on wetland regions along the line, the system using the method for evaluating ecological impact of water transportation engineering construction on wetland regions along the line according to any one of claims 1-8, the system comprising: a data acquisition module for acquiring multi-source data for evaluating ecological impact of water transportation engineering construction on wetland regions along the line; a preprocessing module for performing data preprocessing operation on the multi-source data; an index system construction module for constructing a multi-dimensional ecological impact index system; an index score calculation module for calculating standardized impact scores of the ecological impact indexes. ； where i is the i-th index, n is the number of indexes, w i is the weight of the i-th index, determined by AHP in step S3, i is the normalized impact score Score of the i-th index. ​ ​ ​ ​ ​ ​ ​ The comprehensive influence index calculation module is configured to calculate a comprehensive influence index according to the standardized influence score of each index and the corresponding weight; The evaluation module is configured to evaluate the ecological influence of the waterway engineering construction on the wetland along the waterway according to the comprehensive influence index.

Images