A method and system for dynamic accounting of river and lake culture service value

Abstract

This invention provides a method and system for dynamically calculating the value of river and lake cultural services, relating to the field of value assessment technology. The method includes: constructing a multi-dimensional time-series baseline indicator system; standardizing each indicator in the multi-dimensional time-series baseline indicator system; obtaining indicator combination weights based on the standardized indicators using an analytic hierarchy process (AHP) algorithm and an entropy weighting algorithm; calculating a comprehensive index of the time-series river and lake cultural service value based on the indicator combination weights; calculating a seasonal demand coefficient; constructing a time-series coupled value model based on the comprehensive index of the time-series river and lake cultural service value and the seasonal demand coefficient; and calculating the value of river and lake cultural services using the time-series coupled value model. This invention enables dynamic monitoring and unified quantification of multi-dimensional indicators, truly reflecting the spatiotemporal variation patterns of river and lake baselines, while ensuring objective and reasonable weight allocation and scientific coupling of value calculation, effectively improving the accuracy of evaluation results.

Description

Technical Field

[0001] This invention relates to the field of value assessment technology, and in particular to a method and system for dynamic accounting of the value of river and lake cultural services. Background Technology

[0002] Rivers and lakes, as vital spatial carriers where natural ecosystems and cultural landscapes are highly integrated, possess multiple service functions, including hydrological ecology, environmental landscape, historical culture, and leisure and recreation. The scientific quantification and dynamic assessment of their cultural service value play a crucial supporting role in river and lake ecological protection and restoration, cultural tourism resource development, and long-term operation and maintenance management. With the continuous advancement of ecological civilization construction and the widespread implementation of comprehensive river and lake management projects, accurately grasping the baseline conditions and seasonal demand changes of rivers and lakes, and objectively calculating their cultural service value and the added value of engineering projects, have become core requirements for the refined management and sustainable utilization of rivers and lakes.

[0003] Currently, river and lake value assessments mostly adopt traditional ecological service value accounting methods or single-indicator evaluation systems. Some technologies conduct static evaluations by constructing indicator systems for ecological and landscape dimensions. Some studies rely on statistical data and expert scores for qualitative and semi-quantitative analysis. Some methods only focus on the ecological background or tourism revenue calculation. Although some models introduce time series data, they mostly use simple annual averages or fixed coefficients for value conversion, without fully combining the multidimensional background attributes of rivers and lakes with the spatiotemporal demand fluctuation characteristics for coupled analysis.

[0004] However, existing technologies mostly conduct river and lake value assessments in a static manner, which makes it difficult to truly reflect the spatiotemporal dynamic characteristics of river and lake systems. At the same time, they lack scientific and reasonable coupling methods for weight determination and value accounting, resulting in insufficient accuracy of the assessment results. Summary of the Invention

[0005] To address the technical issues that existing technologies mostly rely on static methods for river and lake value assessment, making it difficult to accurately reflect the spatiotemporal dynamic characteristics of river and lake systems, and that lack a scientific and reasonable coupling method for weight determination and value calculation, resulting in insufficient accuracy of assessment results.

[0006] The technical solution provided by this invention is as follows: The first aspect of this invention provides a method for dynamically calculating the service value of river and lake culture, comprising: S1: Construct a multi-dimensional time-series baseline indicator system; S2: Standardize each indicator in the multi-dimensional time-series baseline indicator system; S3: Based on the standardized indicators, the combined weights of the indicators are obtained through the analytic hierarchy process (AHP) and the entropy weighting algorithm. S4: Calculate the comprehensive index of river and lake cultural service value over time based on the weights of the indicator combinations; S5: Calculate the seasonal demand coefficient; S6: Construct a time-series coupled value model based on the comprehensive index of river and lake cultural service value and the seasonal demand coefficient; S7: Calculate the cultural service value of rivers and lakes through a time-series coupled value model.

[0007] A second aspect of the present invention provides a dynamic accounting system for the service value of rivers and lakes, comprising: processor; The memory stores computer-readable instructions, which, when executed by the processor, implement the dynamic accounting method for the service value of river and lake culture, as described in the first aspect.

[0008] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the dynamic accounting method for the service value of river and lake culture as described in the first aspect.

[0009] The beneficial effects of the technical solution provided by this invention include: In this embodiment of the invention, a multi-dimensional time-series baseline indicator system is constructed and standardized, enabling dynamic monitoring and unified quantification of multi-dimensional indicators. This allows the evaluation to truly reflect the spatiotemporal variation patterns of the river and lake baseline. By using the analytic hierarchy process (AHP) and entropy weighting algorithm to obtain the combined weights of the indicators, and then calculating the comprehensive index of the time-series river and lake cultural service value based on these weights, a time-series coupled value model is constructed in conjunction with the seasonal demand coefficient. Ultimately, this achieves accurate accounting of the river and lake cultural service value, ensuring that the weight allocation is objective and reasonable and the value calculation is scientifically coupled, thereby improving the accuracy of the evaluation results. Attached Figure Description

[0010] Figure 1 A flowchart illustrating a method for dynamically calculating the service value of rivers and lakes according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a dynamic accounting system for the service value of rivers and lakes provided in an embodiment of the present invention. Detailed Implementation

[0011] Reference manual attached Figure 1 The diagram illustrates a flowchart of a dynamic accounting method for the cultural service value of rivers and lakes provided in an embodiment of the present invention.

[0012] This invention provides a method for dynamically calculating the service value of rivers and lakes, which may include the following steps: S1: Construct a multi-dimensional time-series baseline indicator system.

[0013] It should be noted that a five-dimensional time-series baseline indicator system encompassing hydrology, water quality, morphology, ecology, and landscape was constructed. Time-series data were collected monthly / quarterly, and each indicator was assigned a score of 1–5.

[0014] Optionally, the multi-dimensional time-series baseline indicator system specifically includes: hydrological dimension, water quality dimension, morphological dimension, ecological dimension, and landscape dimension.

[0015] The hydrological dimensions specifically include: flow stability, water level variation, flow velocity, water depth, water surface width, and flow pattern richness.

[0016] Among them, flow stability refers to the degree of fluctuation in river and lake flow throughout the year, reflecting the stability of water flow and affecting recreational safety. Continuous monitoring data from hydrological stations are used, with a monitoring period of no less than one year and at least three monitoring sessions per month. The quantification method is: flow variation coefficient = standard deviation / mean, with the quantified value being the reciprocal of the variation coefficient. The scoring standards are: 1 point (≤1.0), 2 points (1.0-2.0), 3 points (2.0-3.0), 4 points (3.0-4.0), and 5 points (≥4.0).

[0017] Water level fluctuation refers to the difference between the highest and lowest water levels of rivers and lakes within a year, affecting the utilization of waterfront spaces and landscape stability. Continuous monitoring at hydrological stations is used to record the highest and lowest water levels throughout the year, with a monitoring period of no less than one year. The quantification method is to directly use the water level fluctuation (m), with smaller fluctuations receiving higher scores. The scoring criteria are: 1 point (≥5.0m), 2 points (3.0-5.0m), 3 points (1.5-3.0m), 4 points (0.5-1.5m), and 5 points (≤0.5m).

[0018] Flow velocity refers to the speed at which water flows, affecting the recreational experience and landscape effect. Flow velocity meters are used for monitoring, with typical cross-sections selected and monitored monthly for a period of no less than one year. The quantification method is as follows: average flow velocity (m / s) is used, and flow velocities are graded according to suitability for recreation. The scoring criteria are: 1 point (≤0.1m / s or ≥2.0m / s), 2 points (0.1-0.3m / s or 1.5-2.0m / s), 3 points (0.3-0.5m / s or 1.0-1.5m / s), 4 points (0.5-0.8m / s or 0.8-1.0m / s), and 5 points (0.8-1.2m / s).

[0019] Water depth refers to the average depth of rivers and lakes, influencing the types of recreational activities and landscape layers. Monitoring is conducted using depth sounders, with monitoring points evenly distributed, covering the main areas of rivers and lakes, and monitored monthly. The quantification method is as follows: using average water depth (m), categorized according to suitable recreational depth. The scoring standards are: 1 point (≤0.5m or ≥8m), 2 points (0.5-1.5m or 6-8m), 3 points (1.5-2.5m or 4-6m), 4 points (2.5-3.5m or 2-4m), and 5 points (3.5-5m).

[0020] Among them, water surface width refers to the average width of the river and lake surface, which affects the openness of the landscape and the scale of recreational space. The average width is calculated using a combination of remote sensing imagery and field surveys, and is monitored quarterly. The quantification method is as follows: using the average water surface width (m), it is graded according to width and adapted to different river and lake types. The scoring standards are: for lakes and reservoirs, 1 point (≤50m), 2 points (50-100m), 3 points (100-500m), 4 points (500-1000m), and 5 points (≥1000m); for streams, 1 point (≤5m), 2 points (5-10m), 3 points (10-20m), 4 points (20-50m), and 5 points (≥50m).

[0021] Among them, flow richness refers to the diversity of water flow patterns, including rapids, slow currents, waterfalls, and cascades, etc., and is used to enhance the scenic appeal by referencing the evaluation of tourism resource aesthetic value. Through field surveys, the number and distribution density of various flow patterns are statistically analyzed, with surveys conducted every six months. The quantification method is: Flow Richness Index = Number of Flow Patterns × Distribution Density. The scoring criteria are: 1 point (≤1 type), 2 points (2 types), 3 points (3 types), 4 points (4 types), and 5 points (≥5 types).

[0022] The water quality dimension specifically includes: water quality category and transparency.

[0023] The water quality category refers to the water quality grade classified according to the "Surface Water Environmental Quality Standard" (GB3838-2002), which reflects the cleanliness of the water body. Monitoring is carried out in accordance with national standards, once a month, with monitoring points evenly covering the main areas of rivers and lakes. The water quality category is determined by comprehensively considering key indicators such as chemical oxygen demand (COD) and ammonia nitrogen. The quantification method is to directly assign values ​​to the water quality category, where Class I is 5 points, Class II is 4 points, Class III is 3 points, Class IV is 2 points, and Class V and below is 1 point. The scoring standard is: 1 point (Class V and below), 2 points (Class IV), 3 points (Class III), 4 points (Class II), and 5 points (Class I).

[0024] Transparency refers to the ability of water to transmit light, used to supplement water quality classification assessments, reflecting the degree of turbidity, and directly affecting the visual effect of the landscape. Monitoring is conducted using the Sebastian disc method, once a month, with monitoring points covering the main areas of rivers and lakes. The quantification method is based on transparency (cm), with the quantified value = transparency / 20, and values ​​exceeding 100cm scored as 5 points. The scoring criteria are: 1 point (≤20cm), 2 points (20-40cm), 3 points (40-60cm), 4 points (60-80cm), and 5 points (≥80cm).

[0025] The morphological dimensions specifically include: shoreline naturalization rate, habitat richness, river meandering degree, and the proportion of waterfront public space.

[0026] The shoreline naturalization rate refers to the proportion of natural shoreline length to total shoreline length, reflecting the ecological nature and landscape naturalness of the shoreline. The total shoreline length and natural shoreline length are measured through remote sensing image interpretation combined with field surveys. The quantification method involves calculating the shoreline naturalization rate (%) and assigning scores based on the naturalization rate value. The scoring standards are: 1 point (≤20%), 2 points (20%-40%), 3 points (40%-60%), 4 points (60%-80%), and 5 points (≥80%).

[0027] Habitat richness refers to the diversity of habitat types around rivers and lakes and within water bodies, including shallows, deep pools, and reed beds, and is evaluated with reference to the "rarity and uniqueness" of tourism resources. Field surveys are conducted every six months to count the number and evenness of habitat types. The quantification method is: Habitat richness = Number of habitat types × Evenness index. Scoring standards are: 1 point (≤1 type), 2 points (2 types), 3 points (3 types), 4 points (4 types), and 5 points (≥5 types).

[0028] River meandering is defined as the ratio of the actual length of a river channel to its straight length, reflecting the natural morphology and landscape diversity of the river. The actual length and straight length of the river channel are measured using remote sensing imagery, and the ratio is calculated. The quantification method is meandering = actual length / straight length, with scores assigned based on the meandering value. The scoring criteria are: 1 point (≤1.1), 2 points (1.1-1.3), 3 points (1.3-1.5), 4 points (1.5-1.7), and 5 points (≥1.7).

[0029] The proportion of waterfront public space refers to the ratio of the area of ​​waterfront public open space to the area of ​​river and lake basins, reflecting recreational accessibility and use value. The area of ​​waterfront public space is calculated through remote sensing image interpretation combined with on-site measurements. The quantification method is to calculate the area percentage (%), and grade it according to the percentage value (a percentage ≥ 10% is scored as 5 points). The scoring standards are: 1 point (≤ 1%), 2 points (1%-3%), 3 points (3%-5%), 4 points (5%-10%), and 5 points (≥ 10%).

[0030] The ecological dimension specifically includes: aquatic vegetation coverage, biodiversity index, and wetland integrity.

[0031] Aquatic vegetation coverage rate refers to the proportion of aquatic vegetation coverage area to the surface area of ​​rivers and lakes, reflecting the ecological status and aesthetic appeal of aquatic bodies. Vegetation coverage area is monitored and calculated through remote sensing image interpretation combined with field sampling surveys. The quantification method involves calculating the coverage rate (%) and assigning scores based on the coverage rate value. The scoring standards are: 1 point (≤20%), 2 points (20%-40%), 3 points (40%-60%), 4 points (60%-80%), and 5 points (≥80%).

[0032] The biodiversity index reflects the richness and diversity of aquatic organisms such as fish and benthic organisms in rivers and lakes, and is evaluated with reference to the "rarity and uniqueness" of tourism resources. It is calculated using the Shannon-Wiener index through field sampling surveys. The quantification method uses a Shannon-Wiener index numerical classification (index ≥ 10 is scored as 5 points). The scoring criteria are: 1 point (≤ 2), 2 points (2-4), 3 points (4-6), 4 points (6-8), and 5 points (≥ 8).

[0033] Wetland integrity refers to the original state and condition of wetlands surrounding rivers and lakes, reflecting ecosystem stability and landscape value. A comprehensive assessment was conducted through field surveys, considering wetland area, vegetation type, and hydrological conditions. The quantification method employed a 0-100 point comprehensive scoring system, assigning scores according to grade. The scoring criteria were: 1 point (≤20 points), 2 points (20-40 points), 3 points (40-60 points), 4 points (60-80 points), and 5 points (≥80 points).

[0034] The landscape dimension specifically includes: the visual openness of the landscape, the harmony of the landscape, and the degree of cultural landscape heritage.

[0035] Among them, the visual openness of the landscape refers to the size of the river and lake landscape that visitors can view from the waterfront space, reflecting the aesthetic value of the landscape. Through on-site surveys, typical recreational nodes were selected and the visual openness angles were measured. The quantification method was to use numerical grading of openness angles (°) (angles ≥360° were scored as 5 points). The scoring criteria were: 1 point (≤72°), 2 points (72°-144°), 3 points (144°-216°), 4 points (216°-288°), and 5 points (≥288°).

[0036] Landscape harmony refers to the degree of integration and coordination between the river and lake landscape and the surrounding buildings, vegetation, and topography. It is used to reflect the aesthetic effect of the landscape and is evaluated with reference to the "sightseeing value" of tourism resources. The evaluation is conducted through a combination of expert scoring and public surveys (sample size ≥ 100), using a 10-point scoring system and following the tourism resource evaluation process. The quantification method involves assigning scores in tiers based on the results. The scoring standards are: 1 point (≤ 2 points), 2 points (2-4 points), 3 points (4-6 points), 4 points (6-8 points), and 5 points (≥ 8 points).

[0037] The cultural landscape preservation rate refers to the degree of preservation of historical relics, intangible cultural heritage, and humanistic landscapes related to water around rivers and lakes, and is evaluated with reference to the "historical, cultural, scientific, and artistic value" of tourism resources. Through on-site surveys, the number and preservation rate of cultural landscapes are counted, and calculations are carried out according to the evaluation standards for the cultural value of tourism resources. The quantification method is: Preservation Rate = Number of intact cultural landscapes / Total number of cultural landscapes × 100%, with scores assigned according to the preservation rate values. The scoring standards are: 1 point (≤20%), 2 points (20%-40%), 3 points (40%-60%), 4 points (60%-80%), and 5 points (≥80%).

[0038] In this embodiment of the invention, by constructing a five-dimensional time-series baseline indicator system encompassing hydrology, water quality, morphology, ecology, and landscape, and dynamically collecting time-series data monthly or quarterly, and uniformly assigning quantitative scores to 18 specific indicators using a 1-5 point system, it is possible to comprehensively, objectively, and multidimensionally depict the baseline endowment, ecological status, landscape characteristics, and cultural value of rivers and lakes at different temporal and spatial scales. This achieves an expansion from single physical indicators to comprehensive cultural service attributes. At the same time, by unifying quantitative standards and monitoring methods, it effectively eliminates deviations caused by differences in the dimensions, magnitudes, and evaluation methods of different indicators. This provides a standardized, continuous, and comparable data foundation for subsequent indicator standardization, weight calculation, and comprehensive index accounting, thereby enhancing the systematicness, scientific nature, and dynamic adaptability of the evaluation of the cultural service value of rivers and lakes.

[0039] S2: Standardize each indicator in the multi-dimensional time series baseline indicator system.

[0040] It should be noted that the standardized formula used for positive indicators is:

[0041] in, i Indicates the index of the evaluation unit. j Indicates the index of the indicator. t Index indicating month / quarter y ij ( t ) indicates the first i The first evaluation unit j The first indicator in the tStandardized values ​​for months / quarters x ij Indicates the first i The first evaluation unit j The original monitoring values ​​of each indicator, x jmin Indicates the first j The minimum value of each indicator. x jmax Indicates the first j The maximum value of each indicator.

[0042] It should be noted that the standardized formula used for negative indicators is:

[0043] In this embodiment of the invention, by standardizing the positive and negative indicators using corresponding formulas, the original indicator values ​​of different dimensions and orders of magnitude are uniformly mapped to a standardized range of 0 to 5. This effectively eliminates the differences in dimensions, numerical ranges, and trends among the indicators, making indicators of different dimensions and types directly comparable and additive. This provides a unified and standardized numerical basis for the subsequent weighted calculation of the comprehensive index, while ensuring that the standardized results of the indicators match the scoring system, thereby improving the rationality, accuracy, and stability of the calculation of the comprehensive index of river and lake cultural service value.

[0044] S3: Based on the standardized indicators, the combined weights of the indicators are obtained through the analytic hierarchy process (AHP) and the entropy weighting algorithm.

[0045] Among them, the Analytic Hierarchy Process (AHP) is a multi-criteria decision-making method that combines qualitative and quantitative analysis. It first decomposes the complex evaluation problem into a hierarchical structure of target layer, criterion layer, and indicator layer. Then, it constructs a judgment matrix by having experts compare the relative importance of indicators at the same level pairwise. The subjective weight of each indicator is calculated, and the rationality of the judgment logic is ensured through consistency checks. It can systematically sort out the hierarchical relationship of indicators in each dimension, reasonably reflect the differences in importance of different elements in the evaluation of the service value of river and lake culture, make the weight allocation fit the actual evaluation logic and professional experience, and improve the rationality and persuasiveness of the comprehensive evaluation results.

[0046] Among them, the entropy weight algorithm is a method to objectively determine the weight of indicators based on the dispersion of the data itself. It measures the data difference by calculating the information entropy of each indicator. The smaller the information entropy, the greater the fluctuation of the indicator value and the stronger the distinguishing ability, and the higher the corresponding difference coefficient and weight. Conversely, the higher the information entropy, the lower the weight. The entropy weight algorithm relies entirely on time-series monitoring data for objective weighting, without depending on human subjective judgment. It can effectively avoid the bias caused by experience-based scoring, and truly reflect the actual contribution of each indicator in the evaluation of the cultural service value of rivers and lakes, thus making the weight allocation more objective and data-driven.

[0047] It should be noted that the weighting method is a combination of the Analytic Hierarchy Process (AHP) and the entropy weighting method, taking into account both subjective experience and objective data, and referring to the expert scoring process for tourism resource evaluation to avoid the bias of single weighting. At the same time, the weights are calibrated in combination with the characteristics of different river and lake categories (e.g., mountain streams focus on hydrological flow patterns and habitat richness, while lakes and reservoirs focus on water level fluctuations and visual openness).

[0048] In one possible implementation, S3 specifically includes: S301: Based on the standardized indicators, subjective weights are obtained through the analytic hierarchy process (AHP).

[0049] In one possible implementation, S301 specifically includes: S3011: Based on the standardized indicators, establish a hierarchical structure model, which specifically includes: a target layer, a criterion layer, and an indicator layer connected in sequence.

[0050] It should be noted that a hierarchical model is established, consisting of the target layer (RLCSVI), the criteria layer (5 dimensions: hydrology, water quality, morphology, ecology, and landscape), and the indicator layer (the aforementioned 18 core indicators).

[0051] Specifically, the target layer is first defined as the River and Lake Cultural Service Value Comprehensive Index (RLCSVI). Secondly, the criteria layer is defined, consisting of five dimensions: hydrology, water quality, morphology, ecology, and landscape. Thirdly, the indicator layer is defined, comprising 18 specific baseline attribute indicators, each belonging to one of the five criteria layers. Finally, a hierarchical relationship is established from top to bottom: the target layer governs the criteria layer, and the criteria layer governs the indicator layer. Elements within the same level are independent of each other, ultimately forming a complete three-tiered structural model.

[0052] S3012: Assess the relative importance of the criteria layer and the indicator layer respectively, and construct a judgment matrix.

[0053] Among them, the judgment matrix is ​​the core matrix in the analytic hierarchy process used to quantify the relative importance of elements at the same level. It is constructed by experts after comparing the indicators pairwise according to scaling rules. The matrix elements reflect the importance of one indicator relative to another and satisfy the reciprocity property. Through this matrix, the weight calculation of indicators and consistency test can be carried out. It can not only transform the qualitative judgment of experts into calculable quantitative data, but also clearly reflect the relative importance of each indicator in the evaluation of the cultural service value of rivers and lakes.

[0054] Specifically, experts in fields such as ecological environment, water conservancy, and culture and tourism (no fewer than 5 people) were invited to use the 1–9 scale method to compare the relative importance of each indicator within the same level in pairs and construct a judgment matrix.

[0055] It should be noted that the scaling rules are as follows: 1 indicates that the two indicators are equally important, 3 indicates that one indicator is slightly more important than the other, 5 indicates that one indicator is significantly more important than the other, 7 indicates that one indicator is strongly more important than the other, and 9 indicates that one indicator is extremely more important than the other. 2, 4, 6, and 8 are the median values ​​for the above adjacent judgments. Furthermore, the importance of the indicators is reciprocal.

[0056] The judgment matrix is ​​specifically as follows:

[0057] in, A Represents the judgment matrix. k Indicates the index of the indicator. a kj Indicates the first k The first indicator is relative to the first j The importance of each indicator n This indicates the number of indicators within the same level.

[0058] S3013: Calculate the subjective weights based on the judgment matrix.

[0059] The formula for calculating subjective weight is as follows:

[0060]

[0061]

[0062] in, Indicates the first j The subjective weight of each indicator, T j Indicates the first j Initial values ​​for the weights of each indicator. M m Indicates the first m The product of row elements.

[0063] In one possible implementation, after S3013, the method further includes: performing a consistency check on the judgment matrix.

[0064] Specifically, first, the largest eigenvalue of the judgment matrix is ​​calculated; second, the consistency index is calculated based on the largest eigenvalue; and finally, the consistency ratio is calculated. When the consistency ratio is less than 0.1, the judgment matrix is ​​valid.

[0065] The formula for calculating the largest eigenvalue is:

[0066] in, λ maxRepresents the largest eigenvalue. W s Represents the weight column vector, T This indicates transpose.

[0067] The specific formula for calculating the consistency index is as follows:

[0068] in, CI This indicates a consistency index.

[0069] The formula for calculating the consistency ratio is as follows:

[0070] in, CR Indicates the consistency ratio. RI This represents the average random consistency index.

[0071] It should be noted that when the number of indicators n When it is 1 or 2, RI A value of 0 indicates the number of indicators within the same level. n It should be greater than 2. When n When =3, RI =0.58. When n When =4, RI =0.90. When n When =5, RI =1.12. When n When =6, RI =1.24. When n When =7, RI =1.32. When n When =8, RI =1.41. When n When =9, RI =1.45.

[0072] S302: Based on the standardized indicators, the objective weights are obtained through the entropy weight algorithm.

[0073] It should be noted that, based on the standardized indicator data, the information entropy of each indicator is calculated, and the objective weight is determined according to the magnitude of the information entropy. The smaller the information entropy, the higher the indicator's distinguishability, and the greater its weight.

[0074] The specific formula for calculating the objective weight is as follows:

[0075] in, Indicates the first j The objective weight of each indicator, G j Indicates the firstj The coefficient of difference for each indicator E j Indicates the first j Information entropy of each indicator U Indicates the number of samples. u Indicates the sample index. P uj Indicates the first j The first indicator u The proportion of each sample y uj Indicates the first j The first indicator u Standardized values ​​for each sample.

[0076] S303: Combine subjective weights and objective weights according to a preset ratio to obtain the indicator combination weights.

[0077] Specifically, subjective weights and objective weights are combined in a 4:6 ratio (taking into account both expert experience and data objectivity) to obtain the combined weights of the indicators.

[0078] The specific weights of the indicator combination are as follows:

[0079] in, W j Indicates the first j The weighting of each indicator combination.

[0080] Those skilled in the art can set the preset ratio according to actual needs, and the present invention does not limit this.

[0081] It should be noted that the sum of the weights of all indicators is 1. For different river and lake categories, the weights of specific indicators can be appropriately increased by 5%-10%, while the weights of other indicators can be appropriately decreased to improve adaptability. Weights can also be adjusted according to the time sequence; for example, during the flood season: the weights of hydrological indicators are increased; during the peak tourist season: the weights of landscape and water quality are increased; in winter: the weights of ecology and morphology are increased.

[0082] In this embodiment of the invention, a combined weight is obtained by integrating the subjective weighting of the analytic hierarchy process (AHP) algorithm with the objective weighting of the entropy weighting algorithm. This approach leverages the AHP to clarify the hierarchical logic of multi-dimensional indicators, incorporates expert experience and industry knowledge to ensure that the weights conform to the evaluation rules of river and lake cultural service value. At the same time, the entropy weighting method fully explores the discrete characteristics of the time-series monitoring data to avoid human subjective bias. The combined weight is then formed by weighting the data in a 4:6 ratio, which takes into account both subjective rationality and objective authenticity. Furthermore, the weights can be flexibly fine-tuned for different river and lake types and different time-series stages. This significantly improves the scientificity, applicability, and relevance of the indicator weight allocation, laying a reliable weight foundation for the subsequent accurate calculation of the comprehensive index of river and lake cultural service value.

[0083] S4: Calculate the comprehensive index of cultural service value of rivers and lakes over time based on the weights of the indicator combinations.

[0084] The formula for calculating the comprehensive index of the cultural service value of rivers and lakes over time is as follows:

[0085] in, RLCSVI This represents the comprehensive index of the cultural service value of rivers and lakes over time.

[0086] It should be noted that the comprehensive index of cultural service value of rivers and lakes in time series ranges from 0 to 5. The higher the score, the better the basic attributes of the rivers and lakes and the greater the potential for cultural service value. The specific classification is as follows: low potential (0-2.0), medium-low potential (2.0-3.0), medium potential (3.0-4.0), and high potential (4.0-5.0).

[0087] In this embodiment of the invention, based on a predetermined combination of indicator weights, a comprehensive index of the cultural service value of rivers and lakes over time is obtained through weighted summation. This integrates standardized indicators from multiple dimensions and time periods into a single, intuitive quantitative result, enabling dynamic evaluation and horizontal comparability of the potential cultural service value of rivers and lakes. Furthermore, by standardizing the index value range to 0-5 and classifying it into potential levels, the index clearly reflects the quality and value of the baseline conditions of rivers and lakes at different times. This provides a concise and clear quantitative basis for subsequent value quantification, time-series comparison, and management decisions, enhancing the practicality and readability of the evaluation results.

[0088] S5: Calculate the seasonal demand coefficient.

[0089] Specifically, the number of tourists in each month (or season) of the past 5-10 years and the average monthly (or season) number of tourists over the years are collected for each evaluation unit of the evaluation object. The data comes from statistics, culture and tourism departments and field surveys, and the seasonal demand coefficient is calculated.

[0090] The formula for calculating the seasonal demand coefficient is as follows:

[0091] in, S ( t ) indicates the first t Seasonal demand coefficient for each month / quarter.

[0092] In this embodiment of the invention, by collecting the number of tourists in each month (or season) and the average number of tourists over the past 5-10 years for the evaluation object, and using a standardized formula to calculate the seasonal demand coefficient, the fluctuation differences in tourist demand at different times can be accurately quantified, and the demand change characteristics of different time periods such as peak season, off-season, flood season, and winter can be objectively reflected.

[0093] S6: Construct a time-series coupled value model based on the comprehensive index of cultural service value of rivers and lakes over time and the seasonal demand coefficient.

[0094] Among them, the temporal coupling value model is a multiple regression model constructed with the temporal river and lake cultural service value comprehensive index as the core background variable and combined with the seasonal demand coefficient. By fitting the quantitative relationship between historical value data and the index and seasonal factors, it dynamically couples the ecological background endowment with the changes in temporal and spatial demand. It can reflect the supporting role of the river and lake's own background conditions on the cultural service value, and also reflect the value differences brought about by demand fluctuations and environmental changes in different periods such as peak tourist season, flood season, and winter. After the goodness of fit and significance tests are verified, it can realize the accurate inference and quantitative calculation of the cultural service value of rivers and lakes in different temporal and spatial scenarios.

[0095] Specifically, the annual cultural service value of each evaluation unit over the past 5-10 years was collected, with data sourced from statistics, cultural tourism departments, and field surveys. A time-series coupled value model was constructed using multiple linear regression.

[0096] In one possible implementation, S6 specifically includes: S601: Determine the variables for the time-series coupled value model.

[0097] The variables specifically include: dependent variable, independent variable, interaction term, and control variable.

[0098] Among them, the dependent variable is the first t The value of cultural services per month (or quarter).

[0099] The independent variables are the comprehensive index of the cultural service value of rivers and lakes over time and the seasonal demand coefficient.

[0100] Among them, the interaction item is the product of the comprehensive index of the cultural service value of rivers and lakes over time and the seasonal demand coefficient, which reflects the coupling effect between the baseline and tourists.

[0101] Among them, the control variables are comprehensive factors such as location, supporting facilities, and population.

[0102] S602: Construct a time-series coupled value model based on seasonal demand coefficients, variables, and the comprehensive index of river and lake cultural service value over time.

[0103] Specifically, the time-series coupling value model is as follows:

[0104] in, ECSV This indicates the service value of river and lake culture. A’ Represents the regression coefficient. K This represents a constant term, which is affected by location, supporting facilities, and basic conditions.

[0105] Furthermore, the least squares method is used to perform regression fitting on the historical data, and the regression coefficients and constant terms are solved.

[0106] In this embodiment of the invention, a time-series river and lake cultural service value comprehensive index is used as the core background variable. Combined with seasonal demand coefficients and the introduction of control variables such as location and supporting facilities, a time-series coupled value model is constructed. This model can dynamically couple the ecological background endowment of rivers and lakes with seasonal demand fluctuations, regional basic conditions, and other factors. The model parameters are calibrated by fitting historical data using the least squares method. This model can accurately reflect the combined impact of the river and lake's own conditions and external demands on the cultural service value, and can also quantify the value differences under different time and space scenarios.

[0107] In one possible implementation, after S602, the method further includes: verifying the time-series coupled value model.

[0108] Specifically, goodness of fit is used. R 2 The model was validated using the F-test to ensure its applicability for subsequent value extrapolation. R 2 A value ≥0.7 indicates a good model fit. When the F-test corresponds to... P A value <0.05 indicates that the model is significantly effective. If the model's fit is insufficient, it can be optimized by introducing quadratic terms, interaction terms, or time dummy variables. The fitting accuracy can also be improved by increasing the sample size. Furthermore, the regression coefficients can be calibrated separately for different types of rivers and lakes to further improve the model's adaptability and inference accuracy.

[0109] In this embodiment of the invention, by conducting goodness-of-fit and F-significance tests on the time-series coupled value model, and optimizing the model by introducing higher-order terms, expanding the sample, or categorical calibration coefficients when the fit effect is insufficient, the reliability and significance of the model can be effectively verified, ensuring the accuracy and reliability of the value extrapolation results. At the same time, it enhances the model's adaptability to different river and lake types and different spatiotemporal scenarios, providing a stable and rigorous model guarantee for the subsequent accurate calculation of the cultural service value of rivers and lakes, and the development of dynamic evaluation and decision-making applications.

[0110] S7: Calculate the cultural service value of rivers and lakes through a time-series coupled value model.

[0111] The specific method for calculating the cultural service value of rivers and lakes is as follows:

[0112] in, v Index indicating month / quarter.

[0113] In this embodiment of the invention, relying on a validated time-series coupled value model, the cultural service value of rivers and lakes is calculated monthly or quarterly and then summed. This enables refined calculation of value at different times and quantitative summary of overall value, intuitively reflecting the total cultural service value of rivers and lakes within the complete evaluation cycle. At the same time, it takes into account the dynamic changes of inherent endowments and seasonal needs, making the value calculation results more consistent with actual spatiotemporal characteristics.

[0114] In one possible implementation, after S7, the following is also included: S8: Calculate the value preservation and appreciation benefits of river and lake cultural services based on their service value.

[0115] The specific formula for calculating the value preservation and appreciation benefits of river and lake cultural services is as follows:

[0116] in, This indicates the value preservation and appreciation benefits of river and lake cultural services. ECSV after This represents the annual cultural service value of rivers and lakes before engineering measures were implemented, calculated based on the monitoring results of the five-dimensional baseline indicator system before the implementation of engineering measures. ECSV before The annual cultural service value of rivers and lakes after the implementation of engineering measures is calculated based on the monitoring results of the five-dimensional baseline indicator system after the implementation of engineering measures.

[0117] In this embodiment of the invention, by comparing the difference in annual river and lake cultural service value before and after the implementation of engineering measures, the value preservation and appreciation benefits are quantitatively calculated. This can intuitively and accurately reflect the actual improvement effect of engineering measures such as ecological governance and landscape enhancement on the cultural service value of rivers and lakes, providing a clear quantitative basis for engineering benefit evaluation, scheme selection and subsequent operation and maintenance decisions. At the same time, it realizes a complete closed loop from baseline indicator monitoring to value benefit accounting, effectively supporting the scientific management of river and lake ecological protection and cultural utilization.

[0118] Reference manual attached Figure 2 The diagram shows a schematic representation of a dynamic accounting system for the cultural service value of rivers and lakes provided in an embodiment of the present invention.

[0119] This invention also provides a dynamic accounting system 20 for the value of river and lake cultural services, applied to the aforementioned dynamic accounting method for the value of river and lake cultural services, comprising: Processor 201.

[0120] The memory 202 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 201, the dynamic accounting method for the value of river and lake cultural services, as described in the method embodiment, is implemented.

[0121] The dynamic accounting system 20 for the value of river and lake cultural services provided by this invention can execute the above-mentioned dynamic accounting method for the value of river and lake cultural services and achieve the same or similar technical effects. To avoid duplication, this invention will not elaborate further.

[0122] This invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the dynamic accounting method for the cultural service value of rivers and lakes as described in the method embodiments.

[0123] The present invention provides a computer-readable storage medium that can implement the steps and effects of the dynamic accounting method for the cultural service value of rivers and lakes in the above-described method embodiments. To avoid repetition, the present invention will not repeat them.

[0124] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for dynamically calculating the service value of river and lake culture, characterized in that, include: S1: Construct a multi-dimensional time-series baseline indicator system; S2: Standardize each indicator in the multi-dimensional time-series baseline indicator system; S3: Based on the standardized indicators, the combined weights of the indicators are obtained through the analytic hierarchy process (AHP) and the entropy weighting algorithm. S4: Calculate the comprehensive index of river and lake cultural service value over time based on the weighted combination of the aforementioned indicators; S5: Calculate the seasonal demand coefficient; S6: Construct a time-series coupled value model based on the comprehensive index of river and lake cultural service value and the seasonal demand coefficient; S7: Calculate the cultural service value of rivers and lakes using the time-series coupled value model.

2. The method for dynamically calculating the service value of river and lake culture according to claim 1, characterized in that: The multi-dimensional time-series baseline indicator system specifically includes: hydrological dimension, water quality dimension, morphological dimension, ecological dimension, and landscape dimension.

3. The method for dynamically calculating the service value of river and lake culture according to claim 1, characterized in that: S3 specifically includes: S301: Based on the standardized indicators, subjective weights are obtained through the aforementioned hierarchical analysis algorithm; S302: Based on the standardized indicators, obtain the objective weights using the entropy weight algorithm; S303: Combine the subjective weight and the objective weight according to a preset ratio to obtain the index combination weight.

4. The method for dynamically calculating the service value of river and lake culture according to claim 3, characterized in that: S301 specifically includes: S3011: Based on the standardized indicators, establish a hierarchical structure model, wherein the hierarchical structure model specifically includes: a target layer, a criterion layer, and an indicator layer connected in sequence. S3012: Assess the relative importance of the criterion layer and the indicator layer respectively, and construct a judgment matrix; S3013: Calculate the subjective weights based on the judgment matrix.

5. The method for dynamically calculating the service value of river and lake culture according to claim 4, characterized in that: Following S3013, the following is also included: Perform a consistency check on the judgment matrix.

6. The method for dynamically calculating the service value of river and lake culture according to claim 1, characterized in that: S6 specifically includes: S601: Determine the variables of the time-series coupled value model; S602: Construct the time-series coupled value model based on the seasonal demand coefficient, the variables, and the time-series river and lake cultural service value comprehensive index.

7. The method for dynamically calculating the service value of river and lake culture according to claim 6, characterized in that: Following S602, the following is also included: The time-series coupled value model is validated.

8. The method for dynamically calculating the service value of river and lake culture according to claim 1, characterized in that: Following S7, it also includes: S8: Calculate the value preservation and appreciation benefits of river and lake cultural services based on the stated value of river and lake cultural services.

9. A dynamic accounting system for the service value of river and lake culture, characterized in that, include: processor; A memory storing computer-readable instructions, which, when executed by the processor, implement the dynamic accounting method for the service value of river and lake culture as described in any one of claims 1 to 8.

10. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions, which, when executed by a processor, implement the steps of the dynamic accounting method for the value of river and lake cultural services as described in any one of claims 1 to 8.

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