Water network path evaluation method based on spatial analysis algorithm

Abstract

The invention relates to a GIS application technology, in particular to a water network path evaluation method based on a spatial analysis algorithm. According to the method, influence factors, including a line length factor, a tunnel proportion factor, an ecological red line factor, a basic farmland factor, a geological condition factor, a cross building factor and a maximum static pipe pressure factor, of a water network path are selected, and then the influence factors are divided into natural factors and non-natural factors; the calculation data of the natural factors are obtained through geological faults, seismic points or digital elevation model data by a spatial analysis method, and the non-natural factors directly adopt original data; and finally, an index differentiation quantitative scoring algorithm model is determined, different weight values are given according to the importance of the influence factors, and a designer quickly carries out scheme demonstration and adjustment based on the score values. According to the method, the standard of calculation methods of all the influence factors is unified, corresponding evaluation tools, systems or platforms are developed according to the algorithm model, the minute-level water network path adjustment and reevaluation result calculation process can be achieved, multiple times of modification and evaluation work can be carried out in a short time, a large amount of labor cost is saved, and the design efficiency is greatly improved.

Description

Technical Field

[0001] The present invention relates to a GIS application technology, in particular to a water network path evaluation method based on a spatial analysis algorithm. Background Art

[0002] Water network evaluation is the process of comprehensively evaluating multiple design options for connecting water transmission lines, after the starting and ending points have been determined, during the planning and design phase of a water conservancy project. This process aims to understand the current status of the water network, existing problems, and potential for optimization, thereby providing a scientific basis for the planning, management, and protection of the water system. Water network evaluation is crucial during the planning and design phase of a water conservancy project, directly impacting the accuracy and economic benefits of the water network design.

[0003] Traditional methods for evaluating water networks rely heavily on the experience of design engineers and simple geographic data analysis. These methods often struggle to ensure the overall scientific and economic viability of route selection when faced with complex terrain and diverse constraints. With the rapid development of geographic information system (GIS) technology and improvements in computer hardware performance, a growing number of designers are applying various spatial analysis algorithms within GIS (such as overlay analysis, intersection analysis, and hydrological analysis) to project planning and design, enabling comprehensive consideration of multi-dimensional and multi-factor influences.

[0004] Traditional water network path evaluation methods use GIS to overlay water network paths and related image factors to conduct multi-factor impact analysis and overall path evaluation. This method only uses GIS technology as a display tool and does not use or only uses simple spatial analysis algorithms (such as distance measurement and area measurement). In essence, it still requires subjective evaluation based on the experience of engineers. This method has the following disadvantages: 1. Current data acquisition is difficult and inefficient. Before the evaluation begins, it is necessary to collect and prepare current data on various influencing factors within the design scope (such as ecological red lines, basic farmland, current topography, current water systems, geological structures, slopes, and static pipe pressure ranges) among relevant competent departments. This data is not only large in volume and inefficient to acquire, but also difficult to integrate and display, and faces high professional barriers.

[0005] 2. It is highly subjective and factors are easily overlooked. Water network routing planning involves numerous influencing factors. Using only layer overlays and manual judgment is prone to omissions, and evaluation results can vary from person to person depending on the experience of the evaluator.

[0006] 3. The evaluation complexity is high and the cycle is long. Since there are many influencing factors and the evaluation mainly relies on the experience of designers without a unified evaluation standard, different evaluators will have different modification opinions, resulting in a relatively long finalization cycle in the entire water network path design work. Summary of the Invention

[0007] Based on the existing water network path evaluation methods, there is no solution for multi-factor automatic evaluation based on GIS spatial analysis algorithms. The present invention proposes a water network path evaluation method based on spatial analysis algorithms.

[0008] The water network path evaluation method based on spatial analysis algorithms of the present invention is characterized by being realized through the following steps: 1) Determine the influencing factors: According to the specific work content of the water network path planning and design, sort out and determine the characteristics and influence ranges of the influencing factors involved, including the line length factor, tunnel proportion factor, ecological red line factor, basic farmland factor, geological condition factor, cross-building factor, and maximum static pipe pressure factor; 2) Divide the influencing factors into natural factors and non-natural factors. The natural factors include the geological condition factor, cross-building factor, slope factor, and maximum static pipe pressure factor. The calculation data of the natural factors are obtained through spatial analysis methods using geological faults, earthquake points, or digital elevation model data; The non-natural factors include the line length factor, tunnel proportion factor, ecological red line factor, and basic farmland factor. The original data of the non-natural factors are all existing design data or policy data that cannot be adjusted again after the start of scoring. Therefore, the calculation data of the non-natural factors directly adopt the original data; 3) Determine the index differential quantization scoring algorithm model: To enhance the stability and comparability of the algorithm, establish a method of index normalization based on range normalization. For the identified influencing factors, according to their influence on the project, assign the same value range to each influencing factor. Specifically: The calculation method of the scoring value of the line length factor is: Where, is the scoring value of the line length factor, Li is the current line length, and Lmin is the minimum length; The calculation method of the scoring value of the tunnel proportion factor is: When PSi ≤ 15%: When 15% < PSi ≤ 30%: When PSi > 30%: Among them, PSi is the ratio of the current tunnel to the length of the line, is the score value of the tunnel proportion factor, PSmin is the minimum value of the tunnel proportion to the line length; The calculation method for the ecological red line factor score is: in, is the score value of the ecological red line factor, PHi is the ratio of the ecological red line length occupied by the current pipeline section to the length of the line; The scoring method for basic farmland factors is as follows: in, is the score value of the basic farmland factor, PJmin is the minimum ratio of the length of the basic farmland occupied by the pipeline section to the length of the line where it is located, and PJi is the ratio of the length of the basic farmland occupied by the current pipeline section to the length of the line where it is located; The scoring method for geological condition factors is as follows: in, is the scoring value of the geological condition factor, DCmin is the minimum number of fault points crossed by the tunnel section of the line, and DCi is the number of fault points crossed by the tunnel section of the current line; The scoring value of the cross-building factor is calculated as follows: in, is the score value of the crossing building factor, JCmin is the minimum number of crossing points involving crossing buildings in the line pipeline section, and JCi is the number of crossing points involving crossing buildings in the current line pipeline section; The slope factor score is calculated as follows: in, is the score value of the slope factor, PDmin is the length of the pipeline segment where the slope exceeds the specified limit, and PDi is the length of the pipeline segment where the slope exceeds the specified limit; The scoring value of the maximum static pipe pressure factor is calculated as follows: in, is the score value of the maximum static pipe pressure factor, GYmin is the minimum length of the line pipeline section within the specified height difference range, and GYi is the length of the current line pipeline section within the specified height difference range; Establish a total scoring model for water network path planning: f0_final=f1_len*p1+f2_sdcdzb*p2+f3_sthx*p3+f4_jbnt*p4+f5_dztj*p5+f6_jcjzw*p6+f7_pd*p7+f8_zdjgy*p8 Among them, f0_final is the total score value of the water network path planning, p1~p8 are the score weights of each influencing factor, and different weight values ​​are assigned according to the importance of the influencing factors related to the route score. If there are multiple designed water network paths, the total score value fi_final can be calculated for all designed water network paths separately, and then the total score values ​​can be summarized to view the theoretical recommendation index and advantages and disadvantages of different design paths. Designers can quickly verify and adjust the plan based on the score values.

[0009] In the present invention, the method for selecting the impact factor is: According to the general management and principles of water conservancy project planning and design and document review, the planning and design of water conservancy projects must meet the three dimensions of economy, technology and compliance.

[0010] From an economic perspective, line length is directly related to earthwork volume, pipe usage, and construction period; this factor can intuitively reflect the cost advantage of the path. The cost of tunnel construction is approximately 3-5 times that of an open channel. When the proportion exceeds 30%, it will significantly increase the project budget. Segmented scoring is in line with the cost standards of the water conservancy industry. The number of intersecting structures (such as river channels and road crossing points) affects the complexity of pipeline connections, which directly affects the difficulty of construction technology and the construction and operation and maintenance costs.

[0011] From a safety perspective, the overlap between geological faults and seismic hotspots directly affects the pipeline's ability to resist deformation; exceeding the maximum static pipe pressure may lead to the risk of pipe burst; areas with large slopes are prone to landslide disasters. Consideration of the influence of slope factors complies with the slope stability evaluation requirements of the "Specifications for Geological Survey of Water Conservancy and Hydropower Engineering".

[0012] From a compliance perspective, the proportion of ecological red lines occupied aligns with the principle of "prioritizing linear engineering avoidance" in the "Ecological Red Line Management Measures." The proportion of basic farmland occupied is positively correlated with the difficulty of land approval. In principle, both ecological red lines and basic farmland are off-limits areas. However, in actual engineering practice, there are instances where land use types are adjusted through land swaps to avoid key projects. Therefore, compliance evaluation factors are incorporated into ecological red lines and basic farmland, with weights used to control their importance rather than a single-vote veto.

[0013] Some other factors that affect the evaluation of water network paths, such as slope aspect, built-up area, stable cultivated land, climate, etc., have less influence on the economy, technology and compliance of water network paths than the eight identified influencing factors, or can be covered by the above-mentioned influencing factors. For example: the impact of slope aspect on path selection can be indirectly covered by the slope factor; water network paths are generally not planned and designed within the built-up area; stable cultivated land is already included in the basic farmland; the impact of climate on the planning and design of water network paths has little influence.

[0014] Here, f0_final is the total score for the water network routing plan, and p1-p8 are the weights for each influencing factor. Weights p1-p8 can be determined based on the project's specific circumstances by establishing a two-tiered influencing factor system combined with the Delphi method. For example, if a project prioritizes economic efficiency (route length factor, tunnel ratio factor, and intersecting structure factor), safety (geological condition factor, maximum static pipe pressure factor, and slope factor), and compliance (ecological red line factor and prime farmland factor), the impacts can be categorized into these three dimensions. Experts in these three first-tier fields can be invited to use the Delphi method to determine the weights for each factor. Similarly, a two-tiered influencing factor system can be established by combining engineering economic efficiency (route length factor, tunnel ratio factor, and intersecting structure factor), technical feasibility (geological condition factor, slope factor, maximum static pipe pressure factor), and ecological compliance (ecological red line factor and prime farmland factor).

[0015] Specifically, the calculation data for the geological condition factor in step 2) is the number of fault points crossed by the tunnel section of the line. There are two ways to obtain the number of fault points crossed by the tunnel section of the line: Method 1 is to obtain it directly from official departments. The specific steps are as follows: Directly obtain geological fault vector line data from authoritative official departments and institutions; Extract the tunnel segment vector lines in each water network path, use the intersection analysis in spatial analysis to obtain the intersection points of the fault vector line and each water network path vector line, then count the number of intersection points on each water network path and substitute them into the scoring model to calculate the geological condition factor value. ; Method 2 is to use spatial analysis algorithm to obtain the data. The specific steps are as follows: Obtain historical earthquake location data and geological structure data within the analysis area; Conduct density analysis on historical earthquake point data to identify areas where epicenters frequently occur and potentially active fault zones; conduct buffer zone analysis on geological structural boundaries in geological structural data to further understand fault zone areas that may affect earthquake activity; Spatial connection is performed between the earthquake point density analysis results and the geological structure boundary buffer zone to find the spatial overlap relationship between earthquake points and fault buffer zones; Identify areas of seismic activity associated with faults through hotspot analysis and find areas of high-frequency seismic activity; Identify the centerline of the surface element and calculate the fault vector line data; Extract the tunnel segment vector lines in each water network path, use the intersection analysis in spatial analysis to obtain the intersection points between the fault vector line and the vector lines of each water network path, and then count the number of intersection points on each water network path.

[0016] Specifically, the calculation data for the intersection building factor in step 2) is the number of intersection building crossing points involved in the line section, which is obtained using a spatial analysis algorithm. The specific steps are: Get digital elevation model data representing the terrain Fill the water flow dead corners in the digital elevation model data through depression filling analysis; Through D8 flow analysis, the flow direction is assigned to the steepest downslope adjacent point; Through cumulative flow analysis, the cumulative value of all flows flowing into each downslope pixel in the output raster is calculated; Use the screening tool to filter and retain all pixel points that can become water system runoff; Through river chain analysis, the spatial link relationship between each retained pixel point is obtained; The Tonstral method of river network classification assigns classes to runoff segments representing branches of a linear network; Through river network vectorization analysis, the interconnected pixels are converted into water network vector lines; Determine the minimum cross-river network level and extract the water network line for the construction of cross-buildings; Extract pipeline segment vector lines in the water network path; Use the intersection analysis in spatial analysis to obtain the intersection points of the fault vector line and the vector lines of each water network path pipeline segment; Count the number of intersections on each water network path.

[0017] Specifically, the calculation data of the slope factor in step 2) is the length of the pipeline section where the slope exceeds the specified limit, which is obtained using the spatial analysis algorithm. The specific steps are: Obtaining digital elevation model data representing terrain; Obtain slope analysis raster data through slope analysis; Use the screening tool to filter and retain the area surface vectors whose slope exceeds the specified limit; Extract pipeline segment vector lines in water network paths; Use the intersection analysis in spatial analysis to obtain the intersection lines of the vector surface of the slope exceeding limit area and the vector lines of each water network path pipeline segment; Count the length of slope exceeding the limit on each water network path separately.

[0018] Specifically, the calculation data for the maximum static pipe pressure factor in step 2) is the length of the line pipeline within the specified height difference range, which is obtained using a spatial analysis algorithm. The specific steps are: Obtaining digital elevation model data representing terrain; Use the filter tool to filter and retain the digital elevation model data within the elevation range where the upper limit is determined by the starting point elevation and the lower limit is determined by the specified elevation difference; Use the raster to vector tool to convert the digital elevation model data within the elevation range into a static pipe pressure range vector surface; Extract pipeline segment vector lines in water network paths; Use the intersection analysis in spatial analysis to obtain the intersection line between the static pipe pressure range vector surface and the vector line of each water network path pipeline segment; Count the length of the static pipe pressure range on each water network path separately.

[0019] Specifically, in step 3), the weights of p1 to p8 are determined through the Delphi method, which involves conducting multiple rounds of questionnaires on the designer or expert team, issuing a weight distribution table for the two-tiered influencing factor system, and performing a consistency check on the weight scores of each factor. When the consistency ratio is less than a predetermined threshold (such as 0.1), the expert team is considered to have reached a consensus. The process ends and the average value of the expert team is obtained as the final weight distribution table to ensure the scientific nature of the weight distribution. Otherwise, a cycle of meeting discussions and questionnaires is repeated until the expert team reaches a consensus.

[0020] The beneficial effects of the present invention are: 1. The amount of existing data required is reduced. Some natural factor data can be obtained through spatial analysis of one or more basic spatial data sets, meeting the accuracy requirements of the planning and design phase and eliminating the need for obtaining some existing data.

[0021] 2. Design an objective evaluation algorithm that comprehensively considers the influence of multiple factors without omission. Design a full-process algorithm model that considers all influencing factors and comprehensive scoring. This allows for scientific spatial analysis and calculations based on objective and real spatial data within a unified coordinate system, eliminating any omissions.

[0022] 3. The evaluation algorithm model is standardized and highly efficient. The evaluation algorithm uses a standardized calculation method for each influencing factor. Developing corresponding evaluation tools, systems, or platforms based on this algorithm model enables minute-by-minute water network routing adjustments and re-evaluation result calculations. This allows for multiple modifications and evaluations to be performed in a short period of time, saving significant labor costs and significantly improving design efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1This is a three-dimensional display diagram of different line schemes in Example 1.

[0024] Figure 2 This is a three-dimensional display diagram of the cross-building factor in Example 1.

[0025] Figure 3 Schematic diagram of the rating pop-up window for different routes in Example 1.

[0026] Figure 4 Schematic diagram of geological condition factor analysis in Example 1.

[0027] Figure 5 Schematic diagram of cross-building factor analysis in Example 1.

[0028] Figure 6 Schematic diagram of slope factor analysis of Example 1.

[0029] Figure 7 Schematic diagram of maximum static pipe pressure factor analysis in Example 1. DETAILED DESCRIPTION

[0030] Example 1: The following is an evaluation of two water network design schemes for an irrigation area in Yunnan.

[0031] This method involves eight influencing factors: line length factor, tunnel ratio factor, ecological red line factor, basic farmland factor, geological condition factor, intersecting building factor, slope factor, and maximum static pipe pressure factor. Among them, the line length factor, tunnel ratio factor, ecological red line factor, and basic farmland factor are non-natural factors. They can be obtained through communication with designers and application to relevant authorities and cannot be changed. After calculation, the scores of each factor are shown in the table below: The geological condition factor, the cross-building factor, the slope factor, and the maximum static pipe pressure factor are natural factors. The digital elevation model data is obtained from GIS, and the factor data can be obtained through the natural factor spatial analysis method in this method.

[0032] Taking ArcGIS Pro, a commonly used software in the GIS industry, as an example, this paper explains how to analyze and extract four natural factors from digital elevation model data: Geological condition factors: First, determine the locations of the two design lines, add nearby historical earthquake points and magnitude data, then conduct an earthquake point density analysis to find the areas where earthquakes frequently occur, then add geological structure data, identify the geological structure boundaries near the lines, perform a 500-meter buffer zone analysis on the geological structure boundaries, find the spatial overlapping relationship surface between the earthquake-prone areas and the fault buffer zones, and finally identify the center lines of the overlapping surface elements, solve the fault vector line data, and perform an intersection analysis on the fault vector line and the design line to obtain the intersection points of the pipeline section and the tunnel section. Finally, obtain a detailed diagram of the intersection points, that is, the intersection points of the tunnel section and the fault vector line.

[0033] Crossing building factor: First, determine the locations of the two design routes and add digital elevation model data. Then, determine the minimum crossing river network level through depression filling analysis, D8 flow direction analysis, flow analysis, flow screening, river chain analysis, Trale river network classification, and river network vectorization analysis. Finally, through intersection analysis, obtain the intersection points of the fault vector line and the vector lines of each water network path pipeline segment.

[0034] Slope factor: First, determine the locations of the two design routes and add digital elevation model data. Then, perform slope analysis to obtain slope analysis raster data. Finally, filter and retain the area surface vectors where the slope exceeds the specified limit. Then, use the intersection analysis in spatial analysis to obtain the intersection lines of the vector surface of the area where the slope exceeds the limit and the vector lines of each water network path pipeline segment.

[0035] Maximum static pipe pressure factor: First, determine the locations of the two design routes and add digital elevation model data. Filter and retain the digital elevation model data within the elevation range defined by subtracting the specified elevation difference (100 meters) from the starting elevation (1950 meters). Use the raster-to-vector tool to convert the digital elevation model data within the elevation range into a static pipe pressure range vector surface. Finally, use intersection analysis to obtain the intersection of the static pipe pressure range vector surface and the vector lines of each water network path pipeline segment.

[0036] After calculation, the score values ​​of each factor are shown in the following table: Through triple verification of literature research, engineering case analysis and expert consultation, a hierarchical two-level influencing factor system was established. The Delphi method combined with the hierarchical analysis method was used to determine the weights. Five industry experts were invited to conduct three rounds of weight scoring, and finally a consistency test result of consistency ratio CR=0.032<0.1 was obtained to ensure the scientific nature of the weight distribution.

[0037] The final scoring results are as follows: From this we can see that: Design Scheme 2 outperforms Design Scheme 1 in terms of six influencing factors, including line length, tunnel ratio, geological conditions, intersecting buildings, slope, and maximum static pipe pressure. Design Scheme 1 is superior to Design Scheme 2 in terms of the two influencing factors of ecological red line and basic farmland; The overall evaluation of Design Scheme 2 is better than that of Design Scheme 1.

[0038] Comparative Example: Based on Example 1, the following lists the impact of reducing the number of factors on the evaluation results under the same data basis and cases.

[0039] Excluding the "geological condition factor" (weight 12%) from the original 8 factors, the remaining 7 factors are: line length (15%), tunnel proportion (15%), ecological red line (15%), basic farmland (15%), intersecting buildings (10%), slope (10%), and maximum static pipe pressure (8%).

[0040] The weights were recalculated using the AHP method. The new CR was 0.041 < 0.1, which was acceptable. The results are shown in the following table: From this we can draw two conclusions: ① The advantage of Option 2 is reduced The original total score difference was 1.75 (9.314-7.562), and after removing the geological condition factor, the difference was reduced to 1.03, which concealed the absolute advantage of Option 2 in geological safety.

[0041] ② Lack of risk assessment Yunnan is located in an earthquake-prone zone. After eliminating geological conditions, it is impossible to quantify the potential threat of fault crossing to pipeline safety. This may lead to Option 1 being misjudged as "acceptable" due to ignoring geological risks.

Claims

1. Water network path evaluation method based on spatial analysis algorithm, characterized by It is achieved through the following steps: Determine the influencing factors: According to the specific work content of the water network path planning and design, sort out and determine the characteristics and influence ranges of the involved influencing factors, including the line length factor, the proportion of tunnel factor, the ecological red line factor, the basic farmland factor, the geological condition factor, the cross-building factor, and the maximum static pipe pressure factor; Divide the influencing factors into natural factors and non-natural factors. The natural factors include the geological condition factor, the cross-building factor, the slope factor, and the maximum static pipe pressure factor. The calculation data of the natural factors are obtained through spatial analysis methods using geological fault, earthquake point, or digital elevation model data. The non-natural factors include the line length factor, the proportion of tunnel factor, the ecological red line factor, and the basic farmland factor. The original data of the non-natural factors are all existing design data or policy data that cannot be adjusted again after the start of scoring. Therefore, the calculation data of the non-natural factors directly adopt the original data; Determine the index differential quantization scoring algorithm model: To enhance the stability and comparability of the algorithm, establish an index normalization method based on range normalization. For the identified influencing factors, according to their influence on the project, assign the same value range to each influencing factor. Specifically: The calculation method of the scoring value of the line length factor is: in, is the score value of the line length factor, Li is the current line length, and Lmin is the minimum length; The calculation method of the scoring value of the proportion of tunnel factor is: When PSi ≤ 15%: When 15% < PSi ≤ 30%: When PSi > 30%: Among them, PSi is the ratio of the current tunnel to the length of the line, is the score value of the tunnel proportion factor, PSmin is the minimum value of the tunnel proportion to the line length; The calculation method of the scoring value of the ecological red line factor is: in, is the score value of the ecological red line factor, PHi is the ratio of the ecological red line length occupied by the current pipeline section to the length of the line; The calculation method of the scoring value of the basic farmland factor is: in, is the score value of the basic farmland factor, PJmin is the minimum ratio of the length of the basic farmland occupied by the pipeline section to the length of the line where it is located, and PJi is the ratio of the length of the basic farmland occupied by the current pipeline section to the length of the line where it is located; The calculation method of the scoring value of the geological condition factor is: in, is the scoring value of the geological condition factor, DCmin is the minimum number of fault points crossed by the tunnel section of the line, and DCi is the number of fault points crossed by the tunnel section of the current line; The calculation method of the scoring value of the cross-building factor is: in, is the score value of the crossing building factor, JCmin is the minimum number of crossing points involving crossing buildings in the line pipeline section, and JCi is the number of crossing points involving crossing buildings in the current line pipeline section; The calculation method of the scoring value of the slope factor is: in, is the score value of the slope factor, PDmin is the length of the pipeline segment where the slope exceeds the specified limit, and PDi is the length of the pipeline segment where the slope exceeds the specified limit; The calculation method of the scoring value of the maximum static pipe pressure factor is: in, is the score value of the maximum static pipe pressure factor, GYmin is the minimum length of the line pipeline section within the specified height difference range, and GYi is the length of the current line pipeline section within the specified height difference range; Establish the total scoring model for water network path planning: f0_final = f1_len * p1 + f2_sdcdzb * p2 + f3_sthx * p3 + f4_jbnt * p4 + f5_dztj * p5 + f6_jcjzw * p6 + f7_pd * p7 + f8_zdjgy * p8 Among them, f0_final is the total scoring value of the water network path planning, and p1~p8 are the scoring weights of each influencing factor. Different weight values are assigned according to the importance of the influencing factors related to the line scoring. If there are multiple designed water network paths, the total scoring value fi_final of all designed water network paths can be calculated respectively, and then the total scoring values can be summarized to view the theoretical recommendation index, advantages and disadvantages between different design paths, and the designers can quickly conduct scheme demonstration and adjustment based on the scoring value.

2. The water network path evaluation method based on spatial analysis algorithm according to claim 1 is characterized in that The calculation data of the geological condition factor described in step 2) is the number of fault points crossed by the tunnel section of the line. There are two ways to obtain the number of fault points crossed by the tunnel section of the line: Method 1 is to directly obtain it from the official department. The specific steps are: Directly obtain the geological fault vector line data from authoritative official departments and institutions; Extract the tunnel segment vector lines in each water network path, use the intersection analysis in spatial analysis to obtain the intersection points of the fault vector line and each water network path vector line, then count the number of intersection points on each water network path and substitute them into the scoring model to calculate the geological condition factor value. ; Method 2 is to obtain it by using a spatial analysis algorithm. The specific steps are: Obtain the historical earthquake point data and geological structure data in the analysis area; Conduct density analysis on historical earthquake point data to identify areas where epicenters frequently occur and potentially active fault zones; conduct buffer zone analysis on geological structural boundaries in geological structural data to further understand fault zone areas that may affect earthquake activity; Spatial connection is performed between the earthquake point density analysis results and the geological structure boundary buffer zone to find the spatial overlap relationship between earthquake points and fault buffer zones; Identify areas of seismic activity associated with faults through hotspot analysis and find areas of high-frequency seismic activity; Identify the centerline of the surface element and calculate the fault vector line data; Extract the tunnel segment vector lines in each water network path, use the intersection analysis in spatial analysis to obtain the intersection points between the fault vector line and the vector lines of each water network path, and then count the number of intersection points on each water network path.

3. The water network path evaluation method based on spatial analysis algorithm according to claim 1 is characterized in that The calculation data for the intersection building factor in step 2) is the number of intersection building crossing points involved in the line section, which is obtained using a spatial analysis algorithm. The specific steps are: Get digital elevation model data representing the terrain Fill the water flow dead corners in the digital elevation model data through depression filling analysis; Through D8 flow analysis, the flow direction is assigned to the steepest downslope adjacent point; Through cumulative flow analysis, the cumulative value of all flows flowing into each downslope pixel in the output raster is calculated; Use the screening tool to filter and retain all pixel points that can become water system runoff; Through river chain analysis, the spatial link relationship between each retained pixel point is obtained; The Tonstral method of river network classification assigns classes to runoff segments representing branches of a linear network; Through river network vectorization analysis, the interconnected pixels are converted into water network vector lines; Determine the minimum cross-river network level and extract the water network line for the construction of cross-buildings; Extract pipeline segment vector lines in water network paths; Use the intersection analysis in spatial analysis to obtain the intersection points of the fault vector line and the vector lines of each water network path pipeline segment; Count the number of intersections on each water network path.

4. The water network path evaluation method based on spatial analysis algorithm according to claim 1 is characterized in that The calculation data of the slope factor in step 2) is the length of the pipeline section where the slope exceeds the specified limit, which is obtained using the spatial analysis algorithm. The specific steps are as follows: Obtaining digital elevation model data representing terrain; Obtain slope analysis raster data through slope analysis; Use the screening tool to filter and retain the area surface vectors whose slope exceeds the specified limit; Extract pipeline segment vector lines in water network paths; Use the intersection analysis in spatial analysis to obtain the intersection lines of the vector surface of the slope exceeding limit area and the vector lines of each water network path pipeline segment; Count the length of slope exceeding the limit on each water network path separately.

5. The water network path evaluation method based on spatial analysis algorithm according to claim 1 is characterized in that The calculation data for the maximum static pipe pressure factor in step 2) is the length of the line pipeline within the specified elevation range, which is obtained using a spatial analysis algorithm. The specific steps are: Obtaining digital elevation model data representing terrain; Use the filter tool to filter and retain the digital elevation model data within the elevation range where the upper limit is determined by the starting point elevation and the lower limit is determined by the specified elevation difference; Use the raster to vector tool to convert the digital elevation model data within the elevation range into a static pipe pressure range vector surface; Extract pipeline segment vector lines in water network paths; Use the intersection analysis in spatial analysis to obtain the intersection line between the static pipe pressure range vector surface and the vector line of each water network path pipeline segment; Count the length of the static pipe pressure range on each water network path separately.

6. The water network path evaluation method based on spatial analysis algorithm according to claim 1 is characterized in that Step 3) The weights of p1-p8 are determined through the Delphi method, which involves conducting multiple rounds of questionnaires on the designer or expert team, issuing a weight distribution table for the two-tiered influencing factor system, and performing a consistency check on the weight scores of each factor. When the consistency ratio is less than a predetermined threshold, the expert team is considered to have reached a consensus. The process ends and the average value of the expert team is obtained as the final weight distribution table to ensure the scientific nature of the weight distribution. Otherwise, a cycle of meeting discussions and questionnaires is repeated until the expert team reaches a consensus.

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