Water conservancy project evaluation method and system based on BIM

Abstract

The invention relates to the technical field of engineering evaluation, in particular to a BIM (Building Information Modeling)-based hydraulic engineering project evaluation method and system. The method comprises the following steps: acquiring water and soil conservation engineering information, and constructing a water and soil conservation engineering digital model according to the water and soil conservation engineering information; acquiring real-time ecological monitoring data, and establishing a spatial mapping relationship between the real-time ecological monitoring data and the water and soil conservation engineering digital model according to the real-time ecological monitoring data and the water and soil conservation engineering digital model; analyzing the real-time ecological monitoring data and the spatial mapping relationship, and determining a cost risk trigger event set; and according to the cost risk trigger event set, determining a cost correction suggestion, and according to the cost correction suggestion, generating and outputting a dynamic cost assessment report. The adaptability of the water and soil conservation project cost evaluation process to the dynamic change of the ecological environment is improved, and technical support is provided for sustainable development of water conservancy projects.

Description

Technical Field

[0001] The present application relates to the technical field of engineering evaluation, and in particular to a BIM-based water conservancy project evaluation method and system. Background Art

[0002] Water conservancy projects involve complex construction processes and a variety of materials. Reasonable water conservancy project cost assessment methods can provide decision makers with quantitative analysis basis, help them make more informed choices in project feasibility studies, investment decisions and resource allocation, and improve the efficiency and success rate of project implementation.

[0003] However, in the process of cost assessment of soil and water conservation ecological construction projects, the existing water conservancy project cost assessment technology is difficult to accurately assess the dynamic impact of ecological factors on project costs, because soil and water conservation ecological construction projects have ecological restoration and sustainable development as their core goals, and their construction process is dynamically affected by the ecological environment. This leads to a significant deviation between the cost assessment results and the actual project cost. Summary of the Invention

[0004] This application provides a BIM-based water conservancy project evaluation method and system to solve the above technical problems.

[0005] In a first aspect, the present application provides a BIM-based water conservancy project evaluation method, the method comprising: Acquiring soil and water conservation project information, and constructing a soil and water conservation project digital model based on the soil and water conservation project information; Acquiring real-time ecological monitoring data, and establishing a spatial mapping relationship between the real-time ecological monitoring data and the digital model of the soil and water conservation project based on the real-time ecological monitoring data and the digital model of the soil and water conservation project; Analyzing the real-time ecological monitoring data and the spatial mapping relationship to determine a set of cost risk triggering events; According to the cost risk triggering event set, cost correction suggestions are determined, and according to the cost correction suggestions, a dynamic cost assessment report is generated and output.

[0006] Through this solution, a digital model of soil and water conservation projects is constructed based on soil and water conservation project information, breaking through the limitations of traditional two-dimensional assessment and establishing a three-dimensional spatial benchmark for dynamic analysis. By establishing a spatial mapping relationship between ecological data and the digital model of soil and water conservation projects, accurate positioning of monitoring data to project entities is achieved. On this basis, a multi-dimensional risk identification mechanism is used to accurately capture cost risk events caused by ecological factors, and a set of cost risk triggering events is constructed. Based on the corresponding cost correction suggestions, a dynamic cost assessment report is integrated and provided to target users, thereby improving the adaptability of the soil and water conservation project cost assessment process to dynamic changes in the ecological environment and providing technical support for the sustainable development of water conservancy projects.

[0007] Optionally, the digital model of the soil and water conservation project is constructed using a BIM modeling tool, and the digital model of the soil and water conservation project includes three-dimensional components of terrain surfaces, three-dimensional components of water-soil interface structures, and three-dimensional components of ecological vegetation.

[0008] Through this solution, three-dimensional components of terrain surfaces are used to support high-precision terrain analysis, thereby improving the accuracy of cost assessment for terrain transformation. Three-dimensional components of water-soil boundary structures are used to support refined analysis of water-soil boundaries, thereby improving the accuracy of cost assessment for water-soil boundary transformation. Three-dimensional components of ecological vegetation are used to support vegetation coverage analysis, thereby improving the accuracy of cost assessment for vegetation replanting.

[0009] Optionally, the real-time ecological monitoring data is collected by a sensor network composed of several IoT sensors of different sensor types deployed in the soil and water conservation project construction area; The sensor types include soil temperature and humidity sensors, runoff monitors, and vegetation coverage detectors; The real-time ecological monitoring data includes a sensor index set, a soil erosion index set, a surface runoff coefficient set, and a local vegetation coverage rate set.

[0010] Through this solution, a sensor network consisting of several soil temperature and humidity sensors, runoff detectors, and vegetation coverage detectors is used to construct real-time ecological monitoring data containing a sensor index set, a soil erosion index set, a surface runoff coefficient set, and a local vegetation coverage set. Through the all-weather monitoring capability of multi-dimensional ecological parameters, data support is provided for the accuracy and real-time nature of subsequent cost fluctuation analysis.

[0011] Optionally, establishing a spatial mapping relationship between the real-time ecological monitoring data and the soil and water conservation project digital model includes: Determining the spatial coordinates of each of the IoT sensors according to the sensor index; According to the terrain area corresponding to the terrain curved surface three-dimensional component, the water and soil conservation engineering region is divided into several regional grid units; According to the space coordinates and the regional grid units, each soil erosion index in the soil erosion index set is mapped to the terrain curved surface three-dimensional component in the corresponding regional grid unit to determine a terrain-soil mapping relationship set; According to the space coordinates and the regional grid units, each surface runoff coefficient in the surface runoff coefficient set is mapped to the water-soil interface structure three-dimensional component in the corresponding regional grid unit to determine a runoff-structure mapping relationship set; According to the space coordinates and the regional grid units, each vegetation coverage in the local vegetation coverage set is mapped to the water-soil interface structure three-dimensional component in the corresponding regional grid unit to determine a vegetation-region mapping relationship set; According to the terrain-soil mapping relationship set, the runoff-structure mapping relationship set and the vegetation-region mapping relationship set, the spatial mapping relationship is constructed.

[0012] According to the space coordinates and the regional grid units of each Internet of Things sensor, each soil erosion index, surface runoff coefficient and local vegetation coverage is respectively mapped to the corresponding three-dimensional component in the regional grid unit, and a terrain-soil mapping relationship set, a runoff-structure mapping relationship set and a vegetation-region mapping relationship set are constructed to comprehensively reflect the spatial mapping relationship between the ecological parameters and the water and soil conservation engineering region, and to provide comprehensive scientific data support for subsequent analysis of cost fluctuation events caused by each ecological parameter in the corresponding region.

[0013] Optionally, the real-time ecological monitoring data and the spatial mapping relationship are analyzed to determine a cost risk triggering event set, including: The design soil erosion threshold of each terrain curved surface three-dimensional component in the water and soil conservation engineering digital model, the runoff bearing capacity threshold of each water-soil interface structure three-dimensional component and the target vegetation coverage of each ecological vegetation three-dimensional component in the engineering region are obtained. According to the design soil erosion threshold, the terrain-soil mapping relationship set is analyzed to identify whether there is a high-risk soil erosion region, and if there is, a terrain reinforcement event is triggered. According to the runoff bearing capacity threshold, the runoff-structure mapping relationship set is analyzed to identify whether there is a high-risk runoff damage structure, and if there is, a water-soil interface reinforcement event is triggered. According to the target vegetation coverage, the vegetation-region mapping relationship set is analyzed to identify whether there is a low-efficiency vegetation coverage region, and if there is, a vegetation increment reseeding event is triggered. According to the terrain reinforcement event, the water-soil junction reinforcement event and the vegetation increment reseeding event, the construction cost risk triggering event set is constructed.

[0014] Through the scheme, according to the design soil erosion threshold, the runoff bearing capacity threshold and the target vegetation coverage, the soil erosion risk, the runoff damage risk and the vegetation degradation analysis of each local area reflected in the terrain-soil mapping relationship set, the runoff-structure mapping relationship set and the vegetation-area mapping relationship set are analyzed, whether there is a soil erosion high-risk area / a runoff damage high-risk structure / a vegetation coverage low-efficiency area is judged, and then the corresponding terrain reinforcement event, the water-soil junction reinforcement event and the vegetation increment reseeding event are triggered to construct the construction cost risk triggering event set, the collaborative assessment of engineering risk and ecological risk is realized, and the assessment accuracy of the fluctuation of the construction cost under the change of ecological environment is improved.

[0015] Optionally, the analysis of the terrain-soil mapping relationship set according to the design soil erosion threshold to identify whether there is a soil erosion high-risk area comprises: According to the slope attribute of the terrain curved surface three-dimensional component, the terrain correction coefficient adjustment is performed on the design soil erosion threshold to generate a dynamic soil erosion threshold; The linear interpolation algorithm is adopted to map multiple soil erosion indexes in the same regional grid cell to the curved surface grid vertex of the terrain curved surface three-dimensional component; If the ratio of the soil erosion index of the curved surface grid vertex to the dynamic soil erosion threshold is greater than a preset erosion ratio, the corresponding regional grid cell is marked as the soil erosion high-risk area.

[0016] Through the scheme, based on the terrain slope data, the dynamic soil erosion threshold mechanism and the curved surface vertex level mapping method are adopted to realize the accurate identification of the soil erosion high-risk area, avoid the false alarm in the gentle slope area and the missing report in the steep slope area caused by the use of a unified threshold, and then improve the accuracy of the subsequent construction cost fluctuation analysis process triggered by the terrain reinforcement event.

[0017] Optionally, the analysis of the runoff-structure mapping relationship set according to the runoff bearing capacity threshold to identify whether there is a runoff damage high-risk structure comprises: According to the junction topological relationship of the water-soil junction structure three-dimensional component and the runoff bearing capacity threshold, a joint threshold of the runoff bearing capacity of the structure junction is extracted; The multiple surface runoff coefficients mapped to the same water-soil junction structure three-dimensional component are weighted and averaged to obtain a comprehensive runoff coefficient of the structure; If the difference between the structure comprehensive runoff coefficient and the runoff bearing capacity joint threshold exceeds the preset bearing difference threshold, the water-soil junction structure three-dimensional component corresponding to the water-soil junction structure three-dimensional component is marked as the runoff damage high-risk structure.

[0018] Through the scheme, according to the junction topological relationship of the water-soil junction structure three-dimensional component and the runoff bearing capacity threshold, the runoff bearing capacity joint threshold of the structure junction is analyzed and obtained, and on this basis, combined with the structure comprehensive runoff coefficient and the preset bearing difference threshold, the runoff damage high-risk structure is accurately identified according to the difference between the structure comprehensive runoff coefficient and the runoff bearing capacity joint threshold, and the accuracy of the subsequent cost fluctuation analysis process caused by the water-soil junction reinforcement event is improved.

[0019] Optionally, the vegetation-coverage mapping relationship set is analyzed according to the target vegetation coverage to identify whether there is a vegetation coverage inefficient area, including: According to the vegetation type attribute of the ecological vegetation three-dimensional component, a preset vegetation growth cost coefficient database is associated; According to the preset vegetation growth cost coefficient database, the vegetation coverage in the same regional grid unit is seasonally corrected to generate a standardized vegetation coverage; If the standardized vegetation coverage is less than the target vegetation coverage by an amplitude greater than a preset vegetation difference amplitude, the regional grid unit corresponding to the regional grid unit is marked as a vegetation coverage inefficient area.

[0020] Through the scheme, in the process of identifying the vegetation coverage inefficient area, the vegetation coverage corresponding to different regions is corrected based on seasons to obtain the standardized vegetation coverage, so as to reflect the real vegetation coverage. When the standardized vegetation coverage is less than the target vegetation coverage by an amplitude greater than a preset vegetation difference amplitude, it indicates that the vegetation coverage in the corresponding region has been reduced to the degree that requires artificial intervention for reseeding. At this time, the regional grid unit corresponding to the regional grid unit is marked as a vegetation coverage inefficient area, the evaluation accuracy of the vegetation coverage inefficient area is improved, and the accuracy of the subsequent cost fluctuation analysis process caused by the vegetation increment reseeding event is improved.

[0021] Optionally, the cost correction suggestion is determined according to the set of cost risk triggering events, including: The reinforcement engineering quota coefficient corresponding to the soil erosion high-risk area, the material quota coefficient of the water-soil junction structure, and the vegetation reseeding unit price parameter corresponding to the vegetation coverage inefficient area are extracted from the preset BIM model component attribute library; According to the topographic reinforcement event, the topographic reinforcement area is determined, and the topographic reinforcement cost increment is determined according to the product of the reinforcement engineering quota coefficient and the topographic reinforcement area, and the topographic construction difficulty additional cost is superimposed. According to the soil-water interface reinforcement event, the reinforcement length of the interface is determined, and the incremental cost of structure reinforcement is determined by multiplying the reinforcement length of the interface by the material quota coefficient and adding the additional cost of the construction difficulty of the interface; Determine the vegetation replanting area based on the vegetation incremental replanting event, and determine the vegetation replanting cost increment based on the product of the vegetation replanting area and the vegetation unit price parameter and the added seasonal maintenance cost; The cost correction suggestion is generated based on the terrain reinforcement cost increment, the structure reinforcement cost increment and the vegetation replanting cost increment.

[0022] Through this plan, on the basis of the standardized data of the reinforcement project quota coefficient, material quota coefficient and replanting unit price parameters, combined with the static indicators pointed by the terrain reinforcement area, the reinforcement length of the junction and the vegetation replanting area, the dynamic factors pointed by the additional cost of terrain construction difficulty, the additional cost of junction construction difficulty and the seasonal maintenance cost are further considered, and a comprehensive quantitative analysis is carried out to obtain the incremental cost of terrain reinforcement, the incremental cost of structure reinforcement and the incremental cost of vegetation replanting. On this basis, cost correction suggestions are generated to obtain comprehensive and accurate dynamic cost assessment results.

[0023] In a second aspect, the present application provides a BIM-based water conservancy project evaluation system, the system comprising: A model building module is used to obtain soil and water conservation project information and build a soil and water conservation project digital model based on the soil and water conservation project information; a mapping analysis module for acquiring real-time ecological monitoring data and establishing a spatial mapping relationship between the real-time ecological monitoring data and the digital model of the soil and water conservation project based on the real-time ecological monitoring data and the digital model of the soil and water conservation project; A risk analysis module, configured to analyze the real-time ecological monitoring data and the spatial mapping relationship to determine a set of cost risk triggering events; The report output module is used to determine cost correction suggestions based on the cost risk trigger event set, and generate and output a dynamic cost assessment report based on the cost correction suggestions. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0025] Figure 1 A schematic diagram of an application scenario provided in one embodiment of the present application; Figure 2 A flowchart of a BIM-based water conservancy project evaluation method provided in one embodiment of the present application; Figure 3 A structural diagram of a BIM-based water conservancy project evaluation system provided in one embodiment of the present application. DETAILED DESCRIPTION

[0026] To make the purpose, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0027] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0028] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0029] In the process of cost assessment of soil and water conservation ecological construction projects, the existing water conservancy project cost assessment technology is difficult to accurately assess the dynamic impact of ecological factors on project costs, because soil and water conservation ecological construction projects take ecological restoration and sustainable development as their core goals, and their construction process is dynamically affected by the ecological environment. This leads to a significant deviation between the cost assessment results and the actual project cost.

[0030] Based on this, the present application provides a BIM-based water conservancy project evaluation method and system. According to the soil and water conservation project information, a digital model of the soil and water conservation project is constructed to break through the limitations of the traditional two-dimensional evaluation and establish a three-dimensional spatial benchmark for dynamic analysis. By establishing a spatial mapping relationship between ecological data and the digital model of the soil and water conservation project, the precise positioning of the monitoring data to the engineering entity is achieved. On this basis, the cost risk events caused by ecological factors are accurately captured through a multi-dimensional risk identification mechanism, and a cost risk triggering event set is constructed. Then, according to the corresponding cost correction suggestions, a dynamic cost evaluation report is integrated and provided to the target users, thereby improving the adaptability of the soil and water conservation project cost evaluation process to the dynamic changes of the ecological environment and providing technical support for the sustainable development of water conservancy projects.

[0031] Figure 1 This is a schematic diagram of an application scenario provided by this application. The method provided by this application can be applied to the cost assessment process of soil and water conservation projects to improve their adaptability to dynamic changes in the ecological environment, providing technical support for the sustainable development of water conservancy projects.

[0032] Specifically, the method of the present application is applied to any server, which communicates with the Internet of Things sensor and the water conservancy project design unit, obtains the soil and water conservation project information provided by the water conservancy project design unit through the server, and constructs a digital model of the soil and water conservation project based on the soil and water conservation project information, breaking through the limitations of traditional two-dimensional evaluation, establishing a three-dimensional spatial benchmark for dynamic analysis, obtaining real-time ecological monitoring data, and achieving precise positioning of the monitoring data to the engineering entity by establishing a spatial mapping relationship between the real-time ecological monitoring data and the digital model of the soil and water conservation project. On this basis, the cost risk events caused by ecological factors are accurately captured through a multi-dimensional risk identification mechanism, and a cost risk triggering event set is constructed. Then, according to the corresponding cost correction suggestions, a dynamic cost assessment report is integrated and provided to the target user, thereby improving the adaptability of the soil and water conservation project cost assessment process to the dynamic changes in the ecological environment and providing technical support for the sustainable development of water conservancy projects. The specific implementation method can refer to the following embodiments.

[0033] Figure 2 This is a flow chart of a BIM-based water conservancy project evaluation method provided in one embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201. Acquire soil and water conservation project information, and construct a soil and water conservation project digital model based on the soil and water conservation project information.

[0034] Soil and water conservation project information can be a multimodal data set including elements such as soil and water conservation project design parameters, construction drawings, material properties and ecological restoration goals. Soil and water conservation project information is provided by water conservancy project design units.

[0035] The digital model of soil and water conservation projects can be a three-dimensional digital engineering model built based on BIM technology, which includes components such as terrain surfaces, soil and water structures, and ecological vegetation.

[0036] Specifically, traditional water conservancy project cost assessment mainly relies on two-dimensional drawings and static quota indicators, which makes it difficult to reflect the impact of three-dimensional characteristics such as terrain complexity and spatial relationships of ecological structures in soil and water conservation projects on construction costs. Especially during the construction of soil and water conservation projects, spatial attributes such as changes in surface runoff paths and dynamic evolution of vegetation coverage will directly affect the amount of construction materials and project difficulty, thereby causing dynamic fluctuations in construction costs. By constructing a BIM model of the soil and water conservation project, the three-dimensional visualization expression and spatial relationship analysis of the project elements can be realized, and an accurate spatial benchmark can be established for subsequent dynamic cost analysis. During the modeling process, BIM modeling tools such as Autodesk Revit can be used to construct a digital model of the soil and water conservation project based on the design parameters and material properties in the soil and water conservation project information.

[0037] S202: Acquire real-time ecological monitoring data, and establish a spatial mapping relationship between the real-time ecological monitoring data and the digital model of the soil and water conservation project based on the real-time ecological monitoring data and the digital model of the soil and water conservation project.

[0038] Real-time ecological monitoring data can be ecological environmental parameters within the construction area of ​​soil and water conservation projects. Real-time ecological monitoring data can be obtained through different types of Internet of Things sensors.

[0039] The spatial mapping relationship can be the spatial position association relationship between ecological monitoring data and three-dimensional components of the BIM model.

[0040] Specifically, existing cost assessment methods for soil and water conservation projects mostly use a method of periodically collecting data using manually carried equipment. This method cannot perceive dynamic changes such as accelerated soil erosion rate and runoff path deviation during construction in real time, resulting in delayed risk identification. By establishing a gridded spatial coordinate system in the BIM model, the ecological and environmental parameters collected by the sensors are mapped to the corresponding construction areas and structures through a spatial interpolation algorithm. The above-mentioned dynamic spatial mapping mechanism is used to break through the limitations of the separation of data and models in traditional assessments. For example, when the soil erosion index of a grid unit in a certain area exceeds the design threshold, the corresponding terrain surface component in the BIM model can be immediately located for risk marking, thereby achieving accurate association between ecological data and engineering entities, and accurately identifying whether there is a risk of fluctuation in the current project cost.

[0041] S203: Analyze the real-time ecological monitoring data and spatial mapping relationship to determine the cost risk triggering event set.

[0042] The cost risk triggering event set may be a set of local engineering change events caused by changes in the ecological environment within the construction area.

[0043] Specifically, risk identification in the traditional soil and water conservation project cost assessment process is mostly based on historical data and experience judgment, lacking a dynamic quantitative analysis model, making it difficult to accurately predict and identify the chain cost changes caused by ecological factors. Based on the real-time ecological monitoring data and spatial mapping relationship, a multi-dimensional risk identification mechanism is used to analyze the events that may trigger cost fluctuations in the space to which different real-time ecological monitoring data currently belong, and to construct a set of cost risk triggering events to ensure the accuracy and comprehensiveness of cost risk fluctuation predictions.

[0044] S204: Determine cost correction suggestions based on the cost risk trigger event set, and generate and output a dynamic cost assessment report based on the cost correction suggestions.

[0045] Cost correction suggestions can be engineering adjustment suggestions made to meet the needs of additional projects caused by cost fluctuations due to changes in the ecological environment.

[0046] A dynamic cost assessment report can be a multi-dimensional analysis document that integrates a visual map of risk events, cost increment details, and construction recommendations.

[0047] Specifically, after obtaining the set of cost risk triggering events, the cost correction suggestions including construction scope, project type and construction cost are determined according to the impact scope corresponding to different cost risk events and the additional construction projects and costs required to eliminate the risks. The additional costs are incorporated into the existing basic cost assessment results, and a dynamic cost assessment report is generated through the data visualization engine and provided to the target users.

[0048] Through this solution, a digital model of soil and water conservation projects is constructed based on soil and water conservation project information, breaking through the limitations of traditional two-dimensional assessment and establishing a three-dimensional spatial benchmark for dynamic analysis. By establishing a spatial mapping relationship between ecological data and the digital model of soil and water conservation projects, accurate positioning of monitoring data to project entities is achieved. On this basis, a multi-dimensional risk identification mechanism is used to accurately capture cost risk events caused by ecological factors, and a set of cost risk triggering events is constructed. Based on the corresponding cost correction suggestions, a dynamic cost assessment report is integrated and provided to target users, thereby improving the adaptability of the soil and water conservation project cost assessment process to dynamic changes in the ecological environment and providing technical support for the sustainable development of water conservancy projects.

[0049] In some embodiments, the digital model of the soil and water conservation project is constructed using BIM modeling tools, and the digital model of the soil and water conservation project includes three-dimensional components of terrain surfaces, three-dimensional components of water-soil interface structures, and three-dimensional components of ecological vegetation.

[0050] BIM modeling tools can be construction engineering software that supports three-dimensional parametric modeling, such as Autodesk Revit, Bentley OpenRoads, etc., which are derived from the building information modeling technology system widely used in the engineering construction field.

[0051] The three-dimensional terrain surface component can be a three-dimensional surface model element that reflects the real terrain undulation characteristics of the soil and water conservation project area, and is derived from the three-dimensional reconstruction process of UAV aerial survey point cloud data or terrain mapping data.

[0052] The three-dimensional components of the water-soil interface structure can be parametric three-dimensional model components that represent engineering structures at the water-soil interface, such as retaining walls and drainage ditches, and are derived from BIM parametric modeling of engineering design drawings.

[0053] The ecological vegetation three-dimensional component can be a three-dimensional layer model that expresses the distribution area and growth characteristics of vegetation, which comes from the GIS data conversion of the ecological planning scheme.

[0054] Specifically, the two-dimensional drawings used in traditional water conservancy project cost assessments have three major technical defects: First, two-dimensional plane projections cannot accurately reflect the impact of changes in terrain slope on earthwork volume, resulting in deviations in terrain transformation cost estimates; second, the spatial topological relationship of water-soil interface structures is difficult to fully present in plane drawings, resulting in distortion in the evaluation of the collaborative working efficiency of structures; third, the spatial coupling relationship between ecological vegetation coverage and terrain surfaces lacks three-dimensional visual expression, resulting in insufficient accuracy in ecological restoration cost calculations; by constructing a BIM digital model that integrates three types of three-dimensional components, three-dimensional spatial analysis and dynamic association of engineering elements can be achieved. Among them, most of the construction costs in soil and water conservation projects are related to terrain transformation. Through Civil 3D software converts elevation point cloud data into NURBS surfaces with slope attributes, and obtains three-dimensional components of terrain surfaces, which can accurately calculate the amount of earthwork excavation and filling in different slope ranges. Compared with the traditional contour analysis method, the three-dimensional surface model can identify hidden terrain mutation areas and avoid cost omissions caused by terrain misjudgment. For example, a slope area appears as a gentle slope in the two-dimensional projection, but the three-dimensional model reveals that it has a local steep slope, which requires additional retaining wall construction costs; Revit parametric modeling technology is used to create a structural object family library with material attribute labels, and the three-dimensional components of the water-soil interface structure are obtained, which can automatically count the uneven terrain. By establishing topological connections between structures, the amount of concrete used for the same structural type can simulate the chain reaction of structures under runoff impact. For example, at the connection between a drainage ditch and a retaining wall, the 3D model can detect a design gap error of less than 5 cm. This error is difficult to detect in a 2D drawing, but it will lead to some runoff overflow risk and increase sealing costs. InfraWorks can also overlay GIS vegetation distribution data with the terrain surface in 3D to produce a 3D ecological vegetation component. This can calculate vegetation density based on different regional characteristics and accurately assess the cost of replanting vegetation due to insufficient vegetation survival rate.

[0055] Through this solution, three-dimensional components of terrain surfaces are used to support high-precision terrain analysis, thereby improving the accuracy of cost assessment for terrain transformation. Three-dimensional components of water-soil boundary structures are used to support refined analysis of water-soil boundaries, thereby improving the accuracy of cost assessment for water-soil boundary transformation. Three-dimensional components of ecological vegetation are used to support vegetation coverage analysis, thereby improving the accuracy of cost assessment for vegetation replanting.

[0056] In some embodiments, real-time ecological monitoring data is collected through a sensor network composed of several different types of Internet of Things sensors deployed in the construction area of ​​the soil and water conservation project; the sensor types include soil temperature and humidity sensors, runoff monitors, and vegetation coverage detectors; the real-time ecological monitoring data includes a sensor index set, a soil erosion index set, a surface runoff coefficient set, and a local vegetation coverage set.

[0057] The sensor network composed of IoT sensors can be a low-power wide-area ecological parameter monitoring system built based on the LoRaWAN protocol.

[0058] The soil temperature and humidity sensor may be an embedded monitoring device that uses the TDR (Time Domain Reflectometry) principle.

[0059] The runoff monitor may be a runoff flow measurement device based on the Doppler ultrasonic principle.

[0060] The vegetation cover detector may be an embedded device supported by vegetation cover remote sensing technology.

[0061] The sensor index set may be a structured data table containing sensor device IDs, geographic coordinates, and installation parameters.

[0062] The soil erosion index set may be a parameter set used to characterize the degree of soil erosion in different regions. The soil erosion index set may be obtained through a RUSLE (Revised Universal Soil Loss Equation) model based on the data collected by the aforementioned series of IoT sensors.

[0063] The surface runoff coefficient set may be a parameter set used to characterize the change in surface runoff volume in different regions. The surface runoff coefficient set may be obtained through measured data from a runoff monitoring instrument.

[0064] The local vegetation coverage rate set may be a numerical value set representing the ratio of the vegetation projection area to the area of ​​the target statistical region. The local vegetation coverage rate set may be obtained through measured data of a vegetation coverage detector.

[0065] Specifically, the existing ecological monitoring of the construction process of soil and water conservation projects has the following problems: First, the manual sampling method leads to insufficient spatiotemporal resolution of data, making it difficult to capture dynamic ecological changes during the construction process; second, a single type of sensor cannot construct the complete data dimension required for multi-physical field coupling analysis; third, the spatial correspondence between monitoring data and engineering models is fuzzy, resulting in low risk positioning accuracy; soil and water conservation project areas usually have complex terrain and scattered monitoring points. Through the LoRaWAN network, soil temperature and humidity sensors, runoff monitors and vegetation coverage detectors are integrated into a network, and corresponding sampling intervals are set for different sensors to form a dynamic three-dimensional monitoring of the ecological environment. Compared with the traditional GPRS networking method, LoRaWAN's 10km transmission radius and -148dBm receiving sensitivity can effectively overcome the signal attenuation problem in mountainous environments, ensuring that the data return rate remains at a high level, which is suitable for the characteristics of soil and water conservation project construction areas that are mostly located in mountainous environments; soil temperature and humidity sensors can capture the accelerated erosion caused by sudden changes in soil moisture content; runoff monitors can identify the risk of runoff path deviation; vegetation cover detectors can detect areas of vegetation degradation. The three types of sensor data are aligned with timestamps and matched with spatial grids to construct an ecological coupling analysis system of "soil-hydrology-vegetation" to support dynamic analysis of the cost of soil and water conservation projects.

[0066] Through this solution, a sensor network consisting of several soil temperature and humidity sensors, runoff detectors, and vegetation coverage detectors is used to construct real-time ecological monitoring data containing a sensor index set, a soil erosion index set, a surface runoff coefficient set, and a local vegetation coverage set. Through the all-weather monitoring capability of multi-dimensional ecological parameters, data support is provided for the accuracy and real-time nature of subsequent cost fluctuation analysis.

[0067] In some embodiments, the spatial coordinates of each IoT sensor are determined based on the sensor index; the area where the soil and water conservation project is located is divided into a number of regional grid units based on the terrain area corresponding to the three-dimensional component of the terrain surface; each soil erosion index in the soil erosion index set is mapped to the three-dimensional component of the terrain surface in the corresponding regional grid unit based on the spatial coordinates and the regional grid unit, and a terrain-soil mapping relationship set is determined; each surface runoff coefficient in the surface runoff coefficient set is mapped to the three-dimensional component of the water-soil interface structure in the corresponding regional grid unit based on the spatial coordinates and the regional grid unit, and a runoff-structure mapping relationship set is determined; each vegetation coverage rate in the local vegetation coverage rate set is mapped to the three-dimensional component of the water-soil interface structure in the corresponding regional grid unit based on the spatial coordinates and the regional grid unit, and a vegetation-region mapping relationship set is determined; and a spatial mapping relationship is constructed based on the terrain-soil mapping relationship set, the runoff-structure mapping relationship set, and the vegetation-region mapping relationship set.

[0068] The spatial coordinates may be the coordinate information of the current sensor layout position in the digital model of the soil and water conservation project.

[0069] The regional grid unit can be a polygonal space unit obtained by dividing the soil and water conservation project construction area based on the area approximation principle; The terrain-soil mapping relationship set may be a dataset reflecting the spatial correlation relationship between the terrain surface and the soil erosion index.

[0070] The runoff-structure mapping relationship set may be a data set reflecting the spatial correlation relationship between the water-soil interface and the runoff coefficient.

[0071] The vegetation-region mapping relationship set may be a dataset used to express the matching relationship between vegetation coverage and regional unit grids.

[0072] Specifically, the soil and water conservation project area often spans complex terrain, and the sensor deployment location directly affects the data representativeness. The three-dimensional coordinates of the sensor are obtained through GNSS-RTK positioning technology (plane accuracy ±2cm) and converted into the local coordinate system of the BIM model to determine the sensor spatial coordinates and eliminate the spatial mapping offset caused by the coordinate system difference. The area where the soil and water conservation project is located is divided into several polygonal regional grid units (better than the adjacency uniformity of the square grid) to achieve spatial aggregation of monitoring data. The soil erosion index / surface runoff coefficient / local vegetation coverage rate collected by each IoT sensor are marked to the three-dimensional components within the grid unit of the sensor area, and the terrain-soil mapping relationship set, runoff-structure mapping relationship set and vegetation-region mapping relationship set are constructed to comprehensively reflect the spatial mapping relationship between ecological parameters and the soil and water conservation project area.

[0073] Through this solution, each soil erosion index, surface runoff coefficient, and local vegetation coverage rate are mapped to the corresponding three-dimensional components within their regional grid units according to the spatial coordinates and regional grid units of each IoT sensor. A terrain-soil mapping relationship set, a runoff-structure mapping relationship set, and a vegetation-region mapping relationship set are constructed to comprehensively reflect the spatial mapping relationship between ecological parameters and soil and water conservation project areas, providing comprehensive scientific data support for the subsequent analysis of cost fluctuation events caused by various ecological parameters in their corresponding areas.

[0074] In some embodiments, the design soil erosion threshold of each of the three-dimensional components of the terrain surface in the digital model of the soil and water conservation project, the runoff bearing capacity threshold of each of the three-dimensional components of the water-soil interface structure, and the target vegetation coverage rate of the project area where each of the three-dimensional components of the ecological vegetation are located are obtained; according to the design soil erosion threshold, the terrain-soil mapping relationship set is analyzed to identify whether there is a high-risk area for soil erosion, and if so, a terrain reinforcement event is triggered; according to the runoff bearing capacity threshold, the runoff-structure mapping relationship set is analyzed to identify whether there is a high-risk structure for runoff damage, and if so, a water-soil interface reinforcement event is triggered; according to the target vegetation coverage rate, the vegetation-region mapping relationship set is analyzed to identify whether there is an inefficient vegetation coverage area, and if so, a vegetation incremental replanting event is triggered; according to the terrain reinforcement event, the water-soil interface reinforcement event and the vegetation incremental replanting event, a cost risk triggering event set is constructed.

[0075] The design soil erosion threshold can be the critical value of soil loss per unit area specified in the soil and water conservation project design specifications.

[0076] The runoff bearing capacity threshold can be the maximum runoff impact that the structure at the water-soil interface can bear.

[0077] The target vegetation coverage rate can be the vegetation coverage rate expected to be achieved during the design process of soil and water conservation projects.

[0078] High-risk areas for soil erosion may be areas where soil erosion conditions have reached a level that requires construction intervention.

[0079] The terrain reinforcement event may be an event signal indicating that terrain reinforcement is required in the current area.

[0080] Structures at high risk of runoff damage may be structures at the water-soil interface that have a high probability of being damaged by surface runoff.

[0081] The water-soil boundary reinforcement event may be an event signal indicating that structures at the water-soil boundary in the current area need to be reinforced.

[0082] Inefficient vegetation coverage areas may be areas where the local vegetation coverage rate does not meet the corresponding standards.

[0083] The vegetation incremental replanting event may be an event signal indicating that vegetation in the current area needs to be replanted.

[0084] Specifically, the reinforcement requirements reflected by the soil erosion index under different terrains are different. On steep slopes, soil erosion usually develops faster and has a large impact range, which means that stronger reinforcement measures are needed to prevent soil loss. On relatively flat terrain, although soil erosion may also occur, its development speed is usually slower and the impact range is small, and the corresponding reinforcement measures have lower intensity requirements. According to the designed soil erosion threshold, the terrain-soil mapping relationship set is analyzed, and the erosion risks caused by different soil erosion indices under the influence of their terrain are quantitatively compared and analyzed to identify whether there are high-risk areas for soil erosion. If there are high-risk areas for soil erosion, a terrain reinforcement event is triggered, indicating that the current area needs to be reinforced, which means that the current soil state will have a significant impact on the construction cost of the project in the current area; the degree of damage caused by runoff changes to the structure at the water-soil interface depends on the runoff bearing capacity of the corresponding components. According to the runoff bearing capacity threshold, the runoff-structure mapping relationship set is analyzed, and the damage risk of the water-soil interface components with clear runoff bearing capacity under runoff changes is quantitatively compared and analyzed. , identify whether there are high-risk structures for runoff damage. If there are high-risk structures for runoff damage, it means that the risk of soil and water loss caused by runoff erosion at the water-soil interface in the current area has increased significantly. The structures at the water-soil interface in the current area need to be reinforced, which means that the current state of the structures will have a significant impact on the construction cost of the project in the current area. The impact of vegetation coverage cannot be simply considered from a global perspective. For example, if the vegetation coverage rate of an entire area meets the standard, but the vegetation in a local area is very sparse and degraded, then soil and water runoff is likely to break through this area and develop into a systemic risk. Based on the target vegetation coverage rate, the vegetation-region mapping relationship set is analyzed, and the vegetation coverage performance in different regions is targeted and quantitatively analyzed to determine whether there are areas with low vegetation coverage. If so, it means that the vegetation in the corresponding area needs to be targeted and replanted, triggering a vegetation incremental replanting event. Based on terrain reinforcement events, water-soil interface reinforcement events, and vegetation incremental replanting events, a cost risk triggering event set is constructed to comprehensively measure the different levels of impact caused by changes in current dynamic ecological factors on project cost fluctuations.

[0085] Through this scheme, according to the designed soil erosion threshold, runoff carrying capacity threshold and target vegetation coverage, the soil erosion risk, runoff damage risk and vegetation degradation risk of each local area reflected in the terrain-soil mapping relationship set, runoff-structure mapping relationship set and vegetation-region mapping relationship set are analyzed respectively to determine whether there are high-risk areas for soil erosion / high-risk structures for runoff damage / areas with low vegetation coverage, and then trigger corresponding terrain reinforcement events, water-soil boundary reinforcement events and vegetation incremental replanting events to construct a cost risk trigger event set, realize the coordinated assessment of engineering risk and ecological risk, and improve the accuracy of the assessment of fluctuations in engineering cost under changes in the ecological environment.

[0086] In some embodiments, the designed soil erosion threshold is adjusted by a terrain correction coefficient based on the slope properties of the terrain surface three-dimensional component to generate a dynamic soil erosion threshold; a linear interpolation algorithm is used to map multiple soil erosion indices within the same regional grid unit to the surface grid vertices of the terrain surface three-dimensional component; if the ratio of the soil erosion index of a surface grid vertex to the dynamic soil erosion threshold is greater than a preset erosion ratio, the corresponding regional grid unit is marked as a high-risk area for soil erosion.

[0087] The slope attribute can be the inclination of the ground surface at the vertices of the terrain surface mesh.

[0088] Dynamic soil erosion threshold is the critical value of soil loss per unit area after slope correction.

[0089] The linear interpolation algorithm may be a spatial interpolation method based on inverse distance weighted (IDW), which is a standard algorithm from the GIS spatial analysis tool library.

[0090] The surface mesh vertices may be node coordinate points constituting the terrain surface triangulation network.

[0091] The preset erosion ratio may be a preset maximum ratio at which the actual erosion amount is allowed to exceed a threshold value, which is derived from a risk tolerance standard corresponding to the safety level of the soil and water conservation project.

[0092] Specifically, the traditional soil erosion risk assessment process typically uses a fixed threshold as a benchmark and determines soil erosion risk through a simple numerical comparison. This approach does not account for spatial terrain heterogeneity. For example, within the same project area, the soil erosion resistance of a 5° gentle slope can differ by up to three times that of a 30° steep slope. Using a unified threshold can lead to false positives in gentle slope areas and missed positives in steep slope areas. Based on the slope properties of the three-dimensional terrain surface component, the designed soil erosion threshold is adjusted by a terrain correction coefficient (dynamic threshold = design threshold × (1 - 0.018 × slope)) to generate a dynamic soil erosion threshold. Simultaneously, a linear interpolation algorithm is used to map multiple soil erosion indices within the same regional grid cell to the surface mesh vertices of the three-dimensional terrain surface component. The numerical relationship between the ratio of the soil erosion index to the dynamic soil erosion threshold at each surface mesh vertex and a preset erosion ratio is quantitatively analyzed. If the ratio of the soil erosion index to the dynamic soil erosion threshold at a surface mesh vertex is greater than the preset erosion ratio, the corresponding terrain surface is at high risk due to the influence of its corresponding soil erosion index, and the corresponding regional grid cell is marked as a high-risk area for soil erosion.

[0093] This solution, based on terrain slope data, uses a dynamic soil erosion threshold mechanism and surface vertex-level mapping to accurately identify high-risk areas for soil erosion. This avoids the false positives in gentle slope areas and missed positives in steep slope areas caused by the use of a unified threshold, thereby improving the accuracy of subsequent cost fluctuation analysis processes triggered by terrain reinforcement events.

[0094] In some embodiments, based on the topological relationship of the junction of the three-dimensional components of the water-soil interface structure and the runoff bearing capacity threshold, the joint threshold of the runoff bearing capacity at the structure junction is extracted; a weighted average calculation is performed on multiple surface runoff coefficients mapped to the same three-dimensional component of the water-soil interface structure to obtain the comprehensive runoff coefficient of the structure; if the difference between the comprehensive runoff coefficient of the structure and the joint threshold of the runoff bearing capacity exceeds a preset bearing difference threshold, the corresponding three-dimensional component of the water-soil interface structure is marked as a high-risk structure for runoff damage.

[0095] The topological relationship of the interface can be the spatial adjacency and mechanical transmission relationship between the connection nodes of the structure at the water-soil interface. The topological relationship of the interface can be obtained based on the connector system attribute data in the Autodesk Revit model.

[0096] The joint threshold of runoff bearing capacity can be the maximum runoff impact force of the joint bearing at the junction of adjacent structures. The joint threshold of runoff bearing capacity can be obtained by performing fluid impact simulation on the structure according to the joint structural state of the structure and the runoff bearing capacity of a single material.

[0097] The comprehensive runoff coefficient of a structure can be a quantitative coefficient used to characterize the impact of multi-source runoff on the same structure.

[0098] The preset bearing difference threshold may be a maximum ratio by which the actual runoff bearing capacity is allowed to deviate from the design value.

[0099] Specifically, the traditional runoff bearing risk assessment process of the structure at the water-soil boundary does not consider the mechanical conduction effect of adjacent structural members when impacted by runoff, for example, the connection between the drainage ditch and the retaining wall. The traditional method separately assesses the bearing capacity of the two, ignores the stress superposition effect at the joint, directly takes the maximum value of the monitoring data as the basis for evaluation, and does not consider the spatial joint distribution characteristics of the structure. The scheme quantifies the cooperative bearing capacity at each structure boundary through mathematical analysis means (joint threshold value = min (main structure threshold value, from structure threshold value) x joint efficiency coefficient, the joint efficiency coefficient is obtained from the construction quality report), determines the joint threshold value of the runoff bearing capacity at the structure boundary, and simultaneously performs weighted average processing on multiple surface runoff coefficients mapped to the same water-soil boundary structure three-dimensional member, to obtain a comprehensive runoff coefficient of the structure. When the difference between the comprehensive runoff coefficient of the structure and the joint threshold value of the runoff bearing capacity exceeds the preset bearing difference threshold value, it indicates that the current joint structure has a high probability of being damaged by the current runoff, and the corresponding water-soil boundary structure three-dimensional member is marked as a high-risk structure damaged by runoff.

[0100] Through the scheme, according to the joint threshold value of the runoff bearing capacity of the water-soil boundary structure three-dimensional member, the joint threshold value of the runoff bearing capacity of the structure is analyzed, and based on this, the comprehensive runoff coefficient of the structure and the preset bearing difference threshold value are combined, and the difference between the comprehensive runoff coefficient of the structure and the joint threshold value of the runoff bearing capacity is used to accurately identify the high-risk structure damaged by runoff, thereby improving the accuracy of the subsequent cost fluctuation analysis process caused by the water-soil boundary reinforcement event.

[0101] In some embodiments, according to the vegetation type attribute of the ecological vegetation three-dimensional member, a preset vegetation growth cost coefficient database is associated; according to the preset vegetation growth cost coefficient database, the vegetation coverage in the same regional grid unit is seasonally corrected to generate a standardized vegetation coverage; if the standardized vegetation coverage is less than the target vegetation coverage by an amount greater than a preset vegetation difference amount, the corresponding regional grid unit is marked as a vegetation coverage inefficient area.

[0102] The vegetation type attribute can be a plant species identification (such as evergreen shrubs) labeled by the ecological vegetation three-dimensional member, which is derived from the vegetation classification label defined in the Revit family parameter during the digital model construction phase.

[0103] The preset vegetation growth cost coefficient database can be a database containing the planting and maintenance cost per unit area of different vegetation types.

[0104] Seasonal correction can be a process of adjusting the vegetation coverage based on phenological period for climate adaptability.

[0105] The standardized vegetation coverage can be an equivalent value of vegetation coverage after eliminating the influence of seasonal differences.

[0106] The preset vegetation difference range can be a maximum threshold value allowing the actual vegetation coverage to deviate from the target value.

[0107] Specifically, the evaluation standard of vegetation coverage cannot be static, but should be dynamically adjusted according to the current season. For example, the natural vegetation coverage of a region fluctuates by 30%-50% between dry season and rainy season. Using a static target value (such as a unified requirement of 85% throughout the year) will lead to misjudgment of some areas as vegetation coverage low-efficiency areas in the dry season, and will cover up the real problems in the rainy season. By making targeted seasonal corrections to the vegetation coverage in different regions, the standardized vegetation coverage is obtained to reflect the real vegetation coverage. When the standardized vegetation coverage is lower than the target vegetation coverage by a range greater than the preset vegetation difference range, it indicates that the vegetation coverage in the corresponding region has been reduced to the extent that requires artificial intervention for reseeding. At this time, the corresponding regional grid unit is marked as a vegetation coverage low-efficiency area.

[0108] Through the scheme, in the process of identifying vegetation coverage low-efficiency areas, the vegetation coverage corresponding to different regions is corrected based on the season to obtain the standardized vegetation coverage to reflect the real vegetation coverage. When the standardized vegetation coverage is lower than the target vegetation coverage by a range greater than the preset vegetation difference range, it indicates that the vegetation coverage in the corresponding region has been reduced to the extent that requires artificial intervention for reseeding. At this time, the corresponding regional grid unit is marked as a vegetation coverage low-efficiency area, improving the evaluation accuracy of vegetation coverage low-efficiency areas and further improving the accuracy of the subsequent cost fluctuation analysis process triggered by vegetation increment reseeding events.

[0109] In some embodiments, the reinforcement engineering quota coefficient corresponding to the soil erosion high-risk area, the material quota coefficient of the water-soil interface structure, and the vegetation reseeding unit price parameter corresponding to the vegetation coverage low-efficiency area are extracted from the preset BIM model component attribute library; the terrain reinforcement area is determined according to the terrain reinforcement event, and the terrain reinforcement cost increment is determined according to the product of the reinforcement engineering quota coefficient and the terrain reinforcement area, and the terrain construction difficulty additional cost is added; the interface reinforcement length is determined according to the water-soil interface reinforcement event, and the structure reinforcement cost increment is determined according to the product of the interface reinforcement length and the material quota coefficient, and the interface construction difficulty additional cost is added; the vegetation reseeding area is determined according to the vegetation increment reseeding event, and the vegetation reseeding cost increment is determined according to the product of the vegetation reseeding area and the vegetation unit price parameter, and the seasonal maintenance cost is added; and the cost correction suggestion is generated according to the terrain reinforcement cost increment, the structure reinforcement cost increment, and the vegetation reseeding cost increment.

[0110] The reinforcement engineering quota coefficient can be the standard construction cost of unit area earthwork reinforcement.

[0111] The material quota coefficient can be the standard construction cost of reinforcing the structure at the water-soil interface per unit length.

[0112] The vegetation replanting unit price parameter may be a standard construction cost for vegetation replanting per unit area.

[0113] The terrain reinforcement area may be the terrain area that needs to be reinforced corresponding to the current terrain reinforcement event.

[0114] The terrain construction difficulty surcharge can be an increase in construction cost based on the terrain slope and accessibility.

[0115] The terrain reinforcement cost increment may be the total cost corresponding to the current terrain reinforcement event.

[0116] The reinforcement length at the junction can be the length of the structure that needs to be reinforced in the current water-soil junction reinforcement event.

[0117] The additional cost of construction difficulty at the junction may be the additional construction cost caused by the complexity of the construction environment at the junction.

[0118] The incremental cost of structure reinforcement can be the total cost corresponding to the current soil-water boundary reinforcement event.

[0119] The vegetation replanting area may be the area requiring vegetation replanting corresponding to the current vegetation incremental replanting event.

[0120] Seasonal maintenance costs can be the increased maintenance costs after vegetation replanting due to seasonal climate factors (such as drought and frost).

[0121] The vegetation replanting cost increment may be the total cost corresponding to the current vegetation incremental replanting event.

[0122] Specifically, the BIM model API is called, the component attribute library is traversed, and the reinforcement engineering quota coefficients in high-risk areas of soil erosion, the material quota coefficients of water-soil interface structures, and the vegetation replanting unit price parameters in low-efficiency vegetation areas are extracted; the terrain reinforcement area and the reinforcement length at the interface are calculated through the spatial analysis module of the BIM model, and the vegetation replanting area is determined based on the Boolean operation of the vegetation three-dimensional components. Combined with the overall analysis of historical construction information, the additional cost of terrain construction difficulty, the additional cost of construction difficulty at the interface and the seasonal maintenance cost are determined. Further, based on the reinforcement engineering quota coefficient, material quota coefficient and vegetation replanting unit price parameters, the terrain reinforcement cost increment, structure reinforcement cost increment and vegetation replanting cost increment are respectively obtained. On this basis, based on the total cost increment, the total cost increment is accumulated on the basis of the basic cost assessment result to generate cost correction suggestions to obtain a comprehensive and accurate dynamic cost assessment result.

[0123] Through this plan, on the basis of the standardized data of the reinforcement project quota coefficient, material quota coefficient and replanting unit price parameters, combined with the static indicators pointed by the terrain reinforcement area, the reinforcement length of the junction and the vegetation replanting area, the dynamic factors pointed by the additional cost of terrain construction difficulty, the additional cost of junction construction difficulty and the seasonal maintenance cost are further considered, and a comprehensive quantitative analysis is carried out to obtain the incremental cost of terrain reinforcement, the incremental cost of structure reinforcement and the incremental cost of vegetation replanting. On this basis, cost correction suggestions are generated to obtain comprehensive and accurate dynamic cost assessment results.

[0124] Figure 3 A structural diagram of a BIM-based water conservancy project evaluation system provided in one embodiment of the present application is shown in FIG. Figure 3 As shown, a BIM-based water conservancy project evaluation system 300 of this embodiment includes: a model building module 301 , a mapping analysis module 302 , a risk analysis module 303 and a report output module 304 .

[0125] The model building module 301 is used to obtain soil and water conservation project information and build a soil and water conservation project digital model based on the soil and water conservation project information; A mapping analysis module 302 is configured to obtain real-time ecological monitoring data and establish a spatial mapping relationship between the real-time ecological monitoring data and the digital model of the soil and water conservation project based on the real-time ecological monitoring data and the digital model of the soil and water conservation project; The risk analysis module 303 is used to analyze the real-time ecological monitoring data and the spatial mapping relationship to determine a set of cost risk triggering events; The report output module 304 is configured to determine cost correction suggestions based on the cost risk triggering event set, and generate and output a dynamic cost assessment report based on the cost correction suggestions.

[0126] Optionally, in the model construction module 301, the digital model of the soil and water conservation project is constructed using a BIM modeling tool, and the digital model of the soil and water conservation project includes three-dimensional components of terrain surfaces, three-dimensional components of water-soil interface structures, and three-dimensional components of ecological vegetation.

[0127] Optionally, in the model building module 301, the real-time ecological monitoring data is collected through a sensor network composed of several Internet of Things sensors of different sensor types deployed in the soil and water conservation project construction area; the sensor types include soil temperature and humidity sensors, runoff monitors and vegetation coverage detectors; the real-time ecological monitoring data includes a sensor index set, a soil erosion index set, a surface runoff coefficient set and a local vegetation coverage set.

[0128] Optionally, the mapping analysis module 302 is specifically configured to: Determining the spatial coordinates of each of the IoT sensors according to the sensor index; According to the terrain area corresponding to the three-dimensional component of the terrain surface, the area where the soil and water conservation project is located is divided into several regional grid units; according to the spatial coordinates and the regional grid units, each soil erosion index in the soil erosion index set is mapped to the three-dimensional component of the terrain surface in the corresponding regional grid unit to determine a terrain-soil mapping relationship set; according to the spatial coordinates and the regional grid units, each surface runoff coefficient in the surface runoff coefficient set is mapped to the three-dimensional component of the water-soil boundary structure in the corresponding regional grid unit to determine a runoff-structure mapping relationship set; according to the spatial coordinates and the regional grid units, each vegetation coverage in the local vegetation coverage set is mapped to the three-dimensional component of the water-soil boundary structure in the corresponding regional grid unit to determine a vegetation-region mapping relationship set; according to the terrain-soil mapping relationship set, the runoff-structure mapping relationship set and the vegetation-region mapping relationship set, the spatial mapping relationship is constructed.

[0129] Optionally, the risk analysis module 303 is specifically configured to: Obtain the design soil erosion threshold of each of the three-dimensional components of the terrain surface, the runoff bearing capacity threshold of each of the three-dimensional components of the water-soil interface structure, and the target vegetation coverage rate of the project area where each of the three-dimensional components of the ecological vegetation is located in the digital model of the soil and water conservation project; analyze the terrain-soil mapping relationship set based on the design soil erosion threshold to identify whether there is a high-risk area for soil erosion; if so, trigger a terrain reinforcement event; analyze the runoff-structure mapping relationship set based on the runoff bearing capacity threshold to identify whether there is a high-risk structure for runoff damage; if so, trigger a water-soil interface reinforcement event; analyze the vegetation-region mapping relationship set based on the target vegetation coverage rate to identify whether there is an inefficient vegetation coverage area; if so, trigger a vegetation incremental replanting event; construct the cost risk triggering event set based on the terrain reinforcement event, the water-soil interface reinforcement event, and the vegetation incremental replanting event.

[0130] Optionally, when analyzing the terrain-soil mapping relationship set according to the designed soil erosion threshold and identifying whether there is a high-risk area for soil erosion, the risk analysis module 303 is specifically configured to: Based on the slope properties of the three-dimensional terrain surface component, the designed soil erosion threshold is adjusted by a terrain correction coefficient to generate a dynamic soil erosion threshold. A linear interpolation algorithm is used to map multiple soil erosion indices within the same regional grid unit to the surface grid vertices of the three-dimensional terrain surface component. If the ratio of the soil erosion index of a surface grid vertex to the dynamic soil erosion threshold is greater than a preset erosion ratio, the corresponding regional grid unit is marked as the high-risk area for soil erosion.

[0131] Optionally, when analyzing the runoff-structure mapping relationship set based on the runoff bearing capacity threshold and identifying whether there are structures with a high risk of runoff damage, the risk analysis module 303 is specifically configured to: According to the topological relationship of the junction of the three-dimensional components of the water-soil interface structure and the runoff bearing capacity threshold, the joint threshold of the runoff bearing capacity at the structure junction is extracted; the weighted average calculation of multiple surface runoff coefficients mapped to the same three-dimensional component of the water-soil interface structure is performed to obtain the comprehensive runoff coefficient of the structure; if the difference between the comprehensive runoff coefficient of the structure and the joint threshold of the runoff bearing capacity exceeds the preset bearing difference threshold, the corresponding three-dimensional component of the water-soil interface structure will be marked as the structure with high risk of runoff damage.

[0132] Optionally, when analyzing the vegetation-region mapping relationship set according to the target vegetation coverage rate to identify whether there is an area with inefficient vegetation coverage, the risk analysis module 303 is specifically configured to: According to the vegetation type attributes of the ecological vegetation three-dimensional component, a preset vegetation growth cost coefficient database is associated; according to the preset vegetation growth cost coefficient database, the vegetation coverage rate within the grid cells in the same area is seasonally corrected to generate a standardized vegetation coverage rate; if the amplitude by which the standardized vegetation coverage rate is lower than the target vegetation coverage rate is greater than the preset vegetation difference amplitude, the corresponding regional grid cell is marked as an inefficient vegetation coverage area.

[0133] Optionally, the report output module 304 is specifically configured to: The reinforcement engineering quota coefficient corresponding to the high-risk area for soil erosion, the material quota coefficient of the water-soil boundary structure, and the vegetation replanting unit price parameter corresponding to the low-efficiency vegetation coverage area are extracted from the preset BIM model component attribute library; according to the terrain reinforcement event, the terrain reinforcement area is determined, and the terrain reinforcement cost increment is determined by multiplying the reinforcement engineering quota coefficient and the terrain reinforcement area, adding the additional cost of terrain construction difficulty; according to the water-soil boundary reinforcement event, the reinforcement length of the junction is determined, and the structure reinforcement cost increment is determined by multiplying the reinforcement length of the junction and the material quota coefficient, adding the additional cost of junction construction difficulty; according to the vegetation increment replanting event, the vegetation replanting area is determined, and the vegetation replanting cost increment is determined by multiplying the vegetation replanting area and the vegetation unit price parameter, adding the seasonal maintenance cost; according to the terrain reinforcement cost increment, the structure reinforcement cost increment, and the vegetation replanting cost increment, the cost correction suggestion is generated.

[0134] The system of this embodiment can be used to execute the method of any of the above embodiments. Its implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A BIM-based water conservancy project evaluation method, characterized in that: include: Acquiring soil and water conservation project information, and constructing a soil and water conservation project digital model based on the soil and water conservation project information; Acquiring real-time ecological monitoring data, and establishing a spatial mapping relationship between the real-time ecological monitoring data and the digital model of the soil and water conservation project based on the real-time ecological monitoring data and the digital model of the soil and water conservation project; Analyzing the real-time ecological monitoring data and the spatial mapping relationship to determine a set of cost risk triggering events; According to the cost risk triggering event set, cost correction suggestions are determined, and according to the cost correction suggestions, a dynamic cost assessment report is generated and output.

2. The method according to claim 1, characterized in that The digital model of the soil and water conservation project is constructed using a BIM modeling tool, and the digital model of the soil and water conservation project includes a three-dimensional component of a terrain surface, a three-dimensional component of a water-soil interface structure, and a three-dimensional component of ecological vegetation.

3. The method according to claim 2, characterized in that The real-time ecological monitoring data is collected through a sensor network composed of several different types of IoT sensors deployed in the soil and water conservation project construction area; The sensor types include soil temperature and humidity sensors, runoff monitors, and vegetation coverage detectors; The real-time ecological monitoring data includes a sensor index set, a soil erosion index set, a surface runoff coefficient set, and a local vegetation coverage rate set.

4. The method according to claim 3, characterized in that The establishing of a spatial mapping relationship between the real-time ecological monitoring data and the soil and water conservation project digital model includes: Determining the spatial coordinates of each of the IoT sensors according to the sensor index; Dividing the area where the soil and water conservation project is located into a number of regional grid units according to the terrain area corresponding to the three-dimensional component of the terrain curved surface; Mapping each soil erosion index in the soil erosion index set to the terrain surface three-dimensional component in the corresponding regional grid unit according to the spatial coordinates and the regional grid unit to determine a terrain-soil mapping relationship set; Mapping each surface runoff coefficient in the surface runoff coefficient set to the three-dimensional component of the water-soil interface structure in the corresponding regional grid unit according to the spatial coordinates and the regional grid unit, and determining a runoff-structure mapping relationship set; Mapping each vegetation coverage rate in the local vegetation coverage rate set to the three-dimensional component of the soil-water boundary structure in the corresponding regional grid cell according to the spatial coordinates and the regional grid cell, and determining a vegetation-region mapping relationship set; The spatial mapping relationship is constructed according to the terrain-soil mapping relationship set, the runoff-structure mapping relationship set, and the vegetation-region mapping relationship set.

5. The method according to claim 4, characterized in that The analyzing the real-time ecological monitoring data and the spatial mapping relationship to determine a set of cost risk triggering events includes: Obtaining a designed soil erosion threshold value for each three-dimensional component of the terrain curved surface, a runoff bearing capacity threshold value for each three-dimensional component of the water-soil interface structure, and a target vegetation coverage rate for the project area where each three-dimensional component of the ecological vegetation is located in the digital model of the soil and water conservation project; Analyzing the terrain-soil mapping relationship set according to the designed soil erosion threshold to identify whether there is a high-risk area for soil erosion, and if so, triggering a terrain reinforcement event; Analyzing the runoff-structure mapping relationship set based on the runoff bearing capacity threshold to identify whether there are structures with high risk of runoff damage, and if so, triggering a soil-water interface reinforcement event; Analyzing the vegetation-region mapping relationship set according to the target vegetation coverage rate to identify whether there are areas with inefficient vegetation coverage, and if so, triggering a vegetation incremental replanting event; The cost risk triggering event set is constructed based on the terrain reinforcement event, the water-soil boundary reinforcement event and the vegetation incremental replanting event.

6. The method according to claim 5, characterized in that Analyzing the terrain-soil mapping relationship set according to the designed soil erosion threshold to identify whether there is a high-risk area for soil erosion includes: Adjusting the designed soil erosion threshold by a terrain correction coefficient according to the slope attribute of the three-dimensional component of the terrain curved surface to generate a dynamic soil erosion threshold; Using linear interpolation algorithm, multiple soil erosion indices in the same regional grid cells are mapped to the surface grid vertices of the three-dimensional component of the terrain surface; If the ratio of the soil erosion index of a surface grid vertex to the dynamic soil erosion threshold is greater than a preset erosion ratio, the corresponding regional grid unit is marked as the soil erosion high-risk area.

7. The method according to claim 5, characterized in that The step of analyzing the runoff-structure mapping relationship set based on the runoff bearing capacity threshold to identify whether there are structures with a high risk of runoff damage includes: Extracting the runoff bearing capacity joint threshold at the structure interface based on the topological relationship at the interface of the three-dimensional components of the water-soil interface structure and the runoff bearing capacity threshold; The weighted average calculation of multiple surface runoff coefficients mapped to the same three-dimensional components of the water-soil interface structure is performed to obtain the comprehensive runoff coefficient of the structure; If the difference between the comprehensive runoff coefficient of the structure and the combined threshold of the runoff bearing capacity exceeds a preset bearing difference threshold, the corresponding three-dimensional component of the water-soil interface structure will be marked as the structure with high risk of runoff damage.

8. The method according to claim 5, characterized in that Analyzing the vegetation-region mapping relationship set according to the target vegetation coverage rate to identify whether there is an area with inefficient vegetation coverage includes: Associating a preset vegetation growth cost coefficient database according to the vegetation type attributes of the three-dimensional ecological vegetation component; Based on the preset vegetation growth cost coefficient database, seasonal correction is performed on the vegetation coverage within the grid cells of the same region to generate a standardized vegetation coverage; If the normalized vegetation coverage is lower than the target vegetation coverage by a greater amount than a preset vegetation difference, the corresponding regional grid unit is marked as an inefficient vegetation coverage area.

9. The method according to claim 5, characterized in that Determining cost correction suggestions based on the cost risk triggering event set includes: Extracting the reinforcement engineering quota coefficient corresponding to the soil erosion high-risk area, the material quota coefficient of the water-soil interface structure, and the vegetation replanting unit price parameter corresponding to the vegetation coverage low-efficiency area from the preset BIM model component attribute library; Determine the terrain reinforcement area according to the terrain reinforcement event, and determine the terrain reinforcement cost increment by multiplying the reinforcement project quota coefficient by the terrain reinforcement area and adding the additional cost of terrain construction difficulty; According to the soil-water interface reinforcement event, the reinforcement length of the interface is determined, and the incremental cost of structure reinforcement is determined by multiplying the reinforcement length of the interface by the material quota coefficient and adding the additional cost of the construction difficulty of the interface; Determine the vegetation replanting area based on the vegetation incremental replanting event, and determine the vegetation replanting cost increment based on the product of the vegetation replanting area and the vegetation unit price parameter and the added seasonal maintenance cost; The cost correction suggestion is generated based on the terrain reinforcement cost increment, the structure reinforcement cost increment and the vegetation replanting cost increment.

10. A BIM-based water conservancy project evaluation system, characterized by: include: A model building module is used to obtain soil and water conservation project information and build a soil and water conservation project digital model based on the soil and water conservation project information; a mapping analysis module for acquiring real-time ecological monitoring data and establishing a spatial mapping relationship between the real-time ecological monitoring data and the digital model of the soil and water conservation project based on the real-time ecological monitoring data and the digital model of the soil and water conservation project; A risk analysis module, configured to analyze the real-time ecological monitoring data and the spatial mapping relationship to determine a set of cost risk triggering events; The report output module is used to determine cost correction suggestions based on the cost risk trigger event set, and generate and output a dynamic cost assessment report based on the cost correction suggestions.

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