Bridge type selection decision-making system based on geological and hydrological coupling model

Abstract

The invention discloses a bridge type selection decision-making system based on a geological and hydrological coupling model, and relates to the technical field of bridge construction.The bridge type selection decision-making system sets a bridge construction area, collects hydrological information data in the bridge construction area, and processes the collected hydrological information data in a data processing mode after collection is completed; after processing is completed, a bridge construction drawing is collected in real time, on-site construction verification is conducted on a bridge ground pile casing based on the processed hydrological information data, and a bridge construction process standard is formulated based on a construction verification result; meanwhile, the current construction condition is collected in real time, a bridge type selection decision is constructed based on the formulated bridge construction process standard, finally, the bridge type selection decision is determined and executed through a data twinborn prediction mode based on the constructed bridge type selection decision, and the reasonability of bridge construction is improved.

Description

Technical Field

[0001] This invention relates to the field of bridge construction technology, specifically to a bridge selection decision system based on a geological-hydrological coupling model. Background Technology

[0002] Hydrological highway bridge engineering faces challenges due to complex terrain and significant variations in geological conditions. Frequent geological disasters such as floods, landslides, fault zones, and steep valleys severely impact bridge structural design and construction. Complex hydrogeological conditions greatly affect the bearing capacity and stability of the foundation, and conventional foundation treatment methods struggle to effectively adjust to different geological conditions, easily leading to uneven settlement, slippage, and embedment failure. Furthermore, due to constraints imposed by terrain, limited construction machinery, operational safety, and environmental protection requirements, there is an urgent need to establish a foundation type selection criterion and construction method support system adapted to complex geological conditions, thereby ensuring long-term service performance and operational safety. Summary of the Invention

[0003] The purpose of this invention is to provide a bridge selection decision system based on a geological-hydrological coupling model, which solves the problems existing in the background technology.

[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The present invention provides a bridge selection decision system based on a geological-hydrological coupling model, specifically including the following steps: S1. Define the bridge construction area and collect hydrological information data within the bridge construction area; S2. The collected hydrological information data is processed through data processing methods to obtain processed hydrological information data; S3. Real-time acquisition of bridge construction drawings and on-site construction verification of bridge pile casings based on processed hydrological information data, and formulation of bridge construction process standards based on the construction verification results. S4. Collect current construction information in real time and make bridge selection decisions based on established bridge construction process standards; S5. Based on the constructed bridge selection decision, determine and execute the bridge selection decision through data twin prediction.

[0005] Preferably, the step of defining the bridge construction area and collecting hydrological information data within the bridge construction area specifically includes the following steps: Construct a three-dimensional coordinate system and divide the designated bridge construction area based on the constructed three-dimensional coordinate system; The center point of the bridge construction area is set as the origin of the three-dimensional coordinate system, and the bridge construction area is divided into units of 1m. Based on the division results, the bridge construction parameters are determined, including the bridge height, width and length. Set the hydrological information data collection cycle within the bridge construction area. ,in, For the first One collection cycle; Based on the hydrological information data collection cycle, hydrological information data is collected within the bridge construction area; The hydrological information data includes: river runoff, river flow, rainfall, and changes in river water level.

[0006] Preferably, the step of processing the collected hydrological information data to obtain processed hydrological information data includes the following steps: The collected hydrological information data is standardized by using data standardization methods to obtain standardized hydrological information data. The data standardization formula is as follows: ; in, This indicates the collected hydrological information data. This represents standardized hydrological information data; This represents the maximum value in hydrological data; This represents the minimum value in hydrological information data; Real-time estimation of infiltration within the bridge construction area based on water balance formula; The estimated infiltration rate within the bridge construction area is defined as: River water level change + Rainfall + River runoff - River flow. The river's runoff volume is measured by hydrological stations on the upstream river. The permeability within the bridge construction area was compared and corrected using the permeability calculation formula; Permeability calculation formula:

[0007] in, This indicates the amount of seepage within the bridge construction area. Z represents the infiltration rate of the j-th river branch within the bridge construction area, and Z represents the number of branches. This represents the permeability coefficient of the water exchange layer in the j-th river branch. This represents the area of ​​the j-th river branch within the bridge construction area; Based on the calculated infiltration amount within the bridge construction area, an error threshold is set. If the difference between the estimated infiltration amount and the calculated infiltration amount within the bridge construction area is within the error range, the estimation process continues; otherwise, the data in the real-time estimation are verified.

[0008] Preferably, the real-time acquisition of bridge construction drawings and on-site construction verification of bridge pile casings based on processed hydrological data, and the formulation of bridge construction process standards based on the construction verification results, includes the following steps: S31. Optimize the protective casing of bridge piles; The bridge pile casing is designed with a three-section design, with flanges and rubber sealing rings used at the joints to improve assembly and disassembly efficiency and sealing performance, and to facilitate rapid splicing and removal of deep sections. Gradient wall thickness + reinforcing rib design: The wall thickness of the casing is optimized to a gradient distribution of 8–12 mm, and a reasonable arrangement of reinforcing ribs is set, which improves the resistance to lateral pressure to ≥250 kPa and effectively prevents local buckling and deformation. S32. Real-time acquisition of bridge construction drawings and on-site construction verification of bridge pile casings based on processed hydrological information data; Based on on-site hydrogeological data, the frequency and speed of the sinking vibration are adjusted in real time to ensure vertical and stable sinking; Improved mud mixing system: Using an optimized formula, the mud viscosity is controlled within the range of 25–30s, which effectively reduces permeability, enhances the wall protection effect, and improves the stability of quicksand layer in the bridge construction area; S33. Summarize the optimization of bridge pile casings and on-site construction verification to formulate bridge construction process standards.

[0009] Preferably, the real-time acquisition of current construction information and the construction of bridge selection decisions based on established bridge construction process standards include the following steps: Real-time data collection of current construction status and bridge selection decisions based on construction period and cost; The beam selection decision model for minimizing construction period is shown below: ; in, This represents the decision model for minimizing the project duration. This indicates the estimated completion time for all procedures in the current construction phase. This represents the estimated completion time of the k-th process. Indicates the number of processes. This indicates that minimizing the construction period will reduce the cost of beam selection decisions. This indicates the fixed daily cost. This represents the material cost under the decision of minimizing the construction period; The bridge selection decision model that minimizes construction costs is shown below:

[0010] in, This represents a production cost minimization decision model. This represents the material cost in a bridge selection decision that minimizes construction costs. Minimize production costs and decision execution costs.

[0011] Preferably, the bridge selection decision based on the constructed bridge selection is determined through data twin prediction and the following steps are performed: S51. Real-time data collection of current construction conditions and construction of the hidden Markov model in conjunction with the bridge selection decision model. ;in A collection space for the bridge construction status. , for The first bridge construction status in the picture. for The total number of operating states of the power generation equipment; For the bridge construction state observation vector space, , for The first observation vector in the middle, for The total number of observed vectors; S52. Based on real-time data collection of current construction conditions, hidden Markov model, and bridge selection decision model, determine and execute bridge selection decisions.

[0012] Preferably, the process of determining and executing bridge selection decisions based on real-time acquisition of current construction conditions, a hidden Markov model, and a bridge selection decision model includes the following steps: S521. Initialize parameters using the Cuckoo algorithm: Each particle is defined as being based on a set of bridge selection decisions, and the population size is set accordingly. S522. Calculate the fitness of each particle: The bridge selection decision is used as the fitness function of the Cuckoo Algorithm, and the fitness of each particle is calculated. The fitness calculation formula is as follows: ; in, Indicates particle fitness. The weights are respectively the execution costs of the construction period minimization decision model, the beam selection decision model for minimizing construction period, the production cost minimization decision model, and the execution cost of the production cost minimization decision model; S523. Set a fitness threshold, and based on the calculated particle fitness and the set fitness threshold, select particles with fitness values ​​greater than the fitness threshold to construct a bridge selection decision set. Based on the current construction situation, the corresponding bridge selection is determined from the constructed bridge selection decision set; The completion rate of the current construction is calculated based on the selection of each bridge type, and the corresponding bridge type is determined and implemented based on the calculated completion rate. The completion rate of the current construction is the ratio of the current construction area to the estimated area in the corresponding bridge construction drawings.

[0013] The present invention also provides a bridge selection decision system based on a geological-hydrological coupling model, comprising: a data acquisition module, a data processing module, a construction verification module, a bridge selection decision module, and a construction execution module; The data acquisition module is used to collect hydrological information data within the bridge construction area; The data processing module is used to process the collected hydrological information data to obtain processed hydrological information data. The construction verification module is used to collect bridge construction drawings in real time and conduct on-site construction verification of bridge pile casings based on processed hydrological information data. The bridge selection decision module is used to construct bridge selection decisions based on the established bridge construction process standards. The construction execution module is used to determine and execute bridge selection decisions through data twin prediction.

[0014] The beneficial effects of this invention are as follows: (1) This invention sets up a bridge construction area and collects hydrological information data within the bridge construction area. After the data collection is completed, the collected hydrological information data is processed through data processing. After processing, the bridge construction drawings are collected in real time, and the bridge pile casing is verified on-site based on the processed hydrological information data. The bridge construction process standard is formulated based on the construction verification results. At the same time, the current construction situation is collected in real time, and the bridge selection decision is constructed based on the formulated bridge construction process standard. Finally, based on the constructed bridge selection decision, the bridge selection decision is determined and executed through data twin prediction, thereby improving the rationality of bridge construction.

[0015] (2) This invention combines “numerical analysis + field test + structural design + process optimization” to comprehensively consider hydrogeology, structural stress and construction technology, forming a theoretical and practical closed loop to ensure the accuracy of bridge selection decision.

[0016] (3) The present invention constructs the hidden Markov model by collecting the current construction situation in real time and combining it with the bridge selection decision model. After the construction is completed, the bridge selection decision is determined and executed based on the real-time collection of the current construction situation, the hidden Markov model and the bridge selection decision model, thus ensuring the real-time nature of the bridge selection decision. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the bridge selection decision system based on the geological-hydrological coupling model of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] In a specific embodiment of the present invention, Reference Figure 1 As shown, this invention provides a bridge selection decision system based on a geological-hydrological coupling model, comprising the following steps: S1. Define the bridge construction area and collect hydrological information data within the bridge construction area; S2. The collected hydrological information data is processed through data processing methods to obtain processed hydrological information data; S3. Real-time acquisition of bridge construction drawings and on-site construction verification of bridge pile casings based on processed hydrological information data, and formulation of bridge construction process standards based on the construction verification results. S4. Collect current construction information in real time and make bridge selection decisions based on established bridge construction process standards; S5. Based on the constructed bridge selection decision, determine and execute the bridge selection decision through data twin prediction. Furthermore, referring to Figure 1 As shown, the specific steps for defining the bridge construction area and collecting hydrological information data within the bridge construction area include: Construct a three-dimensional coordinate system and divide the designated bridge construction area based on the constructed three-dimensional coordinate system; The center point of the bridge construction area is set as the origin of the three-dimensional coordinate system, and the bridge construction area is divided into units of 1m. Based on the division results, the bridge construction parameters are determined, including the bridge height, width and length. Furthermore, the data collection cycle for hydrological information within the bridge construction area is set. ,in, For the first One collection cycle; Furthermore, based on the hydrological information data collection cycle, hydrological information data is collected within the bridge construction area; The hydrological information data includes: river runoff, river flow, rainfall, and changes in river water level; Furthermore, referring to Figure 1 As shown, the collected hydrological information data is processed using data processing methods to obtain the processed hydrological information data, including the following steps: The collected hydrological information data is standardized by using data standardization methods to obtain standardized hydrological information data. The data standardization formula is as follows: The data standardization formula is as follows: ; in, This indicates the collected hydrological information data. This represents standardized hydrological information data; This represents the maximum value in hydrological data; This represents the minimum value in hydrological information data; Furthermore, the infiltration rate within the bridge construction area is estimated in real time based on the water balance formula; The estimated infiltration rate within the bridge construction area is defined as: River water level change + Rainfall + River runoff - River flow. The river's runoff volume is measured by hydrological stations on the upstream river. Furthermore, the permeability within the bridge construction area was compared and corrected using the permeability calculation formula; Permeability calculation formula:

[0021] in, This indicates the amount of seepage within the bridge construction area. Z represents the infiltration rate of the j-th river branch within the bridge construction area, and Z represents the number of branches. This represents the permeability coefficient of the water exchange layer in the j-th river branch. This represents the area of ​​the j-th river branch within the bridge construction area; Based on the calculated seepage amount within the bridge construction area, an error threshold is set. If the difference between the estimated seepage amount and the calculated seepage amount within the bridge construction area is within the error range, the estimation process continues; otherwise, the data in the real-time estimation are verified. Furthermore, referring to Figure 1As shown, the process of real-time acquisition of bridge construction drawings and on-site verification of bridge pile casing construction based on processed hydrological data, followed by the formulation of bridge construction process standards based on the verification results, includes the following steps: S31. Optimize the protective casing of bridge piles; The bridge pile casing is designed in a three-section manner (3m each), with flanges and rubber sealing rings used at the joints to improve assembly and disassembly efficiency and sealing performance, and to facilitate rapid splicing and removal of deep sections. Furthermore, the gradient wall thickness + reinforcing rib design: the wall thickness of the casing is optimized to a gradient distribution of 8–12 mm, and a reasonable arrangement of reinforcing ribs is set, which improves the lateral pressure resistance to ≥250 kPa and effectively prevents local buckling and deformation. S32. Real-time acquisition of bridge construction drawings and on-site construction verification of bridge pile casings based on processed hydrological information data; Based on on-site hydrogeological data, the sinking vibration frequency (20–35Hz) and speed (0.5–1.0m / min) are adjusted in real time to ensure vertical and stable sinking; Furthermore, the mud mixing system was improved: an optimized formula (bentonite: CMC: soda ash = 100:1.5:4) was used to control the mud viscosity within the range of 25–30s, effectively reducing permeability, enhancing the wall protection effect, and improving the stability of the quicksand layer in the bridge construction area. S33. Summarize the optimization of bridge ground pile casings and on-site construction verification to formulate bridge construction process standards; Furthermore, referring to Figure 1 As shown, the process of collecting real-time data on the current construction status and making bridge selection decisions based on established bridge construction process standards includes the following steps: Real-time data collection of current construction status and bridge selection decisions based on construction period and cost; The beam selection decision model for minimizing construction period is shown below: ; in, This represents the decision model for minimizing the project duration. This indicates the estimated completion time for all procedures in the current construction phase. This represents the estimated completion time of the k-th process. Indicates the number of processes. This indicates that minimizing the construction period will reduce the cost of beam selection decisions. This indicates the fixed daily cost. This represents the material cost under the decision of minimizing the construction period; The bridge selection decision model that minimizes construction costs is shown below:

[0022] in, This represents a production cost minimization decision model. This represents the material cost in a bridge selection decision that minimizes construction costs. Minimize production costs and decision execution costs; Furthermore, referring to Figure 1 As shown, based on the constructed bridge selection decision, the bridge selection decision is determined through data twin prediction and the following steps are executed: S51. Real-time data collection of current construction conditions and construction of the hidden Markov model in conjunction with the bridge selection decision model. ;in A collection space for the bridge construction status. , for The first bridge construction status in the picture. for The total number of operating states of the power generation equipment; For the bridge construction state observation vector space, , for The first observation vector in the middle, for The total number of observed vectors; S52. Based on real-time data collection of current construction conditions, hidden Markov model, and bridge selection decision model, determine and execute bridge selection decisions; S521. Initialize parameters using the Cuckoo algorithm: Each particle is defined as being based on a set of bridge selection decisions, and the population size is set accordingly. S522. Calculate the fitness of each particle: The bridge selection decision is used as the fitness function of the Cuckoo Algorithm, and the fitness of each particle is calculated. The fitness calculation formula is as follows: ; in, Indicates particle fitness. The weights are respectively the execution costs of the construction period minimization decision model, the beam selection decision model for minimizing construction period, the production cost minimization decision model, and the execution cost of the production cost minimization decision model; S523. Set a fitness threshold, and based on the calculated particle fitness and the set fitness threshold, select particles with fitness values ​​greater than the fitness threshold to construct a bridge selection decision set. Furthermore, based on the current construction situation, the corresponding bridge selection is determined from the constructed bridge selection decision set; The completion rate of the current construction is calculated based on the selection of each bridge type, and the corresponding bridge type is determined and implemented based on the calculated completion rate. The completion rate of the current construction is the ratio of the current construction area to the estimated area in the corresponding bridge construction drawings; In one specific embodiment, the bridge selection decision system of the geological-hydrological coupling model further includes: a data acquisition module, a data processing module, a construction verification module, a bridge selection decision module, and a construction execution module; The data acquisition module is used to collect hydrological information data within the bridge construction area; The data processing module is used to process the collected hydrological information data to obtain processed hydrological information data. The construction verification module is used to collect bridge construction drawings in real time and conduct on-site construction verification of bridge pile casings based on processed hydrological information data. The bridge selection decision module is used to construct bridge selection decisions based on the established bridge construction process standards. The construction execution module is used to determine and execute bridge selection decisions through data twin prediction.

[0023] It should be noted that, The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A bridge selection decision system based on a geological-hydrological coupled model, characterized in that, Includes the following steps: S1. Define the bridge construction area and collect hydrological information data within the bridge construction area; S2. The collected hydrological information data is processed through data processing methods to obtain processed hydrological information data; S3. Real-time acquisition of bridge construction drawings and on-site construction verification of bridge pile casings based on processed hydrological information data, and formulation of bridge construction process standards based on the construction verification results. S4. Collect current construction information in real time and make bridge selection decisions based on established bridge construction process standards; S5. Based on the constructed bridge selection decision, determine and execute the bridge selection decision through data twin prediction.

2. The bridge selection decision system based on a geological-hydrological coupling model according to claim 1, characterized in that, The process of defining the bridge construction area and collecting hydrological information data within that area specifically includes the following steps: Construct a three-dimensional coordinate system and divide the designated bridge construction area based on the constructed three-dimensional coordinate system; The center point of the bridge construction area is set as the origin of the three-dimensional coordinate system, and the bridge construction area is divided into units of 1m. Based on the division results, the bridge construction parameters are determined, including the bridge height, width and length. Set the hydrological information data collection cycle within the bridge construction area. ,in, For the first One collection cycle; Based on the hydrological information data collection cycle, hydrological information data is collected within the bridge construction area; The hydrological information data includes: river runoff, river flow, rainfall, and changes in river water level.

3. The bridge selection decision system based on a geological-hydrological coupling model according to claim 1, characterized in that, The process of processing the collected hydrological information data to obtain the processed hydrological information data includes the following steps: The collected hydrological information data is standardized by using data standardization methods to obtain standardized hydrological information data. The data standardization formula is as follows: The data standardization formula is as follows: ； in, This indicates the collected hydrological information data. This represents standardized hydrological information data; This represents the maximum value in hydrological data; This represents the minimum value in hydrological information data; Real-time estimation of infiltration within the bridge construction area based on water balance formula; The estimated infiltration rate within the bridge construction area is defined as: River water level change + Rainfall + River runoff - River flow. The river's runoff volume is measured by hydrological stations on the upstream river. The permeability within the bridge construction area was compared and corrected using the permeability calculation formula; Permeability calculation formula: ； in, This indicates the amount of seepage within the bridge construction area. Z represents the infiltration rate of the j-th river branch within the bridge construction area, and Z represents the number of branches. This represents the permeability coefficient of the water exchange layer in the j-th river branch. This represents the area of ​​the j-th river branch within the bridge construction area; Based on the calculated infiltration amount within the bridge construction area, an error threshold is set. If the difference between the estimated infiltration amount and the calculated infiltration amount within the bridge construction area is within the error range, the estimation process continues; otherwise, the data in the real-time estimation are verified.

4. The bridge selection decision system based on a geological-hydrological coupling model according to claim 1, characterized in that, The process of real-time acquisition of bridge construction drawings and on-site construction verification of bridge pile casings based on processed hydrological data, followed by the formulation of bridge construction process standards based on the verification results, includes the following steps: S31. Optimize the protective casing of bridge piles; The bridge pile casing is designed with a three-section design, with flanges and rubber sealing rings used at the joints to improve assembly and disassembly efficiency and sealing performance, and to facilitate rapid splicing and removal of deep sections. Gradient wall thickness + reinforcing rib design: The wall thickness of the casing is optimized to a gradient distribution of 8–12 mm, and a reasonable arrangement of reinforcing ribs is set, which improves the resistance to lateral pressure to ≥250 kPa and effectively prevents local buckling and deformation. S32. Real-time acquisition of bridge construction drawings and on-site construction verification of bridge pile casings based on processed hydrological information data; Based on on-site hydrogeological data, the frequency and speed of the sinking vibration are adjusted in real time to ensure vertical and stable sinking; Improved mud mixing system: Using an optimized formula, the mud viscosity is controlled within the range of 25–30s, which effectively reduces permeability, enhances the wall protection effect, and improves the stability of quicksand layer in the bridge construction area; S33. Summarize the optimization of bridge pile casings and on-site construction verification to formulate bridge construction process standards.

5. The bridge selection decision system based on a geological-hydrological coupling model according to claim 1, characterized in that, The process of collecting real-time data on the current construction status and making bridge selection decisions based on established bridge construction process standards includes the following steps: Real-time data collection of current construction status and bridge selection decisions based on construction period and cost; The beam selection decision model for minimizing construction period is shown below: ； in, This represents the decision model for minimizing the project duration. This indicates the estimated completion time for all procedures in the current construction phase. This represents the estimated completion time of the k-th process. Indicates the number of processes. This indicates that minimizing the construction period will reduce the cost of beam selection decisions. This indicates the fixed daily cost. This represents the material cost under the decision of minimizing the construction period; The bridge selection decision model that minimizes construction costs is shown below: ； in, This represents a production cost minimization decision model. This represents the material cost in a bridge selection decision that minimizes construction costs. Minimize production costs and decision execution costs.

6. The bridge selection decision system based on a geological-hydrological coupling model according to claim 1, characterized in that, The bridge selection decision based on the constructed model is determined and executed through data twin prediction. Includes the following steps: S51. Real-time data collection of current construction conditions and construction of the hidden Markov model in conjunction with the bridge selection decision model. ;in A collection space for the construction status of the bridge. , for The first bridge construction status in the picture. for The total number of operating states of the power generation equipment; For the bridge construction state observation vector space, , for The first observation vector in the middle, for The total number of observed vectors; S52. Based on real-time data collection of current construction conditions, hidden Markov model, and bridge selection decision model, determine and execute bridge selection decisions.

7. The bridge selection decision system based on a geological-hydrological coupling model according to claim 6, characterized in that, The process of determining and executing bridge selection decisions based on real-time data collection of current construction conditions, hidden Markov models, and bridge selection decision models includes the following steps: S521. Initialize parameters using the Cuckoo algorithm: Each particle is defined as being based on a set of bridge selection decisions, and the population size is set accordingly. S522. Calculate the fitness of each particle: The bridge selection decision is used as the fitness function of the Cuckoo Algorithm, and the fitness of each particle is calculated. The fitness calculation formula is as follows: ； in, Indicates particle fitness. The weights are respectively the execution costs of the construction period minimization decision model, the beam selection decision model for minimizing construction period, the production cost minimization decision model, and the execution cost of the production cost minimization decision model; S523. Set a fitness threshold, and based on the calculated particle fitness and the set fitness threshold, select particles with fitness values ​​greater than the fitness threshold to construct a bridge selection decision set. Based on the current construction situation, the corresponding bridge selection is determined from the constructed bridge selection decision set; The completion rate of the current construction is calculated based on the selection of each bridge type, and the corresponding bridge type is determined and implemented based on the calculated completion rate. The completion rate of the current construction is the ratio of the current construction area to the estimated area in the corresponding bridge construction drawings.

8. The bridge selection decision system based on a geological-hydrological coupling model according to claim 1, characterized in that, include: The system includes a data acquisition module, a data processing module, a construction verification module, a bridge selection decision module, and a construction execution module. The data acquisition module is used to collect hydrological information data within the bridge construction area; The data processing module is used to process the collected hydrological information data to obtain processed hydrological information data. The construction verification module is used to collect bridge construction drawings in real time and conduct on-site construction verification of bridge pile casings based on processed hydrological information data. The bridge selection decision module is used to construct bridge selection decisions based on the established bridge construction process standards. The construction execution module is used to determine and execute bridge selection decisions through data twin prediction.

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