A channel silt distribution active detection and identification method combined with GIS channel information

Abstract

The present application relates to the technical field of channel exploration and hydrodynamic sediment simulation, and particularly relates to a channel silt distribution active detection and identification method combined with GIS channel information, comprising: constructing a GIS three-dimensional hydrodynamic sediment coupling model; obtaining boundary and initial conditions; introducing a salinity and suspended sediment joint stratification effect correction function to calculate the corrected eddy viscosity coefficient; using a multi-component suspended sediment motion control equation to dynamically simulate and inverse, obtaining the silt accumulation spatio-temporal distribution data; superimposing the accumulation amount data and the GIS channel base map to generate a silt distribution heat map. The present application realizes active detection, dynamic inversion and visual warning of channel silt distribution, can effectively identify the accumulation risk under normal and typhoon conditions, and provides scientific support for channel maintenance and navigation scheduling.

Description

Technical Field

[0001] This invention relates to the field of waterway detection and hydrodynamic sediment simulation technology, and in particular to an active detection and identification method for waterway silt distribution that combines GIS waterway information. Background Technology

[0002] Siltation in waterways is a key factor affecting navigation safety and waterway maintenance efficiency, especially in estuarine areas with high sediment content, such as the North Channel of the Yangtze River Estuary. Due to the combined effects of runoff, tides, saline-freshwater mixing, and extreme weather events like typhoons, the distribution of silt within the channel exhibits significant spatiotemporal heterogeneity. Traditional methods for detecting silt in waterways primarily rely on single-beam or multi-beam echo sounders for cross-sectional measurements, combined with fixed-point bottom sediment sampling, to obtain information on water depth and seabed changes. However, these methods have the following shortcomings: 1. Passive detection methods and poor timeliness: Traditional measurement relies on shipborne equipment for regular inspections, which results in long data collection cycles and makes it difficult to achieve real-time or near-real-time monitoring of silt distribution. It also fails to reflect the rapid siltation changes in the waterway after strong dynamic events (such as typhoons and floods). 2. Limited spatial coverage makes it difficult to obtain continuous distribution: The spacing between measurement sections is limited, and the silt distribution map obtained by interpolation has a large degree of uncertainty, making it difficult to accurately depict the continuous spatial distribution characteristics of silt in the waterway (especially near the deep channel and guide breakwater). 3. Lack of proactive inversion capability for physical processes: Traditional methods can only obtain the "already occurred" sedimentation results and cannot proactively predict or invert the sediment transport and sedimentation process under complex hydrodynamic-sediment coupling. In particular, they ignore the inhibition mechanism of the combined salinity and suspended sediment stratification effect on the near-bottom turbulent structure, resulting in insufficient simulation capability for the sediment settling-scouring-floating mud generation process under high sediment content water conditions.

[0003] Therefore, we propose an active detection and identification method for channel silt distribution that combines GIS channel information to solve the above problems. Summary of the Invention

[0004] The purpose of this invention is to provide an active detection and identification method for waterway silt distribution that combines GIS waterway information. This method solves the problems in the prior art where waterway silt detection relies on manual fixed-point measurement, has poor timeliness, cannot reflect the continuous spatiotemporal distribution of silt, and is difficult to accurately simulate the inhibition of turbulence and silt transport and return to the channel by near-bottom high-sediment-laden water bodies under the combined effects of salinity and suspended sediment.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A method for actively detecting and identifying channel silt distribution using GIS channel information includes the following steps: S1. Constructing a GIS digital waterway environment: Based on the topography and engineering layout map of the North Channel of the Yangtze River Estuary, a GIS three-dimensional hydrodynamic-sediment coupling model containing unstructured triangular meshes is established. S2. Obtaining Boundaries and Initial Conditions: Collect tidal data of the open sea boundary, upstream flow boundary data, and on-site water sediment content data, and input them into the GIS model as model-driven data; S3. Coupled stratification effect correction: A combined stratification effect correction function of salinity and suspended sediment is introduced into the model to simulate the inhibitory effect of high concentration of sediment near the bottom layer on water turbulence, and the eddy viscosity coefficient considering the influence of density gradient is calculated. S4. Dynamic simulation and inversion: Using the multi-component suspended sediment motion control equations and the modified eddy viscosity coefficient, the convection, diffusion and sedimentation processes of suspended sediment are simulated, and the spatiotemporal distribution data of sediment deposition in the waterway are obtained through inversion. S5. Visualization Output: The calculated siltation data is overlaid with the GIS waterway base map to generate a heat map of waterway silt distribution, enabling proactive identification and early warning of siltation thickness.

[0006] The GIS three-dimensional hydrodynamic-sediment coupling model constructed in step S1 is based on the FVCOM model, and its hydrodynamic control equations adopt the three-dimensional primitive control equations in the Cartesian coordinate system. The continuity equation is: ; The vertical direction uses σ-coordinate transformation, and the transformation formula is: ; Where u and v are the horizontal velocity components, and w is the vertical velocity. Vertical coordinates For the height of the free surface, The total water depth.

[0007] The joint stratification effect correction function in step S3 is specifically as follows: A dimensionless stratification parameter R is introduced to uniformly describe the inhibitory effects of salinity stratification and sediment stratification on turbulence. The calculation formula is as follows: ; Where g is the acceleration due to gravity, ρ is the water density considering the effects of salinity and suspended sediment concentration, q is the turbulence intensity, and l is the turbulence scale; based on parameter R, the eddy viscosity coefficient v t The correction is made, and the correction formula is: ; The modified eddy viscosity coefficient is used to reflect the constraint of near-bottom high sediment content water body on water flow turbulence.

[0008] The calculation of the water density ρ needs to consider the combined effect of salinity and suspended sediment. The calculation formula is as follows: ; Where S is the water salinity, C is the sediment concentration, and ρ is the water concentration. s This represents the density of sediment particles; the calculated density is used to determine the density gradient term in the stratification parameter R.

[0009] The governing equation for the multi-component suspended sediment movement in step S4 is: ; in, For the first Component suspended sediment concentration, v ’ t w is the eddy viscosity coefficient after stratification correction. s The equation represents the sediment settling velocity and is used to simulate the transport and settling process of sediments with different particle sizes in the waterway.

[0010] The sediment settling velocity The calculation formula is: ; in For single-particle sediment settling velocity in still water, To incorporate the correction function for both the flocculation and settling stages and the constrained settling stages, this function comprehensively considers the sediment concentration. ,salinity turbulent dissipation rate Including the effect of temperature, it is used to accurately calculate the settling velocity of cohesive fine-grained sediment in estuaries.

[0011] Step S4 also includes setting the bottom boundary conditions: Set the sediment erosion rate at the bottom boundary. With siltation rate The dynamic equilibrium equation; When the bed shear stress is greater than the critical scouring stress, calculate the scouring rate: ; in, Let i be the bed scour intensity of the i-th component of sediment. It is the porosity of the bed surface sediment. The proportion of the i-th component (sediment) is given by this value. It is the shear stress on the bed surface. It is the critical scour stress of the i-th component of sediment; When the bed shear stress is less than the critical accumulation stress, calculate the accumulation rate: ; This boundary condition was used to simulate the physical mechanism of the formation and disappearance of floating silt at the bottom of the waterway. The silt distribution heat map generated in step S5 includes normal siltation distribution and abnormal siltation distribution. The abnormal siltation distribution is simulated by inputting meteorological and hydrological data under typhoon weather to identify the spatiotemporal distribution range and thickness of floating silt in the waterway during typhoons, thereby determining the "window period" for ship navigation.

[0012] This invention has at least the following beneficial effects: This invention constructs a GIS-based three-dimensional hydrodynamic-sediment coupling model, combining multi-component suspended sediment movement control equations and bottom scouring and deposition boundary conditions to achieve dynamic simulation and inversion of channel silt distribution, replacing the traditional passive inspection method relying on shipborne depth sounding. This method can reflect the continuous spatial distribution and evolution of silt in the channel in real time or near real time, significantly improving the timeliness and spatial coverage of silt monitoring.

[0013] The present invention also has the following beneficial effects: This invention introduces a correction function for the combined stratification effect of salinity and suspended sediment in the calculation of eddy viscosity coefficient. By quantifying the inhibitory effect of density gradient on turbulence through dimensionless stratification parameters, the corrected eddy viscosity coefficient can more accurately simulate the restraining effect of high-concentration sediment near the bottom layer on water turbulence, thereby improving the simulation accuracy of sediment deposition, scouring and floating mud formation processes under high sediment content water conditions (such as estuaries).

[0014] The present invention also has the following beneficial effects This invention overlays simulated siltation data with a GIS waterway base map to generate a siltation distribution heat map, supporting the spatial distribution identification of normal siltation. Simultaneously, by inputting meteorological and hydrological data under typhoon weather, it simulates the spatiotemporal distribution range and thickness changes of floating mud during typhoons, providing waterway management departments with a scientific basis for the "window period" of ship navigation, effectively supporting waterway maintenance and navigation scheduling decisions. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of the present invention; Figure 2 This invention demonstrates the physical setup for a combined salinity and suspended sediment stratification experiment; Figure 3 This is a table showing the relationship between the stratification parameter R and the turbulence suppression rate Sq in this invention; Figure 4 This is a table showing the relationship between the stratification parameter R and the eddy viscosity coefficient of this invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0018] ; Table 1 Example 1: Construction of a GIS hydrodynamic model based on the joint stratification effect refer to Figure 1-4 Referring to Table 1, this embodiment mainly explains how to construct a GIS three-dimensional hydrodynamic-sediment coupling model that includes corrections for salinity and suspended sediment stratification effects. This is the basis for realizing active detection of sediment distribution.

[0019] S1. Constructing a GIS-based digital waterway environment: The North Channel of the Yangtze River Estuary was selected as the research object. Based on the topographic map and engineering layout map of the area, an unstructured triangular mesh was established in the GIS platform. The mesh was locally densified near the deep-water channel and guide breakwater to adapt to complex boundary conditions. A GIS three-dimensional hydrodynamic-sediment coupling model was established based on the FVCOM model. Its hydrodynamic control equations adopted the three-dimensional primitive control equations in the Cartesian coordinate system, where the continuity equation is: ; The vertical direction uses σ-coordinate transformation, and the transformation formula is: ; in, , The horizontal velocity component is... Vertical velocity, Vertical coordinates For the height of the free surface, The total water depth.

[0020] S2, Coupling Layering Effect Correction: To simulate the inhibitory effect of high-concentration sediment near the bottom layer on water turbulence, a dimensionless stratification parameter R is introduced. First, the water density ρ, considering the effects of salinity and suspended sediment concentration, is calculated. Then, the stratification parameter is calculated: ; Where g is the gravitational acceleration, ρ is the water density considering the effects of salinity and suspended sediment concentration, q is the turbulence intensity, and l is the turbulence scale; Based on parameter R, the eddy viscosity coefficient v t The correction is made, and the correction formula is: ; The modified eddy viscosity coefficient is used to reflect the constraint of near-bottom high sediment content water body on water flow turbulence.

[0021] Example 2: Dynamic Simulation of Multi-Component Suspended Sand Movement and Bottom Boundary Based on Example 1, this embodiment focuses on explaining the transport and diffusion process of multi-component suspended sediment and the dynamic balance calculation of bottom scouring and sedimentation.

[0022] S1. Multi-component suspended sediment motion simulation: Using the multi-component suspended sediment motion control equation, combined with the modified eddy viscosity coefficient v' from Example 1 t This simulates the convection, diffusion, and sedimentation processes of suspended sediment. The equations are as follows: ; in, For the first Component suspended sediment concentration The eddy viscosity coefficient is the stratified correction coefficient. This refers to the sediment settling velocity.

[0023] S2, Correction for sediment settling velocity: In estuary areas, sediment settling velocity is significantly affected by flocculation and other limiting effects. Calculation of sediment settling velocity... When this is the case, the correction formula is used: ; in For single-particle sediment settling velocity in still water, To incorporate the correction function for both the flocculation and settling stages and the constrained settling stages, this function comprehensively considers the sediment concentration. ,salinity turbulent dissipation rate Including the effect of temperature, it is used to accurately calculate the settling velocity of cohesive fine-grained sediment in estuaries.

[0024] S3, Bottom Boundary Condition Setting: Set the sediment erosion rate at the bottom boundary. With siltation rate The dynamic equilibrium equations are: ; in, Let i be the bed scour intensity of the i-th component of sediment. It is the porosity of the bed surface sediment. The proportion of the i-th component (sediment) is given by this value. It is the shear stress on the bed surface. It is the critical scour stress of the i-th component of sediment; When the bed shear stress is less than the critical accumulation stress, calculate the accumulation rate: ; By simulating the physical mechanism of the formation and disappearance of floating mud at the bottom of the waterway using this boundary condition, the spatiotemporal distribution data of sediment deposition in the waterway can be obtained through inversion.

[0025] Example 3: Visualized Early Warning of Silt Distribution under Normal and Abnormal Conditions This embodiment demonstrates the application of the present invention in actual navigation management, including routine siltation analysis and emergency early warning during typhoon weather.

[0026] S1. Identification of normal siltation distribution: The spatiotemporal distribution data of sediment deposition in the waterway calculated in Example 2 were input into the GIS system. The calculated sediment deposition data was spatially overlaid with the GIS waterway base map to generate a heat map of waterway sediment distribution. Different colors in the heat map represent different sediment deposition thicknesses, allowing managers to visually identify high-risk areas of sediment deposition in the waterway and achieve proactive identification and early warning of sediment deposition thickness.

[0027] S2. Simulation of Abnormal Siltation Distribution (Typhoon Window): This simulation is designed for extreme weather conditions. Meteorological and hydrological data (such as typhoon flooding and high-wind-wave flow field data) under typhoon conditions are input for simulation. The model of this invention is used to identify the spatiotemporal distribution range and thickness variations of floating silt in the waterway during typhoons.

[0028] Simulations revealed that during typhoons, the churning action of wind and waves thickens and expands the bottom silt layer, causing a sudden decrease in channel depth. Based on the simulation results, the timeframes for channel depth to recover to safe navigation standards before and after a typhoon were calculated, thus determining the "window period" for ship passage and providing a scientific basis for maritime authorities to formulate navigation scheduling plans.

[0029] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A method for actively detecting and identifying the distribution of silt in waterways by combining GIS waterway information, characterized in that, Includes the following steps: S1. Constructing a GIS digital waterway environment: Based on the topography and engineering layout map of the North Channel of the Yangtze River Estuary, a GIS three-dimensional hydrodynamic-sediment coupling model containing unstructured triangular meshes is established. S2. Obtaining Boundaries and Initial Conditions: Collect tidal data of the open sea boundary, upstream flow boundary data, and on-site water sediment content data, and input them into the GIS model as model-driven data; S3. Coupled stratification effect correction: A combined stratification effect correction function of salinity and suspended sediment is introduced into the model to simulate the inhibitory effect of high concentration of sediment near the bottom layer on water turbulence, and the eddy viscosity coefficient considering the influence of density gradient is calculated. S4. Dynamic simulation and inversion: Using the multi-component suspended sediment motion control equations and the modified eddy viscosity coefficient, the convection, diffusion and sedimentation processes of suspended sediment are simulated, and the spatiotemporal distribution data of sediment deposition in the waterway are obtained through inversion. S5. Visualization Output: The calculated siltation data is overlaid with the GIS waterway base map to generate a heat map of waterway silt distribution, enabling proactive identification and early warning of siltation thickness.

2. The method for active detection and identification of channel silt distribution combining GIS channel information according to claim 1, characterized in that, The GIS three-dimensional hydrodynamic-sediment coupling model constructed in step S1 is based on the FVCOM model, and its hydrodynamic control equations adopt the three-dimensional primitive control equations in the Cartesian coordinate system. The continuity equation is: ； The vertical direction uses σ-coordinate transformation, and the transformation formula is: ； Where u and v are the horizontal velocity components, and w is the vertical velocity. Vertical coordinates For the height of the free surface, The total water depth.

3. The method for active detection and identification of channel silt distribution combining GIS channel information according to claim 1, characterized in that, The joint stratification effect correction function in step S3 is specifically as follows: A dimensionless stratification parameter R is introduced to uniformly describe the inhibitory effects of salinity stratification and sediment stratification on turbulence. The calculation formula is as follows: ； Where g is the acceleration due to gravity, ρ is the water density considering the effects of salinity and suspended sediment concentration, q is the turbulence intensity, and l is the turbulence scale; based on parameter R, the eddy viscosity coefficient v t The correction is made, and the correction formula is: ； The modified eddy viscosity coefficient is used to reflect the constraint of near-bottom high sediment content water body on water flow turbulence.

4. The method for active detection and identification of channel silt distribution combining GIS channel information according to claim 3, characterized in that, The calculation of the water density ρ needs to consider the combined effect of salinity and suspended sediment. The calculation formula is as follows: ； Where S is the water salinity, C is the sediment concentration, and ρ is the water concentration. s This represents the density of sediment particles; the calculated density is used to determine the density gradient term in the stratification parameter R.

5. The method for active detection and identification of channel silt distribution combining GIS channel information according to claim 1, characterized in that, The governing equation for the multi-component suspended sediment movement in step S4 is: ； in, For the first Component suspended sediment concentration, v ’ t w is the eddy viscosity coefficient after stratification correction. s The equation represents the sediment settling velocity and is used to simulate the transport and settling process of sediments with different particle sizes in the waterway.

6. The method for active detection and identification of channel silt distribution combining GIS channel information according to claim 5, characterized in that, The sediment settling velocity The calculation formula is: ； in For single-particle sediment settling velocity in still water, To incorporate the correction function for both the flocculation and settling stages and the constrained settling stages, this function comprehensively considers the sediment concentration. ,salinity Turbulent dissipation rate of water flow Including the effect of temperature, it is used to accurately calculate the settling velocity of cohesive fine-grained sediment in estuaries.

7. The method for active detection and identification of channel silt distribution combining GIS channel information according to claim 1, characterized in that, Step S4 also includes setting the bottom boundary conditions: Set the sediment erosion rate at the bottom boundary. With siltation rate The dynamic equilibrium equation; When the bed shear stress is greater than the critical scouring stress, calculate the scouring rate: ； in, Let i be the bed scour intensity of the i-th component of sediment. It is the porosity of the bed surface sediment. The proportion of the i-th component (sediment) is given by this value. It is the shear stress on the bed surface. It is the critical scour stress of the i-th component of sediment; When the bed shear stress is less than the critical accumulation stress, calculate the accumulation rate: ； This boundary condition is used to simulate the physical mechanism of the formation and disappearance of floating silt at the bottom of the waterway.

8. The method for active detection and identification of channel silt distribution combining GIS channel information according to claim 1, characterized in that, The silt distribution heat map generated in step S5 includes normal siltation distribution and abnormal siltation distribution. The abnormal siltation distribution is simulated by inputting meteorological and hydrological data under typhoon weather to identify the spatiotemporal distribution range and thickness of floating silt in the waterway during typhoons, thereby determining the "window period" for ship navigation.

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