CN113343483A - Slope flow dynamic visualization method based on shortest confluence time - Google Patents

Slope flow dynamic visualization method based on shortest confluence time Download PDF

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CN113343483A
CN113343483A CN202110719243.0A CN202110719243A CN113343483A CN 113343483 A CN113343483 A CN 113343483A CN 202110719243 A CN202110719243 A CN 202110719243A CN 113343483 A CN113343483 A CN 113343483A
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slope
flow
grid
watershed
basin
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CN113343483B (en
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林广发
李清远
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Fujian Normal University
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02ATECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A10/00TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE at coastal zones; at river basins
    • Y02A10/40Controlling or monitoring, e.g. of flood or hurricane; Forecasting, e.g. risk assessment or mapping

Abstract

The invention discloses a slope flow dynamic visualization method based on shortest confluence time, which comprises the following steps: and establishing a confluence cumulative graph, performing hole filling treatment on the original digital elevation model of the basin to obtain a non-hole digital elevation model, and obtaining a basin water flow directional diagram and the confluence cumulative graph. And rasterizing the watershed water flow, and calculating the length value of the slope flow. Step two: establishing a basin calculation model; carrying out slope analysis on the DEM in the depression-free land to obtain the slope value of each grid unit in the flow field; analyzing the soil in the drainage basin; rasterizing the watershed, and constructing a grid computing model according to an SCS-CN model; setting a rainfall scene, and acquiring runoff depth and net rain intensity; E. the method comprises the following steps of distinguishing a slope unit and a river channel unit; F. calculating the converging time of the slope surface flow; G. constructing a slope flow path; H. and inputting matrix data. Step three: and performing visual simulation and dynamic visualization of the watershed slope flow by using the matrix data. The method of the invention can make the slope flow visualization more accurate.

Description

Slope flow dynamic visualization method based on shortest confluence time
Technical Field
The invention relates to the field of hydrology, in particular to a slope flow dynamic visualization method based on shortest confluence time.
Background
The slope surface flow is a thin layer water flow which is formed by rainfall or snow melting and flows along the slope surface under the action of gravity, and is generated when the rainfall exceeds the soil infiltration and ground depression storage capacity. The slope flow is the initial stage of surface runoff and is the most basic unit of soil erosion in a watershed. The water flow of the slope is influenced by natural or artificial factors such as soil types, vegetation coverage, land utilization types, rainfall characteristics, flow channels and the like, the movement rule and the hydraulic characteristics of the slope are very complex, and the slope changes along with the change of time and space. And the dynamic visualization of the slope flow can visually present the dynamic forming process of the slope flow which changes along with time and space, thereby being convenient for people to observe and analyze.
At present, two kinds of visual methods related to slope surface flow are available in the literature, one is that three-dimensional modeling and image rendering functions of computer graphics are utilized to express a three-dimensional surface space hydrological process, for example, as described in the literature, "three-dimensional visual test of surface space hydrological process — take Zhejiang loess ridge watershed as an example"), the method enables the influence of confluence accumulation on the surface runoff flow velocity to be incapable of being accurately evaluated due to the visual separation of hydrological model calculation and surface space hydrological process; and secondly, performing dynamic visual simulation on surface runoff by utilizing a vectorized surface runoff path, as described in The literature of The simulation of surface runoff using a flow-path network model. However, the method does not distinguish the river channel unit and the slope unit, and certain errors exist.
Disclosure of Invention
In order to enable the visualization method of the slope flow to be more suitable for the motion rule and the hydraulic characteristic of the slope flow, the invention provides a slope flow dynamic visualization method based on the shortest confluence time.
The invention adopts the following technical scheme.
A slope flow dynamic visualization method based on shortest confluence time comprises the following steps.
The method comprises the following steps: a confluence accumulation map is established.
This step is divided into the following sections.
A. Performing hole filling treatment on an original digital elevation model of the basin to obtain a non-hole digital elevation model, performing water flow direction analysis on the non-hole digital elevation model to obtain a basin water flow directional diagram, and performing convergence accumulation analysis on the non-hole digital elevation model to obtain a convergence accumulation diagram of the basin.
B. The method comprises the steps of rasterizing basin water flow, setting a convergence starting point, dividing the flow direction of the water flow into three types including a grid transverse direction, a grid longitudinal direction and a grid diagonal direction, and calculating the length value of the slope flow according to the three types, wherein the lengths of the slope flow of the grid transverse direction water flow and the grid longitudinal direction water flow are the size of grid units, and the length of the slope flow of the grid diagonal direction water flow is 2 times of the size of the grid units.
Step two: and establishing a basin calculation model.
This step is divided into the following sections.
A. And carrying out slope analysis on the DEM without the depression to obtain the slope value of each grid unit in the flow field.
B. Analyzing the watershed soil to obtain watershed soil type data and watershed land coverage type data, and accordingly obtaining a Manning roughness coefficient and a CN value of the grid in the watershed.
C. And rasterizing the watershed, and constructing a grid computing model according to the SCS-CN model.
D. Setting a rainfall scene, and acquiring runoff depth of the drainage basin in the scene so as to obtain net rain intensity.
E. And constructing a grid calculation model matrix according to a slope surface flow motion wave equation, and distinguishing slope units and river channel units.
F. And calculating the converging time of the slope surface flow.
G. And constructing a slope flow path.
H. And inputting matrix data.
Step three: and performing visual simulation and dynamic visualization of the watershed slope flow by using the matrix data.
And (4) performing the filling treatment in the step one, wherein the used tool is a hydrological analysis module of ArcGIS.
And step two, gradient analysis is carried out, and a tool used in the gradient analysis is an ArcGIS space analysis module.
And the watershed soil type data in the second step are obtained by scanning, geometrically correcting, digitizing and range cropping the watershed soil map.
And the watershed land cover type data in the second step are obtained by performing geometric correction and visual interpretation on the SPOT5 remote sensing image of the watershed.
And in the matrix data input of the second step, the recording times of the same slope flow path are 1.
And performing visual simulation and dynamic visualization in the third step, wherein the used tools are a Tracking analysis module and a Time Slider module of ArcGIS.
According to the method, when the confluence cumulative graph is established, the digital elevation model is subjected to rasterization, the digital elevation model is described by the optimal fuzzy partition model, and the high-precision confluence cumulative graph can be established by utilizing the strong computing capability of a computer.
The basin calculation model in the method is established based on gradient analysis and soil analysis, the actual conditions of the basin can be accurately reflected and are in accordance with the reality, and the soil analysis fully considers the Manning roughness coefficient and the CN value and has higher accuracy.
The method is based on the convergence time method, the flow velocity of the slope flow and the convergence time of the slope flow are calculated by a space distributed hydrological model, the change of the slope flow can be described under multiple time granularities, and a corresponding matrix is established, so that the time animation can accord with the change characteristic of the slope flow at higher precision.
The invention adopts the matrix to record slope flow analysis data, uses animation software to visualize the matrix data, and can conveniently compare slope flow simulation results under different rainfall settings for decision-making and analysis.
Drawings
The invention is described in further detail below with reference to the accompanying drawings:
FIG. 1 is a schematic view of the water flow direction of the process of the present invention;
FIG. 2 is a schematic of the water flow path of the method of the present invention;
FIG. 3 is a schematic view of the water flow path assuming a confluence time of 1s in the method of the present invention;
FIG. 4 is a schematic view of the water flow paths for achieving the shortest confluence time in the method of the present invention;
FIG. 5 is a schematic diagram of a convergence time matrix for the method of the present invention;
FIG. 6 is a schematic diagram of a convergence time matrix for achieving the shortest convergence time in the method of the present invention;
FIG. 7 is a schematic diagram of a slope flow pattern simulated by the method of the present invention at a time t =10 min;
FIG. 8 is a schematic diagram of a slope flow pattern simulated by the method of the present invention at a time t =60 min;
fig. 9 is a schematic diagram of a slope flow shape at a time t =120min simulated by the method of the present invention;
fig. 10 is a schematic diagram of a slope flow shape at a time t =240min simulated by the method of the present invention.
Detailed Description
As shown in one of fig. 1 to 10, a method for dynamically visualizing a slope flow based on a shortest confluence time includes the following steps.
The method comprises the following steps: a confluence accumulation map is established.
This step is divided into the following sections.
A. The method comprises the steps of using an ArcGIS hydrological analysis module to carry out hole filling treatment on an original digital elevation model of a basin to obtain a non-hole digital elevation model, carrying out water flow direction analysis on the non-hole digital elevation model to obtain a basin water flow directional diagram shown in a figure 1, and carrying out convergence accumulation analysis on the non-hole digital elevation model to obtain a convergence accumulation diagram of the basin.
B. As shown in fig. 2, 3 and 4, the watershed water flow is rasterized, a convergence starting point is set, the flow direction of the water flow is divided into three types, namely a grid transverse direction, a grid longitudinal direction and a grid diagonal direction, and the slope flow length value is calculated, wherein the slope flow length of the water flow in the grid transverse direction and the grid longitudinal direction is the size of a grid unit, and the slope flow length of the water flow in the grid diagonal direction is 2 times of the size of the grid unit.
Step two: establishing a basin calculation model;
the step is divided into the following parts;
A. and (3) performing slope analysis on the DEM in the depression-free land by using an ArcGIS space analysis module to obtain a slope value of each grid unit in the flow field, wherein the slope value is a slope-to-fall ratio, and data are marked on the corresponding grid.
B. The method comprises the steps of scanning, geometrically correcting, digitizing and range cropping the drainage basin soil map, analyzing the drainage basin soil to obtain drainage basin soil type data, geometrically correcting and visually interpreting SPOT5 remote sensing images of the drainage basin to obtain drainage basin soil coverage type data, obtaining a Manning roughness coefficient and a CN value of a grid in the drainage basin according to the data, and marking the data on the corresponding grid.
C. And rasterizing the watershed, and constructing a grid computing model according to the SCS-CN model.
D. Setting a rainfall scene, and acquiring runoff depth of the drainage basin in the scene so as to obtain net rain intensity.
E. And (3) constructing a grid calculation model matrix according to a slope flow motion wave equation, firstly reading slope flow path data, then initializing a rainfall scene, traversing each grid unit, calculating convergence accumulation time on each grid unit according to data marking in the A, B, C process, and distinguishing a slope unit and a river channel unit by using a preset threshold value and marking.
F. And calculating the flow converging time of the slope surface, and setting the soil humidity in the early stage of the drainage basin as a normal condition. And constructing a grid calculation model according to the SCS-CN model, and acquiring runoff depth of the drainage basin under a given rainfall scene so as to obtain net rain intensity. And calculating the slope surface flow confluence time by the shortest confluence time grid.
G. Constructing a slope flow path; firstly, taking a grid unit with a convergence cumulative value of 0 as a starting point of a slope flow path, tracking the slope flow path in a slope unit marking matrix according to a D8 algorithm, acquiring a next point of the slope flow path, and marking the next point as a target point until the end point or a basin boundary of the slope flow, thereby constructing the slope flow path.
H. Matrix data input, establishing a matrix by using grid marks and confluence time in the E, F, G process, and inputting related data of water flow paths and path forming time. In the actual process of forming the slope flow, the slope flow paths with the grid units as the starting points are necessarily overlapped, and for the overlapped slope flow paths, the arrival time is sequential, so that the overlapping process is cleaned simultaneously in the process. Fig. 1 is a schematic diagram of water flow directions obtained by performing hole filling on an original digital elevation model according to a D8 algorithm, and fig. 2, 3 and 4 are schematic diagrams of water flow paths. As shown in fig. 3, the water flow from the starting points (1A, 1B, 1C, 1D, 1E, 1F, 1G) to 3C forms a superposed path 2F- >3C (fig. 4). Assuming that the time for the water flow to flow from any grid cell to the adjacent grid cell on the water flow path is 1s (fig. 3), the shortest confluence time for the water flow to flow from the starting points (1A, 1B, 1C, 1D, 1E, 1F, 1G) to 3C is 2s, and the water flow path 2F- >3C is formed at the 2 nd s after the start of rainfall. Fig. 5 is a schematic diagram of a bus time matrix, fig. 6 is a schematic diagram of a shortest bus time matrix, and fig. 5 and 6 have a corresponding relationship. In consideration of the redundancy problem of data storage, when the water flow dynamic visualization simulation is carried out, the water flow paths 2F- >3C are recorded in the river network space-time data only once and are drawn at the 2 nd s, and then the drawing is not repeated. That is, the shortest confluence time of the water flow from the grid unit 2F to the grid unit 3C is 2s, and the value thereof is stored in the confluence time matrix corresponding to the grid unit 2F. Given an onset time of rainfall such as 2005/08/1409: 00:00, the actual formation time of the water flow path 2F- >3C is 2005/08/1409: 00: 02.
Step three: performing visual simulation and dynamic visualization of the river basin slope flow by using matrix data, and Tracking a river basin slope flow path by using ArcGIS Tracking analysis to realize two-dimensional dynamic visual simulation of the river basin slope flow; by means of a Time Slider module of ArcScene, three-dimensional dynamic visualization of the slope flow is achieved by means of Time animation. Fig. 7, 8, 9, and 10 correspond to slope flow patterns at time t =10min, time t =60min, time t =120min, and time t =240min, respectively.

Claims (7)

1. A slope flow dynamic visualization method based on shortest confluence time is characterized by comprising the following steps;
the method comprises the following steps: establishing a confluence accumulation graph; the step is divided into the following parts;
A. performing hole filling treatment on an original digital elevation model of the basin to obtain a non-hole digital elevation model, performing water flow direction analysis on the non-hole digital elevation model to obtain a basin water flow directional diagram, and performing convergence accumulation analysis on the non-hole digital elevation model to obtain a convergence accumulation diagram of the basin;
B. rasterizing a watershed water flow, setting a convergence starting point, dividing the flow direction of the water flow into three types, namely a grid transverse direction, a grid longitudinal direction and a grid diagonal direction, and calculating the length value of a slope flow according to the three types, wherein the lengths of the slope flows of the grid transverse direction water flow and the grid longitudinal direction water flow are the size of a grid unit, and the length of the slope flow of the grid diagonal direction water flow is 2 times of the size of the grid unit;
step two: establishing a basin calculation model; the step is divided into the following parts;
A. carrying out slope analysis on the DEM in the depression-free land to obtain the slope value of each grid unit in the flow field;
B. analyzing the watershed soil to obtain watershed soil type data and watershed land coverage type data, and accordingly obtaining a Manning roughness coefficient and a CN value of a grid in the watershed;
C. rasterizing the watershed, and constructing a grid computing model according to an SCS-CN model;
D. setting a rainfall scene, and acquiring runoff depth of a drainage basin in the scene so as to obtain net rain intensity;
E. constructing a grid calculation model matrix according to a slope surface flow motion wave equation, and distinguishing slope units and river channel units;
F. calculating the converging time of the slope surface flow;
G. constructing a slope flow path;
H. inputting matrix data;
step three: and performing visual simulation and dynamic visualization of the watershed slope flow by using the matrix data.
2. The method for dynamically visualizing the flow of the slope based on the shortest confluence time as recited in claim 1, wherein: and (4) performing the filling treatment in the step one, wherein the used tool is a hydrological analysis module of ArcGIS.
3. The method for dynamically visualizing the flow of the slope based on the shortest confluence time as recited in claim 1, wherein: and step two, gradient analysis is carried out, and a tool used in the gradient analysis is an ArcGIS space analysis module.
4. The method for dynamically visualizing the flow of the slope based on the shortest confluence time as recited in claim 1, wherein: and the watershed soil type data in the second step are obtained by scanning, geometrically correcting, digitizing and range cropping the watershed soil map.
5. The method for dynamically visualizing the flow of the slope based on the shortest confluence time as recited in claim 1, wherein: and the watershed land cover type data in the second step are obtained by performing geometric correction and visual interpretation on the SPOT5 remote sensing image of the watershed.
6. The method for dynamically visualizing the flow of the slope based on the shortest confluence time as recited in claim 1, wherein: and in the matrix data input of the second step, the recording times of the same slope flow path are 1.
7. The method for dynamically visualizing the flow of the slope based on the shortest confluence time as recited in claim 1, wherein: and performing visual simulation and dynamic visualization in the third step, wherein the used tools are a Tracking analysis module and a Time Slider module of ArcGIS.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102034001A (en) * 2010-12-16 2011-04-27 南京大学 Design method for distributed hydrological model by using grid as analog unit
WO2018103510A1 (en) * 2016-12-05 2018-06-14 中国水利水电科学研究院 Method for evaluation of surface runoff storage capacity of river basin green infrastructure
CN110717231A (en) * 2019-09-11 2020-01-21 中国水利水电科学研究院 Sub-basin confluence simulation method based on slope channel river channel three-level structure
CN111651885A (en) * 2020-06-03 2020-09-11 南昌工程学院 Intelligent sponge urban flood forecasting method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102034001A (en) * 2010-12-16 2011-04-27 南京大学 Design method for distributed hydrological model by using grid as analog unit
WO2018103510A1 (en) * 2016-12-05 2018-06-14 中国水利水电科学研究院 Method for evaluation of surface runoff storage capacity of river basin green infrastructure
CN110717231A (en) * 2019-09-11 2020-01-21 中国水利水电科学研究院 Sub-basin confluence simulation method based on slope channel river channel three-level structure
CN111651885A (en) * 2020-06-03 2020-09-11 南昌工程学院 Intelligent sponge urban flood forecasting method

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
JINKANG DU 等: "Development and testing of a new storm runoff routing approach based on time variant spatially distributed travel time method", 《JOURNAL OF HYDROLOGY》 *
张文富 等: "基于元胞自动机模型的河道汇流过程模拟", 《地球信息科学》 *
李清远: "水文模型驱动的山洪过程动态可视化方法研究", 《中国优秀博硕士学位论文全文数据库(硕士)基础科学辑》 *

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