CN112084643A - Drainage basin extraction method based on digital elevation and soil parameters - Google Patents
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Abstract
The invention discloses a drainage basin extraction method based on digital elevation and soil parameters, which relates to the technical field of hydrology and comprises the following steps: acquiring grid data of a digital elevation model of an area to be extracted; according to the grid data of the digital elevation model, taking each grid as a central grid, and calculating the distance weight drop between each central grid and a neighborhood grid; determining soil characteristic parameters of an area to be extracted, wherein the soil characteristic parameters comprise soil saturation hydraulic conductivity and soil erodible factors; determining the flow direction of the central grids according to the distance weight fall, the saturated water conductivity of the soil and the soil erodible factor, and calculating the confluence area value of each grid; and determining a river basin network and a river basin range in the area to be extracted according to a preset threshold and the confluence area value of each grid. The method for extracting the drainage basin fully considers the influence of the heterogeneity of soil spatial distribution on the flow direction of the runoff, and then flow direction calculation is carried out based on the elevation and the soil characteristic parameters, so that the accuracy of drainage basin extraction is improved.
Description
Technical Field
The invention relates to the technical field of hydrology, in particular to a drainage basin extraction method based on digital elevation and soil parameters.
Background
The drainage basin is an area which is surrounded by a ground water diversion line and can collect rainwater and enable the rainwater to flow out of an outlet of the drainage basin, and is a basic unit for hydrologic cycle research and water resource management. Because the basin extraction method based on the Digital Elevation Model (DEM) has the characteristics of rapidness, high efficiency, time saving and labor saving, the method is widely applied to hydrological numerical simulation and water safety management.
It should be understood that in the process of extracting the drainage basin based on the DEM, the accuracy of the drainage basin extraction result is directly determined by the flow direction calculation. In the related art, a Single Flow Direction (SFD) algorithm or a Multiple Flow Direction (MFD) algorithm is generally used for Flow Direction calculation.
Specifically, the single-flow algorithm considers that runoff generated by the computing grid and runoff gathered in an uphill direction flow to the only adjacent grid in a downhill direction. In 1984, O' Callagham et al proposed the classic D8 algorithm, whose main ideas were: and calculating the distance weight difference between grids based on the elevation, namely dividing the height difference between the grids by the distance between the grids, and assuming that runoff converged into the central grid only flows into the grid with the largest distance weight difference among 8 adjacent grids. The method does not consider the random surface of the terrain, and can not determine the runoff flow direction under the following 3 conditions: (1) two or more grids adjacent to the grid have the same steepest gradient; (2) a flat area, i.e. the grid adjacent to it has the same elevation as the central grid; (3) closed depressions, i.e. the central grid, are lowest in elevation.
In 1991, Fairefield proposed a Rho8 algorithm, which adds a terrain random factor to flow direction calculation, and replaces the D8 algorithm with a random variable K (K ═ 1/(2-r), and r ∈ [0,1]) to use the distance between the center points of the grids as a processing method for the horizontal distance between the two grids. The method solves the problem that only 8 flow directions are limited in the D8 algorithm, but the calculation result is easy to generate swing or cross runoff which is parallel runoff in plain areas.
In 1992, Lea proposed the Lea algorithm based on the Rho8 algorithm. The method considers that the runoff is a rolling ball passing through each terrain surface in the steepest slope direction, the runoff direction is not determined by the terrain slope between adjacent grids, but is determined by the slope direction of each central grid surface, and the flow direction value is between 0 and 2 pi. The method can perform continuous flow direction judgment, but as a single flow direction algorithm, as with the D8 and Rho8 algorithms, the following problems still exist: (1) the flow direction is single, only inflow of accumulated runoff in an uphill direction can be simulated, diversion of the accumulated runoff cannot be simulated, and the accumulated runoff is not consistent with diffuse flow of actual runoff on the ground; (2) the outflow path is over simplified, the unit cells are regarded as point sources, the outflow path is one-dimensional linear motion from point to point, and the actual surface runoff is planar two-dimensional motion; (3) the water system width is rough, and the cell width is obviously not in accordance with the actual situation as it is.
On the other hand, the multi-flow algorithm considers the fact that the runoff motion has a dispersive nature, and does not distribute the inflow of the central grid to a single adjacent grid in its entirety, but to all or part of the adjacent grid cells in a certain proportion. In 1991, Quinn et al proposed a multi-flow algorithm FD 8-Quinn. The method considers that the confluence of the central grid flows into all adjacent grids with lower elevations, and the runoff flow is distributed according to the flow direction proportion. The method still treats the accumulated runoff of the central grid as a point source, and the runoff path is still a one-dimensional line.
In 1994, Costa-Cabral et al provided a DEMON algorithm by fully considering the two-dimensional and uniform characteristics of the runoff on the grid cells. The method selects a suitable plane based on 4 points of the 3 x 3 grid, represents the runoff flow direction using the elevation tensor, and calculates the width of the runoff path accordingly. However, since 3 points define a plane, the selected plane does not necessarily pass through all the corner points of the 3 x 3 grid. Such non-uniform planes may lead to non-uniform radial flow directions.
In 1997, a D-infinity method was proposed by the Tarboton's Lea method and the DEMON method. The method uses 8 triangles formed by the central point of the unit grid and 8 grid points around the central point to replace a plane, and takes the slope direction of the triangle where the maximum slope is positioned as a runoff direction (the value can be taken between 0 pi and 2 pi). In addition, two adjacent grids determined by the triangle with the maximum gradient are used as runoff flow distribution units, and runoff flow is distributed according to the proximity degree of the central grid point and the connection line of the two adjacent grid points to the maximum slope direction.
In 2007, Yoghun and Quinn propose an improved multi-Flow algorithm IMFD (improved Multiple Flow direction) based on the fundamental principle of FD 8-Quinn. Compared with the FD8-Quinn algorithm, the IMFD proposes that the effective contour length in the convergence cumulative distribution is calculated by a cone inscribed circle method, the self area of the calculated grid is added into the calculation of the unit contour convergence area, and meanwhile, the judgment, identification and classification of abnormal grids (convex-concave and flat areas) are enhanced.
However, in both of the above two flow direction calculation methods, the terrain is used as the only factor influencing the flow direction of the runoff, and particularly for a small-scale runoff having a short runoff path and a small watershed area, the accuracy of calculating the runoff path is reduced, and the accuracy of watershed extraction is adversely affected.
Disclosure of Invention
The invention provides a drainage basin extraction method based on digital elevation and soil parameters, which fully considers the influence of heterogeneity of terrain and soil space distribution on the flow direction of runoff and improves the accuracy of drainage basin extraction.
The application provides a drainage basin extraction method based on digital elevation and soil parameters, which comprises the following steps:
acquiring grid data of a digital elevation model of an area to be extracted;
according to the grid data of the digital elevation model, taking each grid as a central grid, and calculating the distance weight difference between each central grid and a neighborhood grid;
determining soil characteristic parameters of the area to be extracted, wherein the soil characteristic parameters comprise soil saturation hydraulic conductivity and soil erodible factors;
determining the flow direction of the central grids according to the distance weight difference, the saturated water conductivity of the soil and the soil erodible factor, and calculating the confluence area value of each grid;
and determining a river basin network and a river basin range in the area to be extracted according to a preset threshold value and the confluence area value of each grid.
Optionally, the step of calculating a distance weight difference between each central grid and a neighboring grid by using each grid as a central grid according to the grid data of the digital elevation model includes:
detecting whether a depression exists in the terrain contained in the grid data of the digital elevation model; if yes, performing depression filling on the grid data of the digital elevation model;
and calculating the distance weight difference between each central grid and the adjacent grids thereof by iteration by taking each grid as the central grid in turn from the grid data of the digital elevation model.
Optionally, the step of determining a flow direction of the central grid according to the distance weight difference, the soil saturation hydraulic conductivity and the soil erodible factor, and calculating a confluence area value of each grid includes:
converting the soil characteristic parameters into a two-dimensional array with the same resolution as the grid data of the digital elevation model to obtain grid data of the soil characteristic parameters; the soil characteristic parameter grid data comprise soil saturation hydraulic conductivity grid data and soil erodible factor grid data;
calculating the optimized distance weight drop of the central grid and the adjacent grids according to the distance weight drop, the soil saturated hydraulic conductivity grid data and the soil erodible factor grid data;
determining the flow direction of the central grid according to the optimized distance weight difference;
calculating the effective equal-height line length of the outflow of the central grid in the downhill direction, and calculating the runoff distribution weight of the central grid according to the optimized distance weight drop, the resolution of the grid data of the digital elevation model and the effective equal-height line length;
distributing the runoff flow in the ascending direction of the central grid according to the runoff distribution weight to obtain confluence area grid data; the convergence area grid data includes a convergence area value corresponding to each neighborhood grid.
Optionally, the step of determining a flow direction of the central grid according to the optimized distance weight difference includes:
when the optimal distance weight difference is a positive value, the flow direction is that the central grid flows out to the neighborhood grid;
and when the optimal distance weight difference is a negative value, the flow direction is that the neighborhood grid flows into the central grid.
Optionally, the optimized distance weight difference is calculated by using the following formula:
h(i,j)＝tanβj·K(i,j)·KS(i,j)
h (i, j) represents the optimal distance weight difference between the ith central grid and the jth neighborhood grid, K (i, j) represents the soil erodible factor grid data of the ith central grid in the jth neighborhood grid direction, and K (i, j) represents the soil erodible factor grid data of the ith central grid in the jth neighborhood grid directionS(i, j) shows the soil saturation water conductivity grid data of the ith central grid in the jth neighborhood grid direction, tan betajRepresenting the distance weight difference between the center grid and the jth neighbor grid.
Optionally, the runoff distribution weight is calculated by using the following formula:
wherein r (i, j) represents the runoff distribution weight of the ith central grid in the jth neighborhood grid direction, L (i, j) represents the effective contour line of the ith central grid in the jth neighborhood grid direction, dx represents the side length of the central grid, h (i, j) represents the optimized distance weight difference between the ith central grid and the jth neighborhood grid, and m represents the number of the neighborhood grids.
Optionally, the step of determining a drainage basin region in the region to be extracted according to a preset threshold and a confluence area of the neighborhood grid includes:
determining a confluence area threshold;
traversing the data of the confluence area grids, comparing the confluence area threshold value with the confluence area value in each confluence area grid, and determining the confluence area grid with the confluence area value larger than the confluence area threshold value as a basin area.
Optionally, the step of determining, according to a preset threshold, a watershed region in the region to be extracted includes:
determining a river basin network in the area to be extracted, and determining a river basin area according to the river basin network.
Optionally, the step of determining a river network of a river basin in the area to be extracted includes:
traversing the confluence area grid data, determining the grid with the confluence area value equal to the confluence area threshold value as the starting point of the river basin and river network, and determining the grid with the maximum confluence area value as the water outlet of the river basin.
Optionally, the soil erodible factor is calculated by using the following formula:
wherein, SN1SAN, SIL, CLA and C represent the sand content, silt content, clay content and organic carbon content (%) of the soil in the area to be extracted, respectively, 1-SAN/100.
Compared with the prior art, the drainage basin extraction method based on the digital elevation and the soil parameters, provided by the invention, at least has the following beneficial effects:
according to the watershed extraction method, the flow direction of the central grid is determined according to the grid data of the digital elevation model and soil characteristic parameters, wherein the soil characteristic parameters comprise the soil saturation hydraulic conductivity and the soil erodible factor. On one hand, the saturated water conductivity of the soil represents the runoff conducting capacity of the soil, and the stronger the water conductivity of the soil is, the easier the water content of the soil is increased, so that runoff is easier to generate; on the other hand, the soil erodible factor represents the soil erosion resistance, and the worse the erosion resistance, the easier it is to be eroded by water to form runoff. Therefore, the method for extracting the drainage basin fully considers the influence of the heterogeneity of soil space distribution on the flow direction of the runoff, and further calculates the flow direction based on the elevation and the soil characteristic parameters, so that the accuracy of the drainage basin extraction is improved.
Of course, it is not necessary for any product in which the present invention is practiced to achieve all of the above-described technical effects simultaneously.
Other features of the present invention and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic flow chart illustrating a drainage basin extraction method based on digital elevation and soil parameters according to an embodiment of the present disclosure;
FIG. 2 is a diagram illustrating a traversal window provided in the embodiment of FIG. 1;
FIG. 3 is a schematic flow chart illustrating a method for extracting a watershed based on digital elevation and soil parameters according to the embodiment of FIG. 1;
FIG. 4 is a schematic view of a bus analysis provided in the embodiment of FIG. 1;
fig. 5a is a schematic view of a DEM distribution of an ingale strait basin according to an embodiment of the present invention;
fig. 5b is a schematic diagram illustrating a distribution of saturated water conductivity of the soil of the ingale strait basin according to the embodiment of the present application;
fig. 5c is a schematic diagram illustrating distribution of soil erodible factors of the ingale strait river basin according to the embodiment of the present application;
fig. 6a is a schematic diagram illustrating a DEM distribution of a royal family dam basin according to an embodiment of the present invention;
fig. 6b is a schematic diagram illustrating a distribution of saturated water conductivity of soil in a drainage basin of a queen dam according to an embodiment of the present application;
fig. 6c is a schematic diagram illustrating a distribution of soil erodible factors in a drainage basin of the royal family dam according to an embodiment of the present disclosure;
fig. 7a is a schematic diagram illustrating a DEM distribution of a yellow bridge drainage basin according to an embodiment of the present disclosure;
fig. 7b is a schematic diagram illustrating a distribution of saturation hydraulic conductivity of soil in a yellow bridge drainage basin according to an embodiment of the present disclosure;
FIG. 7c is a schematic diagram illustrating a distribution of soil erosion factors in a yellow bridge watershed according to an embodiment of the present disclosure;
fig. 8a is a schematic diagram illustrating an elevation-based extraction result of an oriole strait current field according to an embodiment of the present application;
fig. 8b is a schematic diagram illustrating an extraction result of the bird landing gorge river basin based on elevation and soil characteristic parameters according to an embodiment of the present application;
FIG. 9a is a schematic diagram illustrating the result of extracting Wangcha watershed based on elevation according to an embodiment of the present invention;
FIG. 9b is a schematic diagram illustrating the result of Wangjia dam basin extraction based on elevation and soil characteristic parameters according to an embodiment of the present disclosure;
FIG. 10a is a schematic diagram illustrating the result of extracting yellow bridge drainage basins based on elevation according to an embodiment of the present application;
fig. 10b is a schematic diagram illustrating a yellow bridge drainage basin extraction result based on elevation and soil characteristic parameters according to an embodiment of the present application.
Detailed Description
Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
Fig. 1 is a schematic flow chart of a drainage basin extraction method based on digital elevation and soil parameters according to an embodiment of the present disclosure. As shown in fig. 1, the present application provides a drainage basin extraction method based on digital elevation and soil parameters, which is characterized by comprising:
s1, acquiring grid data of the digital elevation model of the area to be extracted;
step S2, according to the grid data of the digital elevation model, taking each grid as a central grid, and calculating the distance weight difference between each central grid and a neighborhood grid;
s3, determining soil characteristic parameters of the area to be extracted, wherein the soil characteristic parameters comprise soil saturation hydraulic conductivity and soil erodible factors;
step S4, determining the flow direction of the central grids according to the distance weight fall, the saturated water conductivity of the soil and the soil erodible factor, and calculating the confluence area value of each grid;
and step S5, determining a river basin network and a river basin range in the area to be extracted according to a preset threshold value and the confluence area value of each grid.
It should be understood that the DEM model can express continuous terrain changes through discrete elevation point data, and contains rich information of terrain, landform, hydrological features and the like, so that the embodiment can extract the natural basin feature information reflecting the area to be extracted from the grid data of the digital elevation model.
Specifically, in the flow direction analysis, the distance weight difference between the central grid and the neighborhood grid is first calculated according to the elevation data in the DEM model. Table 1 shows the grid data of the digital elevation model provided in the embodiment of fig. 1, and fig. 2 shows a schematic diagram of the traversal window provided in the embodiment of fig. 1. Specifically, the grid data of the digital elevation model includes a plurality of grids having the same size, and each grid correspondingly includes elevation point data. Referring to table 1 and fig. 2, in the present embodiment, a window of 3 × 3 size is taken as an example, the DEM grid data is traversed, a grid o corresponding to the center of the window is taken as a center grid, and 8 grids (m 1-m 8) around the center grid are taken as neighborhood grids. Obviously, the elevation point data corresponding to the central grid is 10, and the elevation point data of the neighborhood grids m 1-m 8 are 11, 12, 13, 10, 9, 8, 7 and 8, respectively, wherein the unit of the elevation data can be meter.
In this embodiment, the flow direction of the central grid needs to be determined by combining the distance weight difference and the soil characteristic parameter. The soil characteristic parameters comprise the saturation hydraulic conductivity of the soil and the erodible factor of the soil. On one hand, the saturated water conductivity of the soil represents the runoff conducting capacity of the soil, and the stronger the water conductivity of the soil is, the easier the water content of the soil is increased, so that runoff is easier to generate; on the other hand, the soil erodible factor represents the soil erosion resistance, and the worse the erosion resistance, the easier it is to be eroded by water to form runoff. Therefore, the influence of the heterogeneity of the soil spatial distribution on the runoff flow direction is fully considered, the flow direction is calculated based on the elevation and the soil characteristic parameters, and the accuracy of the drainage basin extraction is improved.
TABLE 1
| 11 | 12 | 13 |
| 10 | 10 | 9 |
| 8 | 7 | 8 |
In this embodiment, the neighborhood grid m2 to m7 is obtained by sequentially labeling other grids (except for the center grid) in the order of preceding and succeeding columns, with the neighborhood grid m1 at the upper left corner of the center grid as the starting point. In some other embodiments of the present application, any one neighborhood grid may be used as a starting point, and then seven other neighborhood grids are marked according to a preset data reading and writing rule. This is not a limitation of the present application.
Optionally, in step S2, the step of calculating distance weight differences between each central grid and the neighboring grids by using each grid as a central grid according to the grid data of the digital elevation model includes:
detecting whether depressions exist in the terrain contained in the grid data of the digital elevation model; if yes, performing depression filling on the grid data of the digital elevation model;
and calculating the distance weight difference between each central grid and each adjacent grid thereof by taking each grid as the central grid in the grid data of the digital elevation model through iteration.
In this embodiment, the grid data of the digital elevation model needs to be preprocessed to eliminate the hole in the data before calculating the watershed features. As can be appreciated, a depression refers to a depressed area in the digital elevation model grid data, i.e., an area having elevation values lower than the elevation values of the area surrounding it; the presence of depressions may prevent the water flow from flowing out, resulting in water system breakage and wrong water flow direction, and further cause the extracted watershed characteristics to be inconsistent with the actual situation. Therefore, preprocessing the grid data of the digital elevation model is a premise for accurately extracting the characteristics of the drainage basin and is also a reliable guarantee for extracting the drainage basin and correctly establishing a drainage basin hydrological network.
It should be noted that, according to the cause of formation of the hollow in the grid data of the digital elevation model, the hollow can be divided into a real hollow and a 'pseudo hollow'; the former is the real existing terrain, such as karst terrain, which does not need to be filled, and the latter is the 'false terrain' formed by artificial mistakes in grid data interpolation and grid precision of the digital elevation model, so that the 'false hollow' needs to be filled in a preprocessing stage.
Optionally, in this embodiment, the elevation values of the grid on which the hole is located are stepped up to the elevation value of at least one adjacent grid, thereby eliminating all holes in the grid data of the digital elevation model. Of course, in some other embodiments of the present application, other methods may be adopted to fill the hollow space, and in the preprocessing stage of the grid data of the digital elevation model, other data processing steps may be further included to further improve the accuracy of the drainage basin extraction, which is not limited by this embodiment.
Optionally, in this embodiment, the distance weight difference between the central grid and the neighbor grid is calculated according to the following formula:
in the formula, tan betajRepresenting the distance weight difference between the central grid and the jth neighborhood grid, h representing the elevation point data corresponding to the central grid, hjRepresenting elevation point data corresponding to the jth neighborhood grid, and D representing the distance between the central grid and the jth neighborhood grid, wherein the distance between the vertically adjacent central grid and the neighborhood grid is 1dx, and the distance between the diagonally adjacent central grid and the neighborhood grid is 1dx
Where dx is the side length of each grid.
The following description will be made by taking the grid data of the digital elevation model shown in table 1 as an example. With continued reference to Table 1 and FIG. 2, for neighborhood grid m1 at the top left corner of central grid o, its height difference from central grid 0 is 10-11-1, and the distance between the two grids is
The distance weight between the neighborhood grid m1 and the center grid o is thus given by
Further, after the above calculation is performed on the 8 neighborhood grids (m1 to m8) of the center grid o, the distance weight difference of the 8 neighborhood grids shown in table 2 can be obtained.
TABLE 2
Fig. 3 is a schematic flow chart of another method for extracting a drainage basin based on digital elevation and soil parameters according to the embodiment of fig. 1. Optionally, referring to fig. 3, in the step S4, the step of determining the flow direction of the central grid according to the distance weight fall, the soil saturation water conductivity, and the soil erodible factor, and calculating the confluence area value of each grid includes:
The flow direction refers to the direction of water flow when the water flow leaves each grid, and since soil is also one of the main factors influencing the flow direction of runoff, the embodiment determines the flow direction of runoff of the central grid by combining the elevation of the area to be extracted and the soil characteristic parameters.
Specifically, the saturated hydraulic conductivity of the soil and the erodable factor of the soil can affect the calculation of the runoff flow direction, wherein the saturated hydraulic conductivity of the soil represents the runoff conducting capacity of the soil, the stronger the water conductivity of the soil is, the easier the water content of the soil is increased, the runoff is easier to generate, the erodable factor of the soil represents the water erosion resistance of the soil, and the worse the water erosion resistance is, the easier the runoff is eroded by water to form. In this embodiment, the Soil saturation hydraulic conductivity and the Soil erodible factor may be calculated and obtained by using a SPAW (Soil-Plant-aggregate-Water) model and an EPIC (Soil Erosion-Productivity Impact estimation) model respectively on the basis of Soil texture parameters provided by a Soil database, and the Soil characteristic parameters are converted into Soil characteristic parameter grid data having the same resolution as the digital elevation model grid data by using a geographic information system processing software ArcGIS.
Therefore, the extraction of the watershed characteristics mainly comprises the steps of flow direction analysis, confluence analysis, water system extraction and the like, wherein the flow direction analysis is the core of the watershed extraction and directly influences the subsequent confluence area, the runoff path and the subsequent determination.
Alternatively, in the step S3, the soil erodible factor is calculated by the following formula:
wherein, SN1SAN, SIL, CLA and C represent the sand content, silt content, clay content and organic carbon content (%) of the soil in the area to be extracted, respectively, 1-SAN/100.
In this embodiment, the soil erodible factor of the region to be extracted is calculated by using an EPIC model. The EPIC model is a model specially designed for soil erosion and land productivity, and can calculate the soil erodible factor of the area to be extracted according to the sand content, the silt content, the clay content and the organic carbon content of the input soil.
Of course, in some other embodiments of the present application, the soil erodibility factor may also be calculated using the torri. d model or Shirazi formula. This is not a limitation of the present application.
Optionally, in step 402, the optimized distance weight difference is calculated by using the following formula:
h(i,j)＝tanβj·K(i,j)·KS(i,j)
h (i, j) represents the optimal distance weight difference between the ith central grid and the jth neighborhood grid, K (i, j) represents the soil erodible factor grid data of the ith central grid in the jth neighborhood grid direction, and K (i, j) represents the soil erodible factor grid data of the ith central grid in the jth neighborhood grid directionS(i, j) shows the soil saturation water conductivity grid data of the ith central grid in the jth neighborhood grid direction, tan betaj' denotes the distance weight difference between the center grid and the jth neighbor grid.
Table 3 shows the soil characteristic parameter grid data provided by the embodiment of fig. 1, and table 4 shows the optimized distance weight difference provided by the embodiment of fig. 1. Specifically, please combine table 2 and table 3, after calculating the distance weight difference between the central grid and the neighborhood grid, the soil characteristic parameter corresponding to each neighborhood grid is multiplied by the distance weight difference, and the obtained product is used as the optimized distance weight difference. Taking neighborhood grid m1 as an example, the grid corresponds to a soil characteristic parameter of 0.5, i.e., K (i, j) · KS(i, j) is 0.5, and the distance weight difference corresponding to the grid is set
Multiplying, namely calculating to obtain the optimal distance weight difference at the neighborhood grid m1
Further, the 8 neighborhood grids are respectively calculated according to the steps to obtain the optimal distance weight difference shown in table 4.
It can be understood that, in the embodiment, the distance weight fall is optimized by using the soil characteristic parameters, and the influence of the heterogeneity of soil spatial distribution on the runoff flow direction can be fully considered; particularly, the elevation, the saturated water conductivity of the soil and the soil erodibility factor are applied to flow direction analysis, so that the influence of two factors, namely the terrain and the soil after rainfall falls on the ground, on the formation of a radial flow path can be perfected, and the accuracy of basin extraction can be improved.
TABLE 3
| 0.5 | 0.2 | 0.3 |
| 1.5 | 0.4 | 0.3 |
| 1.6 | 1.6 | 0.2 |
TABLE 4
Optionally, in step 403, the step of determining the flow direction of the central grid according to the optimized distance weight difference includes:
when the optimal distance weight difference is a positive value, the flow direction is the central grid and flows out to the neighborhood grids;
when the optimal distance weight difference is a negative value, the flow direction is that the neighborhood grid flows into the center grid.
In this example, tan βjCharacterised by the magnitude of the terrain slope, tan betajThe larger the gradient is, the steeper the gradient is, the more easily the water flow flows to the place under the action of gravity, therefore, when the product of the soil saturation hydraulic conductivity grid data, the soil erodible factor grid data and the distance weight fall is larger, the steeper the terrain at the place and the more easily the covered soil collects the water flow, so that the distribution weight of the runoff flow of the accumulated water flow of the central grid flowing to the neighborhood grid is correspondingly larger, the comprehensive influence of the terrain and the soil on the flow direction is correctly reflected, and the reasonability and the accuracy of basin extraction are ensured.
Optionally, in step 404, the runoff distribution weight is calculated by using the following formula:
wherein r (i, j) represents the runoff distribution weight of the ith central grid in the jth neighborhood grid direction, L (i, j) represents the effective contour line of the ith central grid in the jth neighborhood grid direction, dx represents the side length of the central grid, h (i, j) represents the optimized distance weight difference between the ith central grid and the jth neighborhood grid, and m represents the number of the neighborhood grids.
In this embodiment, the number m of the neighborhood grids may be 8, and the effective contour line may be obtained by calculation using a cone inscribed circle method. It can be understood that the runoff distribution weight of each neighborhood grid is calculated through the elevation value, the soil erodible factor and the soil saturation hydraulic conductivity, the calculated confluence area value can reflect the influence of terrain change and soil parameters on water flow distribution, and then the runoff distribution is closer to the actual situation.
Optionally, in step 405, the step of determining a drainage basin region in the region to be extracted according to the preset threshold and the confluence area of the neighborhood grid includes:
determining a confluence area threshold;
traversing the data of the confluence area grids, comparing the confluence area threshold value with the confluence area value in each confluence area grid, and determining the confluence area grid with the confluence area value larger than the confluence area threshold value as a basin area.
Table 5 shows the flow distribution weights provided in the embodiment of fig. 1, and fig. 4 shows a schematic diagram of a confluence analysis provided in the embodiment of fig. 1. Referring to table 5 and fig. 4, in the present embodiment, if the upstream bus area value of the central grid is 1000 and the bus area threshold is 40, the bus area values corresponding to the neighborhood grids m4, m5, m6 and m7 are 44, 28, 708 and 220, respectively; further, neighborhood grids having a confluence area value of more than 40, that is, neighborhood grids m4, m6, and m7, are determined as the watershed regions.
It can be understood that the main purpose of the confluence analysis is to determine a flow path, a confluence area value represents the amount of water flowing through each neighborhood grid, the strength of the water flow convergence capacity of the neighborhood grids is reflected, and the larger the confluence area value is, the more water flows flowing to the neighborhood grids upstream are represented, and runoff is generated more easily. Therefore, a reasonable confluence area threshold is set according to the specific environment of the region to be extracted, and accuracy of basin calculation is improved.
TABLE 5
| 0.044 | ||
| 0.22 | 0.708 | 0.028 |
Optionally, the step of determining a watershed region in the region to be extracted according to a preset threshold includes:
determining a river basin network in the area to be extracted, and determining the river basin area according to the river basin network.
Specifically, the watershed extraction mainly includes extraction of a watershed boundary and a watershed river network. The river basin boundary is an important feature for defining the range of the river basin, and the river basin network is an important feature for determining the composition of the rainfall runoff converging path and the digital river network of the river basin. Obtaining accurate watershed characteristic information is an important prerequisite for watershed water balance estimation, water circulation process simulation, hydraulic engineering layout and scheduling.
Optionally, the step of determining a river network of a river basin in the area to be extracted includes:
traversing the grid data of the confluence area, determining the grid with the confluence area value equal to the confluence area threshold value as the starting point of the river network of the basin, and determining the grid with the maximum confluence area value as the water outlet of the basin.
It is understood that the watershed water outlet is a junction of different branch flows in the water system, is a merging grid of all grids in the sub-watershed and is also a grid for water flow of the sub-watershed. Specifically, from the connection relationship of the watershed water system structure, at least two confluence grids and one outflow grid are arranged on the critical peripheral grid of the water outlet, and the water flow of the sub-watershed is converged and flows out of the range of the sub-watershed, so that the maximum confluence area value is obtained. In addition, the larger the confluence area value of the water outlet, the easier the surface runoff is generated in the watershed, and the better the development degree of the river channel is.
In order to verify the influence of the terrain and soil on the runoff flow direction and the runoff distribution, the drainage basin extraction method based on the digital elevation and the soil parameters is described below by taking the bird-falling gorge drainage basin, the royal family dam drainage basin and the yellow bridge drainage basin in different climatic regions as examples.
Fig. 5a is a schematic view showing a DEM distribution of an ingale strait basin provided in the embodiment of the present application, fig. 6a is a schematic view showing a DEM distribution of a royal dam basin provided in the embodiment of the present application, and fig. 7a is a schematic view showing a DEM distribution of a yellow bridge basin provided in the embodiment of the present application, and the DEM resolutions of the three basins are all 1 km. The strait basin is located in a black river sub basin in an arid and semi-arid climate area, the Wangjia dam basin is located in a Huaihe river sub basin in a humid semi-humid area, and the yellow bridge basin is located in a Yangtze river sub basin in the humid area. Selecting an area where an ingale strait river basin is located, an area where a Wangjia river basin is located and an area where a yellow bridge river basin is located as areas to be extracted, and obtaining DEM raster data of the three areas to be extracted through DEM distribution shown in figures 5a, 6a and 7 a.
Fig. 5b, 6b and 7b are schematic diagrams illustrating distribution of saturation hydraulic conductivity of soil of the ingale strait valley, the royal dam valley and the yellow bridge valley provided in the embodiment of the present application, and fig. 5c, 6c and 7c are schematic diagrams illustrating distribution of corrosion factors of soil of the ingale strait valley, the royal dam valley and the yellow bridge valley provided in the embodiment of the present application. With reference to fig. 5b-7b and fig. 5c-7c, the soil characteristic parameters of the three regions to be extracted can be calculated and converted into soil characteristic parameter grid data. It will be appreciated that the resolution of the converted soil characteristic parameter grid data should be the same as the resolution of the DEM grid data, i.e. the resolution is also 1 Km.
Fig. 8a is a schematic diagram illustrating extraction results of bird-falling isthmus drainage basins based on elevation provided in the embodiment of the present application, fig. 8b is a schematic diagram illustrating extraction results of bird-falling isthmus drainage basins based on elevation and soil characteristic parameters provided in the embodiment of the present application, fig. 9a is a schematic diagram illustrating extraction results of royal family dam drainage basins based on elevation provided in the embodiment of the present application, fig. 9b is a schematic diagram illustrating extraction results of royal family dam drainage basins based on elevation and soil characteristic parameters provided in the embodiment of the present application, fig. 10a is a schematic diagram illustrating extraction results of yellow bridge drainage basins based on elevation provided in the embodiment of the present application, and fig. 10b is a schematic diagram illustrating extraction results of yellow bridge drainage basins based on elevation and soil characteristic parameters provided in the embodiment of the present application. And further, combining the DEM raster data and the soil characteristic parameter raster data, analyzing the flow direction of the area to be extracted and distributing runoff to obtain drainage basin extraction results of the three areas to be extracted. Referring to fig. 8a, 8b, 9a, 9b, 10a and 10b, compared with the method for extracting the drainage basin based on elevation alone, the drainage basin extraction method based on elevation and soil parameters provided by the present application does not cause abrupt and unacceptable changes in the drainage basin extraction result, and the influence of the spatial heterogeneity of the soil characteristic parameters on the runoff flow direction is mainly reflected at the beginning of the formation of the drainage basin network.
With continued reference to figures 8b, 9b and 10b, at the bird landing fjord a1, the radial flow path is diverted from the area covered with mollicgleysols (glm) soil to a location covered with gellicleptosols (lpi) soil; at B1 of the queen dam basin, the runoff path was diverted from eutrica planosols (ple) soil to Dystric cambis (CMd) soil; whereas at C1, C2 of the yellow bridge basin, the runoff path is diverted from Haplic acrises (Ach) soil to cumulilic anthrosols (atc) soil. Wherein, the saturated water conductivity of the soil GLm, LPi, PLe, CMd, Ach and ATc is 10.090, 59.350, 4.890, 21.490, 0.580 and 10.220 respectively, and the erodible factors of the soil are 0.283, 0.256, 0.214, 0.290, 0.263 and 0.329 respectively.
It can be seen that after the physical characteristic parameters of the soil are added, the local flow direction changes are from the soil with small saturated water conductivity and soil erodible factor to the soil with larger flow direction, i.e. the runoff flows to the soil with stronger water conductivity and erodibility more easily, which is consistent with the natural phenomenon that the runoff is more easily gathered and formed at the places with high water conductivity and erodibility in nature. Because the runoff path and the confluence distance of the small-scale watershed are short, the influence of the change of the initial runoff path on the watershed river network and the watershed boundary is more obvious, and compared with the watershed extraction based on elevation, the watershed extraction method based on the digital elevation and the soil parameters has more difference in the small-scale yellow bridge watershed.
According to the embodiment, the drainage basin extraction method based on the digital elevation and the soil parameters, provided by the invention, at least has the following beneficial effects:
according to the drainage basin extraction method based on the digital elevation and the soil parameters, the flow direction of the central grid is determined according to the grid data of the digital elevation model and the soil characteristic parameters, wherein the soil characteristic parameters comprise the soil saturation hydraulic conductivity and the soil erodible factor. On one hand, the saturated water conductivity of the soil represents the runoff conducting capacity of the soil, and the stronger the water conductivity of the soil is, the easier the water content of the soil is increased, so that runoff is easier to generate; on the other hand, the soil erodible factor represents the soil erosion resistance, and the worse the erosion resistance, the easier it is to be eroded by water to form runoff. Therefore, the method for extracting the drainage basin fully considers the influence of the heterogeneity of soil space distribution on the flow direction of the runoff, and further calculates the flow direction based on the elevation and the soil characteristic parameters, so that the accuracy of the drainage basin extraction is improved.
Although some specific embodiments of the present invention have been described in detail by way of examples, it should be understood by those skilled in the art that the above examples are for illustrative purposes only and are not intended to limit the scope of the present invention. It will be appreciated by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the invention. The scope of the invention is defined by the appended claims.
Claims (10)
1. A drainage basin extraction method based on digital elevation and soil parameters is characterized by comprising the following steps:
acquiring grid data of a digital elevation model of an area to be extracted;
according to the grid data of the digital elevation model, taking each grid as a central grid, and calculating the distance weight difference between each central grid and a neighborhood grid;
determining soil characteristic parameters of the area to be extracted, wherein the soil characteristic parameters comprise soil saturation hydraulic conductivity and soil erodible factors;
determining the flow direction of the central grids according to the distance weight difference, the saturated water conductivity of the soil and the soil erodible factor, and calculating the confluence area value of each grid;
and determining a river basin network and a river basin range in the area to be extracted according to a preset threshold value and the confluence area value of each grid.
2. The method for extracting watershed based on digital elevation and soil parameters according to claim 1, wherein the step of calculating distance weight difference between each central grid and a neighborhood grid by taking each grid as a central grid according to the grid data of the digital elevation model comprises:
detecting whether a depression exists in the terrain contained in the grid data of the digital elevation model; if yes, performing depression filling on the grid data of the digital elevation model;
and calculating the distance weight difference between each central grid and the adjacent grids thereof by iteration by taking each grid as the central grid in turn from the grid data of the digital elevation model.
3. The method for extracting watershed based on digital elevation and soil parameters according to claim 2, wherein the step of determining the flow direction of the central grid according to the distance weight fall, the soil saturation hydraulic conductivity and the soil erodible factor and calculating the confluence area value of each grid comprises:
converting the soil characteristic parameters into a two-dimensional array with the same resolution as the grid data of the digital elevation model to obtain grid data of the soil characteristic parameters; the soil characteristic parameter grid data comprise soil saturation hydraulic conductivity grid data and soil erodible factor grid data;
calculating the optimized distance weight drop of the central grid and the adjacent grids according to the distance weight drop, the soil saturated hydraulic conductivity grid data and the soil erodible factor grid data;
determining the flow direction of the central grid according to the optimized distance weight difference;
calculating the effective equal-height line length of the outflow of the central grid in the downhill direction, and calculating the runoff distribution weight of the central grid according to the optimized distance weight drop, the resolution of the grid data of the digital elevation model and the effective equal-height line length;
distributing the runoff flow in the ascending direction of the central grid according to the runoff distribution weight to obtain confluence area grid data; the convergence area grid data includes a convergence area value corresponding to each neighborhood grid.
4. The method for extracting watershed based on digital elevation and soil parameters according to claim 3, wherein the step of determining the flow direction of the central grid according to the optimized distance weight difference comprises:
when the optimal distance weight difference is a positive value, the flow direction is that the central grid flows out to the neighborhood grid;
and when the optimal distance weight difference is a negative value, the flow direction is that the neighborhood grid flows into the central grid.
5. The method for extracting watershed based on digital elevation and soil parameters according to claim 3, wherein the optimized distance weight difference is calculated by adopting the following formula:
h(i,j)＝tanβj·K(i,j)·KS(i,j)
h (i, j) represents the optimal distance weight difference between the ith central grid and the jth neighborhood grid, K (i, j) represents the soil erodible factor grid data of the ith central grid in the jth neighborhood grid direction, and K (i, j) represents the soil erodible factor grid data of the ith central grid in the jth neighborhood grid directionS(i, j) represents the soil saturation hydraulic conductivity grid of the ith central grid in the direction of the jth neighborhood gridLattice data, tan βjRepresenting the distance weight difference between the center grid and the jth neighbor grid.
6. The method for extracting watershed based on digital elevation and soil parameters according to claim 5, wherein the runoff distribution weight is calculated by adopting the following formula:
wherein r (i, j) represents the runoff distribution weight of the ith central grid in the jth neighborhood grid direction, L (i, j) represents the effective contour line of the ith central grid in the jth neighborhood grid direction, dx represents the side length of the central grid, h (i, j) represents the optimized distance weight difference between the ith central grid and the jth neighborhood grid, and m represents the number of the neighborhood grids.
7. The method for extracting watershed areas based on digital elevations and soil parameters according to claim 3, wherein the step of determining the watershed areas in the area to be extracted according to a preset threshold and the confluence area of the neighborhood grid comprises the following steps:
determining a confluence area threshold;
traversing the data of the confluence area grids, comparing the confluence area threshold value with the confluence area value in each confluence area grid, and determining the confluence area grid with the confluence area value larger than the confluence area threshold value as a basin area.
8. The method for extracting a drainage basin based on digital elevation and soil parameters as claimed in claim 7, wherein the step of determining the drainage basin area in the area to be extracted according to a preset threshold value comprises:
determining a river basin network in the area to be extracted, and determining a river basin area according to the river basin network.
9. The method for extracting river basin based on digital elevation and soil parameters according to claim 8, wherein the step of determining river basin and river network in the area to be extracted comprises the following steps:
traversing the confluence area grid data, determining the grid with the confluence area value equal to the confluence area threshold value as the starting point of the river basin and river network, and determining the grid with the maximum confluence area value as the water outlet of the river basin.
10. The method for extracting watershed based on digital elevation and soil parameters according to claim 1, wherein the soil erodible factor is calculated by adopting the following formula:
wherein, SN1SAN, SIL, CLA and C represent the sand content, silt content, clay content and organic carbon content (%) of the soil in the area to be extracted, respectively, 1-SAN/100.
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