A method and system for distinguishing watershed types considering surface morphological characteristics

Abstract

The present invention discloses a method for distinguishing the type of watershed considering the surface morphological characteristics, which is used in the field of resource and environmental management. The sub-watershed and slope distinguishing method includes the following steps: extracting the channel source of each channel according to the flow direction data and the channel data; tracing back from each channel source, searching for the longest flow path of the channel, and extracting the elevation value of each pixel on the flow path; using the elevation value of each pixel to calculate the embedding degree index of the longest flow path, and comparing it with the preset threshold value, the type of watershed is judged. The present invention can judge the actual type of the watershed by the degree of development of the internal channel of the watershed; it supports users to set the threshold according to their own needs, which is simple and fast, and has broad application prospects in terrain analysis, watershed simulation and other aspects.

Description

Technical Field

[0001] The present invention relates to the field of resource and environmental management, and in particular to a method and system for distinguishing watershed types by taking into account surface morphological characteristics. Background Art

[0002] In hydrography, a sub-basin is a system of secondary water systems in a watershed, which mainly covers smaller rivers or streams. A slope is a terrain area with a certain slope continuity and a relatively flat surface, usually with a watershed at the top and a channel at the bottom. In traditional terrain data analysis, the location of the river channel is determined by identifying the grid with a large cumulative flow, and the sub-basin corresponding to each river channel is extracted accordingly.

[0003] However, this method has limitations when dealing with longer slopes. Although the grids inside some slopes may show a large cumulative flow, indicating that water is concentrated there, the overall terrain is relatively flat and does not have the terrain features of an obvious embedded river channel. Therefore, dividing it into sub-basins does not conform to the actual physical geography. Conceptually, such areas are more appropriately defined as slopes rather than sub-basins.

[0004] At present, there is a lack of standard methods to effectively distinguish sub-basins and slopes in terrain data analysis, which limits the precise division and management of hydrological landforms. In order to improve the rationality of sub-basin and slope division, it is necessary to develop new geographic information system (GIS) technologies and algorithms. In addition, studying how to optimize the definition of sub-basins and slopes by combining rainfall data and soil type information will also be an important direction for future hydrological geography research.

[0005] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0006] In order to overcome the above problems, the present invention aims to propose a method and system for distinguishing watershed types taking into account surface morphological characteristics, with the aim of solving the problem of lack of a standard method for effectively distinguishing sub-basins and slopes in terrain data analysis, which limits the precise division and management of hydrological landforms. In order to improve the rationality of the division of sub-basins and slopes, it is necessary to develop new geographic information system technologies and algorithms.

[0007] To this end, the specific technical solution adopted by the present invention is as follows:

[0008] According to one aspect of the present invention, a method for distinguishing watershed types taking into account surface morphological characteristics is provided. The method for distinguishing sub-watersheds and slopes comprises the following steps:

[0009] S1. Extract the channel source of each channel according to the flow direction data and the channel data;

[0010] S2, trace back from the source of each channel, search for the longest flow path of the channel, and extract the elevation value of each pixel on the flow path;

[0011] S3. Use the elevation value of each pixel to calculate the embedding index of the longest flow path, and compare it with the preset threshold to determine the type of catchment area.

[0012] Optionally, the channel source includes source pixels of each channel and position information of the channel pixels.

[0013] Optionally, tracing back from the source of each channel, searching for the longest flow path of the channel, and extracting the elevation value of each pixel on the flow path includes the following steps:

[0014] S21, obtaining the channel source of each channel;

[0015] S22, taking the source of the channel as a pixel, using a breadth-first search algorithm to trace back upstream to record the position of each pixel and the distance from the source;

[0016] S23. Select the pixel farthest from the source of the channel, and use this pixel as the starting pixel to trace back the downstream pixels according to the flow direction data until the outlet of the catchment area, so as to obtain the longest flow path in the basin.

[0017] Optionally, taking the channel source as a pixel, tracing upstream using a breadth-first search algorithm to record the position of each pixel and the distance from the source includes the following steps:

[0018] S221, adding the channel source to the queue;

[0019] S222, each time a pixel is dequeued, the upstream pixel in the 8-neighborhood is searched, the distance between the upstream pixel and the source is recorded, and its position information is added to the queue;

[0020] S223, repeat the step of S222 until the queue is empty;

[0021] S224, selecting the pixel with the largest upstream pixel distance value as the starting pixel of the longest flow path, and tracing back to the downstream to obtain the longest flow path.

[0022] Optionally, using the elevation value of each pixel to calculate the embedding degree index of the longest flow path, and comparing it with a preset threshold, determining the type of the catchment area includes the following steps:

[0023] S31. Analyze the maximum elevation, minimum elevation and elevation difference of the flow path based on the longest flow path in the watershed;

[0024] S32, based on the analysis results, calculating the difference between the elevation value of each flow path pixel and the minimum elevation of the flow path, and calculating the cumulative elevation difference of all pixels inside the flow path;

[0025] S33, calculating the cumulative height difference when the terrain has no underlay;

[0026] S34, using the cumulative height difference of all pixels inside the flow path divided by the cumulative height difference when the terrain has no underlay, and then using the underlay degree index calculation formula of the longest flow path in the catchment area to calculate the underlay degree index of the longest flow path in the catchment area;

[0027] S35. Compare the embedding degree index of the longest flow path in the watershed with a preset threshold value to determine the type of the watershed.

[0028] Optionally, the calculation formula for the embedding degree index of the longest flow path in the catchment area is:

[0029]

[0030] Subembedding represents the degree of subembedding;

[0031] H low Indicates the minimum elevation of the flow path;

[0032] H high Indicates the maximum elevation of the flow path;

[0033] n represents the number of flow path pixels;

[0034] H i Indicates the elevation value of the flow path pixel.

[0035] Optionally, comparing the embedding degree index of the longest flow path in the catchment area with a preset threshold value to determine the type of the catchment area includes the following steps:

[0036] If the inset index of the longest flow path in the catchment is less than zero, it means that the terrain is not inset;

[0037] If the inset index of the longest flow path in the catchment area is higher than the preset threshold, it means that the terrain inset is high.

[0038] According to another aspect of the present invention, there is also provided a watershed type identification system taking into account surface morphological characteristics, the sub-watershed and slope identification system comprising: a channel source extraction module, a longest flow path search and elevation extraction module and a watershed type identification module;

[0039] The channel source extraction module, the longest flow path search and elevation extraction module, and the watershed type judgment module are connected in sequence;

[0040] A channel source extraction module is used to extract the channel source of each channel according to the flow direction data and the channel data;

[0041] The longest flow path search and elevation extraction module is used to trace back from the source of each channel, search for the longest flow path of the channel, and extract the elevation value of each pixel on the flow path;

[0042] The watershed type judgment module is used to calculate the embedding degree index of the longest flow path using the elevation value of each pixel, and compare it with the preset threshold to judge the type of the watershed.

[0043] Optionally, the channel source extraction module includes: a channel source extraction module, an upstream tracing and distance recording module, and a longest flow path tracing module;

[0044] The channel source extraction module, the upstream tracing and distance recording module, and the longest flow path tracing module are connected in sequence;

[0045] A channel source extraction module is used to obtain the channel source of each channel;

[0046] The upstream tracing and distance recording module is used to use the channel source as a pixel and use the breadth-first search algorithm to trace upstream to record the position of each pixel and the distance from the source;

[0047] The longest flow path tracing module is used to select the pixel farthest from the source of the channel, and trace the downstream pixels from this pixel as the starting pixel according to the flow direction data until the outlet of the catchment area to obtain the longest flow path in the basin.

[0048] Optionally, the longest flow path search and elevation extraction module includes: a flow path elevation analysis module, a flow path pixel elevation difference and cumulative elevation difference calculation module, a terrain no-underlay cumulative elevation difference calculation module, an underlay degree index calculation module and a watershed type judgment module;

[0049] The flow path elevation analysis module, the flow path pixel elevation difference and cumulative elevation difference calculation module, the terrain no-underlay cumulative elevation difference calculation module, the underlay degree index calculation module and the watershed type judgment module are connected in sequence;

[0050] Flow path elevation analysis module, used to analyze the maximum elevation, minimum elevation and elevation difference of the flow path based on the longest flow path in the basin;

[0051] The flow path pixel elevation difference and cumulative elevation difference calculation module is used to calculate the difference between the elevation value of each flow path pixel and the minimum elevation of the flow path based on the analysis results, and calculate the cumulative elevation difference of all pixels in the flow path;

[0052] The terrain without underlay cumulative height difference calculation module is used to calculate the cumulative height difference when the terrain has no underlay;

[0053] The embedding degree index calculation module is used to divide the cumulative height difference of all pixels in the flow path by the cumulative height difference when the terrain has no embedding, and then use the embedding degree index calculation formula of the longest flow path in the catchment area to calculate the embedding degree index of the longest flow path in the catchment area;

[0054] The watershed type judgment module is used to compare the embedding degree index of the longest flow path in the watershed with a preset threshold value to judge the type of the watershed.

[0055] Compared with the prior art, the present application has the following beneficial effects: the present invention can judge the actual type of the catchment area by the degree of development of the internal channels; it supports users to set thresholds according to their own needs, which is simple and fast, and has broad application prospects in terrain analysis, watershed simulation, etc.; the present invention proposes an embedded degree index by comparing the terrain characteristics of the sub-watershed and the slope, which makes up for the shortcomings in this aspect, clarifies the judgment conditions between the slope and the sub-watershed, improves the rationality of the discrimination of the hydrological and geomorphological units, and can provide more accurate input data for hydrological simulation, geomorphological analysis and other studies. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The above characteristics, features and advantages of the present invention and their implementation methods and methods will become more clearly understood in conjunction with the following description of the embodiments, which are described in detail in conjunction with the accompanying drawings. Herein, a schematic diagram is shown:

[0057] Figure 1 is a flow chart of a method for distinguishing watershed types considering surface morphological characteristics according to an embodiment of the present invention;

[0058] Figure 2 is a principle block diagram of a watershed type identification system taking into account surface morphological characteristics according to an embodiment of the present invention;

[0059] Figure 3 It is a schematic diagram of a structure for calculating the embedding degree in a method for distinguishing watershed types taking into account surface morphological characteristics according to an embodiment of the present invention;

[0060] Figure 4 This is a diagram showing the discrimination results of two watersheds in the Yangtze River Basin in a watershed type discrimination method taking into account surface morphological characteristics according to an embodiment of the present invention.

[0061] In the figure:

[0062] 1. Channel source extraction module; 2. Longest flow path search and elevation extraction module; 3. Watershed type judgment module. DETAILED DESCRIPTION

[0063] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0064] According to an embodiment of the present invention, a method and system for distinguishing the type of watershed taking into account the surface morphological characteristics are provided.

[0065] The present invention is further described with reference to the accompanying drawings and specific embodiments. Figure 1 , Figure 3-Figure 4 As shown, according to an embodiment of the present invention, a method for distinguishing watershed types taking into account surface morphological characteristics is provided. The sub-basin and slope distinguishing method comprises the following steps:

[0066] S1. Extract the channel source of each channel according to the flow direction data and the channel data.

[0067] Preferably, the channel source includes the source pixel of each channel and the position information of the channel pixel.

[0068] S2. Trace back from the source of each channel, search for the longest flow path of the channel, and extract the elevation value of each pixel on the flow path.

[0069] Preferably, tracing back from the source of each channel, searching for the longest flow path of the channel, and extracting the elevation value of each pixel on the flow path includes the following steps:

[0070] S21, obtaining the channel source of each channel. In the channel network, each non-channel grid has at least one upstream pixel of the channel, so as to determine whether it is the source. After the source is determined, the source is used as the pixel;

[0071] S22, taking the source of the channel as a pixel, using a breadth-first search algorithm to trace back upstream to record the position of each pixel and the distance from the source;

[0072] S23. Select the pixel farthest from the source of the channel, and use this pixel as the starting pixel to trace back the downstream pixels according to the flow direction data until the outlet of the catchment area, so as to obtain the longest flow path in the basin.

[0073] Preferably, taking the channel source as a pixel, tracing upstream using a breadth-first search algorithm to record the position of each pixel and the distance from the source includes the following steps:

[0074] S221, adding the channel source to a queue. A queue is a data structure that can be created using a list in Python. The meaning of the queue in each step may be different. The queue in this step stores the traced upstream pixels.

[0075] S222, each time a pixel is dequeued, the upstream pixel in the 8-neighborhood is searched, the distance between the upstream pixel and the source is recorded, and its position information is added to the queue;

[0076] S223, repeat the step of S222 until the queue is empty;

[0077] S224, selecting the pixel with the largest upstream pixel distance value as the starting pixel of the longest flow path, and tracing back to the downstream to obtain the longest flow path.

[0078] S3. Use the elevation value of each pixel to calculate the embedding index of the longest flow path, and compare it with the preset threshold to determine the type of catchment area.

[0079] Preferably, the elevation value of each pixel is used to calculate the embedding degree index of the longest flow path, and compared with a preset threshold value, and the type of the catchment area is determined, including the following steps:

[0080] S31. Analyze the maximum elevation, minimum elevation and elevation difference of the flow path based on the longest flow path in the watershed;

[0081] S32, based on the analysis results, calculating the difference between the elevation value of each flow path pixel and the minimum elevation of the flow path, and calculating the cumulative elevation difference of all pixels inside the flow path;

[0082] S33, calculating the cumulative height difference when the terrain has no underlay;

[0083] S34, using the cumulative height difference of all pixels inside the flow path divided by the cumulative height difference when the terrain has no underlay, and then using the underlay degree index calculation formula of the longest flow path in the catchment area to calculate the underlay degree index of the longest flow path in the catchment area;

[0084] S35. Compare the embedding degree index of the longest flow path in the watershed with a preset threshold value to determine the type of the watershed.

[0085] Preferably, the calculation formula for the embedding degree index of the longest flow path in the catchment area is:

[0086]

[0087] Subembedding represents the degree of subembedding;

[0088] H low Indicates the minimum elevation of the flow path;

[0089] H high Indicates the maximum elevation of the flow path;

[0090] n represents the number of flow path pixels;

[0091] H i Indicates the elevation value of the flow path pixel.

[0092] Preferably, comparing the embedding degree index of the longest flow path in the catchment area with a preset threshold value to determine the type of the catchment area comprises the following steps:

[0093] If the inset index of the longest flow path in the catchment is zero, it means that the terrain has no inset;

[0094] If the inset index of the longest flow path in the catchment area is higher than the preset threshold, it means that the terrain inset is high.

[0095] In addition, the principle of the present invention is that the development degree of the sub-basin and the slope is different, that is, the slope is flatter than the sub-basin, the ditch of the sub-basin is eroded by river water all year round, and the degree of embedding is large, while the degree of embedding of the slope is small; based on this, a ditch embedding factor is proposed to quantitatively measure the landform development stage, and then the sub-basin and slope are distinguished.

[0096] According to another embodiment of the present invention, Figure 2 As shown, a watershed type discrimination system considering surface morphological characteristics is also provided, and the sub-watershed and slope discrimination system includes: a channel source extraction module 1, a longest flow path search and elevation extraction module 2 and a watershed type judgment module 3;

[0097] The channel source extraction module 1, the longest flow path search and elevation extraction module 2 and the watershed type judgment module 3 are connected in sequence;

[0098] A channel source extraction module 1 is used to extract the channel source of each channel according to the flow direction data and the channel data;

[0099] The longest flow path search and elevation extraction module 2 is used to trace back from the source of each channel, search for the longest flow path of the channel, and extract the elevation value of each pixel on the flow path;

[0100] The watershed type judgment module 3 is used to calculate the embedding degree index of the longest flow path using the elevation value of each pixel, and compare it with a preset threshold to judge the type of the watershed.

[0101] Preferably, the channel source extraction module 2 includes: a channel source extraction module, an upstream tracing and distance recording module and a longest flow path tracing module;

[0102] The channel source extraction module, the upstream tracing and distance recording module, and the longest flow path tracing module are connected in sequence;

[0103] A channel source extraction module is used to obtain the channel source of each channel;

[0104] The upstream tracing and distance recording module is used to use the channel source as a pixel and use the breadth-first search algorithm to trace upstream to record the position of each pixel and the distance from the source;

[0105] The longest flow path tracing module is used to select the pixel farthest from the source of the channel, trace the downstream pixels from this pixel according to the flow direction data until the outlet of the catchment area, and obtain the longest flow path in the basin.

[0106] Preferably, the longest flow path search and elevation extraction module 3 includes: a flow path elevation analysis module, a flow path pixel elevation difference and cumulative elevation difference calculation module, a terrain no-underlay cumulative elevation difference calculation module, an underlay degree index calculation module and a watershed type judgment module;

[0107] The flow path elevation analysis module, the flow path pixel elevation difference and cumulative elevation difference calculation module, the terrain no-underlay cumulative elevation difference calculation module, the underlay degree index calculation module and the watershed type judgment module are connected in sequence;

[0108] Flow path elevation analysis module, used to analyze the maximum elevation, minimum elevation and elevation difference of the flow path based on the longest flow path in the basin;

[0109] The flow path pixel elevation difference and cumulative elevation difference calculation module is used to calculate the difference between the elevation value of each flow path pixel and the minimum elevation of the flow path based on the analysis results, and calculate the cumulative elevation difference of all pixels in the flow path;

[0110] The cumulative height difference calculation module for terrain without underlay is used to calculate the cumulative height difference when the terrain has no underlay. The cumulative height difference here is the difference between all pixels in the longest flow path and the lowest elevation, which is used for subsequent calculations.

[0111] The module for calculating the degree of embedding index is used to divide the cumulative height difference of all pixels inside the flow path by the cumulative height difference when the terrain has no embedding, wherein the cumulative height difference at this location is the difference between the elevation (assumed value) of the longest flow path pixel and the lowest elevation when the terrain has no embedding, and then use the calculation formula for the degree of embedding index of the longest flow path in the catchment area to calculate the degree of embedding index of the longest flow path in the catchment area;

[0112] The watershed type judgment module is used to compare the embedding degree index of the longest flow path in the watershed with a preset threshold value to judge the type of the watershed.

[0113] Specific examples are as follows:

[0114] 1) Based on the digital elevation model (DEM), the D8 flow algorithm (the D8 algorithm is a commonly used single flow algorithm, the principle is to calculate the slope of the central pixel and the pixels in the 8 neighborhoods, and the water will flow from the central pixel into the neighborhood grid with the largest slope) is used to extract the flow direction, confluence accumulation and channel network data;

[0115] 2) Based on the flow direction data, extract the source of each channel in the channel network in the catchment area and the location information of the channel pixel. In the channel data, each non-channel pixel has at least one upstream channel pixel, so as to determine whether it is the source;

[0116] 3) After the source is determined, the source is used as a pixel and the breadth-first search algorithm is used to trace back upstream to record the location of each pixel and its distance from the source;

[0117] 4) Select the pixel farthest from the source of the channel, and trace the downstream pixel from this pixel according to the flow direction data until the outlet of the catchment area. The traced path is the longest flow path in the basin;

[0118] 5) Calculate the maximum elevation, minimum elevation and elevation difference of the longest flow path, calculate the difference between the elevation value of each flow path pixel and the minimum elevation of the flow path, and calculate the cumulative elevation difference of all flow path pixels;

[0119] 6) Calculate the cumulative height difference when there is no inset in the terrain, that is, "the area of ​​a triangle whose length is the horizontal projection length of the flow path and whose height is the height difference between the starting pixel of the flow path and the pixel of the outlet";

[0120] 7) Use the actual cumulative height difference obtained in step 6 to divide the cumulative height difference obtained in step 7 when the terrain has no underembedded area, and then subtract the calculated quotient from "1" to take the absolute value, which is the underembedded degree index of the longest flow path in the catchment area. The minimum value of this index is 0, indicating that the terrain has no underembedded area at all; the maximum value is close to 1, indicating that the terrain has a very high degree of underembedded area;

[0121] 8) 0.65 is used as the preset threshold for judgment (this threshold can be adjusted according to the situation). If the embedding degree is greater than 0.65, it is a sub-basin; otherwise, it is a slope surface.

[0122] In summary, compared with the existing methods, the present invention can judge the actual type of the catchment area by the degree of development of the internal channels; it supports users to set thresholds according to their own needs, which is simple and fast, and has broad application prospects in terrain analysis, watershed simulation, etc.

[0123] In summary, with the help of the above technical scheme of the present invention, the present invention can judge the actual type of the watershed by the degree of development of the internal channels of the watershed; it supports users to set thresholds according to their own needs, which is simple and fast, and has broad application prospects in terrain analysis, watershed simulation, etc.; the present invention compares the terrain characteristics of the sub-basin and the slope, proposes an embedded degree index, which makes up for the shortcomings in this aspect, clarifies the judgment conditions between the slope and the sub-basin, and improves the rationality of the discrimination of hydrological and geomorphological units, which can provide more accurate input data for hydrological simulation, geomorphological analysis and other studies.

[0124] Although the present invention has been disclosed as above with preferred embodiments, the embodiments are merely examples for the convenience of description and are not intended to limit the present invention. Those skilled in the art may make several changes and modifications without departing from the spirit and scope of the present invention. The scope of protection claimed by the present invention shall be based on the claims.

Claims

1. A method for distinguishing watershed types considering surface morphological characteristics, It is characterized in that The sub-basin and slope identification method includes the following steps: S1. Extract the channel source of each channel according to the flow direction data and the channel data; S2, trace back from the source of each channel, search for the longest flow path of the channel, and extract the elevation value of each pixel on the flow path; S3, using the elevation value of each pixel to calculate the embedding degree index of the longest flow path, and comparing it with the preset threshold to determine the type of the catchment area; The method of calculating the embedding degree index of the longest flow path by using the elevation value of each pixel and comparing it with a preset threshold value to determine the type of the catchment area includes the following steps: S31. Analyze the maximum elevation, minimum elevation and elevation difference of the flow path based on the longest flow path in the watershed; S32, based on the analysis results, calculating the difference between the elevation value of each flow path pixel and the minimum elevation of the flow path, and calculating the cumulative elevation difference of all pixels inside the flow path; S33, calculating the cumulative height difference when the terrain has no underlay; S34, using the cumulative height difference of all pixels inside the flow path divided by the cumulative height difference when the terrain has no underlay, and then using the underlay degree index calculation formula of the longest flow path in the catchment area to calculate the underlay degree index of the longest flow path in the catchment area; S35, comparing the embedding degree index of the longest flow path in the catchment area with a preset threshold value to determine the type of the catchment area; The calculation formula for the embedding degree index of the longest flow path in the catchment area is: Subembedding represents the degree of subembedding; H low Indicates the minimum elevation of the flow path; H high Indicates the maximum elevation of the flow path; n represents the number of flow path pixels; H i Indicates the elevation value of the flow path pixel; The step of comparing the embedding degree index of the longest flow path in the catchment area with a preset threshold value to determine the type of the catchment area comprises the following steps: If the inset index of the longest flow path in the catchment is less than zero, it means that the terrain is not inset; If the inset index of the longest flow path in the catchment area is higher than the preset threshold, it means that the terrain inset is high.

2. A method for distinguishing watershed types by considering surface morphological characteristics according to claim 1, It is characterized in that The channel source includes the source pixel of each channel and the position information of the channel pixel.

3. A method for distinguishing watershed types by considering surface morphological characteristics according to claim 1, It is characterized in that The method of tracing back from the source of each channel, searching for the longest flow path of the channel, and extracting the elevation value of each pixel on the flow path includes the following steps: S21, obtaining the channel source of each channel; S22, taking the source of the channel as a pixel, using a breadth-first search algorithm to trace back upstream to record the position of each pixel and the distance from the source; S23. Select the pixel farthest from the source of the channel, and use this pixel as the starting pixel to trace back the downstream pixels according to the flow direction data until the outlet of the catchment area, so as to obtain the longest flow path in the basin.

4. A method for distinguishing watershed types taking into account surface morphological characteristics according to claim 3, It is characterized in that The method of taking the channel source as a pixel and using a breadth-first search algorithm to trace upstream to record the position of each pixel and the distance from the source includes the following steps: S221, adding the channel source to the queue; S222, each time a pixel is dequeued, the upstream pixel in the 8-neighborhood is searched, the distance between the upstream pixel and the source is recorded, and its position information is added to the queue; S223, repeat the step of S222 until the queue is empty; S224, selecting the pixel with the largest upstream pixel distance value as the starting pixel of the longest flow path, and tracing back to the downstream to obtain the longest flow path.

5. A system for distinguishing watershed types by considering surface morphological features, for implementing the method for distinguishing watershed types by considering surface morphological features as claimed in any one of claims 1 to 4, It is characterized in that The sub-basin and slope identification system includes: channel source extraction module, longest flow path search and elevation extraction module and watershed type judgment module; The channel source extraction module, the longest flow path search and elevation extraction module, and the watershed type judgment module are connected in sequence; A channel source extraction module is used to extract the channel source of each channel according to the flow direction data and the channel data; The longest flow path search and elevation extraction module is used to trace back from the source of each channel, search for the longest flow path of the channel, and extract the elevation value of each pixel on the flow path; The watershed type judgment module is used to calculate the embedding degree index of the longest flow path using the elevation value of each pixel, and compare it with the preset threshold to judge the type of the watershed.

6. A watershed type identification system taking into account surface morphological characteristics according to claim 5, It is characterized in that The channel source extraction module includes: a channel source extraction module, an upstream tracing and distance recording module and a longest flow path tracing module; The channel source extraction module, the upstream tracing and distance recording module, and the longest flow path tracing module are connected in sequence; A channel source extraction module is used to obtain the channel source of each channel; The upstream tracing and distance recording module is used to use the channel source as a pixel and use the breadth-first search algorithm to trace upstream to record the position of each pixel and the distance from the source; The longest flow path tracing module is used to select the pixel farthest from the source of the channel, trace the downstream pixels from this pixel according to the flow direction data until the outlet of the catchment area, and obtain the longest flow path in the basin.

7. A watershed type identification system taking into account surface morphological characteristics according to claim 6, It is characterized in that The longest flow path search and elevation extraction module includes: a flow path elevation analysis module, a flow path pixel elevation difference and cumulative elevation difference calculation module, a terrain no underlay cumulative elevation difference calculation module, an underlay degree index calculation module and a watershed type judgment module; The flow path elevation analysis module, the flow path pixel elevation difference and cumulative elevation difference calculation module, the terrain no-underlay cumulative elevation difference calculation module, the underlay degree index calculation module and the watershed type judgment module are connected in sequence; Flow path elevation analysis module, used to analyze the maximum elevation, minimum elevation and elevation difference of the flow path based on the longest flow path in the basin; The flow path pixel elevation difference and cumulative elevation difference calculation module is used to calculate the difference between the elevation value of each flow path pixel and the minimum elevation of the flow path based on the analysis results, and calculate the cumulative elevation difference of all pixels in the flow path; The terrain without underlay cumulative height difference calculation module is used to calculate the cumulative height difference when the terrain has no underlay; The embedding degree index calculation module is used to divide the cumulative height difference of all pixels in the flow path by the cumulative height difference when the terrain has no embedding, and then use the embedding degree index calculation formula of the longest flow path in the catchment area to calculate the embedding degree index of the longest flow path in the catchment area; The watershed type judgment module is used to compare the embedding degree index of the longest flow path in the watershed with a preset threshold value to judge the type of the watershed.

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