Water and soil conservation measure laying method based on sediment connectivity

Abstract

The invention discloses a sediment connectivity-based water and soil conservation measure layout method, which comprises the following steps of: selecting a multispectral unmanned aerial vehicle to carry out aerial survey work of a target watershed so as to obtain unmanned aerial vehicle multispectral data, a digital elevation model and land utilization data in the target watershed; based on the unmanned aerial vehicle multispectral data, the digital elevation model and the land utilization data, obtaining sediment connectivity index spatial distribution in the target drainage basin; based on the sediment connectivity index spatial distribution, identifying a sediment connectivity high-low threshold region in the target drainage basin; erosion characteristics in the sediment connectivity high-low threshold region are obtained, and water and soil conservation measures in the target drainage basin are planned according to the erosion characteristics; and comprehensively evaluating the water and soil conservation measures by adopting an entropy weight method. The transportation process of silt from the source to the downstream is comprehensively considered, the limitation that traditional water and soil conservation measures are laid based on experience or local observation data is made up, and the scientificity, rationality and comprehensive benefits of the water and soil conservation measures are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural water and soil engineering, and more specifically, to a method for arranging soil and water conservation measures based on sediment connectivity. Background Art

[0002] Existing soil and water conservation measures mainly rely on empirical rules or local observation data, and determine the arrangement location and type through field investigations, historical data analysis, etc. These methods usually use basic data such as traditional topographic maps and soil type maps, and combine certain on-site measurement results for planning. In addition, some modern technologies such as Geographic Information System (GIS) are also used for auxiliary analysis, but their applications mostly stay at the basic level of topographic and geomorphic analysis, and fail to make full use of multi-source data for comprehensive evaluation.

[0003] Therefore, although the existing technologies can guide soil and water conservation work to a certain extent, there are still the following limitations:

[0004] 1. Lack of systematicness: Traditional methods focus on local observation data, ignoring the dynamic changes in the sediment transportation process from the source to the downstream, and it is difficult to comprehensively reflect the sediment transport path and its connectivity characteristics.

[0005] 2. Insufficient accuracy: The analysis methods based on experience and simple data cannot accurately identify erosion hotspots, resulting in waste of resources and poor treatment effects.

[0006] 3. Low data utilization efficiency: Although there is abundant multi-source data available, due to the lack of effective integration means, the potential of these data cannot be fully exerted.

[0007] Therefore, how to improve the scientificity, rationality and comprehensive benefits of soil and water conservation measures through scientific analysis and optimized design is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0008] In view of the above problems, the present invention provides a method for arranging soil and water conservation measures based on sediment connectivity to at least solve some of the technical problems mentioned in the above background art.

[0009] In order to achieve the above object, the present invention adopts the following technical solutions:

[0010] The present invention provides a method for arranging soil and water conservation measures based on sediment connectivity, including the following steps:

[0011] S1. Select a multi-spectral unmanned aerial vehicle for aerial survey of the target basin to obtain unmanned aerial vehicle multi-spectral data, digital elevation model and land use data within the target basin;

[0012] S2. Obtain the spatial distribution of sediment connectivity index within the target watershed based on the multi-spectral data of the UAV, the digital elevation model, and the land use data;

[0013] S3. Identify the high and low threshold regions of sediment connectivity within the target watershed based on the spatial distribution of the sediment connectivity index;

[0014] S4. Obtain the erosion characteristics within the high and low threshold regions of sediment connectivity, and plan soil and water conservation measures within the target watershed according to the erosion characteristics;

[0015] S5. Conduct a comprehensive evaluation of the soil and water conservation measures using the entropy weight method.

[0016] Further, the specific steps of step S1 include:

[0017] Use DJI Terra software for flight path planning; select the terrain-following flight mode for the UAV, maintain a constant altitude of 60 m from the ground; and set the heading overlap rate to 90% and the side overlap rate to 80%; set 3 - 5 ground control points within the target watershed before aerial photography, fix the red and white triangular targets with ground nails as ground control points, and measure the coordinates of the control points with a handheld RTK-GPS for aerial survey image correction; use DJI Terra software to process the UAV aerial survey images, generate the digital elevation model within the target watershed, and generate the multi-spectral data of the UAV based on the red light and near-infrared spectral data.

[0018] Further, the specific steps of step S2 include:

[0019] Based on the multi-spectral data of the UAV, obtain the vegetation cover factor layer within the target watershed;

[0020] Based on the digital elevation model and the land use data, obtain the water flow direction, the flow accumulation layer, and the slope factor layer within the target watershed;

[0021] Based on the vegetation cover factor layer, the water flow direction, the flow accumulation layer, and the slope factor layer, obtain the downhill component and the uphill component;

[0022] Calculate the spatial distribution of the sediment connectivity index according to the downhill component and the uphill component.

[0023] Further, the obtaining of the vegetation cover factor layer within the target watershed based on the multi-spectral data of the UAV specifically includes:

[0024] Extract the normalized difference vegetation index data from the multi-spectral data of the UAV;

[0025] Based on the normalized difference vegetation index corresponding to each grid, obtain the vegetation coverage corresponding to each grid;

[0026] Based on the vegetation coverage corresponding to each grid, a vegetation coverage factor layer corresponding to each grid is obtained.

[0027] Furthermore, the obtaining of the water flow direction, the flow accumulation layer and the slope factor layer within the target basin based on the digital elevation model and land use data specifically includes:

[0028] 1) Obtain DEM data from the digital elevation model, and use the filling tool of the ArcGIS platform to perform filling processing on the DEM data; use the water flow direction tool in the spatial analysis tool to extract the water flow direction after filling the DEM, denoted as FlowDir; based on the DEM data, use the slope tool in spatial analysis, and set the slope unit to percentage, denoted as the slopeS layer; calculate the slope factor layer based on the slopeS layer;

[0029] 2) Based on the digital elevation model, use the reclassification tool to identify the land use types within the target basin and assign values to obtain the reclassified land use layer, the Landuse layer; overlay the Landuse layer with the slope factor layer to obtain the land use layer Sx layer under different slopes; based on FlowDir affected by different slopes, use the flow accumulation tool in spatial analysis to calculate the amount of water flowing through the grid cells to obtain the flow accumulation AccSX layer; similarly, overlay the Landuse layer with the vegetation coverage factor layer to obtain the flow accumulation AccCX layer;

[0030] 3) Based on the above FlowDir, input Landuse into the flow accumulation tool in spatial analysis to obtain the flow accumulation, denoted as FlowAcc; based on the raster calculator, add 1 to the flow accumulation value of each grid of FlowAcc to obtain the final flow accumulation layer, denoted as the AccFinal layer.

[0031] Furthermore, the obtaining process of the downhill component includes:

[0032] Calculate the downhill distance along the flow path from each pixel to the sink or outlet on the grid edge, denoted as FlowLen; use the raster data with FlowDir as the water flow direction; use the slope factor and the vegetation coverage factor as the first weight raster data and the second weight raster data respectively; based on the raster calculator, multiply FlowLen, the raster data, the first weight raster data and the second weight raster data to obtain the downhill component.

[0033] The obtaining process of the uphill component includes:

[0034] Based on the slope factor layer, AccSX layer, and AccFinal layer, S mean layer is calculated through a raster calculator; similarly, the AccFinal layer, AccCX layer, and vegetation cover factor layer are selected to calculate the W mean layer; finally, the S mean layer, W mean layer, and AccFinal layer are multiplied by the cell control area to obtain the uphill component layer.

[0035] Furthermore, step S3 specifically includes:

[0036] Based on the ArcGis platform, extract the high-value pixels and low-value pixels in the sediment connectivity index distribution map; use the areas corresponding to the high-value pixels and low-value pixels as the high and low threshold areas of sediment connectivity;

[0037] Among them, the high-value pixels are the pixels of the high point threshold; the low-value pixels are the pixels less than the low point threshold.

[0038] Furthermore, determine the 90th percentile of the distribution characteristics of the sediment connectivity index distribution map in the target watershed as the high point threshold, and the 10th percentile as the low point threshold.

[0039] Furthermore, step S4 specifically includes:

[0040] Based on the ArcGis platform, load the on-site RTK measurement data in tabular form, convert the longitude and latitude in the table into a point layer and export it in vector point format; set the vector point as the target layer and the RTK measurement data as the connection layer, and connect based on the nearest distance to match each vector point with the nearest RTK point;

[0041] Load the sediment connectivity index distribution map file and the orthoimage file, and convert the coordinate systems of these two files to be consistent; overlay the sediment connectivity index distribution map file with the orthoimage file by modifying the attributes and transparency to observe the corresponding relationship between the high threshold area of sediment connectivity and the surface features; compare the spatial distribution of the high threshold area of sediment connectivity and the surface features by adjusting the transparency or switching the layer order; finally, divide the target watershed into different levels and plan the soil and water conservation measures.

[0042] Furthermore, in step S5, the normalized difference vegetation index and the sediment connectivity index are used as entropy weight indicators; the weights of the normalized difference vegetation index and the sediment connectivity index are calculated respectively by the entropy weight method, and the comprehensive effect of the soil and water conservation measures is evaluated based on the weights.

[0043] As can be seen from the above technical solutions, compared with the prior art, the present invention discloses a method for arranging soil and water conservation measures based on sediment connectivity, which has the following beneficial effects:

[0044] The present invention comprehensively considers the sediment transportation process from the source to the downstream, makes up for the limitations of traditional soil and water conservation measures arranged based on experience or local observation data, significantly improves the scientificity, rationality and comprehensive benefits of soil and water conservation measures, and is applicable to the systematic treatment of agricultural small watersheds.

[0045] The present invention uses the cold and hot spot areas of the sediment connectivity index, combines orthophoto images and field investigations to accurately identify erosion hot spot areas, and plans comprehensive soil and water conservation measures according to erosion characteristics and sediment transport paths, which helps to improve the rationality of soil and water conservation measures.

[0046] The technical solutions of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0048] Figure 1 It is a schematic flow chart of the method for arranging soil and water conservation measures based on sediment connectivity provided by the embodiment of the present invention.

[0049] Figure 2 It is a schematic diagram of the sediment connectivity calculation framework provided by the embodiment of the present invention.

[0050] Figure 3 It is a schematic diagram of the comparison between sediment connectivity and orthophoto image provided by the embodiment of the present invention.

[0051] Figure 4 It is a schematic diagram of the soil and water conservation measures provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0053] The embodiment of the present invention discloses a method for arranging soil and water conservation measures based on sediment connectivity. SeeFigure 1 As shown in the figure, it includes the following steps:

[0054] S1. Select a multispectral drone to conduct aerial survey work on the target basin to obtain drone multispectral data, digital elevation model, and land use data within the target basin;

[0055] S2. Based on the drone multispectral data, digital elevation model, and land use data, obtain the spatial distribution of sediment connectivity index within the target basin;

[0056] S3. Based on the spatial distribution of the sediment connectivity index, identify the high and low threshold regions of sediment connectivity within the target basin;

[0057] S4. Obtain the erosion characteristics within the high and low threshold regions of sediment connectivity, and plan soil and water conservation measures within the target basin according to the erosion characteristics;

[0058] S5. Use the entropy weight method to comprehensively evaluate the soil and water conservation measures.

[0059] Next, each of the above steps will be described in detail:

[0060] In the above step S1, select a multispectral drone to conduct aerial survey work on the target basin to obtain drone multispectral data, digital elevation model (DEM), and land use data within the target basin; it includes:

[0061] Use DJI Terra software for flight line planning. Considering the large terrain undulation within the target basin, the flight mode of the drone is selected as terrain-following flight, maintaining a constant height of 60 m from the ground; and set the heading overlap rate to 90% and the side overlap rate to 80%; before aerial photography, set 3 - 5 ground control points within the target basin, use ground nails to fix the red and white triangular target as the ground control point, and use a handheld RTK-GPS to measure the coordinates of the control point for aerial survey image correction; use DJI Terra software to process the drone aerial survey images, generate a digital elevation model within the target basin, and generate drone multispectral data based on red light and near-infrared spectral data.

[0062] In the above step S2, obtain the spatial distribution of the sediment connectivity index within the target basin; it includes:

[0063] S21. Based on the drone multispectral data, obtain the vegetation cover factor layer within the target basin; based on the digital elevation model, obtain the water flow direction, flow accumulation layer, and slope factor layer within the target basin; specifically:

[0064] (1) Based on satellite image data, obtain the vegetation cover factor within the target basin, specifically including:

[0065] 1) Extract the normalized difference vegetation index (NDVI) data from the multi - spectral data of the unmanned aerial vehicle (UAV).

[0066] 2) Based on the NDVI corresponding to each grid, obtain the fractional vegetation cover (FVC) corresponding to each grid, expressed as:

[0067]

[0068] where FCV i represents the fractional vegetation cover corresponding to the \(i\) - th grid; NDVI i represents the normalized difference vegetation index corresponding to the \(i\) - th grid; NDVI min represents the minimum value of the normalized difference vegetation index. It can be the smallest one among all the normalized difference vegetation indices in the top 5% after arranging all the normalized difference vegetation indices corresponding to each grid in ascending order; NDVI max represents the maximum value of the minimum normalized difference vegetation index. It can be the largest one among all the normalized difference vegetation indices in the top 95% after arranging all the normalized difference vegetation indices corresponding to each grid in ascending order.

[0069] 3) Based on the fractional vegetation cover corresponding to each grid, obtain the vegetation cover factor layer corresponding to each grid, expressed as:

[0070]

[0071] where FCV i represents the fractional vegetation cover corresponding to the \(i\) - th grid; C i represents the vegetation cover factor corresponding to the \(i\) - th grid.

[0072] (2) Based on the digital elevation model (DEM) and land - use data, obtain the flow direction, flow accumulation layer, and slope factor layer within the target basin, specifically including:

[0073] 1) Obtain the DEM data from the digital elevation model, and use the fill tool in the ArcGIS platform to fill the depressions in the DEM data; use the flow direction tool in the spatial analysis tool to extract the flow direction after filling the DEM depressions, denoted as FlowDir; based on the DEM data, use the slope tool in the spatial analysis, set the slope unit to percentage, denoted as the slopeS layer; calculate the slope factor layer based on the slopeS layer. Specifically, assign the pixels with slope values less than 0.5 in the slope file to 0.005, the pixels with slope values greater than 100 to 1, and divide the remaining values by 100 to obtain the slope factor.

[0074] 2) Based on the digital elevation model, use the reclassification tool to identify the land use types within the target watershed and assign values to obtain the reclassified land use layer, the Landuse layer; overlay the Landuse layer with the slope factor layer to obtain the land use layer under different slopes, the Sx layer; based on the FlowDir affected by different slopes, use the flow accumulation tool in spatial analysis to calculate the amount of water flowing through the raster cells to obtain the flow accumulation layer, the AccSX layer; similarly, overlay the Landuse layer with the vegetation cover factor layer to obtain the flow accumulation layer, the AccCX layer.

[0075] 3) Based on the above FlowDir, input Landuse into the flow accumulation tool in spatial analysis to obtain the flow accumulation, denoted as FlowAcc; based on the raster calculator, add 1 to the flow accumulation value of each raster in FlowAcc to obtain the final flow accumulation layer, denoted as the AccFinal layer.

[0076] S22. Based on the vegetation cover factor layer, the water flow direction, the flow accumulation layer, and the slope factor layer, obtain the downhill component and the uphill component; specifically:

[0077] (1) The acquisition process corresponding to the downhill component includes:

[0078] Through the flow length tool in spatial analysis, calculate the downhill distance along the flow path from each pixel to the confluence point or the outlet on the raster edge, denoted as FlowLen; use the final water flow direction FlowDir within the target watershed as the raster data of the water flow direction; use the slope factor and the vegetation cover factor as the first weight raster data and the second weight raster data respectively; based on the raster calculator, multiply FlowLen, the raster data, the first weight raster data, and the second weight raster data to obtain the downhill component.

[0079] (2) The acquisition process corresponding to the uphill component includes:

[0080] Based on the slope factor layer, the AccSX layer, and the AccFinal layer, calculate to obtain the S mean layer through the raster calculator; similarly, select the AccFinal layer, the AccCX layer, and the vegetation cover factor layer to calculate to obtain the W mean layer; finally, multiply the S mean layer, the W mean layer, the AccFinal layer by the cell control area to obtain the uphill component layer.

[0081] S23. Calculate the spatial distribution of sediment connectivity index based on the downhill component and uphill component; specifically, use the Log10 function in the raster calculator tool, i.e., Log10(Dup / Ddn), to calculate the spatial distribution map of sediment connectivity index; for the schematic diagram of the sediment connectivity calculation framework, see Figure 2 as shown.

[0082] In the above step S3, based on the spatial distribution of sediment connectivity index, identify the high and low threshold regions of sediment connectivity (i.e., the cold and hot spots of sediment connectivity) in the target watershed; specifically including:

[0083] Based on the ArcGis platform, use the "Extract Values" tool to extract the high-value pixels and low-value pixels in the sediment connectivity index distribution map; regard the regions corresponding to the high-value pixels and low-value pixels as the high and low threshold regions of sediment connectivity; among them, the high-value pixels are the pixels of the high point threshold; the low-value pixels are the pixels less than the low point threshold.

[0084] In the embodiment of the present invention, determine the 90th percentile of the distribution characteristics of the sediment connectivity index distribution map in the target watershed as the high point threshold, and the 10th percentile as the low point threshold.

[0085] Convert the extracted high-value pixels and low-value pixels into vector point data, and use the raster to point tool to convert the hot and cold spot rasters into vector point data for further analysis.

[0086] In the above step S4, obtain the erosion characteristics in the high and low threshold regions of sediment connectivity, and plan the soil and water conservation measures in the target watershed according to the erosion characteristics; specifically including:

[0087] Based on the ArcGis platform (i.e., the geographic information space platform), load the on-site RTK measurement data in tabular form (which can be achieved through the "Add Data" tool), and convert the longitude and latitude in the table into a point layer and export it in vector point format (which can be achieved through the "Display XY Data" tool); set the vector point as the target layer and the RTK measurement data as the connection layer (which can be achieved through the "Spatial Join" tool); connect based on the nearest distance to match each vector point with the nearest RTK point.

[0088] Load the sediment connectivity index distribution map file and the orthophoto image file, and convert the coordinate systems of these two files to be consistent (which can be achieved through the "Project" tool); by modifying the attributes and transparency (for example, right-click on the sediment connectivity index distribution map layer, select "Properties", "Display", and set the transparency (50%)), overlay the sediment connectivity index distribution map file with the orthophoto image file, and observe the correspondence between the high threshold region of sediment connectivity and the surface features (such as bare land, erosion gullies, vegetation cover, etc.), see Figure 3As shown; by adjusting the transparency or switching the layer order, compare the spatial distribution of the high-threshold areas of sediment connectivity with surface features; finally, divide the target watershed into different levels (such as high and low connectivity areas) and plan soil and water conservation measures.

[0089] In the embodiments of the present invention, the process of planning soil and water conservation measures includes the following principles: prioritize the treatment of high-threshold points of sediment connectivity index and erosion hotspots that have a great impact on the downstream; reduce sediment output by blocking sediment transport paths and decreasing sediment connectivity; according to the terrain, soil, vegetation, and land use characteristics of different regions, preferentially adopt eco-friendly biological measures to reduce the damage of engineering measures to the natural environment.

[0090] As Figure 4 shown, Figure 4 is an example diagram of the comprehensive soil and water conservation measures for the area to be analyzed provided by the embodiments of the present invention.

[0091] For the erosion type at the bottom of the gully at point A and the sediment transport path in the nearby area, a grit chamber is built downstream of the gully (designed according to the sediment volume of a once-in-10-year flood, with a length of 10m × width of 3m × depth of 1.5m. A grille is installed at the inlet to intercept debris. The bottom slope of the chamber is 2%, and an overflow weir is set at the outlet, with a width of 0.5m at the weir top. Mechanical silt cleaning is carried out regularly, once after the flood season every year), to collect sediment and clean it regularly. In cooperation with planting reeds (spacing of 0.5m) and cattails (spacing of 1m) in the gully bed, stabilize the gully bed and promote natural sedimentation.

[0092] For the erosion type in the middle of the slope at point B and the sediment transport path in the nearby area, build horizontal terraces or reverse terraces to intercept runoff in sections and reduce soil and water loss. In combination with engineering measures, set up gabion meshes (length of 2m × width of 1m × height of 1m, galvanized steel wire mesh (mesh size 8×10cm), filled with stones with a particle size of 10 - 30cm. Dig a depth of 0.5m, lay a 10cm gravel cushion at the bottom, and fix the gabion layers with steel wires) at the prone-to-collapse places to enhance the slope stability. Build an ecological fence, plant drought-tolerant shrubs Caragana korshinskii along the contour line (double-row staggered layout, row spacing of 0.5m, plant spacing of 0.3m, dig a hole depth of 20cm, 2 - 3 plants in each hole. Match with herbaceous plants (such as Agropyron cristatum) to form a composite barrier, and set up bamboo poles to support against the wind during the initial planting period) to form a natural barrier and slow down the runoff.

[0093] Regarding the erosion type at the C-point slope top and the sediment transport path in the nearby area, plant seabuckthorn shrubs (spacing: 1.5×2 m, hole size: 40×40×40 cm, apply 0.5 kg of compound fertilizer as base fertilizer per hole, cover with plastic film after planting to conserve soil moisture), enhance the soil fixation ability on the ground surface, and reduce runoff scouring. In addition, dig intercepting ditches along the contour lines (laid out along the contour lines, spacing: 20 - 30 m (the spacing is shortened by 5 m for every 5° increase in slope). Cross-section size: bottom width 0.5 m, depth 0.6 m, slope ratio 1:1, longitudinal slope of the ditch bottom ≤ 1%), intercept the runoff at the slope top, and reduce the water flow velocity.

[0094] In the above step S5, the entropy weight method is used to comprehensively evaluate the soil and water conservation measures;

[0095] Among them, using the entropy weight method to comprehensively evaluate the soil and water conservation measures specifically includes: after obtaining various soil and water conservation measures based on the above step S3, taking the normalized difference vegetation index and sediment connectivity index as the entropy weight indicators; calculating the weights of the normalized difference vegetation index and sediment connectivity index respectively through the entropy weight method, and evaluating the comprehensive effect of the soil and water conservation measures based on the weights, and finally selecting the measure with the highest comprehensive score as the optimal plan.

[0096] Since the dimensions and units of different indicators are different, it is necessary to standardize the original data, and the calculation steps are as follows:

[0097] 1. Normalize the positive and negative indicators to eliminate the dimension difference:

[0098] (1) Normalize the positive indicator (NDVI):

[0099]

[0100] In the formula, x is the original indicator value (such as NDVI value, usually in the range of [-1, 1]); X min is the minimum value of this indicator in all grid areas, X max is the maximum value of this indicator in all grid areas; x′ is the result after normalization, in the range of [0, 1], and the larger the value, the higher the vegetation coverage (positive indicator).

[0101] (2) Normalize the negative indicator (IC):

[0102]

[0103] In the formula, x is the original indicator value (such as IC value, without a range); Xmin is the minimum value of this indicator in all grid areas, Xmax is the maximum value of this indicator in all grid areas; x′ is the result after normalization, in the range of [0, 1], and the larger the value, the smaller the interference (negative indicator).

[0104] (3) Calculate the index proportion:

[0105]

[0106] Among them, x ij is the value of the j-th index in the i-th grid area; n is the number of grid samples; p ij represents the proportion corresponding to x ij .

[0107] 2. Calculate the information entropy:

[0108]

[0109] Among them, e j represents the information entropy of the j-th index; when p ij = 0 in the formula, it is defined that p ij lnp ij = 0.

[0110] 3. Calculate the weight:

[0111]

[0112] Among them, w j represents the weight of the j-th index; m represents that there are m indexes in total (in the embodiment of the present invention, m = 2, that is, including the normalized difference vegetation index and the sediment connectivity index)

[0113] 4. Soil and water conservation benefit index (SCE):

[0114] SCE = w IC ·IC'+ w NDVI ·NDVI'

[0115] In the formula, IC' and NDVI' are the values after standardization; w IC and w NDVI are the weights calculated by the entropy weight method.

[0116] Through this method, combined with the calculation of IC and NDVI in the above steps, taking into account the benefits of both engineering measures and biological measures, scientifically quantify the benefits of different soil and water conservation measures (such as terraced fields, afforestation), select the best-benefit soil and water conservation measures that meet the local production reality, and provide decision-making support for the agricultural ecological restoration project.

[0117] In summary, the present invention provides a method for arranging soil and water conservation measures based on sediment connectivity, comprehensively considering the sediment transportation process from the source to the downstream, making up for the limitations of traditional soil and water conservation measures arranged based on experience or local observation data, significantly improving the scientificity, rationality and comprehensive benefits of soil and water conservation measures, and being applicable to the systematic treatment of agricultural small watersheds. By using the cold and hot spot areas of the sediment connectivity index, combined with orthophoto images and field surveys, erosion hot spot areas are accurately identified; according to the erosion characteristics and sediment transport paths, comprehensive soil and water conservation measures are planned, including terrace restoration, intercepting ditch setting, vegetation restoration, etc., and ecological-friendly biological measures are preferably adopted to reduce the environmental damage caused by engineering measures.

[0118] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same and similar parts among the various embodiments, reference can be made to each other. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0119] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for arranging soil and water conservation measures based on sediment connectivity, characterized in that It includes the following steps: S1. Select a multispectral drone to conduct aerial survey work on the target basin to obtain the drone multispectral data, digital elevation model, and land use data within the target basin; S2. Based on the drone multispectral data, digital elevation model, and land use data, obtain the spatial distribution of sediment connectivity index within the target basin; S3. Based on the spatial distribution of the sediment connectivity index, identify the high and low threshold regions of sediment connectivity within the target basin; S4. Obtain the erosion characteristics within the high and low threshold regions of sediment connectivity, and plan the soil and water conservation measures within the target basin according to the erosion characteristics; S5. Use the entropy weight method to comprehensively evaluate the soil and water conservation measures.

2. The method for arranging soil and water conservation measures based on sediment connectivity according to claim 1, wherein The specific content of step S1 includes: Use DJI Terra software for route planning; select the terrain-following flight mode for the drone, keep the constant height from the ground at 60m; and set the forward overlap rate at 90% and the side overlap rate at 80%; set 3 - 5 ground control points within the target basin before aerial photography, use ground nails to fix the red and white triangular targets as ground control points, and measure the coordinates of the control points with a handheld RTK-GPS for aerial survey image correction; use DJI Terra software to process the drone aerial survey images, generate the digital elevation model within the target basin, and generate the drone multispectral data based on the red light and near-infrared spectral data.

3. A method for arranging soil and water conservation measures based on sediment connectivity according to claim 1, characterized in that The specific content of step S2 includes: Based on the drone multispectral data, obtain the vegetation cover factor layer within the target basin; Based on the digital elevation model and land use data, obtain the water flow direction, flow accumulation layer, and slope factor layer within the target basin; Based on the vegetation cover factor layer, water flow direction, flow accumulation layer, and slope factor layer, obtain the downhill component and uphill component; Calculate the spatial distribution of the sediment connectivity index according to the downhill component and the uphill component.

4. A method for arranging soil and water conservation measures based on sediment connectivity according to claim 3, characterized in that, The specific content of obtaining the vegetation cover factor layer within the target basin based on the drone multispectral data includes: Extract the normalized difference vegetation index (NDVI) data from the drone multispectral data; Based on the normalized difference vegetation index corresponding to each grid, obtain the vegetation coverage corresponding to each grid; Based on the vegetation coverage corresponding to each grid, obtain the vegetation cover factor layer corresponding to each grid.

5. A method for arranging soil and water conservation measures based on sediment connectivity according to claim 3, characterized in that, The specific content of obtaining the water flow direction, flow accumulation layer, and slope factor layer within the target basin based on the digital elevation model and land use data includes: 1) Obtain the DEM data from the digital elevation model, use the fill sink tool of the ArcGIS platform to perform fill sink processing on the DEM data; use the flow direction tool in the spatial analysis tool to extract the water flow direction after fill sink of the DEM, denoted as FlowDir; based on the DEM data, use the slope tool in the spatial analysis to set the slope unit as a percentage, denoted as the slopeS layer; calculate the slope factor layer based on the slopeS layer; 2) Based on the digital elevation model, use the reclassification tool to identify the land use types within the target watershed, assign values, and obtain the reclassified land use layer, the Landuse layer; overlay the Landuse layer with the slope factor layer to obtain the land use layer under different slopes, the Sx layer; based on the FlowDir affected by different slopes, use the flow accumulation tool in spatial analysis to calculate the amount of water flowing through the raster cells, and obtain the flow accumulation layer, the AccSX layer; similarly, overlay the Landuse layer with the vegetation cover factor layer to obtain the flow accumulation layer, the AccCX layer. 3) Based on the above FlowDir, input Landuse into the flow accumulation tool in spatial analysis to obtain the flow accumulation, denoted as FlowAcc; based on the raster calculator, add 1 to the flow accumulation value of each raster in FlowAcc to obtain the final flow accumulation layer, denoted as the AccFinal layer.

6. The method for arranging soil and water conservation measures based on sediment connectivity according to claim 5, characterized in that The obtaining process of the downhill component includes: Calculate the downhill distance from each pixel along the flow path to the sink point or outlet on the raster edge, denoted as FlowLen; use FlowDir as the raster data of the water flow direction; use the slope factor and the vegetation cover factor as the first weight raster data and the second weight raster data respectively; based on the raster calculator, multiply FlowLen, the raster data, the first weight raster data, and the second weight raster data to obtain the downhill component. The obtaining process of the uphill component includes: Based on the slope factor layer, AccSX layer, and AccFinal layer, layer S is calculated through the raster calculator; similarly, layer W is calculated by selecting the AccFinal layer, AccCX layer, and vegetation coverage factor layer. mean Finally, the areas of layer S, layer W, the AccFinal layer are multiplied by the cell control area to obtain the uphill component layer. mean Layer; mean Layer, mean Layer, and the AccFinal layer are multiplied by the cell control area to obtain the uphill component layer.

7. A method for arranging soil and water conservation measures based on sediment connectivity according to claim 1, characterized in that, The specific steps of step S3 include: Based on the ArcGis platform, extract the high-value pixels and low-value pixels in the sediment connectivity index distribution map; use the regions corresponding to the high-value pixels and low-value pixels as the high and low threshold regions of sediment connectivity. Among them, the high-value pixel is the pixel with the high point threshold; the low-value pixel is the pixel less than the low point threshold.

8. A method for arranging soil and water conservation measures based on sediment connectivity according to claim 7, characterized in that, Determine the 90th percentile as the high point threshold and the 10th percentile as the low point threshold for the distribution characteristics of the sediment connectivity index distribution map within the target watershed.

9. A method for arranging soil and water conservation measures based on sediment connectivity according to claim 1, characterized in that The specific steps of step S4 include: Based on the ArcGis platform, load the on-site RTK measurement data in tabular form, convert the longitude and latitude in the table into a point layer and export it in vector point format; set the vector point as the target layer and the RTK measurement data as the connection layer, and connect based on the nearest distance to match each vector point with the nearest RTK point. Load the sediment connectivity index distribution map file and the orthophoto image file, and convert the coordinate systems of these two files to be consistent; overlay the sediment connectivity index distribution map file with the orthophoto image file by modifying the attributes and transparency to observe the corresponding relationship between the high threshold region of sediment connectivity and the surface features; compare the spatial distribution of the high threshold region of sediment connectivity and the surface features by adjusting the transparency or switching the layer order; finally, divide the target watershed into different levels and plan the soil and water conservation measures.

10. A method for arranging soil and water conservation measures based on sediment connectivity according to claim 1, characterized in that, In step S5, the normalized difference vegetation index and sediment connectivity index are used as entropy weight indicators; the weights of the normalized difference vegetation index and sediment connectivity index are calculated respectively by the entropy weight method, and the comprehensive effect of soil and water conservation measures is evaluated based on the weights.

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