CN117871423A - Remote sensing estimation method and system for sand transportation rate of small river basin - Google Patents
Remote sensing estimation method and system for sand transportation rate of small river basin Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 68
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- 239000013049 sediment Substances 0.000 claims abstract description 86
- 230000003628 erosive effect Effects 0.000 claims abstract description 42
- 239000002689 soil Substances 0.000 claims abstract description 38
- 238000004162 soil erosion Methods 0.000 claims abstract description 25
- 238000001228 spectrum Methods 0.000 claims abstract description 24
- 239000002344 surface layer Substances 0.000 claims abstract description 20
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Abstract
The invention discloses a small-river basin sand conveying rate remote sensing estimation method and system. The method extracts boundaries of the small watershed, collects rainfall data of the small watershed area, and calculates rainfall erosion force of the small watershed area in a preset time period; monitoring water and soil loss conditions by adopting a water and soil loss model, calculating the soil erosion modulus of each pixel in the boundary of the small river basin, and summing to obtain the total erosion amount of sediment in the small river basin in a preset time period; extracting the water body range of the river or lake at the outlet of the small river basin by utilizing remote sensing spectrum data; constructing the relationship between the sediment surface layer concentration of the water body of the river and lake at the outlet of the small river basin and the spectrum information of the remote sensing satellite by utilizing a water body optical classification method; establishing a relationship between the sediment concentration on the surface layer of the river and lake water body at the outlet of the small river basin and the instantaneous sediment column concentration of the river and lake water body at the outlet of the small river basin: obtaining the total sediment loss of the small river basin in a preset time period by a time interpolation method, and calculating the sediment transport ratio of the small river basin in the preset time period; the algorithm has high precision, wide application range and low cost.
Description
Technical Field
The invention relates to the technical field of small-basin sediment transport ratio calculation, in particular to a small-basin sediment transport rate remote sensing estimation method and system.
Background
The sediment transport ratio reflects the amount of sediment transport and deposition along the course from the erosion source to the section. Under the condition that upstream face erosion, ditch erosion, gravity erosion and river erosion can be estimated, if the migration ratio can be determined, the sand production amount of the river basin can be predicted, so that scientific basis is provided for planning of the river basin, configuration of treatment measures and channel engineering construction, and accurate calculation is very important. The core of calculating the transfer ratio is to estimate the total erosion amount of the basin.
The traditional method mainly adopts the InVEST and SWAT methods to obtain the soil erosion condition. The InVEST model: an integrated assessment model of ecosystem services and trade-offs (Integrated Valuation of Ecosystem Services and Trade-offs). SWAT (Soil and Water Assessment Tool) is an integrated hydrologic and soil process model for assessing soil erosion, water balance, water quality, etc. problems in a basin. The InVEST has the following drawbacks: the data demand is high: the InVEST model requires high input data, and requires large amounts of geographic data, meteorological data, soil data, etc., which may be difficult to obtain or inaccurate in certain areas. Parameter setting is complex: the use of the invent model requires the setting of a number of parameters, which may have a large impact on the results, with some complexity for non-professionals. The model accuracy is limited: the InVEST model is based on a series of assumptions and modeling conventions, the results of which may be limited by these assumptions, and thus in some cases, the results of the model may deviate from the actual situation. Ignoring artifacts: the InVEST model mainly focuses on the influence of natural factors on soil erosion, but ignores the effects of human factors, such as land utilization changes, agricultural management measures and the like, and the comprehensive evaluation of the soil erosion may be insufficient. Irrespective of the water retention capacity of the soil: the InVEST model does not take into account factors such as the water retention capacity and the water utilization efficiency of the soil, which may ignore some important influencing factors in soil erosion assessment. Lack of regional adaptability: the parameters and algorithms of the invent model are typically generic and difficult to adjust and adapt to the specific situation in different regions. It is difficult to consider local details: the invent model is typically based on regional scale assessment, where details and complexity of the regional scale are difficult to capture, and may not be accurate enough for specific soil erosion problems. Lack of field verification: the results of the InVEST model typically need to be compared and validated against field observations, however, there is insufficient field data to validate the results of the model. Nonlinear effects cannot be considered: the invent model generally simulates the soil erosion process based on a linear relationship, and in actual situations, the soil erosion process may have nonlinear effects that may not be accurately reflected in the model evaluation.
The SWAT model database mainly comprises DEM (digital elevation model), which is a commonly used data type in a Geographic Information System (GIS) for representing the elevation information of the ground surface. The method is a digital terrain model, describes height data of different positions on the ground surface, is presented in a grid form, and can be used for analyzing the terrain, making a three-dimensional map, simulating the water flow direction, calculating the gradient and the like.
Soil data, land utilization, meteorological and hydrographic site measured runoff and sediment data. Specifically, the number of SCS runoff curves (CN 2), the base flow α factor (alpha_bnk) for river bank regulation, the groundwater DELAY coefficient (gw_delay), the soil evaporation compensation coefficient (ESCO), the soil effective water content (sol_awc), the base flow α factor (alpha_bf), the main river hydraulic conductivity coefficient (ch_k2), the manning coefficient (ch_n2) of the main river, the initial soil water storage capacity (FFCB), the air temperature reduction rate (TLAPS), the shallow groundwater runoff coefficient (GWQMN), the plant evaporation compensation coefficient (EPCO), the soil wet volume weight (sol_bd), the shallow groundwater evaporation depth threshold (REVAPMN), the maximum canopy cut-off (CANMX), and the like are required parameters.
In summary, the existing calculation method is only suitable for a research area, and needs to be further improved in terms of algorithm application range, cost and precision.
Disclosure of Invention
The invention aims to provide a small-river basin sand conveying rate remote sensing estimation method and system, which are used for solving the problem that the algorithm application range, cost and accuracy in the prior art are to be further improved.
In a first aspect, the present invention provides a method for remotely estimating sand transmission rate in a small river basin, including:
extracting boundaries of the small drainage basin;
collecting rainfall data of the small-basin area, and calculating rainfall erosion force R of the small-basin area in a preset time period according to the rainfall data;
the water and soil loss condition is monitored by adopting the following water and soil loss model, wherein the model is as follows:
A = RKLSBET
in the formula, A is the soil erosion modulus, R is the rainfall erosion force, K is the soil corrosiveness, L is the slope length factor, S is the slope factor, B is the biological measure factor, E is the engineering measure factor, and T is the cultivation measure factor;
according to the water and soil loss model, calculating the soil erosion modulus of each pixel in the boundary of the small river basin and summing to obtain the total erosion amount SS of the sediment in the small river basin in a preset time period Total erosion of ；
Extracting the water body range of the river or lake at the outlet of the small river basin by utilizing remote sensing spectrum data;
by utilizing a water body optical classification method, constructing the relationship between the sediment surface layer concentration of the water body of the river and lake of the small river basin and the remote sensing satellite spectrum information:
in the formula, SS-S is the outlet river of the small river basinThe sediment concentration of the surface layer of the lake water,the spectrum information of the remote sensing satellite is obtained;
establishing a relationship between the sediment concentration on the surface layer of the river and lake water body at the outlet of the small river basin and the instantaneous sediment column concentration of the river and lake water body at the outlet of the small river basin:
in the formula, SS-C is the instantaneous sediment column concentration of the river and lake water body at the outlet of the small river basin;
according to the water body range of the outlet river or lake of the small river basin, the total sediment loss of the small river basin in a preset time period is obtained by a time interpolation method:
SS total loss of
In the formula, SS Total loss of The total sediment loss of the small watershed in a preset time period is obtained;
calculating the sediment transport ratio of the small river basin in a preset time period:
small-river-basin sediment transport ratio=ss within a preset period of time Total loss- SS Total erosion of 。
Further, extracting boundaries of the small basin includes:
smoothing and filling the DEM data of the small drainage basin area to remove noise and discontinuity;
according to the DEM data of the small-river basin area, determining the flow direction of each pixel, wherein the flow direction of each pixel is the direction of the adjacent pixel;
and extracting the small-drainage-basin boundary from the DEM data according to the flow direction.
Further, collecting rainfall data of the small-basin area, and calculating rainfall erosion force R of the small-basin area in a preset time period according to the rainfall data, wherein the rainfall data comprises annual rainfall capacity, rainfall distribution and rainfall frequency.
Further, extracting a small-river-basin outlet river or lake water body range by using remote sensing spectrum data comprises the following steps:
calculating NDWI and NDVI;
the NDWI calculation formula is as follows:
in the method, in the process of the invention,for the reflectivity of the green band, +.>For the reflectivity of the near infrared band, NDWI is the normalized water index;
the NDVI calculation formula is as follows:
in the method, in the process of the invention,for the reflectivity in the near infrared band, +.>For the reflectivity of the red band, NDVI is the normalized vegetation index.
In a second aspect, the present invention provides a small-river basin sand-conveying rate remote sensing estimation system, including:
a first extraction unit for extracting a boundary of the small basin;
the collecting unit is used for collecting rainfall data of the small-basin area and calculating rainfall erosion force R of the small-basin area in a preset time period according to the rainfall data;
the monitoring unit is used for monitoring the water and soil loss condition by adopting the following water and soil loss model, and the model form is as follows:
A = RKLSBET
in the formula, A is the soil erosion modulus, R is the rainfall erosion force, K is the soil corrosiveness, L is the slope length factor, S is the slope factor, B is the biological measure factor, E is the engineering measure factor, and T is the cultivation measure factor;
the first calculation unit is used for calculating the soil erosion modulus of each pixel in the boundary of the small river basin according to the water and soil loss model and summing the soil erosion modulus to obtain the total erosion amount SS of the sediment in the small river basin in a preset time period Total erosion of ；
The second extraction unit is used for extracting the water body range of the river or lake at the outlet of the small river basin by utilizing remote sensing spectrum data;
the construction unit is used for constructing the relationship between the sediment surface layer concentration of the river and lake water body in the small river basin and the remote sensing satellite spectrum information by utilizing a water body optical classification method:
in the formula, SS-S is the sediment concentration of the surface layer of the water body of the river and the lake at the outlet of the small river basin,the spectrum information of the remote sensing satellite is obtained;
the building unit is used for building the relation between the sediment concentration on the surface layer of the water body of the river and the lake at the outlet of the small river basin and the instantaneous sediment column concentration of the water body of the river and the lake at the outlet of the small river basin:
in the formula, SS-C is the instantaneous sediment column concentration of the river and lake water body at the outlet of the small river basin;
the interpolation unit is used for obtaining the total loss of the sediment in the small river basin in a preset time period by a time interpolation method according to the water body range of the river or lake at the outlet of the small river basin:
SS total loss of
In the formula, SS Total loss of The total sediment loss of the small watershed in a preset time period is obtained;
the second calculating unit is used for calculating the sediment transfer ratio of the small river basin in a preset time period:
small-river-basin sediment transport ratio=ss within a preset period of time Total loss- SS Total erosion of 。
Further, extracting boundaries of the small basin includes:
the processing subunit is used for carrying out smoothing and depression filling operation on the DEM data of the small-drainage-basin area and removing noise and discontinuity;
a determining subunit, configured to determine, according to DEM data of the small-drainage-area region, a flow direction of each pixel, where the flow direction of the pixel is a direction of the flow direction adjacent to the pixel;
and the extraction subunit is used for extracting the small-drainage-basin boundary from the DEM data according to the flow direction.
Further, the rainfall data comprises annual rainfall, rainfall distribution and rainfall frequency.
Further, the second extraction unit is used for calculating NDWI and NDVI;
the NDWI calculation formula is as follows:
in the method, in the process of the invention,for the reflectivity of the green band, +.>For the reflectivity of the near infrared band, NDWI is the normalized water index;
the NDVI calculation formula is as follows:
in the method, in the process of the invention,for the reflectivity in the near infrared band, +.>For the reflectivity of the red band, NDVI is a normalized vegetation index.
The invention has the beneficial effects that: according to the remote sensing estimation method and system for the sediment transport rate of the small watershed, the total erosion amount in the small watershed and the sediment outflow amount at the outlet of the small watershed are respectively obtained by utilizing remote sensing data, and then the sediment transport ratio is calculated; the response principle of the water spectrum obtained by remote sensing to sediment is quite clear, and the algorithm precision is high; the application range of the algorithm is wide, and the sediment transport ratio of a small watershed can be rapidly obtained by a remote sensing method; the cost is low, and sediment transfer ratio can be obtained by using open source remote sensing data and matching with a small amount of ground verification points.
Drawings
For a further understanding of the nature and technical aspects of the present invention, reference should be made to the following detailed description of the invention and to the accompanying drawings, which are provided for purposes of reference only and are not intended to limit the invention.
In the drawings of which there are shown,
FIG. 1 is a flow chart of a small-river basin sand conveying rate remote sensing estimation method provided by the invention;
fig. 2 is a graph of the relationship between the sediment surface concentration of the river and lake water body at the outlet of the small river basin and the remote sensing satellite spectrum information.
Detailed Description
In order to further explain the technical means adopted by the present invention and the effects thereof, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings.
Referring to fig. 1 and 2, an embodiment of the present invention provides a small-basin sand-conveying rate remote sensing estimation method, which includes:
step one, extracting boundaries of small watershed.
Specifically, the DEM data of the small drainage basin area is subjected to smoothing and depression filling operation, noise and discontinuity are removed, and continuity and accuracy of the DEM are ensured. According to the DEM data of the small-river basin area, determining the flow direction of each pixel, wherein the flow direction of each pixel is the direction of the adjacent pixel; and extracting the small-drainage-basin boundary from the DEM data according to the flow direction.
And step two, calculating the soil erosion amount.
Specifically, rainfall data of the small-basin area is collected, including annual rainfall, rainfall distribution, rainfall frequency and the like. Sources such as chinese ground weather station daily value data set, chinese soil data set HWSD of world soil database, digital elevation model DEM (30 m), vegetation coverage (FVC), land use type data, etc.
And calculating rainfall erosion force R of the small-basin area within a preset time period according to rainfall data.
The water and soil loss condition is monitored by adopting the following water and soil loss model, wherein the model is as follows:
A = RKLSBET
in the formula, A is the soil erosion modulus, and the unit is t.hm -2 a -1 The method comprises the steps of carrying out a first treatment on the surface of the R is rainfall erosion force, and the unit is MJ.hm -2 ·mm·h -1 ·a -1 The method comprises the steps of carrying out a first treatment on the surface of the K is soil corrosiveness, and the unit is t.hm 2 ·MJ -1 ·hm -2 ·mm -1 H; l is a slope length factor, and is dimensionless; s is a gradient factor, and is dimensionless; b is a biological measure factor, and is dimensionless; e is engineering measure factor, dimensionless; t is a cultivation measure factor, and is dimensionless.
According to the water and soil loss model, calculating the soil erosion modulus of each pixel in the boundary of the small river basin and summing to obtain the total erosion amount SS of the sediment in the small river basin in a preset time period Total erosion of 。
And thirdly, calculating the sediment loss.
Extracting the water body range of the river or lake at the outlet of the small river basin by remote sensing spectral data; specifically, NDWI and NDVI are calculated;
the NDWI calculation formula is as follows:
in the method, in the process of the invention,for the reflectivity of the green band, +.>For the reflectivity of the near infrared band, NDWI is the normalized water index;
the NDVI calculation formula is as follows:
in the method, in the process of the invention,for the reflectivity in the near infrared band, +.>For the reflectivity of the red band, NDVI is the normalized vegetation index.
By utilizing a water body optical classification method, constructing the relationship between the sediment surface layer concentration of the water body of the river and lake of the small river basin and the remote sensing satellite spectrum information:
in the formula, SS-S is the sediment concentration of the surface layer of the water body of the river and the lake at the outlet of the small river basin,is remote sensing satellite spectrum information.
Establishing a relationship between the sediment concentration on the surface layer of the river and lake water body at the outlet of the small river basin and the instantaneous sediment column concentration of the river and lake water body at the outlet of the small river basin:
in the formula, SS-C is the instantaneous sediment column concentration of the river and lake water body at the outlet of the small river basin;
according to the water body range of the outlet river or lake of the small river basin, the total sediment loss of the small river basin in a preset time period is obtained by a time interpolation method:
SS total loss of
In the formula, SS Total loss of Is the total sediment flow of the small watershed within a preset time periodLoss of volume.
Calculating the sediment transport ratio of the small river basin in a preset time period: small-river-basin sediment transport ratio=ss within a preset period of time Total loss- SS Total erosion of 。
According to the embodiment, the remote sensing estimation method for the sediment transport rate of the small watershed, provided by the invention, uses remote sensing data to respectively obtain the total erosion amount in the small watershed and the sediment amount flowing out of the outlet of the small watershed, so as to calculate the sediment transport ratio; the response principle of the water spectrum obtained by remote sensing to sediment is quite clear, and the algorithm precision is high; the application range of the algorithm is wide, and the sediment transport ratio of a small watershed can be rapidly obtained by a remote sensing method; the cost is low, and sediment transfer ratio can be obtained by using open source remote sensing data and matching with a small amount of ground verification points.
The embodiment of the invention also provides a small-river basin sand conveying rate remote sensing estimation system, which comprises the following steps:
a first extraction unit for extracting a boundary of the small basin;
the collecting unit is used for collecting rainfall data of the small-basin area and calculating rainfall erosion force R of the small-basin area in a preset time period according to the rainfall data;
the monitoring unit is used for monitoring the water and soil loss condition by adopting the following water and soil loss model, and the model form is as follows:
A = RKLSBET
in the formula, A is the soil erosion modulus, R is the rainfall erosion force, K is the soil corrosiveness, L is the slope length factor, S is the slope factor, B is the biological measure factor, E is the engineering measure factor, and T is the cultivation measure factor;
the first calculation unit is used for calculating the soil erosion modulus of each pixel in the boundary of the small river basin according to the water and soil loss model and summing the soil erosion modulus to obtain the total erosion amount SS of the sediment in the small river basin in a preset time period Total erosion of ；
The second extraction unit is used for extracting the water body range of the river or lake at the outlet of the small river basin by utilizing remote sensing spectrum data;
the construction unit is used for constructing the relationship between the sediment surface layer concentration of the river and lake water body in the small river basin and the remote sensing satellite spectrum information by utilizing a water body optical classification method:
in the formula, SS-S is the sediment concentration of the surface layer of the water body of the river and the lake at the outlet of the small river basin,the spectrum information of the remote sensing satellite is obtained;
the building unit is used for building the relation between the sediment concentration on the surface layer of the water body of the river and the lake at the outlet of the small river basin and the instantaneous sediment column concentration of the water body of the river and the lake at the outlet of the small river basin:
in the formula, SS-C is the instantaneous sediment column concentration of the river and lake water body at the outlet of the small river basin;
the interpolation unit is used for obtaining the total loss of the sediment in the small river basin in a preset time period by a time interpolation method according to the water body range of the river or lake at the outlet of the small river basin:
SS total loss of
In the formula, SS Total loss of The total sediment loss of the small watershed in a preset time period is obtained;
the second calculating unit is used for calculating the sediment transfer ratio of the small river basin in a preset time period:
small-river-basin sediment transport ratio=ss within a preset period of time Total loss- SS Total erosion of 。
In this embodiment, extracting boundaries of the small watershed includes:
the processing subunit is used for carrying out smoothing and depression filling operation on the DEM data of the small-drainage-basin area and removing noise and discontinuity;
a determining subunit, configured to determine, according to DEM data of the small-drainage-area region, a flow direction of each pixel, where the flow direction of the pixel is a direction of the flow direction adjacent to the pixel;
and the extraction subunit is used for extracting the small-drainage-basin boundary from the DEM data according to the flow direction.
In this embodiment, the rainfall data includes annual rainfall, rainfall distribution, and rainfall frequency.
In this embodiment, the second extracting unit is configured to calculate NDWI and NDVI;
the NDWI calculation formula is as follows:
in the method, in the process of the invention,for the reflectivity of the green band, +.>For the reflectivity of the near infrared band, NDWI is the normalized water index;
the NDVI calculation formula is as follows:
in the method, in the process of the invention,for the reflectivity in the near infrared band, +.>For the reflectivity of the red band, NDVI is the normalized vegetation index.
The embodiment of the invention also provides a storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, part or all of the steps in each embodiment of the small-river basin sediment ratio remote sensing estimation method provided by the invention are realized. The storage medium may be a magnetic disk, an optical disk, a Read-only memory (ROM), a Random Access Memory (RAM), or the like.
It will be apparent to those skilled in the art that the techniques of embodiments of the present invention may be implemented in software plus a necessary general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be embodied in essence or what contributes to the prior art in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the embodiments or some parts of the embodiments of the present invention.
The same or similar parts between the various embodiments in this specification are referred to each other. In particular, for the small watershed sand delivery rate remote sensing estimation system embodiment, since the system is basically similar to the method embodiment, the description is simpler, and the relevant points are referred to the description in the method embodiment.
The embodiments of the present invention described above do not limit the scope of the present invention.
Claims (8)
1. The remote sensing estimation method for the sand conveying rate of the small river basin is characterized by comprising the following steps of:
extracting boundaries of the small drainage basin;
collecting rainfall data of the small-basin area, and calculating rainfall erosion force R of the small-basin area in a preset time period according to the rainfall data;
the water and soil loss condition is monitored by adopting the following water and soil loss model, wherein the model is as follows:
A = RKLSBET；
in the formula, A is the soil erosion modulus, R is the rainfall erosion force, K is the soil corrosiveness, L is the slope length factor, S is the slope factor, B is the biological measure factor, E is the engineering measure factor, and T is the cultivation measure factor;
according to the water and soil loss model, calculating the soil erosion modulus of each pixel in the boundary of the small river basin and summing to obtain the total erosion amount SS of the sediment in the small river basin in a preset time period Total erosion of ；
Extracting the water body range of the river or lake at the outlet of the small river basin by utilizing remote sensing spectrum data;
by utilizing a water body optical classification method, constructing the relationship between the sediment surface layer concentration of the water body of the river and lake of the small river basin and the remote sensing satellite spectrum information:
；
in the formula, SS-S is the sediment concentration of the surface layer of the water body of the river and the lake at the outlet of the small river basin,the spectrum information of the remote sensing satellite is obtained;
establishing a relationship between the sediment concentration on the surface layer of the river and lake water body at the outlet of the small river basin and the instantaneous sediment column concentration of the river and lake water body at the outlet of the small river basin:
；
in the formula, SS-C is the instantaneous sediment column concentration of the river and lake water body at the outlet of the small river basin;
according to the water body range of the outlet river or lake of the small river basin, the total sediment loss of the small river basin in a preset time period is obtained by a time interpolation method:
SS total loss of ；
In the formula, SS Total loss of The total sediment loss of the small watershed in a preset time period is obtained;
calculating the sediment transport ratio of the small river basin in a preset time period:
small-river-basin sediment transport ratio=ss within a preset period of time Total loss- SS Total erosion of 。
2. The method for remotely sensing and estimating the sand transmission rate of a small river basin as claimed in claim 1, wherein the extracting the boundary of the small river basin comprises the following steps:
smoothing and filling the DEM data of the small drainage basin area to remove noise and discontinuity;
according to the DEM data of the small-river basin area, determining the flow direction of each pixel, wherein the flow direction of each pixel is the direction of the adjacent pixel;
and extracting the small-drainage-basin boundary from the DEM data according to the flow direction.
3. The method for remotely sensing and estimating a sand transportation rate in a small basin as claimed in claim 1, wherein in the step of collecting rainfall data of the small basin, the rainfall erosion force R of the small basin in a predetermined period is calculated according to the rainfall data, the rainfall data includes annual rainfall, rainfall distribution and rainfall frequency.
4. The method for remotely sensing and estimating the sand transmission rate of a small river basin according to claim 1, wherein the step of extracting the water body range of the outlet river or lake of the small river basin by using remote sensing spectrum data comprises the following steps:
calculating NDWI and NDVI;
the NDWI calculation formula is as follows:
；
in the method, in the process of the invention,for the reflectivity of the green band, +.>For the reflectivity of the near infrared band, NDWI is the normalized water index;
the NDVI calculation formula is as follows:
；
in the method, in the process of the invention,for the reflectivity in the near infrared band, +.>For the reflectivity of the red band, NDVI is the normalized vegetation index.
5. A small watershed sand delivery rate remote sensing estimation system, comprising:
a first extraction unit for extracting a boundary of the small basin;
the collecting unit is used for collecting rainfall data of the small-basin area and calculating rainfall erosion force R of the small-basin area in a preset time period according to the rainfall data;
the monitoring unit is used for monitoring the water and soil loss condition by adopting the following water and soil loss model, and the model form is as follows:
A = RKLSBET；
in the formula, A is the soil erosion modulus, R is the rainfall erosion force, K is the soil corrosiveness, L is the slope length factor, S is the slope factor, B is the biological measure factor, E is the engineering measure factor, and T is the cultivation measure factor;
the first calculation unit is used for calculating the soil erosion modulus of each pixel in the boundary of the small river basin according to the water and soil loss model and summing the soil erosion modulus to obtain the total erosion amount SS of the sediment in the small river basin in a preset time period Total erosion of ；
The second extraction unit is used for extracting the water body range of the river or lake at the outlet of the small river basin by utilizing remote sensing spectrum data;
the construction unit is used for constructing the relationship between the sediment surface layer concentration of the river and lake water body in the small river basin and the remote sensing satellite spectrum information by utilizing a water body optical classification method:
；
in the formula, SS-S is the sediment concentration of the surface layer of the water body of the river and the lake at the outlet of the small river basin,the spectrum information of the remote sensing satellite is obtained;
the building unit is used for building the relation between the sediment concentration on the surface layer of the water body of the river and the lake at the outlet of the small river basin and the instantaneous sediment column concentration of the water body of the river and the lake at the outlet of the small river basin:
；
in the formula, SS-C is the instantaneous sediment column concentration of the river and lake water body at the outlet of the small river basin;
the interpolation unit is used for obtaining the total loss of the sediment in the small river basin in a preset time period by a time interpolation method according to the water body range of the river or lake at the outlet of the small river basin:
SS total loss of ；
In the formula, SS Total loss of The total sediment loss of the small watershed in a preset time period is obtained;
the second calculating unit is used for calculating the sediment transfer ratio of the small river basin in a preset time period:
small-river-basin sediment transport ratio=ss within a preset period of time Total loss- SS Total erosion of 。
6. The small watershed sand transportation rate remote sensing estimation system of claim 5, wherein extracting boundaries of the small watershed comprises:
the processing subunit is used for carrying out smoothing and depression filling operation on the DEM data of the small-drainage-basin area and removing noise and discontinuity;
a determining subunit, configured to determine, according to DEM data of the small-drainage-area region, a flow direction of each pixel, where the flow direction of the pixel is a direction of the flow direction adjacent to the pixel;
and the extraction subunit is used for extracting the small-drainage-basin boundary from the DEM data according to the flow direction.
7. The small basin sand transfer rate remote sensing estimation system of claim 5, wherein the rainfall data includes annual rainfall, rainfall distribution, and rainfall frequency.
8. The small-basin sand-handling rate remote sensing estimation system of claim 5, wherein the second extraction unit is configured to calculate NDWI and NDVI;
the NDWI calculation formula is as follows:
；
in the method, in the process of the invention,for the reflectivity of the green band, +.>For the reflectivity of the near infrared band, NDWI is the normalized water index;
the NDVI calculation formula is as follows:
；
in the method, in the process of the invention,for the reflectivity in the near infrared band, +.>For the reflectivity of the red band, NDVI is the normalized vegetation index.
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Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202350834U (en) * | 2011-10-31 | 2012-07-25 | 北京林丰源生态园林绿化工程有限公司 | Automatic testing system for water loss and soil erosion |
| CN103940974A (en) * | 2014-02-19 | 2014-07-23 | 西北农林科技大学 | Spatio-temporal dynamic analysis method of soil erosion in meso-scale watershed based on GIS |
| CN103942408A (en) * | 2014-02-19 | 2014-07-23 | 西北农林科技大学 | Annual erosion sediment yield model calculation method of mesoscale drainage basin of loess plateau |
| KR102109917B1 (en) * | 2018-11-16 | 2020-05-12 | 대한민국(관리부서 : 환경부 국립환경과학원장) | Method for automatic inland water boundary extraction using remote sensed hyperspectral images |
| CN111222679A (en) * | 2019-10-28 | 2020-06-02 | 河海大学 | Remote sensing-based river water amount estimation method |
| KR20220105797A (en) * | 2021-01-21 | 2022-07-28 | 공주대학교 산학협력단 | Apparatus and method for predicting the probability of soil loss using a topsoil environment change prediction model |
| CN114819390A (en) * | 2022-05-19 | 2022-07-29 | 厦门市城市规划设计研究院有限公司 | Model method for estimating urban river sediment deposition |
| CN114969655A (en) * | 2022-03-30 | 2022-08-30 | 武汉大学 | Simulation estimation method for sediment transport amount of drainage basin |
| CN115146922A (en) * | 2022-06-02 | 2022-10-04 | 浙江大学 | Watershed soil retention function evaluation method based on RUSLE and SDR models |
| CN116908114A (en) * | 2023-09-07 | 2023-10-20 | 水利部交通运输部国家能源局南京水利科学研究院 | Remote sensing monitoring method for river basin granule organic carbon flux |
| CN117035480A (en) * | 2023-05-30 | 2023-11-10 | 中国水利水电科学研究院 | River basin water and soil loss control degree determining method and system based on river channel sand conveying balance |
| CN117169469A (en) * | 2023-08-09 | 2023-12-05 | 水利部交通运输部国家能源局南京水利科学研究院 | Small watershed water and soil conservation monitoring method and storage medium thereof |
| CN117494419A (en) * | 2023-11-01 | 2024-02-02 | 成都理工大学 | Multi-model coupling drainage basin soil erosion remote sensing monitoring method |
-
2024
- 2024-03-13 CN CN202410282312.XA patent/CN117871423B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202350834U (en) * | 2011-10-31 | 2012-07-25 | 北京林丰源生态园林绿化工程有限公司 | Automatic testing system for water loss and soil erosion |
| CN103940974A (en) * | 2014-02-19 | 2014-07-23 | 西北农林科技大学 | Spatio-temporal dynamic analysis method of soil erosion in meso-scale watershed based on GIS |
| CN103942408A (en) * | 2014-02-19 | 2014-07-23 | 西北农林科技大学 | Annual erosion sediment yield model calculation method of mesoscale drainage basin of loess plateau |
| KR102109917B1 (en) * | 2018-11-16 | 2020-05-12 | 대한민국(관리부서 : 환경부 국립환경과학원장) | Method for automatic inland water boundary extraction using remote sensed hyperspectral images |
| CN111222679A (en) * | 2019-10-28 | 2020-06-02 | 河海大学 | Remote sensing-based river water amount estimation method |
| KR20220105797A (en) * | 2021-01-21 | 2022-07-28 | 공주대학교 산학협력단 | Apparatus and method for predicting the probability of soil loss using a topsoil environment change prediction model |
| CN114969655A (en) * | 2022-03-30 | 2022-08-30 | 武汉大学 | Simulation estimation method for sediment transport amount of drainage basin |
| CN114819390A (en) * | 2022-05-19 | 2022-07-29 | 厦门市城市规划设计研究院有限公司 | Model method for estimating urban river sediment deposition |
| CN115146922A (en) * | 2022-06-02 | 2022-10-04 | 浙江大学 | Watershed soil retention function evaluation method based on RUSLE and SDR models |
| CN117035480A (en) * | 2023-05-30 | 2023-11-10 | 中国水利水电科学研究院 | River basin water and soil loss control degree determining method and system based on river channel sand conveying balance |
| CN117169469A (en) * | 2023-08-09 | 2023-12-05 | 水利部交通运输部国家能源局南京水利科学研究院 | Small watershed water and soil conservation monitoring method and storage medium thereof |
| CN116908114A (en) * | 2023-09-07 | 2023-10-20 | 水利部交通运输部国家能源局南京水利科学研究院 | Remote sensing monitoring method for river basin granule organic carbon flux |
| CN117494419A (en) * | 2023-11-01 | 2024-02-02 | 成都理工大学 | Multi-model coupling drainage basin soil erosion remote sensing monitoring method |
Non-Patent Citations (5)
| Title |
|---|
| 李四海, 恽才兴: "河口表层悬浮泥沙气象卫星遥感定量模式研究", 遥感学报, vol. 5, no. 2, 10 April 2001 (2001-04-10), pages 154 - 160 * |
| 杨强强: "大凌河流域不同空间尺度典型流域泥沙输移比及其影响因素研究", 中国水能及电气化, no. 5, 31 May 2018 (2018-05-31), pages 18 - 22 * |
| 林强;陈一梅;: "厦门湾悬沙分布的多时相遥感分析", 水运工程, no. 12, 25 December 2008 (2008-12-25), pages 51 - 57 * |
| 胡明鉴, 汪稔, 孟庆山, 刘观仕: "坡面松散砾石土侵蚀过程及其特征研究", 岩土力学, no. 11, 30 November 2005 (2005-11-30), pages 1722 - 1726 * |
| 谢红霞, 杨勤科, 李锐, 张晓萍, 程琳, 庞国伟: "延河流域水土保持措施减蚀效应分析", 中国水土保持科学, no. 4, 31 August 2010 (2010-08-31), pages 13 - 19 * |
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