Water and soil loss dynamic monitoring method and system

Abstract

The invention discloses a water and soil loss dynamic monitoring method and system, and relates to the technical field of water and soil loss monitoring. Comprising a data acquisition module, a data processing module, a data analysis module, a risk assessment module and a loss analysis module. The data acquisition module is used for acquiring remote sensing image data, DEM image data, geological data and future rainfall data of a monitoring area. Then numbering the divided areas, then performing independent analysis, and evaluating the water and soil loss conditions of the numbered areas, so that related technicians can conveniently know the water and soil loss conditions of the monitored areas and conveniently analyze the interference of land use types on the water and soil loss; therefore, related technicians can conveniently formulate related water and soil loss treatment schemes, the use effect is good, and good application prospects are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of soil and water loss monitoring, and specifically to a method and system for dynamic monitoring of soil and water loss. Background Technique

[0002] Soil and water loss refers to the phenomenon that due to the influence of natural or human factors, rainwater cannot be absorbed locally, flows downstream, and scours the soil, resulting in the simultaneous loss of water and soil. The main reasons are large ground slopes, improper land use, damage to ground vegetation, unreasonable farming techniques, loose soil quality, deforestation, overgrazing, etc.

[0003] Soil and water loss refers to the damage and loss of water and soil resources and land productivity under the action of external forces such as hydraulic, gravitational, and wind forces, including surface erosion of land and soil and water loss, also known as soil and water loss. Severe soil and water loss will cause a reduction in cultivated land area, a decline in soil fertility, and a decrease in crop yields. Therefore, it is necessary to closely monitor the situation of soil and water loss.

[0004] With the progress of technology, people pay more and more attention to environmental protection and also pay more and more attention to soil and water loss. In order to facilitate the monitoring of soil and water loss, people have invented some methods and systems for monitoring soil and water loss.

[0005] In the existing invention patent with the application publication number CN115469079A and the name of a method and system for dynamic monitoring of soil and water loss, it is recorded that it includes obtaining initial monitoring data of the area to be monitored; screening and processing the initial monitoring data to obtain practical monitoring data; obtaining the annual soil loss amount and prevention and control intensity of the area to be monitored according to the practical monitoring data; classifying the area to be monitored according to the annual soil loss amount and prevention and control intensity; among them, the classified area to be monitored includes a well-governed area, a prevention and supervision area, a loss governance area, and an area in urgent need of key governance; adjusting the monitoring mechanism according to the classified area to be monitored. By collecting the initial monitoring data of the area to be monitored, screening and processing the initial monitoring data, and analyzing it, classifying the area to be monitored according to the annual soil loss amount and prevention and control intensity, and adjusting the corresponding monitoring mechanism according to the classified area, it is beneficial to collect data at any time and timely discover the situation of soil and water loss.

[0006] However, based on the above content in combination with the existing technology, the central solution of the above patent is to collect the initial monitoring data of the area to be monitored, screen and process the initial monitoring data, and conduct analysis. Classify the area to be monitored according to the annual soil loss and prevention intensity, and adjust the corresponding monitoring mechanism according to the classified areas, which is conducive to collecting data at any time and timely discovering the situation of soil erosion. When the area to be monitored is an area in urgent need of key treatment, increase the number of wireless sensor nodes in the area to be monitored, that is, on the basis of the wireless sensor nodes in the original area to be monitored, additionally increase wireless sensor nodes to improve the accuracy of data detection.

[0007] However, there are certain defects in the above solution when it is actually used. The above solution mainly increases the amount of data collection and judges whether there is soil erosion through sufficient data. However, in actual use, soil erosion will combine with the environment and cause other hazards, which cannot be reflected in this regard. In addition, it can only judge the degree of soil erosion, but it cannot analyze the causes of soil erosion and the corresponding contributions, making it impossible for relevant personnel to quickly formulate corresponding strategies and making the formulation of the later treatment plan more cumbersome.

[0008] Therefore, the above solution has relatively large defects when it is actually used and cannot meet people's usage requirements. For this reason, we have developed a method and system for dynamic monitoring of soil erosion. Summary of the Invention

[0009] (I) Technical problems to be solved Aiming at the deficiencies of the existing technology, the present invention provides a method and system for dynamic monitoring of soil erosion. When in use, it divides the monitoring area according to the land use type, then numbers the divided areas, and then conducts separate analysis to evaluate the soil erosion situation in the numbered areas, which can facilitate relevant technical personnel to understand the soil erosion situation in the monitoring area, facilitate relevant technical personnel to analyze the interference of land use type on soil erosion, and thus facilitate relevant technical personnel to formulate relevant soil erosion treatment plans, with good use effects and good application prospects.

[0010] (II) Technical solutions To achieve the above purposes, the present invention is realized through the following technical solutions: A system for dynamic monitoring of soil erosion includes a data acquisition module, a data processing module, a data analysis module, a risk assessment module, and an erosion analysis module: The data acquisition module: is used to acquire remote sensing image data, DEM image data, geological data, and future precipitation data of the monitoring area; Data processing module: Analyze the remote sensing image data to obtain the land use type data within the monitoring area, then divide and number the monitoring area based on the land use type data within the monitoring area, and then analyze the remote sensing image data, DEM image data, and geological data in sequence to obtain the vegetation data, terrain data, and soil data of the numbered area; Data analysis module: Used to analyze the soil data of the processed numbered area, calculate the periodic soil erosion amount of the evaluation area, and analyze the periodic soil erosion amount to evaluate the periodic soil erosion grade of the numbered area; Risk assessment module: Used to obtain the precipitation data of the future period, and calculate the erosion risk of the numbered area in combination with the periodic soil erosion grade, terrain data, and soil data, and compare the erosion risk of the numbered area with its corresponding risk critical value, and formulate corresponding emergency warning strategies according to the comparison results; Erosion analysis module: Used to obtain the soil erosion grade of the numbered area, compare the soil erosion grade with the preset human intervention grade, and execute the corresponding strategy according to the comparison results.

[0011] Preferably, the steps of analyzing the remote sensing image data to obtain the land use type and distribution data within the monitoring area are as follows: Obtain the remote sensing image data of different quarters in the monitoring area; Perform radiometric correction, atmospheric correction, and geometric correction on the obtained remote sensing image data; Extract the feature data of the remote sensing image data, and the feature data includes spectral features, texture features, shape features, and shadow features; Based on the convolutional neural network model and the extracted features, identify and classify the remote sensing image data to obtain the land use type within the monitoring area, and output it in the form of a map.

[0012] Preferably, the steps of analyzing the remote sensing image data to obtain the vegetation data are as follows: Analyze the remote sensing image data after radiometric correction, atmospheric correction, and geometric correction, and extract the data of the red light band and the near-infrared light band; Calculate the vegetation data, and the vegetation data is the vegetation coverage rate. The specific formula is as follows:

[0013] In the formula, is the vegetation coverage rate, and are both constants, is the light radiation value of the near-infrared band, and R is the light radiation value of the red light band; The terrain data includes elevation data, slope data and slope length data. The steps to obtain the terrain data of the numbered area by analyzing the DEM image data are as follows: Load the DEM image data into the GIS data processing software and query the elevation data at each position in the numbered area; Use the slope calculation tool in the GIS data processing software to calculate the slope data, and then calculate the slope length data using the slope data; The soil data is obtained by analyzing the soil samples collected by the stratified sampling method. The soil data includes soil type, soil texture, soil structure and organic matter content.

[0014] Preferably, the formula for calculating the periodic soil and water loss volume of the evaluation area is as follows:

[0015] In the formula, is the periodic soil and water loss volume of the evaluation area, is the current soil erosion modulus of the evaluation area, m is the soil erosion modulus at the end of the previous cycle of the evaluation area, is the area of the evaluation area, is the monitoring period, is the standard year data; Both the current soil erosion modulus of the evaluation area and the soil erosion modulus at the end of the previous cycle of the evaluation area are obtained from the observational data of the observation station.

[0016] Preferably, the formula for evaluating the periodic soil and water loss grade of the numbered area is as follows:

[0017] In the formula, is the periodic soil and water loss grade, is the ceiling function, is the difference in the periodic soil and water loss grade.

[0018] Preferably, the steps to calculate the loss risk of the numbered area by combining the periodic soil and water loss grade, terrain data and soil data are as follows: Obtain the slope data of the terrain data in the numbered area, divide the numbered area according to the slope data, and divide the numbered area into , (50%, 100%), , (150%, 200%) and , 5 grade areas; Calculate the risk resistance of the 5 grade areas separately. The specific formula is as follows:

[0019] In the formula, is risk resistance, is the preset anti-risk coefficient of soil type, is the preset anti-risk coefficient of vegetation type, and n is the slope data randomly selected in each grade area, is the i-th slope data randomly selected; Based on the risk resistance, the erosion risks of 5 grade areas are calculated, and the specific formula is as follows:

[0020] In the formula, is the calculated erosion risk, is the conversion coefficient between the periodic soil erosion grade and the erosion risk, is the slope influence conversion coefficient, is the rainfall data, is the preset hazardous rainfall data, is the rainfall influence conversion coefficient, is the conversion coefficient between the risk resistance and the erosion risk.

[0021] Preferably, the steps of comparing the erosion risk of the numbered area with its corresponding risk critical value and formulating corresponding emergency warning strategies according to the comparison results are as follows: Obtain the land use type data of the numbered area, and calculate the risk critical values of 5 grade areas. The specific formula is as follows:

[0022] In the formula, is the calculated risk critical value of the grade area, is the set standard risk critical value, is the conversion coefficient corresponding to the land use type, <1; Compare the calculated erosion risk of the grade area with its corresponding risk critical value of the grade area; If the erosion risk of the grade area ≥ the risk critical value of the grade area, issue a warning; If the erosion risk of the grade area < the risk critical value of the grade area, do not make a response.

[0023] Preferably, the steps of comparing the soil erosion grade with the preset human intervention grade and executing the corresponding strategy according to the comparison result are as follows: If the soil erosion grade ≥ the human intervention grade, analyze the contribution corresponding to the cause of soil erosion and generate a soil erosion impact report; If the soil erosion grade < the human intervention grade, do not make a response.

[0024] Preferably, the analysis of the causes of soil and water loss includes the causes of rainfall impact, wind impact, and human activity impact; The steps for calculating the contribution ratio corresponding to the causes of soil and water loss are as follows: Obtain precipitation records and wind records during the cycle process; Establish a SWAT model and use the SWAT model to simulate the hydrological processes of different cycles to obtain Y1, Y2, and Y3. Among them, Y1 is the average runoff change data calculated by the SWAT model under the condition that the causes of rainfall impact, wind impact, and human activity impact remain unchanged; Y2 is the average runoff change data calculated by the SWAT model with the cause of rainfall impact as a variable and the causes of wind impact and human activity impact remaining unchanged; Y3 is the average runoff change data calculated by the SWAT model with the cause of wind impact as a variable and the causes of rainfall impact and human activity impact remaining unchanged; Calculate the contribution ratio corresponding to the causes of soil and water loss based on Y1, Y2, and Y3. The specific formula is as follows:

[0025] In the formula, is the contribution ratio of rainfall to soil and water loss, is the contribution ratio of wind to soil and water loss, is the contribution ratio of human activities to soil and water loss, is the average runoff at the beginning of the cycle, is the average runoff at the end of the cycle, is the total contribution ratio of the preset rainfall impact, wind impact, and human activity impact.

[0026] Preferably, a method for dynamic monitoring of soil and water loss includes the following steps: Obtain remote sensing image data, DEM image data, geological data, and future precipitation data of the monitoring area; Analyze the remote sensing image data to obtain land use type data in the monitoring area. Then, divide and number the monitoring area based on the land use type data in the monitoring area. Next, analyze the remote sensing image data, DEM image data, and geological data in turn to obtain vegetation data, terrain data, and soil data of the numbered area; Analyze the processed soil data of the numbered area, calculate the periodic soil and water loss amount of the evaluation area, and analyze the periodic soil and water loss amount to evaluate the periodic soil and water loss grade of the numbered area; Obtain precipitation data for the next cycle, and calculate the loss risk of the numbered area in combination with the periodic soil and water loss grade, terrain data, and soil data. Then, compare the loss risk of the numbered area with its corresponding risk critical value, and formulate corresponding emergency warning strategies according to the comparison results; Obtain the soil and water loss level of the numbered area, compare the soil and water loss level with the preset artificial intervention level, and execute corresponding strategies according to the comparison result.

[0027] (III) Beneficial effects The present invention provides a method and system for dynamic monitoring of soil and water loss, which have the following beneficial effects: 1. The present invention provides a method and system for dynamic monitoring of soil and water loss. When in use, the monitoring area is divided according to the land use type, then the divided areas are numbered, and then analyzed separately to evaluate the soil and water loss situation of the numbered area. This can facilitate relevant technical personnel to understand the soil and water loss situation of the monitoring area, analyze the interference of land use type on soil and water loss, and thus facilitate relevant technical personnel to formulate relevant soil and water loss control plans. It has good use effects and has a good application prospect.

[0028] 2. The present invention provides a method and system for dynamic monitoring of soil and water loss. When in use, the monitoring area is divided according to the land use type, and then the divided areas are further segmented according to the terrain, and then the risk of soil and water loss during rainfall is further analyzed. This can help relevant technical personnel understand the danger of the monitoring area under the conditions of soil and water loss and rainfall, thus facilitating relevant technical personnel to quickly understand the risk areas and risk levels, and facilitating relevant technical personnel to formulate corresponding risk prevention and control strategies. It has a relatively wide applicability, good use effects, and has a good use prospect.

[0029] 3. The present invention provides a method and system for dynamic monitoring of soil and water loss. It can analyze and compare the soil and water loss situation of the monitoring area, generate a corresponding soil and water loss impact report for the soil and water loss situation of the soil and water loss risk area, and analyze the contribution of various causes of soil and water loss, so as to facilitate relevant personnel to accurately formulate corresponding soil and water treatment and control strategies, thereby accelerating the restoration of soil and water, and at the same time reducing the workload of relevant staff. The overall use effect is good and it has a good adaptation prospect. Description of the drawings

[0030] Figure 1 It is a flow block diagram of a soil and water loss dynamic monitoring system of the present invention; Figure 2 It is a graded area diagram with abnormal marks when a soil and water loss dynamic monitoring system of the present invention is in use. Detailed implementation manners

[0031] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with 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. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0032] Research reasons In the existing technology center solution, the initial monitoring data of the area to be monitored is collected, the initial monitoring data is screened and processed, and analyzed. The area to be monitored is classified according to the annual soil loss and the prevention and control intensity, and the corresponding monitoring mechanism is adjusted according to the classified area, which is beneficial to collecting data at any time and timely discovering the soil erosion situation. When the area to be monitored is an area in urgent need of key treatment, the number of wireless sensor nodes in the area to be monitored is increased, that is, on the basis of the original wireless sensor nodes in the area to be monitored, additional wireless sensor nodes are added to improve the accuracy of data detection.

[0033] However, the above solution has certain defects in actual use. The above solution mainly increases the amount of data collection, and judges whether there is soil erosion through sufficient data; However, in actual use, the situation is often complex. The monitoring of soil erosion is mainly for the convenience of subsequent soil restoration. In real life, the main cause of soil erosion is the impact of human activities. In actual use, it is often unclear the degree of the impact of human activities, and the existing solutions do not have relevant records, and often rely on the judgment of relevant technical personnel, and the whole process is relatively complex; In addition, soil erosion will combine with the environment and cause other hazards. In this regard, the existing solutions cannot reflect it, so that other systems or methods must be used to analyze the soil erosion data, making the whole process more complicated; Finally, the existing solutions can only judge the degree of soil erosion, but they cannot analyze the causes of soil erosion and the corresponding contributions, making it impossible for relevant personnel to quickly formulate corresponding strategies, making the formulation of subsequent treatment plans more cumbersome and not meeting people's requirements.

[0034] Design idea In view of the fact that the existing soil erosion monitoring solutions mainly focus on the acquisition and analysis of data to obtain soil erosion-related data, and do not further analyze the soil erosion-related data during the soil monitoring process, and cannot provide a basis for subsequent soil erosion treatment.

[0035] Therefore, during the R & D process, the initial idea was how to achieve the synchronous analysis of soil and water loss - related data in the process of soil and water loss analysis, analyze the relevant data, and combine with the soil and water loss data to understand the impact caused by human activities during the soil and water loss process, so as to formulate a plan to divide the area according to land use types, conduct separate analysis, and facilitate subsequent comparison to understand the impact of soil and water loss caused by human activities.

[0036] However, it was found during the actual use that using this method, the application of soil and water loss data was still relatively simple, mainly staying on the surface of the soil and water loss problem, without further extension of the soil and water loss problem, especially the harm risks caused by the soil and water loss problem.

[0037] Therefore, in the middle stage of R & D, the idea was changed, the plan was adjusted, and a plan for further analysis of soil and water loss data was added. Combining the influence of rainfall, the risks caused by soil and water loss were analyzed to help relevant technical personnel predict the occurrence of risks in advance, so as to facilitate relevant technical personnel to formulate corresponding strategies, reduce the harm caused by the danger, with good use effects and good application prospects.

[0038] However, it was found during the actual use that due to the influence of various reasons on soil and water loss, the above - mentioned analysis was not sufficient to help relevant technical personnel formulate the treatment plan for soil and water loss. Therefore, the above - mentioned plan still had certain drawbacks in actual use.

[0039] Therefore, in the later stage of R & D, fully combining the previous plan, a soil and water loss dynamic monitoring method and system were developed. It fully analyzes the soil and water loss data, and can facilitate relevant technical personnel to understand the contribution of the causes of soil and water loss and the corresponding risks of soil and water loss, so as to facilitate relevant personnel to formulate corresponding treatment plans, with good use effects.

[0040] Research plan As Figure 1 shown, a soil and water loss dynamic monitoring system includes two parts: hardware and software. The hardware part is the same as the existing system, mainly relying on servers and signal transmission devices, while the software part includes a data acquisition module, a data processing module, a data analysis module, a risk assessment module, and a loss analysis module: Data collection The soil and water loss dynamic monitoring system of the present invention, like the existing system, needs to collect the soil and water data of the monitoring area during actual use and analyze the corresponding soil and water data in order to understand the situation of soil and water loss in the monitoring area. And the collection of the soil and water data of the monitoring area is based on the data acquisition module.

[0041] Data acquisition module: used to acquire remote sensing image data, DEM image data, geological data, and future precipitation data of the monitoring area; Remote sensing image data relies on remote sensing technology. When in use, it can be downloaded and obtained through relevant platforms such as satellite application centers. This situation is applicable to large-area analysis.

[0042] It can also be taken by an aircraft or a drone equipped with relevant sensors. This situation is applicable to small-area analysis.

[0043] In addition, it can also be obtained through ground equipment such as hyperspectral spectrometers and lidar. Under normal circumstances, it is obtained by downloading through relevant platforms such as satellite application centers.

[0044] DEM image data is mainly collected and measured through remote sensing technology, such as through drone remote sensing and satellite remote sensing.

[0045] Geological data is mainly obtained through data published by the geological center and analysis of data collected on-site.

[0046] Future precipitation data is obtained through data published by the meteorological bureau.

[0047] Data processing When relevant data is collected, in order to facilitate understanding of the relevant data through data processing, it is necessary to perform certain corrections and other processing on the data, extract the required data from it, and only then can it be used in the subsequent data analysis process. And data processing is based on the data processing module.

[0048] Data processing module: Analyze the remote sensing image data to obtain land use type data in the monitoring area, then divide and number the monitoring area based on the land use type data in the monitoring area, and then analyze the remote sensing image data, DEM image data, and geological data in turn to obtain vegetation data, terrain data, and soil data of the numbered area; The steps to analyze the remote sensing image data to obtain the land use type and distribution data in the monitoring area are as follows: Obtain remote sensing image data of different quarters in the monitoring area. There are certain differences in the results obtained from different seasons. Take the mode of all results; Perform radiometric correction, atmospheric correction, and geometric correction on the obtained remote sensing image data; Extract the characteristic data of the remote sensing image data. The characteristic data includes spectral characteristics, texture characteristics, shape characteristics, and shadow characteristics; The types of land use include paddy fields, dry land, forest land, grassland, water areas, urban and rural construction land, and unused areas.

[0049] The spectral features are mainly hues, and there are obvious differences in hues among different land use types.

[0050] The texture features are mainly distributions.

[0051] Based on the convolutional neural network model and the extracted features, the remote sensing image data is identified and classified to obtain the land use types within the monitoring area, and is output in the form of a map.

[0052] The land use types are marked on the map, and this method can clearly show the situation of the monitoring area.

[0053] By combining multiple features, the land use types can be clearly identified. After being processed by the convolutional neural network model, the convolutional neural network model has high recognition accuracy after training, the analysis results are relatively accurate, the use effect is relatively good, and the processing speed is relatively fast, which can greatly reduce the workload of relevant staff and has a relatively good use effect.

[0054] The steps to obtain vegetation data by analyzing remote sensing image data are as follows: Analyze the remote sensing image data after radiometric correction, atmospheric correction and geometric correction, and extract the data of the red light band and the near-infrared light band; Calculate the vegetation data, and the vegetation data is the vegetation coverage rate. The specific formula is as follows:

[0055] In the formula, is the vegetation coverage rate, and are both constants, is the light radiation value of the near-infrared band, and R is the light radiation value of the red light band; and are set according to the situation of the numbered area, and the and of each numbered area are different.

[0056] The terrain data includes elevation data, slope data and slope length data. The steps to obtain the terrain data of the numbered area by analyzing the DEM image data are as follows: Load the DEM image data into the GIS data processing software, and query the elevation data of each position in the numbered area. The GIS data processing software is existing software, and the required data can be directly analyzed and obtained; Use the slope calculation tool in the GIS data processing software to calculate the slope data, and then use the slope data to calculate the slope length data; Using the GIS data processing software to obtain data is a commonly used technique in the prior art, and this patent does not improve it. Therefore, no more description will be made.

[0057] The soil data is obtained through soil analysis by the stratified sampling method. The soil data includes soil type, soil texture, soil structure, and organic matter content.

[0058] Data analysis After processing the data and learning about the land use type, numbering is further carried out, and then the numbered areas are further processed to understand the soil erosion situation in each area, so as to facilitate subsequent further analysis and judgment. This process is based on the data analysis module.

[0059] Data analysis module: used to analyze the soil data of the numbered areas obtained by processing, calculate the periodic soil erosion amount of the evaluation area, and analyze the periodic soil erosion amount to evaluate the periodic soil erosion grade of the numbered areas; The formula for calculating the periodic soil erosion amount of the evaluation area is as follows:

[0060] In the formula, is the periodic soil erosion amount of the evaluation area, is the current soil erosion modulus of the evaluation area, m is the soil erosion modulus at the end of the previous period of the evaluation area, is the area of the evaluation area, is the monitoring period, is the standard year data; The monitoring period is set according to requirements. The higher the periodic soil erosion grade, the shorter the set monitoring period. By adjusting the monitoring period in the monitoring area in this way, a more reasonable monitoring plan can be formulated.

[0061] The formula for evaluating the periodic soil erosion grade of the numbered areas is as follows:

[0062] In the formula, is the periodic soil erosion grade, is the ceiling function, is the difference in periodic soil erosion grades.

[0063] For example, the monitoring period for the periodic soil erosion grade of level 1 is set to 1 year, the monitoring period for the periodic soil erosion grade of level 2 is set to 10 months, the monitoring period for the periodic soil erosion grade of level 3 is set to 8 months, the monitoring period for the periodic soil erosion grade of level 4 is set to 6 months, the monitoring period for the periodic soil erosion grade of level 5 is set to 4 months, and the monitoring period for the periodic soil erosion grade of level 5 and above is set to 1 month. This kind of design is more reasonable and the monitoring effect is better.

[0064] The current soil erosion modulus of the evaluation area and the soil erosion modulus at the end of the previous cycle of the evaluation area are both obtained from the observational data of the observation station.

[0065] The present invention provides a method and system for dynamic monitoring of soil and water loss. When in use, the monitoring area is divided according to the land use type, then the divided areas are numbered, and then analyzed separately to evaluate the soil and water loss situation of the numbered areas. It can facilitate relevant technical personnel to understand the soil and water loss situation of the monitoring area, facilitate relevant technical personnel to analyze the interference of land use type on soil and water loss, and thus facilitate relevant technical personnel to formulate relevant soil and water loss control plans. It has good use effect and good application prospect.

[0066] Risk analysis After data analysis, when the periodic soil and water loss volume and the periodic soil and water loss grade of the numbered area are understood, further analysis and research are needed to judge the harm caused by soil and water loss, and the process of this risk assessment depends on the risk assessment module.

[0067] Risk assessment module: used to obtain precipitation data for the future cycle, and calculate the loss risk of the numbered area in combination with the periodic soil and water loss grade, terrain data and soil data, and compare the loss risk of the numbered area with its corresponding risk critical value, and formulate corresponding emergency warning strategies according to the comparison results; The steps of calculating the loss risk of the numbered area in combination with the periodic soil and water loss grade, terrain data and soil data are as follows: Obtain the slope data of the terrain data of the numbered area, divide the numbered area according to the slope data, and divide the numbered area into 、(50%, 100%), 、(150%, 200%) and , 5 grade areas; Slope is about 63.45 degrees, slope is about 84.29°, and the interval of the fifth grade is large because the angle exceeds 60°. In this case, soil and water loss is basically not considered. Rainfall combined with gravity will carry away the soil. Therefore, this interval is set relatively large. There is no need to analyze further beyond this case.

[0068] Calculate the risk resistance of the 5 grade areas separately, and the specific formula is as follows:

[0069] In the formula, is the risk resistance, is the preset anti-risk coefficient of the soil type, is the preset anti-risk coefficient of the vegetation type, and n is the slope data randomly selected for each grade area. is the i-th slope data randomly selected; For example, 4 points are selected in a certain grade area, and the slopes are 62%, 78%, 53% and 87% respectively. The calculated is 70%.

[0070] Based on the risk resistance, the loss risks of 5 grade areas are calculated. The specific formula is as follows:

[0071] In the formula, is the calculated loss risk, is the conversion coefficient between the periodic soil and water loss grade and the loss risk, is the slope influence conversion coefficient, is the rainfall data, is the preset harmful rainfall data, is the rainfall influence conversion coefficient, is the conversion coefficient between the risk resistance and the loss risk.

[0072] The higher it is, the more dangerous it indicates.

[0073] The steps of comparing the loss risk of the numbered area with its corresponding risk critical value and formulating corresponding emergency warning strategies according to the comparison results are as follows: Obtain the land use type data of the numbered area and calculate the risk critical values of 5 grade areas. The specific formula is as follows:

[0074] In the formula, is the calculated risk critical value of the grade area, is the set standard risk critical value, is the conversion coefficient corresponding to the land use type, < 1; In actual situations, the larger the slope, the greater the probability of risks. Therefore, for areas with a high slope grade, the set risk critical value will be lower. Only in this way can the risk position be more accurately displayed and it can be convenient for relevant technical personnel to understand the risk.

[0075] Compare the calculated loss risk of the grade area with its corresponding risk critical value of the grade area; If Figure 2As shown, if the risk of loss in the grade area ≥ the risk critical value of the grade area, a warning is issued. In this case, relevant technical personnel are required to quickly formulate a risk control plan. This module can mark abnormal colors on the map and mark the periodic soil and water loss grade at the same time. For example, when the risk of loss < the risk critical value of the grade area, it is marked in green, and when the risk of loss ≥ the risk critical value of the grade area, it is marked in red, which is convenient for relevant personnel to quickly search in the follow-up and is relatively convenient to use; If the risk of loss in the grade area < the risk critical value of the grade area, no response is made.

[0076] The steps of comparing the soil and water loss grade with the preset human intervention grade and executing the corresponding strategy according to the comparison result are as follows: If the soil and water loss grade ≥ the human intervention grade, analyze the contribution corresponding to the cause of soil and water loss and generate a soil and water loss impact report; If the soil and water loss grade < the human intervention grade, no response is made.

[0077] The present invention provides a method and system for dynamic monitoring of soil and water loss. When in use, the monitoring area is divided according to the land use type, and then the divided area is further segmented according to the terrain, and then the risk of soil and water loss during rainfall is further analyzed, which can help relevant technical personnel understand the danger of the monitoring area under the conditions of soil and water loss and rainfall, so as to facilitate relevant technical personnel to quickly understand the risk area and the risk degree, facilitate relevant technical personnel to formulate corresponding risk prevention and control strategies, has a relatively wide applicability, good use effect, and has a good application prospect.

[0078] Cause analysis When the periodic soil and water loss volume and the periodic soil and water loss grade of the numbered area are understood, further analysis and research are needed to analyze how to regulate and improve the soil and water loss situation in the monitoring area. Therefore, it is necessary to analyze the causes of soil and water loss in the monitoring area.

[0079] The loss analysis module: used to obtain the soil and water loss grade of the numbered area, compare the soil and water loss grade with the preset human intervention grade, and execute the corresponding strategy according to the comparison result.

[0080] The human intervention grade is formulated according to the local situation. For areas with high economic conditions, the human intervention grade is set lower.

[0081] Analyzing the causes of soil and water loss includes the causes of rainfall impact, wind impact, and human activity impact; The steps of analyzing the contribution ratio corresponding to the cause of soil and water loss are as follows: Obtain the precipitation record and wind record during the cycle process; The SWAT model was established, and the SWAT model was used to simulate the hydrological processes in different periods, obtaining Y1, Y2, and Y3. Among them, Y1 is the data of the change in the average runoff calculated by the SWAT model under the condition that the reasons for rainfall influence, wind influence, and human activity influence remain unchanged; Y2 is the data of the change in the average runoff calculated by the SWAT model with the reason for rainfall influence as a variable and the reasons for wind influence and human activity influence remaining unchanged; Y3 is the data of the change in the average runoff calculated by the SWAT model with the reason for wind influence as a variable and the reasons for rainfall influence and human activity influence remaining unchanged. The SWAT model simulates the contributions of the reasons for rainfall influence, wind influence, and human activity influence to the changes in the runoff-sediment process.

[0082] Based on Y1, Y2, and Y3, the contribution ratios corresponding to the reasons for soil and water loss are calculated. The specific formula is as follows:

[0083] In the formula, is the contribution ratio of rainfall to soil and water loss, is the contribution ratio of wind to soil and water loss, is the contribution ratio of human activities to soil and water loss, is the average runoff at the beginning of the period, is the average runoff at the end of the period, is the total contribution ratio of the preset rainfall influence, wind influence, and human activity influence.

[0084] In actual use, the reasons for soil and water loss are selected according to the actual situation. Select 3-5 reasons for soil and water loss that have the greatest impact on soil and water loss, and then analyze them in the above manner to calculate the contributions of each reason for soil and water loss, so as to facilitate subsequent adjustment.

[0085] In subsequent adjustment, for example, if the contribution ratio of human activity influence is the highest, the adjustment strategy is to reduce the impact of human activities; if the contribution ratio of rainfall influence is the highest, relevant drainage measures need to be established or climate management of the area needs to be carried out, such as dispersing dark clouds.

[0086] The present invention provides a method and system for dynamic monitoring of soil and water loss, which can analyze and compare the soil and water loss situation in the monitored area, generate a corresponding soil and water loss impact report for the soil and water loss situation in the soil and water loss risk area, and analyze the contributions of various reasons for soil and water loss, so as to facilitate relevant personnel to accurately formulate corresponding soil and water treatment control strategies, thereby accelerating the restoration of soil and water, reducing the workload of relevant staff at the same time, having a good overall use effect, and having a good adaptation prospect.

[0087] The weight coefficient is determined by the coefficient of variation method. The coefficient of variation method is a method of assigning weights to each evaluation index according to the degree of variation between the current value and the target value of each evaluation index. If the values of a certain index vary greatly and can clearly distinguish each evaluated object, it indicates that the discrimination information of this index is rich, so a larger weight should be given to this index. On the contrary, if the values of each evaluated object on a certain index vary little, then the ability of this index to distinguish each evaluation object is weak, so a smaller weight should be given to this index. This method directly utilizes the information contained in each index and calculates the weight of the index, so it has objectivity.

[0088] The other weight coefficients are all discussed by experts through the above method, and most enterprises in this field have corresponding weight coefficients.

[0089] Embodiment 2 A dynamic monitoring method for soil and water loss, comprising the following steps: Obtain remote sensing image data, DEM image data, geological data and future precipitation data of the monitoring area; Analyze the remote sensing image data to obtain land use type data within the monitoring area, then divide and number the monitoring area according to the land use type data within the monitoring area, and then analyze the remote sensing image data, DEM image data and geological data in turn to obtain vegetation data, terrain data and soil data of the numbered area; Analyze the processed soil data of the numbered area, calculate the periodic soil and water loss amount of the evaluation area, and analyze the periodic soil and water loss amount to evaluate the periodic soil and water loss grade of the numbered area; Obtain precipitation data for the future period, and calculate the loss risk of the numbered area in combination with the periodic soil and water loss grade, terrain data and soil data, and compare the loss risk of the numbered area with its corresponding risk critical value, and formulate corresponding emergency warning strategies according to the comparison results; Obtain the soil and water loss grade of the numbered area, compare the soil and water loss grade with the preset human intervention grade, and execute the corresponding strategy according to the comparison result.

[0090] The above formula is obtained by collecting a large amount of data for software simulation to get a formula closest to the real situation, and the preset parameters in the formula are set by technicians in this field according to the actual situation.

[0092] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art will appreciate that the units and algorithm steps of the examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution.

[0093] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. They may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the objectives of the solution of this embodiment.

[0094] As described above, the above is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application.

Claims

1. A dynamic monitoring system for soil and water loss, characterized in that, Including: Data acquisition module: used to acquire remote sensing image data, DEM image data, geological data, and future precipitation data of the monitoring area; Data processing module: analyze the remote sensing image data to obtain land use type data within the monitoring area, then divide and number the monitoring area based on the land use type data within the monitoring area, and then analyze the remote sensing image data, DEM image data, and geological data in sequence to obtain vegetation data, terrain data, and soil data of the numbered area; Data analysis module: used to analyze the processed soil data of the numbered area, calculate the periodic soil and water loss amount of the evaluation area, and analyze the periodic soil and water loss amount to evaluate the periodic soil and water loss grade of the numbered area; Risk assessment module: used to acquire precipitation data for the future period, and calculate the loss risk of the numbered area in combination with the periodic soil and water loss grade, terrain data, and soil data, and compare the loss risk of the numbered area with its corresponding risk critical value, and formulate corresponding emergency warning strategies according to the comparison results; Loss analysis module: used to acquire the soil and water loss grade of the numbered area, compare the soil and water loss grade with the preset human intervention grade, and execute corresponding strategies according to the comparison results.

2. The dynamic soil erosion monitoring system according to claim 1, wherein: The steps for analyzing the remote sensing image data to obtain the land use type and distribution data within the monitoring area are as follows: Acquire remote sensing image data of different quarters in the monitoring area; Perform radiometric correction, atmospheric correction, and geometric correction on the acquired remote sensing image data; Extract the characteristic data of the remote sensing image data, and the characteristic data includes spectral characteristics, texture characteristics, shape characteristics, and shadow characteristics; Based on the convolutional neural network model and the extracted characteristics, identify and classify the remote sensing image data to obtain the land use type within the monitoring area, and output it in the form of a map.

3. A dynamic soil erosion monitoring system according to claim 2, characterized in that: The steps for analyzing the remote sensing image data to obtain vegetation data are as follows: Analyze the remote sensing image data after radiometric correction, atmospheric correction, and geometric correction, and extract the data of the red light band and the near-infrared light band; Calculate the vegetation data, and the vegetation data is the vegetation coverage rate. The specific formula is as follows: ； In the formula, is the vegetation coverage rate, and are both constants, is the light radiation value in the near-infrared band, and R is the light radiation value in the red light band; The terrain data includes elevation data, slope data, and slope length data. The steps for analyzing the DEM image data to obtain the terrain data of the numbered area are as follows: Load the DEM image data into the GIS data processing software, and query the elevation data of each location in the numbered area; Use the slope calculation tool in the GIS data processing software to calculate the slope data, and then use the slope data to calculate the slope length data; The soil data is obtained by analyzing the soil collected by the stratified sampling method. The soil data includes soil type, soil texture, soil structure, and organic matter content.

4. A dynamic soil erosion monitoring system according to claim 3, characterized in that: The formula for calculating the periodic soil and water loss amount of the evaluation area is as follows: ； In the formula, is the periodic soil and water loss amount in the evaluation area, is the current soil erosion modulus in the evaluation area, and m is the soil erosion modulus at the end of the previous period in the evaluation area, is the area of the evaluation area, is the monitoring period, is the data of the standard years; Both the current soil erosion modulus of the evaluation area and the soil erosion modulus at the end of the previous period of the evaluation area are obtained from the observation data of the observation station.

5. The dynamic soil erosion monitoring system according to claim 4, wherein: The formula for evaluating the periodic soil and water loss grade of the numbered area is as follows: ； In the formula, is the periodic soil and water loss grade, is the ceiling function, is the difference of the periodic soil and water loss grade.

6. The dynamic monitoring system for soil and water loss according to claim 5, wherein: The steps for calculating the loss risk of the numbered area in combination with the periodic soil and water loss grade, terrain data, and soil data are as follows: Obtain the slope data of the terrain data in the numbered area, divide the numbered area according to the slope data, and divide the numbered area into 、(50%, 100%), 、(150%, 200%) and , 5 grade areas; Calculate the risk resistance of 5 grade areas separately. The specific formula is as follows: ； Wherein, is the risk resistance, is the preset risk resistance coefficient of the soil type, is the preset risk resistance coefficient of the vegetation type, and n is the slope data randomly sampled from each grade area, is the i-th slope data randomly sampled; Calculate the loss risks of five-level regions based on risk resistance. The specific formula is as follows: ； In the formula, is the calculated risk of loss, is the conversion coefficient between the periodic soil and water loss grade and the risk of loss, is the conversion coefficient affected by slope, is the rainfall data, is the preset harmful rainfall data, is the conversion coefficient affected by rainfall, is the conversion coefficient between the risk resistance and the risk of loss.

7. The dynamic monitoring system for soil and water loss according to claim 6, characterized in that: Compare the loss risks of the numbered regions with their corresponding risk critical values, and formulate corresponding emergency warning strategies according to the comparison results. The steps are as follows: Obtain the land use type data of the numbered regions, and calculate the risk critical values of the five-level regions. The specific formula is as follows: ； In the formula, is the risk critical value of the calculated grade area, is the set standard risk critical value, is the conversion coefficient corresponding to the land use type, <1; Compare the calculated loss risks of the level regions with the risk critical values of their corresponding level regions; If the loss risk of the level region ≥ the risk critical value of the level region, issue a warning; If the loss risk of the level region < the risk critical value of the level region, do not make a response.

8. A dynamic soil erosion monitoring system according to claim 7, characterized in that: Compare the soil erosion level with the preset human intervention level, and execute the corresponding strategy according to the comparison result. The steps are as follows: If the soil erosion level ≥ the human intervention level, analyze the contributions corresponding to the causes of soil erosion and generate a soil erosion impact report; If the soil erosion level < the human intervention level, do not make a response.

9. A dynamic monitoring system for soil and water loss according to claim 8, characterized in that: Analyze the causes of soil erosion, including the causes of rainfall impact, wind impact, and human activity impact; The steps to analyze the contribution ratio corresponding to the causes of soil erosion are as follows: Obtain the precipitation records and wind records during the period; Establish a SWAT model, and use the SWAT model to simulate the hydrological processes of different periods to obtain Y1, Y2, and Y3. Among them, Y1 is the average runoff change data calculated by the SWAT model with the causes of rainfall impact, wind impact, and human activity impact unchanged, Y2 is the average runoff change data calculated by the SWAT model with the cause of rainfall impact as a variable and the causes of wind impact and human activity impact unchanged, and Y3 is the average runoff change data calculated by the SWAT model with the cause of wind impact as a variable and the causes of rainfall impact and human activity impact unchanged; Calculate the contribution ratio corresponding to the causes of soil erosion based on Y1, Y2, and Y3. The specific formula is as follows: ； In the formula, is the contribution ratio of rainfall to soil and water loss, is the contribution ratio of wind to soil and water loss, is the contribution ratio of human activities to soil and water loss, is the average runoff at the start of the period, is the average runoff at the end of the period, is the total contribution ratio of the preset rainfall impact, wind impact, and human activity impact.

10. A dynamic monitoring method for soil and water loss, using the system according to any one of claims 1 to 9, characterized in that: Include the following steps: Obtain the remote sensing image data, DEM image data, geological data, and future precipitation data of the monitoring area; Analyze the remote sensing image data to obtain the land use type data within the monitoring area, then divide and number the monitoring area according to the land use type data within the monitoring area, and then analyze the remote sensing image data, DEM image data, and geological data in turn to obtain the vegetation data, terrain data, and soil data of the numbered regions; Analyze the processed soil data of the numbered regions, calculate the periodic soil erosion amount of the evaluation area, and analyze the periodic soil erosion amount to evaluate the periodic soil erosion level of the numbered regions; Obtain the precipitation data of the future period, and calculate the loss risks of the numbered regions in combination with the periodic soil erosion level, terrain data, and soil data, and compare the loss risks of the numbered regions with their corresponding risk critical values, and formulate corresponding emergency warning strategies according to the comparison results; Obtain the soil erosion level of the numbered regions, compare the soil erosion level with the preset human intervention level, and execute the corresponding strategy according to the comparison result.

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