Surface runoff model big data numerical collection and monitoring system and method

Abstract

The present invention provides a surface runoff model big data digitization collection and monitoring system and method, which belongs to the field of vegetation restoration on both sides of the river. The system comprises: a shrub detection data acquisition device in the scour line watershed; a vegetation detection data acquisition device at the sudden change point of the slope cross-section in the scour line watershed; a soil index detection data acquisition device in the scour line watershed; a runoff scour concentration point detection data acquisition device in the scour line watershed; a landmark runoff detection data acquisition device in the scour line watershed; a ground-covering plant detection data acquisition device in the scour line watershed; a dynamic flow velocity detection data acquisition device in the scour line; a data processing device; and a judgment and decision-making module. The present invention judges and selects a vegetation adjustment plan based on the data monitored at the confluence monitoring point, so that the vegetation on both sides of the river can dynamically maintain a stable water absorption capacity, thereby conserving water and soil and slowing down the rise of the river water level during the flood season.

Description

Technical Field

[0001] The present invention belongs to the field of vegetation restoration on both sides of a river channel, and in particular relates to a surface runoff model big data numerical collection and monitoring system and method. Background Art

[0002] The vegetation along a river significantly influences its flow rate and water volume. More vegetation on either side absorbs more rainfall, reducing the amount of water flowing into the river. This, in turn, slows the rise in river levels during flood season and prevents flooding.

[0003] Therefore, by collecting and monitoring data at river confluence points, it is possible to reversely calculate whether the vegetation situation needs to be adjusted. Summary of the Invention

[0004] An object of the present invention is to provide a system and method for collecting and monitoring surface runoff model big data numerically, and to provide at least the advantages described below.

[0005] Another object of the present invention is to provide a surface runoff model big data digital collection and monitoring system and method, which judges and selects vegetation adjustment plans based on the data monitored at the confluence monitoring point, so that the vegetation on both sides of the river can dynamically maintain a stable water absorption capacity, which can not only conserve water and soil, but also slow down the rise in river water levels during flood season.

[0006] The technical solutions of the present invention are as follows:

[0007] The surface runoff model big data numerical collection and monitoring system includes:

[0008] Data collection device for shrub detection in the wash line watershed;

[0009] Vegetation detection data collection device for the sudden change points of slope cross-section within the scour line basin;

[0010] Data collection device for detecting soil indexes in the scour line basin;

[0011] Data collection device for detecting runoff scour concentration points within the scour line basin;

[0012] Landmark runoff detection data collection device within the scour line basin;

[0013] Data collection device for detecting ground cover plants in the scour line watershed;

[0014] Dynamic flow velocity detection data acquisition device in the flushing line;

[0015] The data processing device is connected to the shrub detection data acquisition device in the scour line watershed, the vegetation detection data acquisition device at the sudden change point of slope section in the scour line watershed, the soil index detection data acquisition device in the scour line watershed, the runoff scour concentration point detection data acquisition device in the scour line watershed, the landmark runoff detection data acquisition device in the scour line watershed, the ground-covering plant detection data acquisition device in the scour line watershed and the dynamic flow velocity detection data acquisition device in the scour line, receives the detection data sent by them and calculates and converts them to obtain Q1 surface seepage, Q2 plant absorption, Q3 slope runoff, Q 土 Natural water content of soil, Q 植 Plant self-absorption capacity, Q 径流 Vegetation blocking retention, Q 平蒸 Average evaporation, calculated as Q 降总 ;

[0016] The decision module is based on the Q 降总 and A 受水面积 Calculate U 流速 , A 受水面积 is the drainage area within the scour line at the confluence monitoring point. 流速 Determine which vegetation adjustment plan to adopt.

[0017] Preferably, in the surface runoff model big data numerical collection and monitoring system,

[0018] WhenU 流速 When it is greater than 1, greening adjustments need to be made to the scour slope;

[0019] WhenU 流速 When it is equal to 1, it is necessary to optimize the greening of the slope;

[0020] WhenU 流速 When it is less than 1 and greater than 0.5, it is necessary to comprehensively strengthen the greening rate, ensure the survival rate, comprehensively cultivate greening, and carry out ecological restoration;

[0021] WhenU 流速 When it is equal to 0.5, the vegetation needs to be optimized and improved;

[0022] WhenU 流速 When it is less than 0.5, the ecological standard is met and no adjustment is required.

[0023] The surface runoff model big data numerical collection and monitoring method comprises the following steps:

[0024] Obtain shrub detection data within the scour line watershed at the confluence monitoring point, vegetation detection data at the slope cross-section mutation point within the scour line watershed, soil index detection data within the scour line watershed, runoff scour concentration point detection data within the scour line watershed, landmark runoff detection data within the scour line watershed, ground cover plant detection data within the scour line watershed, and dynamic flow velocity detection data within the scour line;

[0025] Based on the shrub detection data in the scour line watershed, the vegetation detection data at the sudden change point of slope section in the scour line watershed, the soil index detection data in the scour line watershed, the runoff scour concentration point detection data in the scour line watershed, the landmark runoff detection data in the scour line watershed, the ground cover plant detection data in the scour line watershed and the dynamic flow velocity detection data in the scour line, the Q1 surface seepage amount, Q2 plant absorption amount, Q3 slope runoff, Q4 slope runoff, Q5 slope runoff and Q6 slope runoff were calculated. 土 Natural water content of soil, Q 植 Plant self-absorption capacity, Q 径流 Vegetation blocking retention, Q 平蒸 average evaporation;

[0026] Q is calculated according to the following formula 降总 ;

[0027] Q 降总 =Q1+Q2+Q3;

[0028] or Q 降总 =Q 土 +Q 植 +Q 径流 +Q 平蒸；

[0029] Then calculate U according to the following formula 流速 ;

[0030] U 流速 =Q 降总 / A 受水面积， A 受水面积 is the drainage area within the scour line basin at the confluence monitoring point;

[0031] WhenU 流速 When it is greater than 1, greening adjustments need to be made to the scour slope;

[0032] WhenU 流速 When it is equal to 1, it is necessary to optimize the greening of the slope;

[0033] WhenU 流速 When it is less than 1 and greater than 0.5, it is necessary to comprehensively strengthen the greening rate, ensure the survival rate, comprehensively cultivate greening, and carry out ecological restoration;

[0034] WhenU 流速 When it is equal to 0.5, the vegetation needs to be optimized and improved;

[0035] WhenU 流速 When it is less than 0.5, the ecological standard is met and no adjustment is required.

[0036] The present invention has the following beneficial effects:

[0037] The vegetation adjustment plan is judged and selected based on the data monitored at the confluence monitoring point, so that the vegetation on both sides of the river can dynamically maintain a stable water absorption capacity, which can not only conserve water and soil, but also slow down the rise in river water levels during flood season.

[0038] Other advantages, objectives and features of the present invention will be reflected in part from the following description and will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a location distribution diagram of the data acquisition devices in one embodiment of the surface runoff model big data digitization collection and monitoring system provided by the present invention. DETAILED DESCRIPTION

[0040] The present invention will be described in further detail below in conjunction with the accompanying drawings so that those skilled in the art can implement the invention with reference to the description.

[0041] It should be understood that terms such as “having,” “including,” and “comprising” used herein do not prescribe the existence or addition of one or more other elements or combinations thereof.

[0042] The present invention provides a surface runoff model big data digitization collection and monitoring system, which includes:

[0043] Data collection device for shrub detection in the wash line watershed;

[0044] Vegetation detection data collection device for the sudden change points of slope cross-section within the scour line basin;

[0045] Data collection device for detecting soil indexes in the scour line basin;

[0046] Data collection device for detecting runoff scour concentration points within the scour line basin;

[0047] Landmark runoff detection data collection device within the scour line basin;

[0048] Data collection device for detecting ground cover plants in the scour line watershed;

[0049] Dynamic flow velocity detection data acquisition device in the flushing line;

[0050] The data processing device is connected to the shrub detection data acquisition device in the scour line watershed, the vegetation detection data acquisition device at the sudden change point of slope section in the scour line watershed, the soil index detection data acquisition device in the scour line watershed, the runoff scour concentration point detection data acquisition device in the scour line watershed, the landmark runoff detection data acquisition device in the scour line watershed, the ground-covering plant detection data acquisition device in the scour line watershed and the dynamic flow velocity detection data acquisition device in the scour line, receives the detection data sent by them and calculates and converts them to obtain Q1 surface seepage, Q2 plant absorption, Q3 slope runoff, Q 土 Natural water content of soil, Q 植 Plant self-absorption capacity, Q 径流 Vegetation blocking retention, Q 平蒸 Average evaporation, calculated as Q 降总 ;

[0051] The decision module is based on the Q 降总 and A 受水面积 Calculate U 流速 , A 受水面积 is the drainage area within the scour line at the confluence monitoring point. 流速 Determine which vegetation adjustment plan to adopt.

[0052] The location distribution of each data acquisition device is as follows: Figure 1 As shown,

[0053] In one embodiment of the surface runoff model big data numerical collection and monitoring system provided by the present invention,

[0054] WhenU 流速 When it is greater than 1, greening adjustments need to be made to the scour slope;

[0055] WhenU 流速 When it is equal to 1, it is necessary to optimize the greening of the slope;

[0056] WhenU 流速 When it is less than 1 and greater than 0.5, it is necessary to comprehensively strengthen the greening rate, ensure the survival rate, comprehensively cultivate greening, and carry out ecological restoration;

[0057] WhenU 流速 When it is equal to 0.5, the vegetation needs to be optimized and improved;

[0058] WhenU 流速 When it is less than 0.5, the ecological standard is met and no adjustment is required.

[0059] The present invention also provides a method for collecting and monitoring surface runoff model big data numerically, which comprises the following steps:

[0060] Obtain shrub detection data within the scour line watershed at the confluence monitoring point, vegetation detection data at the slope cross-section mutation point within the scour line watershed, soil index detection data within the scour line watershed, runoff scour concentration point detection data within the scour line watershed, landmark runoff detection data within the scour line watershed, ground cover plant detection data within the scour line watershed, and dynamic flow velocity detection data within the scour line;

[0061] Based on the shrub detection data in the scour line watershed, the vegetation detection data at the sudden change point of slope section in the scour line watershed, the soil index detection data in the scour line watershed, the runoff scour concentration point detection data in the scour line watershed, the landmark runoff detection data in the scour line watershed, the ground cover plant detection data in the scour line watershed and the dynamic flow velocity detection data in the scour line, the Q1 surface seepage amount, Q2 plant absorption amount, Q3 slope runoff, Q4 slope runoff, Q5 slope runoff and Q6 slope runoff were calculated. 土 Natural water content of soil, Q 植 Plant self-absorption capacity, Q 径流 Vegetation blocking retention, Q 平蒸 average evaporation;

[0062] Q is calculated according to the following formula 降总 ;

[0063] Q 降总 =Q1+Q2+Q3;

[0064] or Q 降总 =Q 土 +Q 植 +Q 径流 +Q 平蒸；

[0065] Then calculate U according to the following formula 流速 ;

[0066] U 流速 =Q 降总 / A 受水面积， A 受水面积 is the drainage area within the scour line basin at the confluence monitoring point;

[0067] WhenU 流速 When it is greater than 1, greening adjustments need to be made to the scour slope;

[0068] WhenU 流速 When it is equal to 1, it is necessary to optimize the greening of the slope;

[0069] WhenU 流速 When it is less than 1 and greater than 0.5, it is necessary to comprehensively strengthen the greening rate, ensure the survival rate, comprehensively cultivate greening, and carry out ecological restoration;

[0070] WhenU 流速 When it is equal to 0.5, the vegetation needs to be optimized and improved;

[0071] WhenU 流速 When it is less than 0.5, the ecological standard is met and no adjustment is required.

[0072] The present invention has the following characteristics:

[0073] 1. Use a ground self-balancing slope intelligent data acquisition system.

[0074] 2. Integrated data acquisition system: terrain displacement + electrothermal self-measurement + humidity and temperature sensing + moisture density dry sensing + infrared remote sensing + flow rate measurement + carbon content decay collection = holographic aerospace integrated surface diameter model big data numerical collection system.

[0075] 3. Application Scope: By analyzing elevation gradients, soil moisture, and changes in physical and chemical composition, as well as the rate of change in surface flow velocity, the system characterizes vegetation conditions and the rate of hydration absorption, calculates water replenishment, and calculates the rate of vegetation loss and replenishment. By integrating these data, a comprehensive long-term system model is established to detect concentrated points of surface erosion and cross-sectional soil erosion. This effectively guides the replenishment of soil and water loss points and the optimization of vegetation space.

[0076] 4. Advantages: It can be attached to the ground for mobile monitoring and can be permanently or semi-permanently buried for monitoring.

[0077] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the description and implementation methods. They can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. The surface runoff model big data numerical collection and monitoring system is characterized by: include: Data collection device for shrub detection in the wash line watershed; Vegetation detection data acquisition device for the sudden change points of slope cross-section within the scour line basin; Data collection device for soil index detection in the scour line basin; Data collection device for detecting runoff scour concentration points within the scour line basin; Landmark runoff detection data collection device within the scour line basin; Data collection device for detecting ground cover plants in the scour line watershed; Dynamic flow velocity detection data acquisition device in the flushing line; The data processing device is connected to the shrub detection data acquisition device in the scour line watershed, the vegetation detection data acquisition device at the slope cross-section mutation point in the scour line watershed, the soil index detection data acquisition device in the scour line watershed, the runoff scour concentration point detection data acquisition device in the scour line watershed, the landmark runoff detection data acquisition device in the scour line watershed, the ground plant detection data acquisition device in the scour line watershed and the dynamic flow velocity detection data acquisition device in the scour line, and receives the detection data from them, which are Q1 surface seepage, Q2 plant absorption, Q3 slope runoff, Q4 slope runoff, Q5 slope runoff and Q6 slope runoff. 土 Natural water content of soil, Q 植 Plant self-absorption capacity, Q 径流 Vegetation blocking retention, Q 平蒸 Average evaporation, calculated as Q 降总 ; The decision-making module is based on Q 降总 and A 受水面积 Calculate U 流速 , A 受水面积 is the drainage area within the scour line at the confluence monitoring point. 流速 Determine which vegetation adjustment plan to adopt.

2. The surface runoff model big data digitization collection and monitoring system according to claim 1, characterized in that: When U 流速 When it is greater than 1, greening adjustments need to be made to the scour slope; When U 流速 When it is equal to 1, it is necessary to optimize the greening of the slope; When U 流速 When it is less than 1 and greater than 0.5, it is necessary to comprehensively strengthen the greening rate, ensure the survival rate, comprehensively cultivate greening, and carry out ecological restoration; When U 流速 When it is equal to 0.5, the vegetation needs to be optimized and improved; When U 流速 When it is less than 0.5, the ecological standard is met and no adjustment is required.

3. A method for collecting and monitoring surface runoff model big data numerically using the surface runoff model big data numerical collection and monitoring system according to claim 1, characterized in that: The following steps are involved: Obtain shrub detection data within the scour line watershed at the confluence monitoring point, vegetation detection data at the slope cross-section mutation point within the scour line watershed, soil index detection data within the scour line watershed, runoff scour concentration point detection data within the scour line watershed, landmark runoff detection data within the scour line watershed, ground cover plant detection data within the scour line watershed, and dynamic flow velocity detection data within the scour line; Based on the shrub detection data in the scour line watershed, the vegetation detection data at the sudden change point of slope section in the scour line watershed, the soil index detection data in the scour line watershed, the runoff scour concentration point detection data in the scour line watershed, the landmark runoff detection data in the scour line watershed, the ground cover plant detection data in the scour line watershed and the dynamic flow velocity detection data in the scour line, the Q1 surface seepage amount, Q2 plant absorption amount, Q3 slope runoff, Q4 slope runoff, Q5 slope runoff and Q6 slope runoff were calculated. 土 Natural water content of soil, Q 植 Plant self-absorption capacity, Q 径流 Vegetation blocking retention, Q 平蒸 average evaporation; Q is calculated according to the following formula 降总 ; <h2 style=";text-align:left;direction:ltr">Q<h2 style=";text-align:left;direction:ltr"> 降总 <h2 style=";text-align:left;direction:ltr"> =Q1+Q2+Q3; or Q 降总 =Q 土 +Q 植 +Q 径流 +Q 平蒸； Then calculate U according to the following formula 流速 ; U 流速 =Q 降总 / A 受水面积， A 受水面积 is the drainage area within the scour line basin at the confluence monitoring point; When U 流速 When it is greater than 1, greening adjustments need to be made to the scour slope; When U 流速 When it is equal to 1, it is necessary to optimize the greening of the slope; When U 流速 When it is less than 1 and greater than 0.5, it is necessary to comprehensively strengthen the greening rate, ensure the survival rate, comprehensively cultivate greening, and carry out ecological restoration; When U 流速 When it is equal to 0.5, the vegetation needs to be optimized and improved; When U 流速 When it is less than 0.5, the ecological standard is met and no adjustment is required.

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