A wetland ecological monitoring system and method

Abstract

The application provides a wetland ecological monitoring system and method, water level data at different monitoring points of a target wetland is monitored through a water level sensor network; difference characteristics of water levels in each water level data are determined, a moving trend of a transition zone between a wetland and land in the target wetland is determined according to all the difference characteristics; a correlation degree of water levels between each adjacent monitoring point is determined, a confluence characteristic of water bodies in a flow process in the target wetland is determined based on all the correlation degrees and elevation characteristics of each monitoring point in the target wetland, a contraction gradient of water flow in a drainage process of the target wetland is determined according to the confluence characteristic and a water potential direction of the target wetland; the moving trend of the transition zone and the contraction gradient of the water flow are associated and analyzed, and then a disturbance cost of water level change in the target wetland is obtained, and a water level state of the target wetland is calibrated according to the disturbance cost. By using the application, potential losses of wetland ecology caused by dynamic changes of water bodies can be quantified.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ecological monitoring, more particularly, the present application relates to a wetland ecological monitoring system and method. BACKGROUND

[0002] Ecological monitoring refers to systematic and long-term observation and evaluation of ecological systems and their components (such as biology, hydrology, soil, climate, etc.) to understand the dynamic changes, health status and development trend of the ecological system.

[0003] Wetland ecosystems have important ecological functions, including water purification, biodiversity maintenance, flood regulation and carbon sink, etc. However, during the long-term operation of the target wetland, due to changes in hydrological conditions, human activity interference and natural succession, etc., the wetland and the land will change dynamically, thereby affecting the ecological stability and functional performance of the wetland. Traditional wetland monitoring methods mainly rely on fixed-point sampling and remote sensing technology, which are difficult to capture the hydrological dynamics of the wetland and its potential impact on the ecological system in real time and accurately, especially in the comprehensive evaluation of water flow, transition zone migration and ecological response. In addition, the drainage process of the target wetland may cause changes in the water flow path, thereby affecting the hydraulic distribution and ecological processes within the wetland. Therefore, how to quantify the potential loss of the wetland ecology caused by the dynamic changes of the water body has become a problem in the industry. SUMMARY

[0004] The present application provides a wetland ecological monitoring system and method, which can quantify the potential loss of the wetland ecology caused by the dynamic changes of the water body.

[0005] In a first aspect, the present application provides a water level monitoring method for water level monitoring by a wetland ecological monitoring system, comprising the following steps:

[0006] Arranging a water level sensor network in the target wetland, monitoring the water level at different monitoring points in the target wetland based on the water level sensor network, and obtaining water level data of each monitoring point;

[0007] Determining the difference characteristics of the water level in each water level data, performing fluctuation analysis on the transition zone between the wetland and the land in the target wetland according to all the difference characteristics, and obtaining the movement trend of the transition zone;

[0008] Determining the correlation degree of the water level between each adjacent monitoring point, determining the confluence characteristics of the water body in the flow process in the target wetland based on all the correlation degrees and the elevation characteristics of each monitoring point in the target wetland, and determining the contraction gradient of the water flow in the drainage process of the target wetland according to the confluence characteristics and the water potential direction of the target wetland;

[0009] Correlate the moving trend of the transition zone and the contraction gradient of the water flow, and then obtain the disturbance cost of the water level change in the target wetland, and calibrate the water level state of the target wetland according to the disturbance cost.

[0010] In some embodiments, the determining of the difference feature of the water level in each water level data specifically comprises:

[0011] Select one water level data as selected water level data, and convert the selected water level data into a water level sequence;

[0012] Determine the difference feature of the water level in the selected water level data according to the water level sequence;

[0013] Continue to determine the difference feature of the water level in the remaining water level data.

[0014] In some embodiments, the fluctuation analysis of the transition zone between the wetland and the land in the target wetland according to all the difference features to obtain the moving trend of the transition zone specifically comprises:

[0015] Determine the fluctuation interval of the transition zone between the wetland and the land in the target wetland according to all the difference features;

[0016] Predict the moving trend of the transition zone based on the fluctuation interval of the transition zone.

[0017] In some embodiments, the determining of the correlation degree of the water level between each adjacent monitoring point specifically comprises:

[0018] Select one adjacent monitoring point as selected adjacent monitoring point, and determine the water level linkage information between the selected adjacent monitoring points;

[0019] Determine the correlation degree of the water level between the selected adjacent monitoring points according to the water level linkage information;

[0020] Continue to determine the correlation degree of the water level between the remaining adjacent monitoring points.

[0021] In some embodiments, the determination of the confluence feature of the water body in the target wetland in the flowing process based on all the correlation degrees and the elevation features of each monitoring point in the target wetland specifically comprises:

[0022] Determine the elevation features of each monitoring point in the target wetland;

[0023] Determine a plurality of confluence paths in the target wetland according to the elevation features and all the correlation degrees;

[0024] Determine the confluence feature of the water body in the target wetland in the flowing process through all the confluence paths.

[0025] In some embodiments, determining the contraction gradient of the water flow in the target wetland during the drainage process according to the flow convergence feature and the water potential direction of the target wetland specifically comprises:

[0026] determining the water potential direction of the target wetland;

[0027] determining a water flow buffer zone of the target wetland during the drainage process according to the flow convergence feature and the water potential direction;

[0028] obtaining a preset water flow convergence zone of the target wetland;

[0029] determining the contraction gradient of the water flow in the target wetland during the drainage process according to the water flow buffer zone and the preset water flow convergence zone.

[0030] In some embodiments, the disturbance cost of the water level change in the target wetland is obtained by correlating the movement trend of the transition zone and the contraction gradient of the water flow, specifically comprising:

[0031] correlating the movement trend of the transition zone and the contraction gradient of the water flow to obtain the variation correlation information of the water body in the target wetland;

[0032] determining the disturbance cost of the water level change in the target wetland according to the variation correlation information of the water body.

[0033] In a second aspect, the present application provides a wetland ecological monitoring system, which comprises a water level monitoring unit, and the water level monitoring unit comprises:

[0034] a monitoring module, configured to monitor the water level at different monitoring points in the target wetland based on a water level sensor network after the water level sensor network is arranged in the target wetland, and obtain water level data of each monitoring point;

[0035] a processing module, configured to determine the difference features of the water level in each water level data, perform fluctuation analysis on a transition zone between a wetland and a land in the target wetland according to all the difference features, and obtain a movement trend of the transition zone;

[0036] the processing module is further configured to determine the correlation degrees of the water level between each adjacent monitoring point, determine a flow convergence feature of a water body in the target wetland during the flow process based on all the correlation degrees and the elevation features of each monitoring point in the target wetland, and determine a contraction gradient of the water flow in the target wetland during the drainage process according to the flow convergence feature and the water potential direction of the target wetland;

[0037] an execution module, configured to correlate the movement trend of the transition zone and the contraction gradient of the water flow, and further obtain a disturbance cost of the water level change in the target wetland, and calibrate the water level state of the target wetland according to the disturbance cost.

[0038] In a third aspect, the present application provides a computer device, comprising a memory and a processor, the memory stores a code, and the processor is configured to acquire the code and execute the water level monitoring method.

[0039] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the water level monitoring method.

[0040] The technical scheme provided by the embodiments of the present application has the following beneficial effects:

[0041] In the wetland ecological monitoring system and method provided by the present application, first, a water level sensor network is arranged in the target wetland, the water level at different monitoring points in the target wetland is monitored based on the water level sensor network, and water level data of each monitoring point is obtained; the difference characteristics of the water level in each water level data are determined, the transition zone between the wetland and the land in the target wetland is analyzed according to all the difference characteristics, and the moving trend of the transition zone is obtained; the correlation degree of the water level between each adjacent monitoring point is determined, the confluence characteristics of the water body in the target wetland in the flow process are determined based on all the correlation degrees and the elevation characteristics of each monitoring point in the target wetland, and the contraction gradient of the water flow in the drainage process of the target wetland is determined according to the confluence characteristics and the water potential direction of the target wetland; the moving trend of the transition zone and the contraction gradient of the water flow are analyzed in association, and then the disturbance cost of the water level change in the target wetland is obtained, and the water level state of the target wetland is calibrated according to the disturbance cost.

[0042] As can be seen, in the process of wetland ecological monitoring, first, the fluctuation of the transition zone between the wetland and the land is studied by analyzing the difference characteristics of the water level data, and the moving trend of the transition zone can be determined. The transition zone is an important part of the wetland ecological system, and its movement and change will have a significant impact on the habitat of animals and plants and the ecological environment in the wetland; then, the correlation degree and the confluence characteristics are determined, the contraction gradient of the water flow in the drainage process is obtained in combination with the water potential direction, by mastering the contraction gradient of the water flow, the potential losses such as wetland drying, water quality deterioration, and reduction of biological diversity caused by water flow change can be quantified, which provides an important basis for evaluating the vulnerability of the wetland ecological system under the dynamic change of water body; then, the moving trend of the transition zone and the contraction gradient of the water flow are analyzed in association, and then the disturbance cost of the water level change in the target wetland is obtained, and the disturbance cost can directly reflect the negative impact of the change of the water level in the wetland on the wetland ecological system; finally, the water level state of the target wetland is calibrated according to the disturbance cost. By using the above scheme, the potential losses of the wetland ecology caused by the dynamic change of the water body can be quantified. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1is an exemplary flowchart of a water level monitoring method according to some embodiments of the present application;

[0044] Figure 2 is an exemplary flowchart of determining a confluence feature according to some embodiments of the present application;

[0045] Figure 3 is an exemplary flowchart of determining a disturbance cost according to some embodiments of the present application;

[0046] Figure 4 is a structural schematic diagram of a water level monitoring unit according to some embodiments of the present application;

[0047] Figure 5 is a structural schematic diagram of a computer device implementing a water level monitoring method according to some embodiments of the present application. DETAILED DESCRIPTION

[0048] In order to better understand the technical solutions of the present application, the technical solutions of the present application will be described in detail below in combination with the drawings of the specification and specific embodiments.

[0049] Reference Figure 1 The figure is an exemplary flowchart of a water level monitoring method 100 according to some embodiments of the present application, which mainly includes the following steps:

[0050] In step 101, a water level sensor network is arranged in a target wetland, and the water level at different monitoring points of the target wetland is monitored based on the water level sensor network to obtain water level data of each monitoring point.

[0051] It should be noted that, first, in the area with deep water and smooth flow, the pressure type water level sensor can measure the water level more accurately; while in the shallow water area or the place with more floating objects, the ultrasonic sensor is more advantageous because it is not easily disturbed by debris, thereby determining the type of sensor, second, according to the characteristics of the topography and geomorphology of the wetland, the water distribution is divided into different regional layers, including deep water area, shoal area, river branch area, then the spatial sampling algorithm (such as stratified random sampling) is used to randomly determine the monitoring point position in each regional layer according to a certain sampling ratio, to ensure that the water level changes in different regions of the wetland can be comprehensively and effectively monitored, thereby completing the arrangement of the water level sensor in the target wetland, and each monitoring point can monitor a range of ten meters.

[0052] In a specific implementation, after the water level sensor network is arranged in the target wetland, the water level sensor network monitors the water level at different monitoring points in the target wetland in a month, records the water level monitored at early (6 o'clock), noon (12 o'clock), and evening (18 o'clock) in a day, and takes the set of all water levels recorded at each monitoring point as the water level data of the corresponding monitoring point. In other embodiments, other ways of monitoring can also be used, which are not limited here.

[0053] It should be noted that the water level in the water level data in the present application represents the height of the free water surface at the monitoring point relative to the fixed reference position, and the fixed reference position represents the position where the height of the free water surface in the target wetland is 0. In the present embodiment, the lowest elevation position of the target wetland is set as the fixed reference position. In other embodiments, other positions can also be set as the fixed reference position, which is not limited here.

[0054] In step 102, the difference characteristics of the water level in each water level data are determined, and the transition zone between the wetland and the land in the target wetland is analyzed according to all the difference characteristics to obtain the moving trend of the transition zone.

[0055] In some embodiments, the determination of the difference characteristics of the water level in each water level data can be implemented by the following steps:

[0056] A water level data is selected as a selected water level data, and the selected water level data is converted into a water level sequence;

[0057] The difference characteristics of the water level in the selected water level data are determined according to the water level sequence;

[0058] The difference characteristics of the water level in the remaining water level data are continuously determined.

[0059] In a specific implementation, first, all the water levels in the selected water level data are arranged in the order of the collection time, and the sequence obtained by the arrangement is taken as the water level sequence. Then, the difference values between each group of adjacent water levels in the water level sequence are calculated, and all the difference values obtained by the calculation are taken as the difference characteristics of the water level in the selected water level data. In other embodiments, other ways of determination can also be used, which are not limited here.

[0060] It should be noted that the difference characteristics in the present application represent the characteristics of the difference degree of the water level at the monitoring point changing with time, which can be used for analyzing the water level change in the target wetland.

[0061] In some embodiments, the analysis of the transition zone between the wetland and the land in the target wetland according to all the difference characteristics to obtain the moving trend of the transition zone can be implemented by the following steps:

[0062] The fluctuation interval of the transition zone between the wetland and the land in the target wetland is determined according to all the difference characteristics.

[0063] predict the moving trend of the transition zone based on the fluctuation interval of the transition zone.

[0064] It should be noted that in the target wetland, the transition zone between the wetland and the land is a dynamic area, and the change of its position is closely related to the water level change. The difference in water level directly reflects the distribution and movement of the water body in the wetland. When the water level in a certain area rises, the water body expands to the land side, and the transition zone moves to the land. Conversely, when the water level drops, the transition zone shrinks to the interior of the wetland. Therefore, by analyzing the difference in water level, key information about the change of the position of the transition zone can be obtained.

[0065] In a specific implementation, the fluctuation interval of the transition zone between the wetland and the land in the target wetland can be determined according to all the difference characteristics in the following manner: calculating the mean of all the difference values in each difference characteristic, arranging all the means in ascending order, taking the sequence obtained by the arrangement as a difference value sequence, extracting all the difference values that exceed 1.5 times the interquartile range from the front to the back in the difference value sequence by the interquartile range rule, and taking the monitoring range of the two monitoring points corresponding to each extracted difference value as the fluctuation interval of the transition zone between the wetland and the land in the target wetland. The fluctuation interval of the transition zone between the wetland and the land in the target wetland represents the interval of the fluctuation degree of the transition zone between the wetland and the land in the target wetland, and can be used to analyze the trend of the transition zone between the wetland and the land in the target wetland. In other embodiments, other methods can also be used to determine the fluctuation interval of the transition zone between the wetland and the land in the target wetland, which is not limited here.

[0066] In a specific implementation, the moving trend of the transition zone can be predicted based on the fluctuation interval of the transition zone in the following manner: obtaining historical water level data in the fluctuation interval of the transition zone, arranging the historical water level data in time sequence to obtain a historical water level sequence, constructing a moving trend model of the transition zone based on a machine learning model, optimizing the moving trend model by a cross-validation method, inputting the historical water level sequence into the moving trend model, and inferring the moving trend of the transition zone by the moving trend model. In other embodiments, other methods can also be used to determine the moving trend of the transition zone, which is not limited here.

[0067] It should be noted that the moving trend in the present application represents the trend of the movement of the transition zone between the wetland and the land in the target wetland, and can be used to predict the transition zone between the wetland and the land in the target wetland, so as to take appropriate measures in advance.

[0068] In step 103, the correlation between the water levels of each adjacent monitoring point is determined, the confluence characteristics of the water body in the flow process in the target wetland are determined based on all the correlation and the elevation characteristics of each monitoring point in the target wetland, and the contraction gradient of the water flow in the drainage process of the target wetland is determined according to the confluence characteristics and the water potential direction of the target wetland.

[0069] In some embodiments, the determining of the correlation degree of water levels between each adjacent monitoring point can be achieved by the following steps:

[0070] selecting one adjacent monitoring point as a selected adjacent monitoring point, and determining water level linkage information between the selected adjacent monitoring points;

[0071] determining the correlation degree of water levels between the selected adjacent monitoring points according to the water level linkage information;

[0072] continuing to determine the correlation degree of water levels between the remaining adjacent monitoring points.

[0073] In a specific implementation, the water level linkage information between the selected adjacent monitoring points can be determined by the following method: calculating the water level change amount of the selected adjacent monitoring points in the same time interval, and then using a cross-correlation function (such as Cross-Correlation Function) to calculate the correlation coefficient of the water level change of two groups of data under different time delays, and taking the set of all water level change amounts and all correlation coefficients as the water level linkage information between the selected adjacent monitoring points. For example, for the water level data of two adjacent monitoring points A and B, the correlation of the water level change amount of point A at time t and the water level change amount of point B at time t+τ is calculated, τ is the time delay, and the correlation coefficient under different τ values is obtained. The water level linkage information represents information about the correlation of water levels between adjacent monitoring points in the target wetland. In other embodiments, other methods can be used to determine the water level linkage information, which is not limited here.

[0074] In a specific implementation, the correlation degree of water levels between the selected adjacent monitoring points can be determined according to the water level linkage information by the following method: the Pearson correlation coefficient can be used to calculate the water level change correlation degree between the selected adjacent monitoring points by combining all water level change amounts in the water level linkage information, and then the sum of the mean value of all correlation coefficients in the water level linkage information and the water level change correlation degree is taken as the correlation degree of water levels between the selected adjacent monitoring points. In other embodiments, other methods can be used to determine the correlation degree of water levels between the selected adjacent monitoring points, which is not limited here.

[0075] It should be noted that the correlation degree in this application represents a parameter value of the correlation degree of water levels between adjacent monitoring points, which can be used to analyze the water level change in the target wetland.

[0076] In some embodiments, referring to Figure 2 The figure is an exemplary flow chart for determining the confluence feature in some embodiments of the application. In this embodiment, the determination of the confluence feature of the water body in the target wetland during the flow process can be achieved by the following steps based on all the correlation degrees and the elevation features of each monitoring point in the target wetland:

[0077] Firstly, in step 1031, the elevation features of each monitoring point in the target wetland are determined;

[0078] Secondly, in step 1032, a plurality of confluence paths in the target wetland are determined according to the elevation features and all the correlation degrees;

[0079] Finally, in step 1033, the confluence features of the water bodies in the target wetland in the flowing process are determined through all the confluence paths.

[0080] It should be noted that the correlation degree of the water levels of adjacent monitoring points quantifies the synchronism of the water body movement, a high correlation degree indicates that there is a direct hydraulic connection (such as free flow) between the two monitoring points, and a low correlation degree indicates that there may be an obstruction (such as vegetation obstruction or terrain uplift) between the two monitoring points, and the elevation feature is directly related to the flow condition of the water flow, therefore, the confluence of the water bodies in the target wetland in the flowing process can be analyzed through all the correlation degrees and the elevation features of each monitoring point in the target wetland.

[0081] In a specific implementation, the elevation features of each monitoring point in the target wetland can be determined by using the following method, that is, based on the digital elevation model (DEM) technology of remote sensing images, the elevation and terrain slope of each monitoring point in the target wetland are obtained, and the elevation and terrain slope of each monitoring point are taken as the elevation features of the corresponding monitoring point, wherein the elevation features represent the characteristics of the elevation of the monitoring point.

[0082] Among them, all the correlation degrees are combined with all the elevation features, the area with a high correlation degree is taken as a potential water flow path, the high and low terrain in the elevation features is used to determine the water flow direction, and the confluence path is determined in this way, in a specific implementation, the plurality of confluence paths in the target wetland are determined according to the elevation features and all the correlation degrees can be realized by using the following method, that is, starting from each monitoring point, the classical algorithm of the shortest path (such as A* algorithm) is combined with all the correlation degrees and all the elevation features to find each path in the target wetland that is low and has a high correlation degree, and each path is taken as a confluence path, for example, in a certain monitoring point, the adjacent monitoring point with a low elevation and a high correlation degree is preferentially selected as the next node, and a plurality of complete confluence paths are found by continuously iterating, in other embodiments, other ways can also be used for determination, which are not limited here.

[0083] In a specific implementation, the determination of the confluence characteristics of the water in the target wetland during the flow process through all the confluence paths can be achieved by the following method: the length and coverage area of each confluence path are calculated based on the spatial analysis function of the geographic information system software, the water flow velocity on different confluence paths is calculated based on the principle of hydraulics, and the set of the length, coverage area and water flow velocity of each confluence path is taken as the confluence characteristics of the water in the target wetland during the flow process. In other embodiments, the determination can also be achieved by other methods, which are not limited here.

[0084] It should be noted that the confluence characteristics in the present application represent the characteristics of the confluence of the water in the target wetland during the flow process, which can be used to analyze the water condition in the target wetland, so as to manage the target wetland accordingly.

[0085] In some embodiments, the determination of the contraction gradient of the water flow in the target wetland during the drainage process according to the confluence characteristics and the water potential direction of the target wetland can be achieved by the following steps:

[0086] determining the water potential direction of the target wetland;

[0087] determining the water flow buffer zone of the target wetland during the drainage process according to the confluence characteristics and the water potential direction;

[0088] obtaining a preset water flow convergence zone of the target wetland;

[0089] determining the contraction gradient of the water flow in the target wetland during the drainage process according to the water flow buffer zone and the preset water flow convergence zone.

[0090] It should be noted that the analysis of the combination of the confluence characteristics and the water potential direction indicates the water flow concentration area in the confluence characteristics, and the water flow direction on the confluence path is limited by the water potential direction. Under the guidance of the water potential direction, the water flow contraction area during the drainage process can be determined along the confluence path, i.e. the water flow contraction gradient, which is the range of the water flow gradually converging and contracting in the process of flowing to the drainage outlet or other low potential areas due to the influence of topography and water flow resistance.

[0091] In a specific implementation, the determination of the water potential direction of the target wetland can be achieved by the following method: the direction of the water flow in the target wetland is determined based on the principle of water flow from high water level to low water level and the water level height of each monitoring point, and the direction is taken as the water potential direction of the target wetland, wherein the water potential direction represents the flow direction of the water in the target wetland.

[0092] In specific implementation, the water flow buffer zone of the target wetland during drainage can be determined according to the confluence characteristics and the water potential direction in the following manner: the buffer distance of each confluence path segment is calculated according to the set formula (buffer distance = water flow velocity corresponding to the confluence path segment in the confluence characteristics * coverage area corresponding to the confluence path segment in the confluence characteristics * coefficient), and the buffer analysis tool in the geographic information system is used to generate water flow buffer zones on both sides of the confluence path according to the buffer distance of each confluence path segment. The water flow buffer zone represents the area that the water flow may affect during the drainage process of the target wetland. Other methods can also be used to determine the buffer zone in other embodiments, which are not limited here.

[0093] In specific implementation, a preset water flow convergence area is obtained by referring to the planning and design data of the target wetland, wherein the water flow convergence area represents the area where water flows converge in the target wetland; the contraction gradient of the water flow in the target wetland during drainage can be determined by the following method based on the water flow buffer zone and the preset water flow convergence area: the water flow buffer zone and the preset water flow convergence area are superimposed using the spatial overlay analysis function of the geographic information system, and the overlapping area of ​​the water flow buffer zone and the preset water flow convergence area is extracted through intersection analysis, and the overlapping area is taken as the contraction gradient of the water flow in the target wetland during drainage; other methods can also be used to determine this in other embodiments, which are not limited here.

[0094] It should be noted that the contraction gradient in this application represents the actual range in which the water flow gradually contracts towards the convergence area during the drainage process. It can be used to assess the drainage system in the target wetland, improve drainage efficiency, avoid water accumulation, enhance the target wetland's ability to cope with extreme weather such as rainstorms, and reduce the risk of flooding.

[0095] In step 104, the movement trend of the transition zone and the contraction gradient of the water flow are correlated and analyzed to obtain the disturbance cost of water level change in the target wetland. The water level status of the target wetland is calibrated based on the disturbance cost.

[0096] In some embodiments, reference Figure 3 As shown, this figure is an exemplary flowchart for determining the disturbance cost in some embodiments of this application. In this embodiment, the movement trend of the transition zone and the contraction gradient of the water flow are correlated and analyzed to obtain the disturbance cost of water level change in the target wetland. This can be achieved by the following steps:

[0097] First, in step 1041, the movement trend of the transition zone and the contraction gradient of the water flow are correlated to obtain the correlation information of water body changes in the target wetland;

[0098] Then, in step 1042, the disturbance cost of water level changes in the target wetland is determined based on the water body change correlation information.

[0099] It should be noted that the movement of the transition zone is significantly correlated with the change of the flow contraction gradient. As the flow contraction gradient decreases, the transition zone moves rapidly towards the interior of the wetland, which indicates that the change of the water body has a negative impact on the wetland ecology, which may be due to the change of the water flow causing the erosion of the wetland edge to be intensified, or because the flow contraction causes the ecological environment inside the wetland to change, which is not conducive to the survival of vegetation and organisms, thereby causing the transition zone to retreat. This correlation analysis can help us quantify the degree of impact of water body changes on wetland ecology, and then calculate the disturbance cost of the wetland ecosystem in terms of structure and function.

[0100] In specific implementation, the target wetland water body change correlation information can be obtained by correlating the movement trend of the transition zone and the flow contraction gradient, which can be achieved in the following manner: first, cross-verify the movement trend of the transition zone and the flow contraction gradient through spatial overlay analysis (such as the Zonal Statistics tool in geographic information system), calculate the area change rate and direction consistency of the spatial intersection region, analyze the time sequence causality between the transition zone displacement rate and the contraction gradient flow rate using Granger causality test, and use the set of area change rate, direction consistency and time sequence causality as the target wetland water body change correlation information, wherein the change correlation information represents information about the correlation of the water body in the target wetland during flow.

[0101] In specific implementation, the disturbance cost of the water level change in the target wetland can be determined according to the water body change correlation information, which can be achieved in the following manner: using an ecosystem service value evaluation model (such as the InVEST model), taking the change correlation information as an input parameter of the model, setting the corresponding parameters in the model (such as the carbon storage, water purification, and habitat quality module parameters) in combination with the vegetation type, biodiversity data, and soil type of the target wetland, simulating and calculating the change amount of the wetland ecosystem service value under the change correlation information through the model, and taking the change amount of the ecosystem service value as the disturbance cost of the water level change in the target wetland. In other embodiments, the disturbance cost can be determined in other ways.

[0102] It should be noted that the disturbance cost in this application represents the cost of the disturbance degree of the water level dynamic change in the target wetland to the wetland ecology, which can be used to judge the ecology in the target wetland, thereby obtaining the information of the ecology in the target wetland.

[0103] In some embodiments, the water level state of the target wetland can be calibrated according to the disturbance cost in the following steps:

[0104] determining a disturbance threshold interval of the target wetland;

[0105] judging the disturbance cost according to the disturbance threshold interval;

[0106] when the disturbance cost is lower than the lower limit value of the disturbance threshold interval, the water level state of the target wetland is marked as a good state, when the disturbance cost is within the range of the disturbance threshold interval, the water level state of the target wetland is marked as a general state, and when the disturbance cost is higher than the upper limit value of the disturbance threshold interval, the water level state of the target wetland is marked as a poor state.

[0107] In a specific implementation, the disturbance cost calculated is taken as an input feature, and the ecological state is taken as a target variable to construct a decision tree model. Through training data (such as actual data of ecological states of a plurality of target wetlands under different disturbance costs), an optimal division feature and a division threshold value are selected at each node of the decision tree model in the decision tree model. The disturbance cost currently calculated of the target wetland is input into the decision tree model, and the water level state of the target wetland is output through the decision tree model. In other embodiments, the water level state of the target wetland can also be marked in other manners, which is not limited here.

[0108] It should be noted that the disturbance threshold interval can be set according to the specific needs of the target wetland in the present application. For example, if the vegetation in the target wetland is rich, the disturbance threshold interval can be set in a high range, and if the vegetation in the target wetland is scarce, the disturbance threshold interval can be set in a low range. In other embodiments, for example, when the vegetation coverage density in the target wetland is large, the disturbance threshold interval can be set in a high range, so as to improve the protection efficiency of the target wetland.

[0109] In addition, another aspect of the present application, in some embodiments, the present application provides a wetland ecological monitoring system, which comprises a water level monitoring unit, for reference Figure 4 The figure is a structural schematic diagram of a water level monitoring unit according to some embodiments of the present application. The water level monitoring unit 400 comprises a monitoring module 401, a processing module 402 and an execution module 403, which are described as follows:

[0110] The monitoring module 401 is mainly used to monitor the water level at different monitoring points of the target wetland based on the water level sensor network after the water level sensor network is arranged in the target wetland, and obtain the water level data of each monitoring point.

[0111] The processing module 402 is used to determine the difference features of the water levels in each water level data, and analyze the fluctuation of the transition zone between the wetland and the land in the target wetland according to all the difference features, and obtain the moving trend of the transition zone.

[0112] It should be noted that the processing module 402 is further configured to determine difference features of water levels in each water level data, perform fluctuation analysis on a transition zone between a wetland and land in the target wetland according to all the difference features, and obtain a moving trend of the transition zone.

[0113] The execution module 403 is mainly configured to perform correlation analysis on the moving trend of the transition zone and the contraction gradient of the water flow, and further obtain a disturbance cost of water level change in the target wetland, and calibrate a water level state of the target wetland according to the disturbance cost.

[0114] In addition, the present application further provides a computer device, which comprises a memory and a processor, the memory stores a code, and the processor is configured to acquire the code and execute the water level monitoring method described above.

[0115] In some embodiments, with reference to Figure 5 FIG. 1 is a structural schematic diagram of a computer device for implementing a water level monitoring method according to some embodiments of the present application. The water level monitoring method in the above embodiments can be implemented by the computer device shown in FIG. 1. The computer device 500 comprises at least one processor 501, a communication bus 502, a memory 503, and at least one communication interface 504. Figure 5 The processor 501 can be a general central processing unit (CPU) or an application specific integrated circuit (ASIC).

[0116] The communication bus 502 can be used to transmit information between the above components.

[0117]

[0118] ​The memory 503 can be a readonly memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM), or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable readonly memory (EEPROM), a compact disc readonly memory (CDROM) or other optical disk storage, a magneto-optical disk storage, a magnetic disk or other magnetic storage device, or any other medium capable of storing desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to this. The memory 503 can exist independently, and is connected to the processor 501 through the communication bus 502. The memory 503 can also be integrated with the processor 501.

[0119] The memory 503 is configured to store program codes for implementing the solutions of the present application, and the processor 501 is configured to control the execution of the program codes. The processor 501 is configured to execute the program codes stored in the memory 503. The program codes can include one or more software modules. The methods used in the above embodiments can be implemented by the processor 501 and one or more software modules in the program codes in the memory 503.

[0120] The communication interface 504 is configured to communicate with other devices or communication networks, such as an Ethernet, a radio access network (RAN), a wireless local area network (WLAN), etc., using any transceiver-like mechanism.

[0121] In specific implementations, as an example, the computer device can include multiple processors, each of which can be a single CPU processor or a multi-CPU processor. The processor herein can refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0122] The computer device described above can be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device can be a desktop computer, a laptop computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of the present application do not limit the type of the computer device.

[0123] In addition, the present application also provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the water level monitoring method described above.

[0124] Although the preferred embodiments of the present application have been described, those skilled in the art who are informed of the basic inventive concept can make additional changes and modifications to the embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0125] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A water level monitoring method for a wetland ecological monitoring system to monitor water level, characterized in that, The method comprises the following steps: arranging a water level sensor network in the target wetland, monitoring water levels at different monitoring points in the target wetland based on the water level sensor network, and obtaining water level data of each monitoring point; determining difference characteristics of the water levels in each water level data, performing fluctuation analysis on a transition zone between wetlands and land in the target wetland according to all the difference characteristics, and obtaining a moving trend of the transition zone; determining a correlation degree of the water levels between each pair of adjacent monitoring points, determining a confluence feature of water flow in the target wetland in a flowing process based on all the correlation degrees and elevation characteristics of each monitoring point in the target wetland, and determining a contraction gradient of water flow in the target wetland in a drainage process according to the confluence feature and a water potential direction of the target wetland; correlating and analyzing the moving trend of the transition zone and the contraction gradient of the water flow, and then obtaining a disturbance cost of water level change in the target wetland, and calibrating a water level state of the target wetland according to the disturbance cost; wherein the determination of the difference characteristics of the water levels in each water level data comprises: selecting one water level data as selected water level data, and converting the selected water level data into a water level sequence; determining the difference characteristics of the water levels in the selected water level data according to the water level sequence; continuing to determine the difference characteristics of the water levels in the remaining water level data; wherein the fluctuation analysis on the transition zone between wetlands and land in the target wetland according to all the difference characteristics comprises: determining a fluctuation interval of the transition zone between wetlands and land in the target wetland according to all the difference characteristics; predicting the moving trend of the transition zone based on the fluctuation interval of the transition zone; wherein the determination of the confluence feature of water flow in the target wetland in the flowing process based on all the correlation degrees and the elevation characteristics of each monitoring point in the target wetland comprises: determining the elevation characteristics of each monitoring point in the target wetland; determining a plurality of confluence paths in the target wetland according to the elevation characteristics and all the correlation degrees; determining the confluence feature of water flow in the target wetland in the flowing process through all the confluence paths; wherein the determination of the contraction gradient of water flow in the target wetland in the drainage process according to the confluence feature and the water potential direction of the target wetland comprises: determining the water potential direction of the target wetland; determining a water flow buffer zone of the target wetland in the drainage process according to the confluence feature and the water potential direction; obtaining a preset water flow convergence zone of the target wetland; determining the contraction gradient of water flow in the target wetland in the drainage process according to the water flow buffer zone and the preset water flow convergence zone; wherein the correlating and analyzing of the moving trend of the transition zone and the contraction gradient of the water flow, and then obtaining the disturbance cost of water level change in the target wetland comprises: correlating the moving trend of the transition zone and the contraction gradient of the water flow to obtain water body change correlation information in the target wetland; determining the disturbance cost of water level change in the target wetland according to the water body change correlation information.

2. The method of claim 1, wherein, The determination of the correlation degree of the water levels between each pair of adjacent monitoring points comprises: selecting one adjacent monitoring point as a selected adjacent monitoring point, and determining water level linkage information between the selected adjacent monitoring points. determine a correlation degree of water levels between each pair of adjacent monitoring points according to the water level linkage information; continue to determine the correlation degrees of water levels between the remaining pairs of adjacent monitoring points.

3. A wetland ecological monitoring system for monitoring water level using the method of any one of claims 1 or 2, the wetland ecological monitoring system comprising a water level monitoring unit, wherein, The water level monitoring unit comprises: a monitoring module configured to monitor water levels at different monitoring points in a target wetland based on a water level sensor network arranged in the target wetland, and obtain water level data of each monitoring point; a processing module configured to determine difference features of water levels in each water level data, perform fluctuation analysis on a transition zone between a wetland and a land in the target wetland according to all the difference features, and obtain a moving trend of the transition zone; the processing module is further configured to determine correlation degrees of water levels between each pair of adjacent monitoring points, determine a confluence feature of water bodies in the target wetland in a flow process based on all the correlation degrees and elevation features of each monitoring point in the target wetland, and determine a contraction gradient of water flow in a drainage process of the target wetland according to the confluence feature and a water potential direction of the target wetland; a performing module configured to perform correlation analysis on the moving trend of the transition zone and the contraction gradient of the water flow, and thus obtain a disturbance cost of water level changes in the target wetland, and calibrate a water level state of the target wetland according to the disturbance cost.

4. A computer device, comprising: The computer device comprises a memory and a processor, the memory stores a code, and the processor is configured to acquire the code and perform the water level monitoring method according to any one of claims 1 or 2.

5. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 4. The computer program is executed by the processor to implement the water level monitoring method according to any one of claims 1 or 2.

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