Intelligent monitoring and early warning system for watershed water environment

Abstract

The invention provides an intelligent monitoring and early warning system for a watershed water environment. The intelligent monitoring and early warning system comprises the following steps: visually identifying water area features of all sub-regions under a watershed global range and connection features among different sub-regions; on the basis of water area characteristics, determining a sewage draining exit range of the sub-region and detecting dynamic sewage draining exit data so as to generate a sewage draining exit state characterization map, and determining sewage draining exit abnormal information of the sub-region; on the basis of water area features and connection features, water environment dynamic monitoring data is obtained through water environment dynamic monitoring, so that a water environment state representation map is generated, water environment abnormal information of the sub-regions is determined, the water environment change trend of the drainage basin is further determined, and water environment deterioration information of the global range of the drainage basin is predicted; the water environment deterioration condition of the drainage basin is accurately determined; and a water environment change dynamic map of the global range of the drainage basin is generated, so that an early warning notification message is sent to a corresponding base station end, the real water environment state of the whole drainage basin is effectively monitored, and reliable data support is provided for treating the water environment of the drainage basin.

Description

Technical Field

[0001] The present invention relates to the field of water environment monitoring, and in particular to an intelligent monitoring and early warning system for the water environment of a river basin. Background Art

[0002] River basins composed of rivers, lakes and the like have characteristics such as a large water volume and a vast area. The water environment of the river basin directly affects the living and survival of surrounding humans, animals and plants. At the same time, the water system network of the river basin is complex. Once water ecological environment deterioration such as illegal discharge and leakage of pollutants and eutrophication of water bodies occurs in a certain area, pollutants and nutrients will diffuse and transmit to other areas along with the water body exchange within the river basin, threatening the water environment safety of the entire river basin. Existing water environment monitoring of river basins only arranges hydrological and water quality monitoring stations at several discrete points within the river basin. In this way, the hydrological data and water quality data monitored cannot completely represent the water environment of the entire river basin, cannot dynamically and effectively monitor the real water environment state of the entire river basin, and cannot accurately predict the water environment change of the entire river basin, and cannot provide reliable data support for targeted treatment of the water environment of the river basin. Based on monitoring the pollution discharge characteristics of the sewage outfall and the water quality response characteristics of the water environment, establishing the correlation relationship between the "sewage outfall - water environment quality" helps to realize dynamic monitoring and early warning of the entire river basin. Summary of the Invention

[0003] The purpose of the present invention is to provide an intelligent monitoring and early warning system for the water environment of a river basin, visually identify the water area characteristics of all sub-regions under the global scope of the river basin and the connection characteristics between different sub-regions, and characterize the water body conditions between different sub-regions within the river basin and their interrelationships; based on the water area characteristics, determine the scope of the sewage outfall in the sub-region and dynamically monitor the sewage outfall, obtain water quality and water volume data, and generate a sewage outfall state characterization map therefrom to determine the abnormal information of the sewage outfall in the sub-region; based on the water area characteristics and connection characteristics, conduct dynamic monitoring of the water environment to obtain dynamic monitoring data of the water environment, and generate a water environment state characterization map therefrom to determine the abnormal information of the water environment in the sub-region, globally and dynamically characterize the river basin from two aspects of the sewage outfall and the water environment, and further determine the water environment change trend of the river basin, thereby predicting the water environment deterioration information of the global scope of the river basin and accurately determining the water environment deterioration of the river basin; also generate a dynamic map of the water environment change of the global scope of the river basin, and send a warning notification message to the corresponding base station end therefrom, effectively monitoring the real water environment state of the entire river basin and providing reliable data support for treating the water environment of the river basin.

[0004] The present invention is realized through the following technical solutions:

[0005] An intelligent monitoring and early warning system for the water environment of a river basin, comprising:

[0006] The watershed zoning module is used to perform visual recognition on the entire watershed scope to obtain the water area characteristics of all sub-regions under the entire watershed scope and the connection characteristics between different sub-regions;

[0007] The sewage outfall monitoring module is used to determine the sewage outfall scope of the sub-region based on the water area characteristics; based on the sewage outfall scope, perform dynamic monitoring of the sewage outfall in the sub-region to obtain the dynamic sewage outfall data of the sub-region;

[0008] The sewage outfall status recognition module is used to analyze the dynamic sewage outfall data to generate a sewage outfall status characterization map of the sub-region; based on the sewage outfall status characterization map, determine the sewage outfall abnormal information of the sub-region;

[0009] The water environment monitoring module is used to determine the monitoring points of the sub-region based on the water area characteristics and the connection characteristics; based on the monitoring points, perform dynamic monitoring of the water environment in the sub-region to obtain the dynamic water environment monitoring data of the sub-region;

[0010] The water environment status recognition module is used to analyze the dynamic water environment monitoring data to generate a water environment status characterization map of the sub-region; based on the water environment status characterization map, determine the water environment abnormal information of the sub-region;

[0011] The whole watershed status recognition module is used to determine the water environment change trend of the entire watershed scope based on the sewage outfall abnormal information and the water environment abnormal information; based on the water environment change trend, predict the water environment deterioration information of the entire watershed scope;

[0012] The early warning notification module is used to generate a dynamic map of water environment changes in the entire watershed scope based on the water environment deterioration information; based on the dynamic map of water environment changes, send an early warning notification message to the base station terminal corresponding to the entire watershed scope.

[0013] Optionally, the watershed zoning module is used to perform visual recognition on the entire watershed scope to obtain the water area characteristics of all sub-regions under the entire watershed scope and the connection characteristics between different sub-regions, including:

[0014] Obtain the remote sensing image of the entire watershed scope, perform pixel contour and pixel texture recognition on the remote sensing image to obtain the pixel contour distribution characteristic information and pixel texture distribution characteristic information of the entire remote sensing image;

[0015] Perform time evolution analysis on the pixel texture distribution characteristic information to obtain the water body flow velocity distribution information of the entire watershed scope; based on the water body flow velocity distribution information, divide the entire watershed scope into several dynamic sub-regions and several static sub-regions;

[0016] Analyze the pixel contour distribution feature information of each dynamic sub-region and each static sub-region respectively to obtain the water area boundary features of each dynamic sub-region and each static sub-region respectively, as well as the connection node boundary features between the dynamic sub-region and the static sub-region; also determine the connection node water flow features between the dynamic sub-region and the static sub-region based on the pixel texture distribution feature information.

[0017] Optionally, the sewage outlet monitoring module is used to determine the sewage outlet range of the sub-region based on the water area features; based on the sewage outlet range, conduct dynamic monitoring of the sewage outlets in the sub-region to obtain the dynamic sewage outlet data of the sub-region, including:

[0018] Conduct pollution source correlation analysis on the water area boundary features to determine the pollution source information associated between the water body and the land in the sub-region; based on the pollution source information, determine the key supervised sewage outlet range of the sub-region;

[0019] Based on the key supervised sewage outlet range, determine the dynamic monitoring points for the sewage outlets in the sub-region; then conduct dynamic water quality monitoring and dynamic flow monitoring on all monitoring points to obtain the dynamic water quality data and dynamic flow data corresponding to each monitoring point, and use these as the dynamic sewage outlet data of the sub-region.

[0020] Optionally, the sewage outlet status identification module is used to analyze the dynamic sewage outlet data to generate a sewage outlet status representation map of the sub-region; based on the sewage outlet status representation map, determine the sewage outlet abnormal information of the sub-region, including:

[0021] Based on the distribution positions of all monitoring points within the sub-region, conduct integrated analysis on the dynamic water quality data and dynamic flow data corresponding to all monitoring points to obtain the global water quality and water volume change characteristics of the sub-region;

[0022] Based on the global water quality and water volume change characteristics of the sub-region, conduct label identification on the electronic map of the sub-region to generate a sewage outlet status representation map of the sub-region;

[0023] Based on the big data of historical emission conditions, conduct prediction on the pollutant concentration and emission amount of the sewage outlets on the sewage outlet status representation map to determine the location information and time information of the sewage outlet structure collapse events that will occur within the sub-region, and use these as the sewage outlet abnormal information of the sub-region.

[0024] Optionally, the water environment monitoring module is used to determine the monitoring points of the sub-region based on the water area characteristics and the connection characteristics; based on the monitoring points, conduct dynamic monitoring of the water environment of the sub-region to obtain the dynamic monitoring data of the water environment of the sub-region, including:

[0025] Based on the water area boundary characteristics, the connection node boundary characteristics, and the connection node water area characteristics, determine the distribution information of the water body exchange flow rate between the dynamic sub-region and the static sub-region within the global scope of the basin; based on the distribution information of the water body exchange flow rate, determine the monitoring points of the sub-region;

[0026] Based on the coordinate information of the monitoring points, conduct dynamic monitoring of the water quality and hydrology of the monitoring points to obtain the dynamic data of the water quality and hydrology of the water body corresponding to the monitoring points, and use this as the dynamic monitoring data of the water environment of the sub-region.

[0027] Optionally, the water environment state recognition module is used to analyze the dynamic monitoring data of the water environment to generate a water environment state characterization map of the sub-region; based on the water environment state characterization map, determine the water environment abnormal information of the sub-region, including:

[0028] Based on the distribution positions of all monitoring points within the sub-region, integrate and analyze the dynamic data of the water quality and hydrology corresponding to all monitoring points to obtain the global water environment pollutant concentration change characteristics of the sub-region;

[0029] Based on the global water environment pollutant concentration change characteristics of the sub-region, label and identify the electronic map of the sub-region to generate a water environment state characterization map of the sub-region.

[0030] Optionally, the whole basin state recognition module is used to determine the water environment change trend of the global scope of the basin based on the sewage outlet abnormal information and the water environment abnormal information; based on the water environment change trend, predict the water environment deterioration information of the global scope of the basin, including:

[0031] Based on the location information and time information of the sewage outlet anomalies that will occur within the sub-region included in the sewage outlet abnormal information and the location information and time information of the water quality abnormal events that occur within the sub-region included in the water environment abnormal information, conduct correlation analysis using the water environment diffusion model, and determine the movement and diffusion change trend of the water environment pollutants in the global scope of the basin;

[0032] Based on the movement and diffusion change trend of the water environment pollutants, determine the water environment pollutant retention time information of all sub-regions within the global scope of the basin, so as to predict the sub-regions where water environment deterioration occurs in the global scope of the basin.

[0033] Optionally, the early warning notification module is configured to generate a dynamic map of water environment changes in the entire basin based on the water environment deterioration information; and based on the dynamic map of water environment changes, send an early warning notification message to the base station end corresponding to the entire basin, including:

[0034] Based on the location range of the sub-regions with water environment deterioration in the entire basin and the water body exchange flow rate between it and other adjacent sub-regions, perform identification processing on the electronic map of the entire basin to generate a dynamic map of water environment changes;

[0035] Based on the dynamic map of water environment changes, determine the base station ends that can conduct on-site detection of water environment changes in the entire basin within a preset time interval; and based on the network access status of all detection devices inside the base station ends, send corresponding early warning notification instruction messages to the base station ends, so that all detection devices enter the corresponding detection working mode.

[0036] Optionally, based on the network access status of all detection devices inside the base station ends, send corresponding early warning notification instruction messages to the base station ends, so that all detection devices enter the corresponding detection working mode, including:

[0037] Step S1, using the following formula (1), obtain the comprehensive status score of the base station end according to the network access status of all detection devices inside the base station end,

[0038]

[0039] In the above formula (1), E represents the comprehensive status score of the base station end; N represents the total number of detection devices; A i represents the access status of the i-th device. When A i =1, it indicates that the device is online. When A i =0, it indicates that the device is offline; W i represents the working mode value of the i-th device. When W i =1, it indicates that the device is in a periodic working state. When W i =0.5, it indicates that the device is in a sleep state; C i represents a preset importance coefficient; T i represents the online time of the i-th device; T max represents the longest online time among all devices; α i represents an adjustment factor; S i represents the stability score of the device;

[0040] Step S2, using the following formula (2), control the early warning trigger state according to the comprehensive status score of the base station end,

[0041]

[0042] In the above formula (2), P represents the warning trigger status. When P = 1, it indicates that a trigger occurs; when P = 0, it indicates that no trigger occurs. E0 represents the preset status threshold; D represents the deviation between the current status and the historical average status; D max represents the maximum value of the historical deviation;

[0043] Step S3, using the following formula (3), perform work mode switching control according to the warning trigger status,

[0044]

[0045] In the above formula (3), M represents the new work mode quantization value; M0 represents the current work mode quantization value; ΔM represents the difference between the target mode quantization value and the current mode quantization value; P represents the warning status; F represents the equipment failure rate; F max represents the maximum value of the historical equipment failure rate; β represents an adjustment factor used to control the sensitivity of mode switching;

[0046] When M is greater than the preset quantization threshold, switch the detection device from the current work mode to another work mode; otherwise, keep the current work mode of the detection device unchanged.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] A water environment intelligent monitoring and early warning system provided by the present application visually identifies the water area characteristics of all sub - regions under the global scope of the basin and the connection characteristics between different sub - regions, and characterizes the water body conditions between different sub - regions within the basin and their interrelationships; based on the water area characteristics, determine the range of sewage outfalls in the sub - regions and dynamically monitor the sewage outfalls to obtain water quality and flow data, thereby generating a sewage outfall status characterization map and determining the abnormal information of the sewage outfalls in the sub - regions; based on the water area characteristics and connection characteristics, perform dynamic monitoring of the water environment to obtain dynamic monitoring data of the water environment, thereby generating a water environment status characterization map and determining the abnormal information of the water environment in the sub - regions. Dynamically characterize the entire basin from two aspects of sewage outfalls and water environment, and can further determine the water environment change trend of the basin, thereby predicting the water environment deterioration information of the global scope of the basin and accurately determining the water environment deterioration situation of the basin; also generate a dynamic map of water environment changes in the global scope of the basin, and send early warning notification messages to the corresponding base station terminal, effectively monitoring the real water environment status of the entire basin and providing reliable data support for the treatment of the basin water environment. Description of the Drawings

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings. Among them:

[0050] Figure 1 It is a schematic structural diagram of an intelligent monitoring and early warning system for the water environment of a river basin provided by the present invention. Specific embodiments

[0051] To make the above objects, features, and advantages of the present application more obvious and understandable, the following will, with reference to the drawings, give a detailed description of the specific embodiments of the present application. It can be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. Additionally, it should be noted that for the convenience of description, only the parts related to the present application rather than all the structures are shown in the drawings. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0052] The terms "including" and "having" and any variations thereof in the present application are intended to cover non-exclusive inclusion. For example, a process, system, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, systems, products, or devices.

[0053] Referring to "embodiments" herein means that the specific features, structures, or characteristics described in connection with the embodiments may be included in at least one embodiment of the present application. The phrase appears at various positions in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments.

[0054] Please refer to Figure 1 As shown, an intelligent monitoring and early warning system for the water environment of a river basin provided by an embodiment of the present application. The intelligent monitoring and early warning system for the water environment of a river basin includes:

[0055] A river basin zoning module, configured to perform visual recognition on the entire river basin range to obtain the water area characteristics of all sub-regions under the entire river basin range and the connection characteristics between different sub-regions;

[0056] The sewage outlet monitoring module is used to determine the range of sewage outlets in the sub-region based on the characteristics of the water area; based on the range of sewage outlets, dynamically monitor the sewage outlets in the sub-region to obtain the dynamic data of the sewage outlets in the sub-region;

[0057] The sewage outlet status recognition module is used to analyze the dynamic sewage outlet data to generate a sewage outlet status characterization map of the sub-region; based on the sewage outlet status characterization map, determine the abnormal information of the sewage outlets in the sub-region;

[0058] The water environment monitoring module is used to determine the monitoring points in the sub-region based on the characteristics of the water area and the connection characteristics; based on the monitoring points, dynamically monitor the water environment in the sub-region to obtain the dynamic water environment monitoring data of the sub-region;

[0059] The water environment status recognition module is used to analyze the dynamic water environment monitoring data to generate a water environment status characterization map of the sub-region; based on the water environment status characterization map, determine the abnormal information of the water environment in the sub-region;

[0060] The whole basin status recognition module is used to determine the water environment change trend of the whole basin based on the abnormal information of the sewage outlets and the abnormal information of the water environment; based on the water environment change trend, predict the water environment deterioration information of the whole basin;

[0061] The early warning notification module is used to generate a dynamic map of water environment changes in the whole basin based on the water environment deterioration information; based on the dynamic map of water environment changes, send an early warning notification message to the base station corresponding to the whole basin.

[0062] The beneficial effects of the above embodiments are as follows: The intelligent monitoring and early warning system for the water environment of the basin visually recognizes the water area characteristics of all sub-regions under the whole basin and the connection characteristics between different sub-regions, and characterizes the water body conditions of different sub-regions within the basin and their mutual relationships; based on the water area characteristics, determine the range of sewage outlets in the sub-region and dynamically monitor the sewage outlets to obtain water quality and water volume data, and thus generate a sewage outlet status characterization map to determine the abnormal information of the sewage outlets in the sub-region; based on the water area characteristics and connection characteristics, dynamically monitor the water environment to obtain dynamic water environment monitoring data, and thus generate a water environment status characterization map to determine the abnormal information of the water environment in the sub-region, globally and dynamically characterize the basin from two aspects of sewage outlets and water environment, and can further determine the water environment change trend of the basin, and thus predict the water environment deterioration information of the whole basin, accurately determine the water environment deterioration situation of the basin; also generate a dynamic map of water environment changes in the whole basin, and thus send an early warning notification message to the corresponding base station, effectively monitoring the real water environment status of the whole basin and providing reliable data support for the treatment of the water environment of the basin.

[0063] In another embodiment, the watershed zoning module is used to perform visual recognition on the global scope of the watershed to obtain the water area characteristics of all sub-regions under the global scope of the watershed and the connection characteristics between different sub-regions, including:

[0064] Obtain the remote sensing image of the global scope of the watershed, perform pixel contour and pixel texture recognition on the remote sensing image, and obtain the pixel contour distribution feature information and pixel texture distribution feature information of the entire picture of the remote sensing image;

[0065] Perform time evolution analysis on the pixel texture distribution feature information to obtain the water body flow velocity distribution information of the global scope of the watershed; based on the water body flow velocity distribution information, divide the entire watershed into several dynamic sub-regions and several static sub-regions;

[0066] Analyze the pixel contour distribution feature information of each dynamic sub-region and each static sub-region respectively to obtain the water area boundary characteristics of each dynamic sub-region and each static sub-region and the connection node boundary characteristics between the dynamic sub-region and the static sub-region; also based on the pixel texture distribution feature information, determine the connection node water flow characteristics between the dynamic sub-region and the static sub-region.

[0067] The beneficial effects of the above embodiments are as follows. A river basin is usually composed of rivers, lakes, etc. Lakes serve as the water storage and buffer areas for rivers. The water flow inside the lakes is relatively calm, while the water flow in rivers is relatively fierce. Moreover, the water areas and shapes of lakes and rivers are also quite different. The above differences between rivers and lakes lead to different requirements in water environment monitoring. In order to accurately monitor different types of sub-regions such as rivers and lakes within the entire river basin, first, pixel contours and pixel textures of the remote sensing images of the entire river basin are identified to obtain the pixel contour distribution feature information and pixel texture distribution feature information of the entire remote sensing image. There is an obvious boundary between the water body and the land shore in rivers and lakes. By identifying the pixel contours of the remote sensing images, the water area boundaries corresponding to rivers and lakes can be accurately determined. In addition, rivers and lakes are connected through corresponding water channels, and the shape and size of the water channels (such as the bending arc and width of the channels, etc.) will affect the water body exchange between rivers and lakes (such as the water exchange flow rate, etc.). Also, the water flow velocity of rivers is greater than that of lakes, resulting in significant differences in the pixel texture features of the corresponding image areas of rivers and lakes in the remote sensing images. By identifying the pixel texture distribution feature information of the entire remote sensing image, the dynamic sub-regions (such as the sub-regions corresponding to rivers) and static sub-regions (such as the sub-regions corresponding to lakes) within the entire river basin can be accurately distinguished. Specifically, time evolution analysis is performed on the pixel texture distribution feature information, so as to quantitatively characterize the water flow velocity distribution of the entire river basin, and thereby divide the entire river basin into several dynamic sub-regions and several static sub-regions, facilitating subsequent differentiated monitoring of river regions and lake regions. The pixel contour distribution feature information of each dynamic sub-region and each static sub-region is also analyzed to obtain the water area boundary features of each dynamic sub-region and each static sub-region and the connection node boundary features between the dynamic sub-region and the static sub-region (i.e., the boundary features of the water channel between the dynamic sub-region and the static sub-region), so as to identify the physical forms of all sub-regions under the entire river basin.

[0068] In another embodiment, the sewage outfall monitoring module is used to determine the range of the sewage outfall in the sub-region based on the water area characteristics; based on the range of the sewage outfall, perform dynamic monitoring of the sewage outfall in the sub-region to obtain the dynamic data of the sewage outfall in the sub-region, including:

[0069] Perform pollution source correlation analysis on the water area boundary characteristics to determine the pollution source information associated with the water body and the land in the sub-region; based on the pollution source information, determine the range of the key monitored sewage outfalls in the sub-region;

[0070] Based on the range of the sewage outfall, determine the monitoring points for dynamic monitoring of the sewage outfall in this sub-region; then conduct dynamic water quality monitoring and dynamic flow monitoring on all monitoring points to obtain the corresponding dynamic water quality data and dynamic flow data for each monitoring point, and use these as the dynamic sewage outfall data for this sub-region.

[0071] The beneficial effects of the above embodiments are that the types of pollution sources associated with the sewage outfall are diverse, including industrial enterprises, domestic sewage, agricultural non-point sources, rainwater outfalls, etc. Therefore, conduct an analysis of the association between the sewage outfall and pollution sources based on the boundary characteristics of this water area, determine the pollution source information associated with the sewage outfall between the sewage outfall of the incoming water body in this sub-region and the land, and thereby determine the scope of the key regulatory sewage outfall in this sub-region. The scope of the sewage outfall in this sub-region can be, but is not limited to, industrial enterprises, domestic sewage, and agricultural non-point source sewage outfalls with relatively large emissions and involving key regulatory pollutants in the incoming water body of this sub-region. Then, based on this pollution source information, determine the dynamic monitoring points for the key regulatory sewage outfall in this sub-region, so as to conduct dynamic monitoring on the key regulatory sewage outfall in this sub-range. Then conduct dynamic monitoring of water quality and water volume on all monitoring points to obtain the corresponding water quality and water volume dynamic data for each monitoring point, and use these as reliable data support for generating the sewage outfall status characterization map in the follow-up.

[0072] In another embodiment, the sewage outfall status identification module is used to analyze the dynamic sewage outfall data and generate the sewage outfall status characterization map of this sub-region; based on the sewage outfall status characterization map, determine the abnormal information of the sewage outfall in this sub-region, including:

[0073] Based on the distribution positions of all the first monitoring points within this sub-region, conduct integrated analysis on the corresponding dynamic water quality data and dynamic flow data of all monitoring points to obtain the global water quality and water volume change characteristics of this sub-region;

[0074] Based on the global water quality and water volume change characteristics of this sub-region, conduct label identification on the electronic map of this sub-region to generate the sewage outfall status characterization map of this sub-region;

[0075] Based on the big data of historical emission conditions, conduct prediction of the pollutant concentration and emission volume of the sewage outfall on the sewage outfall status characterization map, and determine the location information and time information where sewage outfall anomalies will occur within this sub-region, and use these as the abnormal information of the sewage outfall in this sub-region.

[0076] Based on the distribution positions of all the monitoring points within the sub-region, the beneficial effects of the above embodiments integrate and analyze the water quality dynamic data and flow dynamic data corresponding to all the monitoring points, and can fit the global water quality and water volume change characteristics of the sewage outfalls in the sub-region, so as to realize the global motion characterization of the sub-region from point to surface. Also, based on the global water quality and water volume change characteristics of the sub-region, the water quality and water volume change parameters are marked on the electronic map of the sub-region to generate a sewage outfall state characterization map of the sub-region. And based on the big data of historical emission conditions, the pollutant concentration and emission change conditions of the sewage outfalls are predicted for the sewage outfall state characterization map, and the location information and time information of the sewage outfall anomalies that will occur within the sub-region are determined to accurately and comprehensively identify the sewage outfall anomaly information in the sub-region.

[0077] In another embodiment, the water environment monitoring module is used to determine the monitoring points of the sub-region based on the water area characteristics and the connection characteristics; based on the monitoring points, conduct dynamic monitoring of the water environment of the sub-region to obtain the dynamic monitoring data of the water environment of the sub-region, including:

[0078] Based on the water area boundary characteristics, the connection node boundary characteristics and the connection node water area characteristics, determine the distribution information of the water body exchange flow rate between the dynamic sub-region and the static sub-region within the global scope of the basin; based on the distribution information of the water body exchange flow rate, determine the monitoring points of the sub-region;

[0079] Based on the coordinate information of the monitoring points, conduct dynamic monitoring of the water quality and hydrology of the monitoring points to obtain the dynamic monitoring data of the water quality and hydrology corresponding to the monitoring points, and use this as the dynamic monitoring data of the water environment of the sub-region.

[0080] Based on the water area boundary characteristics, the connection node boundary characteristics and the connection node water area characteristics of the above embodiments, determine the distribution information of the water body exchange flow rate between the dynamic sub-region and the static sub-region within the global scope of the basin, so as to accurately calculate the water body exchange flow value per unit time between the dynamic sub-region and the connected static sub-region; when the water body exchange flow rate exceeds the preset rate threshold, set monitoring points within the corresponding connection node water area, so that the water area where the monitoring points are located can continuously have water body exchange, enabling the monitoring points to conduct full and comprehensive water body monitoring. Also, based on the coordinate information of the monitoring points, conduct dynamic monitoring of the water quality and hydrology of the effective water body monitoring positions to obtain the dynamic monitoring data of the water quality and hydrology corresponding to the monitoring points, providing reliable data support for the subsequent generation of the water environment state characterization map.

[0081] In another embodiment, the water environment state recognition module is used to analyze the dynamic data of the water environment, generate a water environment state characterization map of the sub-region; based on the water environment state characterization map, determine the water environment anomaly information of the sub-region, including:

[0082] Based on the distribution positions of all monitoring points within the sub-region, integrate and analyze the water quality and hydrological dynamic data corresponding to all monitoring points to obtain the global water environment pollutant concentration change characteristics of the sub-region;

[0083] Based on the global water environment pollutant concentration change characteristics of the sub-region, label the electronic map of the sub-region to generate a water environment state characterization map of the sub-region.

[0084] The beneficial effects of the above embodiments are as follows. The dynamic data of water body pollutant concentration, water body water level height, water body oxygen concentration, and water body temperature monitored at each monitoring point reflect the dynamic changes of the water environment at the monitoring point and its surrounding areas. Based on the distribution positions of all monitoring points within the sub-region, integrating and analyzing the water quality and hydrological dynamic data corresponding to all monitoring points can fit the global water environment pollutant concentration change characteristics of the sub-region, so as to realize the global water environment state characterization of the sub-region from point to surface. Additionally, based on the global water environment pollutant concentration change characteristics of the sub-region, label the electronic map of the sub-region with pollutant concentration change parameters to generate a water environment state characterization map of the sub-region. And predict the water environment quality of the water environment state characterization map to determine the location information and time information of water quality anomaly events occurring within the sub-region, accurately and comprehensively identifying the water environment anomaly information of the sub-region.

[0085] In another embodiment, the whole basin state recognition module is used to determine the water environment change trend of the whole basin based on the sewage outlet anomaly information and the water environment anomaly information; based on the water environment change trend, predict the water environment deterioration information of the whole basin, including:

[0086] Based on the location information and time information of the sewage outlet anomaly that will occur within the sub-region included in the sewage outlet anomaly information and the location information and time information of the water quality anomaly event that occurs within the sub-region included in the water environment anomaly information, perform correlation analysis using the water environment diffusion model, and determine the movement and diffusion change trend of water environment pollutants in the whole basin;

[0087] Based on the movement and diffusion change trend of water environment pollutants, determine the water environment pollutant retention time information of all sub-regions within the whole basin, thereby predicting the sub-regions where water environment deterioration occurs in the whole basin.

[0088] Based on the location information and time information of the abnormal sewage outlet within the sub-region included in the abnormal sewage outlet information and the location information and time information of the water quality abnormal event within the sub-region included in the water environment abnormal information, the neural network model analysis is carried out on the global scope of the basin to obtain the movement and diffusion change trend of water environment pollutants in the global scope of the basin, so as to determine the retention time information of water environment pollutants in all sub-regions within the global scope of the basin. When the retention time of water environment pollutants in a certain sub-region exceeds the preset time length threshold, the sub-region is determined as the sub-region where water environment deterioration will occur, which is convenient for subsequent on-site detection of the sub-regions where water environment deterioration occurs.

[0089] In another embodiment, the early warning notification module is used to generate a dynamic map of water environment changes in the global scope of the basin based on the water environment deterioration information; based on the dynamic map of water environment changes, send an early warning notification message to the base station end corresponding to the global scope of the basin, including:

[0090] Based on the location range of the sub-regions where water environment deterioration occurs in the global scope of the basin and the water body exchange flow rate between it and other adjacent sub-regions, the electronic map of the global scope of the basin is marked and processed to generate a dynamic map of water environment changes;

[0091] Based on the dynamic map of water environment changes, determine the base station end that can conduct on-site detection of the water environment changes in the global scope of the basin within a preset time interval; based on the network access status of all detection devices inside the base station end, send a corresponding early warning notification instruction message to the base station end, so that all detection devices enter the corresponding detection working mode.

[0092] The beneficial effect of the above embodiment is that, based on the location range of the sub-regions where water environment deterioration occurs in the global scope of the basin and the water body exchange flow rate between it and other adjacent sub-regions, the electronic map of the global scope of the basin is marked and processed to generate a dynamic map of water environment changes, so that the detection coverage range corresponding to the base station end that the water body pollutants can reach within a preset time interval can be accurately determined in the whole range from the dynamic map of water environment changes. Then, based on the network access status of all detection devices inside the base station end, a corresponding early warning notification instruction message is sent to the base station end, so that all detection devices enter the corresponding detection working mode, enabling the base station end to conduct on-site water environment detection in time when the water environment pollutants reach its corresponding detection coverage range, and improving the authenticity and real-time of water environment detection data.

[0093] In another embodiment, based on the network access status of all detection devices inside the base station end, send a corresponding early warning notification instruction message to the base station end, so that all detection devices enter the corresponding detection working mode, including:

[0094] Step S1: According to the network access status of all detection devices inside the base station, use the following formula (1) to obtain the comprehensive status score of the base station.

[0095]

[0096] In the above formula (1), E represents the comprehensive status score of the base station; N represents the total number of detection devices; A i represents the access status of the i-th device. When A i = 1, it indicates that the device is online. When A i = 0, it indicates that the device is offline; W i represents the working mode value of the i-th device. When W i = 1, it indicates that the device is in a periodic working state. When W i = 0.5, it indicates that the device is in a sleep state; C i represents a preset importance coefficient; T i represents the online time of the i-th device; T max represents the longest online time among all devices; α i represents an adjustment factor; S i represents the stability score of the device.

[0097] Step S2: According to the comprehensive status score of the base station, use the following formula (2) to control the warning trigger status.

[0098]

[0099] In the above formula (2), P represents the warning trigger status. When P = 1, it indicates that the warning is triggered. When P = 0, it indicates that the warning is not triggered; E0 represents a preset status threshold; D represents the deviation between the current status and the historical average status; D max represents the maximum value of the historical deviation.

[0100] Step S3: According to the warning trigger status, use the following formula (3) to perform control of working mode switching.

[0101]

[0102] In the above formula (3), M represents the new working mode quantization value; M0 represents the current working mode quantization value; ΔM represents the difference between the target mode quantization value and the current mode quantization value; P represents the warning status; F represents the device failure rate; F max represents the maximum value of the historical device failure rate; β represents an adjustment factor used to control the sensitivity of mode switching.

[0103] When M is greater than a preset quantization threshold, switch the detection device from the current working mode to another working mode; otherwise, keep the current working mode of the detection device unchanged.

[0104] The beneficial effects of the above embodiments are as follows. Using the above formula (1), based on the network access status of all detection devices inside the base station, the comprehensive status score of the base station is obtained. By introducing the online time, stability, and personalized adjustment factors, the status evaluation becomes more comprehensive. Then, using the above formula (2), based on the comprehensive status score of the base station, the warning trigger status is controlled. By introducing the historical deviation, the flexibility of the warning trigger condition is enhanced. Then, using the above formula (3), based on the warning trigger status, the working mode switching control is performed. By combining the failure rate and the adjustment factor, the working mode switching becomes more intelligent and adapts to different device states.

[0105] Generally speaking, the visual recognition of the intelligent monitoring and warning system for the water environment in this basin characterizes the water area features of all sub-regions under the global scope of the basin and the connection features between different sub-regions, and represents the water body conditions between different sub-regions within the basin and their mutual relationships; based on the water area features, the range of the sewage outfall in the sub-region is determined and the sewage outfall is dynamically monitored to obtain water quality and water volume data, and a sewage outfall status characterization map is generated based on this to determine the abnormal information of the sewage outfall in the sub-region; based on the water area features and connection features, dynamic monitoring of the water environment is carried out to obtain dynamic monitoring data of the water environment, and a water environment status characterization map is generated based on this to determine the abnormal information of the water environment in the sub-region. The global dynamic characterization of the basin is carried out from two aspects of the sewage outfall and the water environment, and the changing trend of the water environment in the basin can be further determined, and based on this, the water environment deterioration information in the global scope of the basin is predicted, and the water environment deterioration situation in the basin is accurately determined; a dynamic map of the water environment change in the global scope of the basin is also generated, and based on this, a warning notification message is sent to the corresponding base station, effectively monitoring the real water environment status of the entire basin and providing reliable data support for the treatment of the water environment in the basin.

[0106] The above is only a specific implementation manner of the present invention, and any improvement made on the premise of the present invention concept is regarded as the protection scope of the present invention.

Claims

1. A basin water environment intelligent monitoring and early warning system, characterized in that: include: A watershed partitioning module is used to visually identify the global scope of the watershed, obtain the water characteristics of all sub-regions under the global scope of the watershed and the connection characteristics between different sub-regions; A sewage outlet monitoring module is used to determine the sewage outlet monitoring range of the sub-area based on the characteristics of the water area; based on the sewage outlet monitoring range, dynamically monitor the sewage outlets of the sub-area to obtain dynamic monitoring data of the sewage outlets of the sub-area; A sewage outlet state identification module, used to analyze the sewage outlet dynamic monitoring data and generate a sewage outlet state representation map of the sub-area; Determining abnormal information of the sewage outlet in the sub-area based on the sewage outlet state representation map; A water environment monitoring module, used to determine the monitoring points of the sub-area based on the water area characteristics and the connection characteristics; based on the monitoring points, dynamically monitor the water environment of the sub-area to obtain dynamic water environment data of the sub-area; A water environment state identification module is used to analyze the water environment dynamic data to generate a water environment state representation map of the sub-area; based on the water environment state representation map, determine the abnormal water environment information of the sub-area; A whole-basin state identification module, used to determine the water environment change trend of the whole basin based on the abnormal information of the sewage outlet and the abnormal information of the water environment; based on the water environment change trend, predict the water environment deterioration information of the whole basin; An early warning notification module, used to generate a dynamic map of water environment changes in the global scope of the basin based on the water environment deterioration information; Based on the dynamic map of water environment changes, an early warning notification message is sent to the base station end corresponding to the global range of the watershed.

2. The intelligent monitoring and early warning system for water environment in a river basin as claimed in claim 1, characterized in that: The watershed partitioning module is used to visually identify the global scope of the watershed, and obtain the water characteristics of all sub-regions under the global scope of the watershed and the connection characteristics between different sub-regions, including: Acquire a remote sensing image of the global range of the watershed, perform pixel contour and pixel texture recognition on the remote sensing image, and obtain pixel contour distribution feature information and pixel texture distribution feature information of the entire remote sensing image; Performing a time evolution analysis on the pixel texture distribution feature information to obtain the water flow velocity distribution information in the global range of the watershed; dividing the entire range of the watershed into a number of dynamic sub-areas and a number of static sub-areas based on the water flow velocity distribution information; The pixel contour distribution feature information of each dynamic sub-region and each static sub-region is analyzed to obtain the water boundary features of each dynamic sub-region and each static sub-region and the boundary features of the connection nodes between the dynamic sub-region and the static sub-region; and the water flow features of the connection nodes between the dynamic sub-region and the static sub-region are determined based on the pixel texture distribution feature information.

3. The intelligent monitoring and early warning system for water environment in a river basin as claimed in claim 2 is characterized by: The sewage outlet monitoring module is used to determine the sewage outlet monitoring range of the sub-area based on the water area characteristics; Based on the monitoring range of the sewage outlet, the sewage outlet of the sub-area is dynamically monitored to obtain dynamic data of the sewage outlet of the sub-area, including: Performing pollution source association analysis on the boundary features of the water area to determine the pollution source information associated between the water body and the land in the sub-area; Based on the pollution source information, determine the scope of the key regulated sewage outlets in the sub-region; Based on the scope of the key regulated sewage outlets, determine the dynamic monitoring points for the sewage outlets in the sub-area; then perform dynamic water quality monitoring and flow rate monitoring on all monitoring points to obtain the dynamic water quality data and flow rate data corresponding to all monitoring locations, which will be used as the dynamic monitoring data for the sewage outlets in the sub-area.

4. The intelligent monitoring and early warning system for water environment in a river basin as claimed in claim 3 is characterized by: The sewage outlet state identification module is used to analyze the dynamic sewage outlet data to generate a sewage outlet state representation map of the sub-area; Determining abnormal information of the sewage outlet in the sub-area based on the sewage outlet state representation map includes: Based on the distribution positions of all monitoring points within the sub-area, the water quality dynamic data and flow dynamic data corresponding to all monitoring points are integrated and analyzed to obtain the global water quality and water quantity change characteristics of the sub-area; Based on the global water quality and water quantity change characteristics of the sub-area, label the electronic map of the sub-area to generate a sewage outlet status representation map of the sub-area; Based on the historical emission status big data, the pollutant concentration and emission amount of the sewage outlet are predicted for the sewage outlet status characterization map, and the location information and time information of the sewage outlet abnormality within the sub-area are determined, which is used as the sewage outlet abnormality information of the sub-area.

5. The intelligent monitoring and early warning system for water environment in a river basin as claimed in claim 2, characterized in that: The water environment monitoring module is used to determine the monitoring points of the sub-area based on the water area characteristics and the connection characteristics; Based on the monitoring points, the water environment of the sub-area is dynamically monitored to obtain the dynamic monitoring data of the water environment of the sub-area, including: Based on the water area boundary characteristics, the connection node boundary characteristics and the connection node water area characteristics, determine the water body exchange flow rate distribution information between the dynamic sub-area and the static sub-area within the global range of the basin; based on the water body exchange flow rate distribution information, determine the monitoring point position of the sub-area; Based on the coordinate information of the monitoring point, the water quality and hydrological dynamic monitoring of the monitoring point is performed to obtain the water quality and hydrological dynamic monitoring data of the water body corresponding to the monitoring point, which is used as the water environment dynamic monitoring data of the sub-area.

6. The intelligent monitoring and early warning system for water environment in a river basin as claimed in claim 5, characterized in that: The water environment status recognition module is used to analyze the water environment dynamic monitoring data and generate a water environment status representation map of the sub-area; Determining abnormal water environment information of the sub-area based on the water environment state representation map includes: Based on the distribution of all monitoring points within the sub-region, the water quality and hydrological dynamic data corresponding to all monitoring points are integrated and analyzed to obtain the global water environment pollutant concentration change characteristics of the sub-region; Based on the global water environment pollutant concentration variation characteristics of the sub-area, the electronic map of the sub-area is labeled to generate a water environment status representation map of the sub-area.

7. The intelligent monitoring and early warning system for water environment in a river basin as claimed in claim 1, characterized in that: The whole basin state identification module is used to determine the water environment change trend of the whole basin based on the abnormal information of the sewage outlet and the abnormal information of the water environment; Based on the water environment change trend, predict the water environment deterioration information of the global range of the basin, including: Based on the location information and time information of the sewage outlet abnormality that will occur within the sub-region included in the sewage outlet abnormality information and the location information and time information of the water quality abnormality event that will occur within the sub-region included in the water environment abnormality information, a water environment diffusion model is used to perform correlation analysis and determine the movement and diffusion change trend of water environment pollutants in the global scope of the basin; Based on the movement and diffusion trend of the water environment pollutants, the residence time information of the water environment pollutants in all sub-regions within the global range of the basin is determined, so as to predict the sub-regions where the water environment deteriorates within the global range of the basin.

8. The intelligent monitoring and early warning system for water environment in a river basin as claimed in claim 1, characterized in that: The early warning notification module is used to generate a dynamic map of water environment changes in the global scope of the basin based on the water environment deterioration information; Based on the dynamic map of water environment changes, sending an early warning notification message to a base station corresponding to the global range of the watershed includes: Based on the location range of the sub-regions where the water environment deteriorates in the global scope of the basin and the water exchange flow rate between them and other adjacent sub-regions, the electronic map of the global scope of the basin is marked and processed to generate a dynamic map of water environment changes; Based on the dynamic map of water environment changes, determine the base station end that can perform on-site detection of water environment changes in the global scope of the river basin within a preset time interval; based on the network access status of all detection equipment inside the base station end, send a corresponding early warning notification instruction message to the base station end, so that all detection equipment enter the corresponding detection working mode.

9. The intelligent monitoring and early warning system for water environment in a river basin as claimed in claim 8, characterized in that: Based on the network access status of all detection devices inside the base station, a corresponding early warning notification instruction message is sent to the base station, so that all detection devices enter a corresponding detection working mode, including: Step S1, using the following formula (1), according to the network access status of all detection devices inside the base station, obtain the comprehensive status score of the base station, In the above formula (1), E represents the comprehensive status score of the base station; N represents the total number of detection devices; A i Indicates the access status of the i-th device. When A i =1, indicating that the device is online. i =0, indicating that the device is offline; W i Indicates the working mode value of the i-th device. When W i =1, indicating that the device is in periodic working state. i =0.5, indicating that the device is in sleep mode; C i Indicates the preset importance coefficient; T i represents the online time of the ith device; T max Indicates the longest online time among all devices; α i represents the adjustment factor; S i Indicates the stability score of the device; Step S2, using the following formula (2), according to the comprehensive status score of the base station, control the early warning triggering state, In the above formula (2), P represents the warning trigger state, when P = 1, it indicates triggering, when P = 0, it indicates not triggering); E0 represents the preset state threshold; D represents the deviation between the current state and the historical average state; D max Indicates the maximum value of historical deviation; Step S3, using the following formula (3), according to the warning trigger state, the working mode switching control is performed: In the above formula (3), M represents the new working mode quantization value; M0 represents the current working mode quantization value; ΔM represents the difference between the target mode quantization value and the current mode quantization value; P represents the warning state; F represents the equipment failure rate; F max It represents the maximum value of the historical equipment failure rate; β represents the adjustment factor, which is used to control the sensitivity of mode switching; When M is greater than a preset quantization threshold, the detection device is switched from the current working mode to another working mode; otherwise, the current working mode of the detection device is kept unchanged.

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