Water affair facility management method and system based on GIS

Abstract

The invention discloses a GIS-based water affair facility management method and system, and relates to the technical field of water affair management, and the method comprises the steps that a geographic information module collects geographic information data of terrains, water systems and water affair facilities, and uploads the geographic information data to a platform layer; the equipment information module collects attributes and working data of each water affair facility and uploads the attributes and working data to the platform layer; the monitoring module monitors water system data of each water system and uploads the water system data to the platform layer; the platform layer establishes a corresponding water system risk threshold based on historical water system data of each water system, and establishes a water volume correlation coefficient model and a water quality correlation coefficient model between the water systems through correlation analysis; and the platform layer establishes a corresponding working data risk threshold based on the historical working data of each water affair facility. According to the water affair facility management system based on the GIS, effective fusion of geographic information data, equipment information data and water system monitoring data is achieved, and the refinement degree of water affair facility management is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water management, and specifically provides a GIS-based water facility management method and system. Background Art

[0002] With the continuous advancement of urban construction and industrial development, the scale of water facilities has gradually expanded, and the efficient utilization and safe management of water resources have become increasingly important. Modern water systems usually involve various types of facilities and equipment, such as water pumps, valves, sluices, sensors, etc. These facilities are widely distributed in different areas of the city and play important roles. How to scientifically manage and efficiently dispatch these devices to ensure the safety of water supply and drainage and environmental quality has become an important research direction in the field of water management.

[0003] At present, GIS (Geographic Information System) technology has been widely applied in the field of water facility management. Through GIS technology, effective integration and visualization of geographical information data such as terrain, water systems, and facility layouts can be achieved, providing important information support for the daily monitoring and operation and maintenance of water facilities. However, there is still a large space for exploration in how to further improve the integration depth of GIS and water facility management to achieve more proactive and accurate management.

[0004] After retrieval, Chinese Patent (Publication No.: CN117689283A) discloses a water system and water management method based on spatio-temporal GIS. The patent includes: a structure management subsystem for processing water member information and generating multiple member association information for characterizing the association relationship between two water member information based on the water member information; an information management subsystem for obtaining original water data according to the water member information; a spatio-temporal GIS subsystem for generating multiple water dynamic sub-models according to the water member information and the original water data, and generating a water dynamic system model according to the multiple water dynamic sub-models; a business management subsystem for generating business change information according to the member association information, the water dynamic sub-model, and the water dynamic system model, and issuing the business change information.

[0005] In the prior art, due to the complexity and dynamic change characteristics of the water system environment and facility operation status, existing management systems usually focus on data collection and presentation, but there is still room for further improvement in predicting the status of water equipment and accurately responding to water system changes using historical data. Therefore, the present invention proposes a GIS-based water facility management method and system. Summary of the Invention

[0006] The purpose of the present invention is to provide a GIS-based water facility management method and system to solve the problems mentioned in the above background art.

[0007] The present invention can be implemented through the following technical solutions: A water service facility management system based on GIS, including a platform layer, a data layer, an application layer (operation and maintenance management, equipment monitoring, early warning, dispatching optimization), and a user layer (operation and maintenance personnel, management personnel, emergency response personnel, dispatching personnel);

[0008] The data layer includes a geographic information module, an equipment information module, and a monitoring module;

[0009] The geographic information module is used to collect geographic information data of terrain, water systems, and water service facilities, and upload them to the platform layer to form corresponding visualization data and a first-level visualization layer;

[0010] The equipment information module is used to collect the attributes and working data of each water service facility and upload them to the platform layer. The platform layer incorporates the attributes and working data of each water service facility into the second-level visualization layer corresponding to the water service facility;

[0011] The monitoring module is used to monitor the water system data of each water system and upload them to the platform layer. The platform layer incorporates the water system data into the second-level visualization layer corresponding to the water system; where the water system data includes water quality data and water volume data;

[0012] Based on the historical water system data of each water system, the historical water system data includes historical water volume data and historical water quality data, the platform layer establishes a water volume correlation coefficient model and a water quality correlation coefficient model between water systems through correlation analysis, and is used to establish the water volume influence coefficient , water quality influence coefficient , water volume influence delay coefficient and water quality influence delay coefficient ;

[0013] And based on the historical working data of each water service facility, the platform layer establishes a water service facility association module, which is used to associate the functions between each water service facility, including:

[0014] Function complementary association: Two or more water service facilities cooperate in the same water supply and drainage task; for example, a water pump and a valve cooperate to control the flow;

[0015] Control dependency association: The control or status of one water service facility depends on another water service facility; for example, the start of a water pump depends on the valve status;

[0016] Standby redundancy association: Two water service facilities have the same function and can be used as spares for each other; for example, two booster pumps operate alternately;

[0017] Geographic proximity association: Two water service facilities are geographically close and affect the water system in the same area; for example, a water quality sensor and a drainage valve in the same area;

[0018] Risk linkage association: The abnormality of a certain water facility may affect the normal operation of other water facilities; for example, abnormal water levels can cause downstream water pumps to be overloaded;

[0019] The platform layer respectively establishes corresponding working data risk thresholds and water system risk thresholds based on the historical working data of each water facility and the historical water system data of each water system;

[0020] When the platform layer obtains real-time working data and real-time water system data, it respectively compares them with the working data risk threshold and the water system risk threshold;

[0021] If the real-time working data of a water facility is greater than the corresponding working data risk threshold, the platform layer marks the corresponding water facility as abnormal;

[0022] If the real-time water system data is greater than the corresponding water system risk threshold, the platform layer calculates the upstream influence source and the downstream diffusion area of the water system based on the water volume correlation coefficient model and the water quality correlation coefficient model, and the platform layer suspiciously marks each water facility at the upstream influence source of the water system and obtains each water facility in the downstream diffusion area of the water system;

[0023] Based on the marked situations of abnormal marks or suspicious marks of water facilities, the platform layer sends corresponding warning messages to the application layer and the user layer.

[0024] A further technical improvement of the present invention lies in: The method for the platform layer to calculate the upstream influence source and the downstream diffusion area of the water system includes the following steps: S1. The platform layer reads the real-time water system data of each water system. When the real-time water system data of a certain water system is greater than the water system risk threshold, it determines that the water system is an abnormal water system;

[0025] The real-time water system data includes water volume data and water quality data ; The water system risk threshold includes the corresponding water volume risk threshold and water quality risk threshold;

[0026] If the water volume data is greater than the water volume risk threshold or the water quality data is greater than the water quality risk threshold, it determines that the water system is an abnormal water system;

[0027] S2. The platform layer retrieves the water volume influence coefficient and the water volume influence delay coefficient from the water volume correlation coefficient model, and retrieves the water quality influence coefficient and the water quality influence delay coefficient from the water quality correlation coefficient model;

[0028] S3. The platform layer traces back the upstream water system data to locate the upstream influence source, including

[0029] a1: Set the data backtracking time window ; , where is the detection time point for determining the abnormal water system, is the preset maximum delay time;

[0030] a2. For the historical water volume data of the candidate upstream water system i , verify whether it satisfies:

[0031] ; If it is satisfied, the platform layer marks this water system as a suspected impact source;

[0032] In the formula, is the water volume impact coefficient; is the preset water volume error tolerance;

[0033] a3. At the same time, for the water quality data of the candidate upstream water system i whether it satisfies:

[0034] ; If it is satisfied, the platform layer marks this water system as a suspected impact source;

[0035] In the formula, is the water quality impact coefficient; is the preset water quality error tolerance;

[0036] a4. For the candidate water system i that simultaneously satisfies the conditions of a2 and a3, the platform layer marks it as the upstream impact source and marks the water service facilities covered by this water system as suspicious;

[0037] S4. The platform layer calculates the downstream diffusion path and diffusion time, including:

[0038] b1. The platform layer collects the water flow propagation speed of the corresponding water system ;

[0039] b2. The platform layer obtains the water quality anomaly duration of the same water quality problem from the historical water system data ;

[0040] S5. The platform layer calculates the downstream diffusion distance and the diffusion area A;

[0041] Among them, ;

[0042] ; In the formula, W is the average river width;

[0043] S6. Based on the geographic information data, the platform layer retrieves all water facilities in the diffusion area A and includes them in the diffusion response list for early warning and dispatching.

[0044] A further technical improvement of the present invention lies in: the method for obtaining the candidate upstream water system i, including:

[0045] Q1. Based on the geographic information data of the geographic information module, the platform layer generates the water system topology diagrams of each water system to describe the water flow directions, connection relationships, and flow paths between water systems;

[0046] Q2. The platform layer locates the position of the water system determined to be abnormal through the water system topology diagram and marks it as ;

[0047] Q3. Retrieve all water systems that meet through the water system topology diagram , and record them as: ; where means is upstream of the abnormal water system in the water system topology structure;

[0048] Q4. Calculate the maximum influence distance through the maximum delay time and the average water flow velocity of the abnormal water system , ;

[0049] The platform layer filters out water systems within the range of the maximum influence distance in the water system topology diagram and meeting the condition that the water flow path reaches to form an effective candidate upstream water system set ;

[0050] where the candidate upstream water system i ∈ , and .

[0051] A further technical improvement of the present invention lies in: the platform layer ranks the importance level, abnormality level, and risk level of each water facility in the diffusion response list based on its function, and calculates the ranking score of each water facility in the diffusion response list through a formula. The formula used is:

[0052] ; in the formula, is the abnormality marking level of the water facility g (normal = 0, suspicious marking = 1, abnormal marking = 2); is the importance level of the water facility g, which is obtained based on the preset of the user; is the spatial distance from the water service facility g to the abnormal occurrence point (including abnormal water systems and abnormal water service facilities); 、 and are the corresponding weighting coefficients, which are obtained through experiments or historical experience;

[0053] The platform layer is based on the sorting score , and performs the following operations on each water service facility in the diffusion response list:

[0054] Hierarchical response: According to the sorting results, perform emergency dispatching one by one or in batches from high to low, and give priority to performing operations such as closing, repairing, isolating or emergency disposal of high-risk facilities;

[0055] Optimization of operation and maintenance resource allocation: Determine the inspection, repair routes and priorities of operation and maintenance personnel according to the sorting to ensure the efficient use of operation and maintenance resources and a quick response to emergencies;

[0056] Optimization of the risk monitoring priority of water service facilities: Prioritize real-time key monitoring of water service facilities with high sorting, and dynamically adjust the monitoring frequency and intensity;

[0057] Precise push of external warning information: According to the sorting results and the severity of the impact of water service facilities, accurately formulate and send warning information, and users and emergency personnel around high-risk water service facilities receive more clear prompts and disposal plans.

[0058] A further technical improvement of the present invention lies in that: the platform layer statistically analyzes the warning information of each water service facility, establishes a warning information statistical table for water service facilities, and the statistical table includes:

[0059] The number of the water service facility g;

[0060] The number of warning information ;

[0061] The grade weight score of each warning information , and the grade weight score is based on the grade of each warning information;

[0062] And the platform layer scores each water service facility based on the warning information statistical table of water service facilities, and the formula used is: ; In the formula, is the total historical warning information score of the water service facility i; is the grade weight score of the jth warning information of the water service facility g;

[0063] The platform layer maps the total historical warning information score of each water service facility to the water system where it is located to obtain the comprehensive risk score of each water system. The formula is: ; In the formula, is the set of all water service facilities corresponding to the kth water system; is the total historical warning information score of water service facilities g; is the water system 's comprehensive risk score;

[0064] The platform layer maps the comprehensive risk score to the water system topology map, and conducts spatial clustering analysis, propagation path analysis, and high-risk facility location to quickly identify the weak links and high-risk areas in the water system, clearly identify high-risk facilities, and clarify the direction and priority order of facility maintenance and renewal investment;

[0065] Among them, spatial clustering analysis is used to identify the aggregation areas of high-risk water systems in the geographical space;

[0066] Propagation path analysis is based on the water flow direction, analyzes the risk level association between the upstream and downstream water systems of high-risk water systems, and identifies possible risk diffusion paths;

[0067] High-risk facility location is used to identify key facilities in water systems with high risk levels and clarify the priority of risk control.

[0068] The present invention also discloses a GIS-based water service facility management method, which includes:

[0069] Step 1: Data collection, collect the geographical information data of terrain, water system, and water service facilities, and form corresponding first-level visualization layers; collect the attribute and working data of each water service facility to form corresponding second-level visualization layers; at the same time, collect the water volume data and water quality data of the water system to form corresponding second-level visualization layers of the water system;

[0070] Step 2: Model construction, establish a water volume correlation coefficient model and a water quality correlation coefficient model based on the historical water volume data and historical water quality data of each water system, and obtain the water volume influence coefficient , water quality influence coefficient , water volume influence delay coefficient and water quality influence delay coefficient ;

[0071] Step 3: Based on the historical working data of each water service facility, establish the functional association between each water service facility;

[0072] Step 4: The platform layer respectively establishes corresponding working data risk thresholds and water system risk thresholds based on the historical working data of each water service facility and the historical water system data of each water system;

[0073] Step 5: The platform layer obtains the real-time working data and real-time water system data of the water service facilities, and compares them with the corresponding working data risk thresholds and water system risk thresholds respectively;

[0074] If the real-time working data of the water service facilities exceeds the risk threshold of the working data, the water service facilities will be marked as abnormal;

[0075] If the real-time water system data exceeds the water system risk threshold, the upstream influence source of the water system and the downstream diffusion area of the water system will be calculated based on the water volume correlation coefficient model and the water quality correlation coefficient model. The water service facilities within the influence source area will be marked as suspicious, and all water service facilities within the diffusion area will be obtained;

[0076] Step Six: Based on the abnormal or suspicious marking situation of the water service facilities, warning information of corresponding levels will be generated and sent to the application layer and the user layer.

[0077] Compared with the prior art, the present invention has the following beneficial effects:

[0078] By constructing a GIS-based water service facility management system, the present invention realizes the effective integration of geographical information data, equipment information data, and water system monitoring data, significantly improves the refinement degree of water service facility management, and significantly improves the prediction ability and rapid response ability to water system abnormal events by introducing the water volume and water quality correlation coefficient models; and based on the abnormal traceability and diffusion prediction method of the model, it can quickly locate the influence source of abnormal events and clarify the potential downstream diffusion area, providing effective decision-making support for operation and maintenance management personnel to realize the timely control and handling of abnormalities;

[0079] Moreover, the water service facility function association module, risk marking mechanism, and hierarchical warning response scheduling strategy proposed by the present invention effectively improve the linkage response ability of the water service system in the face of sudden risks. Through the functional complementarity, control dependence, standby redundancy, geographical proximity, and risk linkage association between facilities, the collaborative management of water service facilities and the water system environment state can be realized, thereby significantly reducing the risk losses caused by sudden water service events and improving the safety and stability of the urban water service system. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] For the convenience of those skilled in the art to understand, the present invention will be further described below with reference to the accompanying drawings.

[0081] Figure 1 It is the system block diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0082] To further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following describes in detail the specific embodiments, structures, features, and effects of the present invention with reference to the accompanying drawings and preferred embodiments.

[0083] Please refer to Figure 1As shown in the figure, the present invention provides a water service facility management system based on GIS, which includes a platform layer, a data layer, an application layer (operation and maintenance management, equipment monitoring, early warning, dispatching optimization), and a user layer (operation and maintenance personnel, management personnel, emergency response personnel, dispatching personnel);

[0084] The data layer includes a geographic information module, an equipment information module, and a monitoring module;

[0085] The geographic information module is used to collect geographic information data of terrain, water systems, and water service facilities, and upload it to the platform layer to form corresponding visualization data and a first-level visualization layer;

[0086] The equipment information module is used to collect the attributes and working data of each water service facility and upload it to the platform layer. The platform layer incorporates the attributes and working data of each water service facility into the second-level visualization layer corresponding to the water service facility;

[0087] Among them, the attributes of water service facilities include equipment number, equipment type, model specifications, installation time, service life, maintenance records, etc.;

[0088] The working data includes operating status, flow data, pressure status, water quality parameters, environmental parameters, communication status, operating duration, etc.;

[0089] The monitoring module is used to monitor the water system data of each water system and upload it to the platform layer. The platform layer incorporates the water system data into the second-level visualization layer corresponding to the water system; among them, the water system data includes water quality data and water volume data;

[0090] The platform layer, based on the historical water system data of each water system, where the historical water system data includes historical water volume data and historical water quality data, establishes a water volume correlation coefficient model and a water quality correlation coefficient model between water systems through correlation analysis, for establishing the water volume impact coefficient 、the water quality impact coefficient 、the water volume impact delay coefficient and the water quality impact delay coefficient ;

[0091] Among them, the water volume correlation coefficient model and the water quality correlation coefficient model include linear or non-linear regression models, time series models, hydrodynamic simulation models, and the model parameters are trained and continuously optimized through historical monitoring data to meet the actual application requirements;

[0092] And the platform layer, based on the historical working data of each water service facility, establishes a water service facility association module for associating the functions between each water service facility, including:

[0093] Functional complementary association: Two or more water service facilities cooperate in the same water supply and drainage task; for example, a water pump and a valve cooperate to control the flow;

[0094] Control Dependency Association: The control or status of one water facility depends on another water facility; for example, the start of a water pump depends on the valve status;

[0095] Standby Redundancy Association: Two water facilities have the same function and can be used as spares for each other; for example, two booster pumps operate alternately;

[0096] Geographical Proximity Association: Two water facilities are geographically close and affect the water system in the same area; for example, water quality sensors and drainage valves in the same area;

[0097] Risk Linkage Association: The abnormality of one water facility may affect the normal operation of other water facilities; for example, abnormal water level may cause overloading of downstream water pumps;

[0098] The platform layer respectively establishes corresponding working data risk thresholds and water system risk thresholds based on the historical working data of each water facility and the historical water system data of each water system;

[0099] When the platform layer obtains real-time working data and real-time water system data, it respectively compares them with the working data risk threshold and the water system risk threshold;

[0100] If the real-time working data of a water facility is greater than the corresponding working data risk threshold, the platform layer marks the corresponding water facility as abnormal;

[0101] If the real-time water system data is greater than the corresponding water system risk threshold, the platform layer calculates the upstream influence source of the water system and the downstream diffusion area based on the water volume correlation coefficient model and the water quality correlation coefficient model, and the platform layer suspiciously marks each water facility at the upstream influence source of the water system and obtains each water facility in the downstream diffusion area of the water system;

[0102] The method for the platform layer to calculate the upstream influence source of the water system and the downstream diffusion area includes the following steps: S1. The platform layer reads the real-time water system data of each water system. When the real-time water system data of a certain water system is greater than the water system risk threshold, it determines that the water system is an abnormal water system;

[0103] The real-time water system data includes water volume data , water quality data ; the water system risk threshold includes the corresponding water volume risk threshold and water quality risk threshold;

[0104] If the water volume data is greater than the water volume risk threshold or the water quality data is greater than the water quality risk threshold, it determines that the water system is an abnormal water system;

[0105] S2. The platform layer retrieves the water volume influence coefficient from the water volume correlation coefficient model And the water volume affects the delay coefficient and retrieve the water quality impact coefficient from the water quality correlation coefficient model and the water quality impact delay coefficient ;

[0106] S3. The platform layer traces back the upstream water system data and locates the upstream impact source, including

[0107] a1: Set the data tracing time window ; , where is the detection time point when the water system is judged to be abnormal, is the preset maximum delay time;

[0108] a2. For the historical water volume data of the candidate upstream water system i , verify whether it satisfies:

[0109] ; If it is satisfied, the platform layer marks this water system as a suspected impact source;

[0110] In the formula, is the water volume impact coefficient; is the preset water volume error tolerance;

[0111] a3. At the same time, for the water quality data of the candidate upstream water system i whether it satisfies:

[0112] ; If it is satisfied, the platform layer marks this water system as a suspected impact source;

[0113] In the formula, is the water quality impact coefficient; is the preset water quality error tolerance;

[0114] a4. For the candidate water system i that satisfies both the conditions of a2 and a3, the platform layer marks it as the upstream impact source and marks the water service facilities covered by this water system as suspicious;

[0115] S4. The platform layer calculates the downstream diffusion path and diffusion time, including:

[0116] b1. The platform layer collects the water flow propagation speed of the corresponding water system , in this embodiment, it can be obtained by setting corresponding sensors in the water system;

[0117] b2. The platform layer obtains the water quality anomaly duration of the same water quality problem from the historical water system data ;

[0118] S5. The platform layer calculates the downstream diffusion distance and the diffusion area A;

[0119] Among them, ;

[0120] ; in the formula, W is the average river width;

[0121] S6. The platform layer retrieves all water facilities in the diffusion area A based on the geographic information data and includes them in the diffusion response list for early warning and scheduling.

[0122] Moreover, the method for obtaining the candidate upstream water system i includes:

[0123] Q1. The platform layer generates the water system topology map of each water system based on the geographic information data of the geographic information module to describe the water flow direction, connection relationship, and flow path between each water system;

[0124] Q2. The platform layer locates the position of the water system determined to be abnormal through the water system topology map and marks it as ;

[0125] Q3. Retrieve all water systems that meet through the water system topology map , and denote it as: ;

[0126] Q4. Calculate the maximum influence distance through the maximum delay time and the average water flow velocity of the abnormal water system, ;

[0127] The platform layer filters out the water systems within the maximum influence distance in the water system topology map and that meet the condition that the water flow path reaches to form an effective set of candidate upstream water systems ;

[0128] Among them, the candidate upstream water system i ∈ and .

[0129] The platform layer ranks the importance, abnormality level, and risk level of each water facility in the diffusion response list based on the functions of each water facility in the diffusion response list, and calculates the ranking score of each water facility in the diffusion response list through a formula. The formula used is:

[0130] ; in the formula, is the abnormality marking level of water facility g (normal = 0, suspicious marking = 1, abnormal marking = 2); is the importance level of water facility g, which is obtained based on the preset of the user; is the spatial distance from water facility g to the abnormal occurrence point (including abnormal water systems and abnormal water facilities); 、 and are the corresponding weighting coefficients, which are obtained through experiments or historical experience;

[0131] The platform layer performs the following operations on each water facility in the diffusion response list based on the sorting score :

[0132] Hierarchical response: According to the sorting results, perform emergency dispatching one by one or in batches from high to low, and give priority to performing operations such as closing, repairing, isolating or emergency handling of high-risk facilities;

[0133] Optimization of operation and maintenance resource allocation: Determine the inspection, repair routes and priorities of operation and maintenance personnel according to the sorting to ensure the efficient use of operation and maintenance resources and a quick response to emergencies;

[0134] Optimization of the risk monitoring priority of water facilities: Give priority to real-time key monitoring of water facilities with high sorting, and dynamically adjust the monitoring frequency and intensity;

[0135] Precise push of external warning information: According to the sorting results and the severity of the impact of water facilities, accurately formulate and send warning information, and users and emergency personnel around high-risk water facilities receive clearer prompts and disposal plans.

[0136] The platform layer sends corresponding warning information to the application layer and the user layer based on the marked situation of abnormal or suspicious marks of water facilities.

[0137] In this embodiment, the warning information is set to three levels, as shown in Table 1 below:

[0138] Table 1

[0139] Warning level Trigger condition Warning content Dispatch response level Level 1 warning Water service facilities are suspiciously marked Remind that there may be abnormalities and attention is needed Submit monitoring to the platform layer and dispatch inspection tasks to the user layer Level 2 warning Water service facilities are abnormally marked Show that there are abnormal risks in the equipment Dispatch maintenance tasks to the user layer and pre-dispatch related water service facilities Level 3 warning Water service facilities are both suspiciously marked and abnormally marked, or multiple water service facilities in the same area are abnormally marked Abnormal risks appear, which may affect water service safety Dispatch maintenance tasks to the user layer and start related water service facilities

[0140] The platform layer counts the warning information of each water facility and establishes a warning information statistical table for water facilities. The statistical table includes:

[0141] Water facility g number;

[0142] Number of warning information ;

[0143] Level weight score of each warning information , and the level weight score is based on the level of each warning information. In this embodiment, the value of the first-level warning is 1, the value of the second-level warning is 2, and the value of the third-level warning is 3;

[0144] And the platform layer scores each water facility based on the statistical table of water facility warning information. The formula used is: ; In the formula, is the total historical warning information score of water facility i; is the grade weight score of the j-th warning information of water facility g;

[0145] The platform layer maps the total historical warning information scores of each water facility to the water system where it is located to obtain the comprehensive risk scores of each water system. The formula is: ; In the formula, is the set of all water facilities corresponding to the k-th water system; is the total historical warning information score of water facility i; is the water system 's comprehensive risk score;

[0146] The platform layer maps the comprehensive risk score to the water system topology map and conducts spatial clustering analysis, propagation path analysis, and high-risk facility location to quickly identify the weak links and high-risk areas in the water system, and clearly identify high-risk facilities, and clarify the direction and priority of facility maintenance and renewal investment;

[0147] Among them, spatial clustering analysis is used to identify the aggregation areas of high-risk water systems in the geographical space;

[0148] Propagation path analysis is based on the water flow direction to analyze the risk level association between the upstream and downstream water systems of high-risk water systems and identify possible risk diffusion paths;

[0149] High-risk facility location is used to identify key facilities in high-risk water systems and clarify the priority of risk control.

[0150] The above is only a preferred embodiment of the present invention, and it does not impose any form of limitation on the present invention. Although the present invention has been disclosed as above with a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments by using the disclosed technical content within the scope of the technical solution of the present invention. However, as long as it does not depart from the content of the technical solution of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A water service facility management system based on GIS, characterized in that, It includes a platform layer, a data layer, an application layer, and a user layer; The data layer includes a geographic information module, a device information module, and a monitoring module; The geographic information module collects geographic information data of terrain, water systems, and water conservancy facilities and uploads it to the platform layer; The device information module collects the attributes and working data of each water conservancy facility and uploads it to the platform layer; The monitoring module monitors the water system data of each water system and uploads it to the platform layer; the water system data includes water quality data and water volume data; The platform layer establishes corresponding water system risk thresholds based on the historical water system data of each water system, and establishes a water volume correlation coefficient model and a water quality correlation coefficient model between water systems through correlation analysis; At the same time, the platform layer establishes corresponding working data risk thresholds based on the historical working data of each water conservancy facility, and establishes a water conservancy facility association module to associate the functions between each water conservancy facility; When the platform layer obtains real-time working data and real-time water system data, it compares them with the working data risk threshold and the water system risk threshold respectively; If the real-time working data is greater than the corresponding working data risk threshold, the platform layer marks the corresponding water conservancy facility as abnormal; If the real-time water system data is greater than the corresponding water system risk threshold, the platform layer calculates the upstream influence source of the water system and the downstream diffusion area of the water system, and the platform layer suspiciously marks each water conservancy facility at the upstream influence source of the water system, and at the same time obtains each water conservancy facility in the downstream diffusion area of the water system; Based on the marking situation of the abnormal marking or suspicious marking of the water conservancy facility, the platform layer sends corresponding warning information to the application layer and the user layer.

2. The water service facility management system based on GIS according to claim 1, wherein The functional associations between the water conservancy facilities in the water conservancy facility association module include: functional complementary association, control dependency association, standby redundancy association, geographical proximity association, and risk linkage association.

3. The water service facility management system based on GIS according to claim 1, wherein The water quantity correlation coefficient model includes a water quantity influence coefficient and a water quantity influence delay coefficient ; The water quality correlation coefficient model includes a water quality impact coefficient and a water quality impact delay coefficient .

4. The water service facility management system based on GIS according to claim 3, characterized in that, The method for the platform layer to calculate the upstream influence source of the water system and the downstream diffusion area of the water system includes the following steps: S1. The platform layer reads the real-time water system data of each water system. When the real-time water system data of a certain water system is greater than the water system risk threshold, it determines that the water system is an abnormal water system; Real-time water system data includes water volume data and water quality data ; The water system risk thresholds include corresponding water volume risk thresholds and water quality risk thresholds; If the water volume data is greater than the water volume risk threshold or the water quality data is greater than the water quality risk threshold, then it is determined that the water system is an abnormal water system; S2. The platform layer retrieves the water volume impact coefficient and the water volume impact delay coefficient from the water volume correlation coefficient model, and retrieves the water quality impact coefficient and the water quality impact delay coefficient from the water quality correlation coefficient model; S3. The platform layer screens the candidate upstream water system i and traces back the upstream water system data. If the upstream water system data meets the error condition, it locates the upstream influence source; S4. The platform layer collects the water flow propagation speed of the corresponding water system , and obtains the duration of water quality anomaly with the same water quality problem from the historical water system data ; S5. Downstream diffusion distance of platform layer calculation and diffusion area A; Among them, ; ; where W is the average river channel width; S6. The platform layer retrieves all water conservancy facilities in the diffusion area A based on the geographic information data and includes them in the diffusion response list.

5. The water service facility management system based on GIS according to claim 4, wherein The specific steps of S3 include: a1: Set the data backtracking time window ; , where is the detection time point when determining the water system anomaly, is the preset maximum delay time; a2. For the historical water volume data of the candidate upstream water system i , verify whether it meets the following: ; If satisfied, the platform layer marks this water system as a suspected impact source; In the formula, is the water volume influence coefficient; is the preset water volume error tolerance; a3. Meanwhile, for the water quality data of the candidate upstream water system i whether it meets: ; If the condition is met, the platform layer will mark this water system as a suspected impact source; In the formula, is the water quality impact coefficient; is the preset water quality error tolerance; a4. For the candidate water system i that simultaneously meets the conditions of a2 and a3, the platform layer marks it as the upstream influence source and suspiciously marks the water conservancy facilities covered by the water system.

6. The water service facility management system based on GIS according to claim 5, characterized in that, The method for obtaining the candidate upstream water system i includes: Q1. The platform layer generates a water system topology map of each water system based on the geographic information data of the geographic information module; Q2. The platform layer locates the position of the water system determined to be abnormal through the water system topology map and marks it as ; Q3. Retrieve all water systems that satisfy from the water system topology map, and denote them as: ; ; Q4. Calculate the maximum influence distance through the maximum delay time and the average water flow velocity of the abnormal water system , ; In the water system topology diagram of the platform layer, filter the water systems within the maximum influence distance and meeting the requirement that the water flow path reaches to form an effective candidate set of upstream water systems ; Among them, candidate upstream water system \(i\in\) , and .

7. The water service facility management system based on GIS according to claim 4, characterized in that Based on the functions of each water facility in the diffusion response list, the platform layer calculates the ranking scores of each water facility in the diffusion response list through formulas , and sorts them. The formula used is: ; where, is the abnormal marking level of water service facility g; is the importance level of water service facility g; is the spatial distance from water service facility g to the abnormal occurrence point; , and are the corresponding weighting coefficients.

8. A GIS-based water service facility management system according to claim 1, characterized in that, The platform layer counts the warning information of each water service facility, establishes a statistical table of warning information for water service facilities, and the statistical table includes the g number of water service facilities, the number of warning information times and the grade weight scores of each warning information ; And the platform layer obtains the total historical warning information score of each water service facility based on the water service facility warning information statistical table , and the formula used is: ; The platform layer maps the total risk scores of the historical warning information of each water facility to the water system where it is located to obtain the comprehensive risk scores of each water system , and the formula is: ; where is the set of all water facilities corresponding to the k-th water system; The platform layer maps the comprehensive risk score to the water system topology map.

9. A GIS-based water facility management method, characterized in that, This method uses the water conservancy facility management system described in any one of claims 1-8, and this management method includes the following steps: Step 1: The platform layer collects the geographic information data of terrain, water systems, and water conservancy facilities, and collects the attributes and working data of each water conservancy facility; Step 2: Establish a water volume correlation coefficient model and a water quality correlation coefficient model based on the historical water volume data and historical water quality data of each water system, and obtain the water volume impact coefficient , the water quality impact coefficient , the water volume impact delay coefficient and the water quality impact delay coefficient ; Step 3: Based on the historical working data of each water conservancy facility, establish the functional associations between each water conservancy facility; Step 4: The platform layer establishes corresponding working data risk thresholds and water system risk thresholds respectively based on the historical working data of each water service facility and the historical water system data of each water system; Step 5: The platform layer obtains the real-time working data and real-time water system data of water service facilities, and compares them with the corresponding working data risk thresholds and water system risk thresholds respectively; If the real-time working data of a water service facility exceeds the working data risk threshold, an abnormal mark is made for the water service facility; If the real-time water system data exceeds the water system risk threshold, the upstream impact source of the water system and the downstream diffusion area of the water system are calculated based on the water volume correlation coefficient model and the water quality correlation coefficient model, suspicious marks are made for the water service facilities within the impact source area, and all water service facilities within the diffusion area are obtained; Step 6: Based on the abnormal marks or suspicious marks of water service facilities, warning information of corresponding levels is generated and sent to the application layer and the user layer.

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