Small reservoir group safety attention engine system

Abstract

This invention belongs to the technical field of administrative supervision and management in the water conservancy industry, specifically relating to a safety concern engine system for small-scale reservoir clusters. This engine system integrates multi-source data, such as the reservoir dam's own health factor (H) and operating environment factor (E), to construct a forecast system for the reservoir cluster's short- and medium-term safety concern index (Sp). This system then uses the reservoir dispatch factor (D) and real-time monitoring factor (B) to revise the calculation and further provide a real-time dam safety concern index (SDB) evaluation system. The engine integrates a data interaction module, a model-driven module, and an intelligent interaction module. It supports intelligent evaluation, rolling ranking, and safety warnings for reservoir clusters at the 10,000-seat level. It is particularly suitable for safety supervision and control of dams across the entire river basin and joint reservoir dispatch during flood season.

Description

Technical Field

[0001] The present invention belongs to the technical field of administrative supervision and management of water conservancy industry, and specifically relates to a safety attention engine system for a small reservoir group. Background Art

[0002] Small reservoir safety risk forecasts and warnings are usually carried out through regular assessments and real-time monitoring. These two methods have the following shortcomings: both methods judge dam safety based on internal factors of the dam, and do not consider external environmental factors such as reservoir water level, flood peak water level and other dam operating conditions; the regular assessment cycle is generally five years, reviewing the dam's engineering characteristics, engineering geology, structural safety, facility safety, etc., and cannot conduct real-time health evaluation; real-time monitoring is to measure the dam's safety parameters in real time through deformation, infiltration, seepage and other monitoring facilities buried in the dam, which can only assist in judging the immediate condition of the dam, and cannot predict the dam's medium- and short-term risks; for tens of thousands of reservoirs, neither method can provide a comprehensive dynamic ranking of safety indicators, and cannot meet the reservoir group's flood season requirements of advanced forecasting, key prevention and emergency scheduling. Summary of the Invention

[0003] The purpose of the present invention is to provide a small reservoir group safety attention engine system to solve the problems existing in the background technology.

[0004] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a small-scale reservoir group safety attention engine system, which is integrated with a data interaction module, a model driving module and an intelligent interaction module;

[0005] The data interaction module includes an engine-built-in static information library table, a dynamic database table, and an evaluation index library table. The data interaction module is used to obtain dynamic and static data of the reservoir group outside the engine, and uses an interface call method to interact with the regional or river basin reservoir group operation and management platform, business system, and perception system. "Regional or river basin reservoir group operation and management platform, business system, and perception system" are common knowledge. For example, the Hunan Provincial Water Resources Department has built the Hunan Small Reservoir Safety Monitoring and Operation Management Platform, the Hunan River and Lake Management System (including the river chief system, sand mining supervision, water area and coastline, river-related construction projects and other businesses), and the flood situation awareness system.

[0006] The model driving module includes an engine-built-in near-expiry index model (applicable to 7 to 1 day before the target date), a spot index model (applicable within 24 hours of the same day), and a real-time index model (applicable within 1 hour), and uses the dynamic data of the reservoir group to calculate the evaluation indicators of each target dam;

[0007] The intelligent interaction module includes an engine-built-in intelligent supervision unit, an intelligent early warning unit and an intelligent scheduling unit. The intelligent interaction module uses the static data and the evaluation indicators of each target dam to provide intelligent supervision, intelligent early warning and intelligent scheduling services to the outside of the engine.

[0008] Preferably, the engine has a built-in static information database table for storing static information such as the name, type, elevation, width, geological conditions, anti-seepage form of the dam group and the reservoir code, name, administrative division, watershed, water system, and design water level;

[0009] The dynamic database table is used to store the reservoir dam operation data required for engine calculation, all of which adopt international units, including the following operation parameters:

[0010] Y r - Operational age, the number of years from the target reservoir's current dam completion date;

[0011] Y d - Assessment period, the number of years between the last dam safety assessment of the target reservoir and the completion of the dam;

[0012] P m - Monthly inspection scores for target reservoir dams are scored by the reservoir inspection officer based on the standardized management regulations for small reservoir projects in the region where the reservoir group is located. When m=0, it is the daily inspection score;

[0013] F p -The maximum water level of the target reservoir during the forecast period;

[0014] F o - Current water level in front of the dam of the target reservoir;

[0015] F m -The highest historical flood level in front of the dam at which the target reservoir can safely pass the flood season;

[0016] L r - Target reservoir amplitude change in front of the dam within 1 hour;

[0017] L h -The fastest one-hour fluctuation of the water level in front of the dam during the safe operation of the target reservoir;

[0018] I r - Real-time monitoring data from typical monitoring stations at the target reservoir's dam, with deformation monitoring data prioritized for concrete dams and seepage deformation monitoring data for earth-rockfill dams;

[0019] I h -The highest historical safety value of the dam of the target reservoir at the typical monitoring station;

[0020] The evaluation index database table is used to store the reservoir group dam safety assessment data output by the model driving module, which are all dimensionless values ​​and include the following factors and indicators:

[0021] H f -Basic health factors;

[0022] H y -Current annual dam health factor;

[0023] H m -The health factor of the current month, when m=0, it is the health factor of the day;

[0024] E p - Dam safety environmental factors of the target reservoir;

[0025] E o -Real-time safety environment factors of the dam of the target reservoir;

[0026] D r -The real-time dispatching factor of the dam of the target reservoir;

[0027] B r -Real-time monitoring factors of the dam of the target reservoir;

[0028] S p - Medium- to short-term dam safety concern index of the target reservoir;

[0029] S o -Dam immediate attention index of the target reservoir;

[0030] S DB -Real-time dam safety concern index of the target reservoir.

[0031] Preferably, the engine has a built-in expiry index model, which calculates the short- to medium-term safety concern index S of the target dam based on formula (1): p :

[0032] Formula (1)

[0033] The instant index model calculates the instant safety concern index S of the target dam based on formula (2): o :

[0034] Formula (2)

[0035] The real-time index model calculates the real-time safety concern index S of the target dam based on formula (3): DB :

[0036] Formula (3).

[0037] Preferably, the engine has a built-in intelligent supervision unit. The engine automatically detects the health factors, environmental factors, scheduling factors and monitoring factors of each dam in the reservoir group in the evaluation index database table. When a negative number, zero or greater than 1 appears, the corresponding dynamic database table is further checked. If there is an abnormality in the supervision index, statistics and responsibilities are notified by item according to the watershed or administrative jurisdiction, forming a closed loop of supervision and management.

[0038] The intelligent early warning unit's engine automatically detects the impending, immediate, and real-time attention indicators of each dam in the reservoir group in the evaluation index database, and ranks them in two ways: by the nine major river basins in China (the Yangtze River Basin, the Yellow River Basin, the Pearl River Basin, the Haihe River Basin, the Huaihe River Basin, the Songliao River Basin, the Southeast River Basin, the Southwest River Basin, and the Inland River Basin) and by provincial administrative regions, and issues three levels of warnings: "Red-Orange-Yellow";

[0039] The intelligent scheduling unit uses the inverse operation of the engine model driving module to achieve optimized scheduling: for dams with a safety assessment of Class III, the engine uses the lowest single-reservoir safety concern index as the automatic optimization scheduling target during the flood season; for cascade reservoirs with water resources and power generation requirements, the maximum storage water volume under an acceptable safety concern warning is used as the automatic optimization scheduling target during the flood season. In addition, the engine supports manual optimization scheduling.

[0040] The basic prompt rules for abnormal regulatory indicators include: d - Reservoirs older than five years indicate the need for safety assessment; L r , I r 、F o -No value, indicating that the monitoring instrument is malfunctioning; P m - No value indicates that the inspection is not in place, and if it is not within the range of 0 to 1, it indicates that the inspection report is abnormal; H f - is equal to 0.6, it is suggested to remove the danger and strengthen the reinforcement, such as m - less than 0.6, prompting to organize special appraisal as soon as possible; F o -When the water level exceeds the corresponding design level in the static database, a prompt will be given to indicate that the system is operating at an over-design water level. The prompt rules for abnormalities in the above basic regulatory indicators will be gradually expanded as the engine application data accumulates.

[0041] Preferably, for a newly built reservoir dam, the highest historical flood level F in front of the dam for the target reservoir to safely pass the flood season is m The initial value is replaced by the dam design high water level multiplied by the safety factor 0.8, until the highest water level in the history of safe flood season of the newly built dam exceeds the design high water level.

[0042] Preferably, for a newly built reservoir dam, the historical highest safety value I of the typical monitoring station of the target reservoir dam is h The initial value is replaced by the design threshold multiplied by a safety factor of 0.8 until the highest historical safety value of the monitoring station exceeds the design threshold.

[0043] Preferably, the target reservoir dams that are assessed as Class I, Class II, or Class III dams according to the reservoir dam safety assessment guidelines have their corresponding basic health factors H f The values ​​are 0.9, 0.8 and 0.6 respectively.

[0044] Preferably, the medium- and short-term safety concern index S of the target reservoir dam p The initial warning value is 1.2, and the real-time safety concern index of the target reservoir is S DB The initial warning value is 1.5.

[0045] The beneficial effects of the present invention are: this engine system comprehensively considers internal and external influencing factors, integrates weather forecasts with real-time rainfall monitoring and construction situation monitoring, and provides operators with medium-term, immediate and real-time early warning indicators to increase dam safety awareness. It can be used for single reservoir safety scheduling, joint scheduling of river basin reservoir groups and rolling ranking of reservoir safety warnings. It is especially beneficial for 10,000-level reservoir groups or full-basin reservoir group management platforms to achieve advanced forecasting, key prevention and emergency scheduling safety flood standards. In addition, operators can rely on this engine system to manage the overall situation and gain insight into management problems such as lack of safety evaluation, inadequate inspections, and failure of monitoring instruments at the first time. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 Schematic diagram of the engine system architecture and operation flow. DETAILED DESCRIPTION

[0047] The specific implementation of the present invention is described in detail below in conjunction with preferred embodiments.

[0048] like Figure 1 As shown in the figure, a small reservoir group safety attention engine system is integrated with three modules: data interaction module, model driving module and intelligent interaction module:

[0049] Data interaction module

[0050] The engine has built-in static information database tables, dynamic database tables and evaluation index database tables, and uses interface calls to interact with regional or river basin reservoir group operation and management platforms, business systems, and perception systems for data.

[0051] Static database table, used to store static information such as the name, type, elevation, width, geological conditions, anti-seepage form of the reservoir group dam and the reservoir code, name, administrative division, watershed, water system, and design water level.

[0052] Dynamic database tables are used to store reservoir and dam operation data required for engine calculations. All data are in international units and include the following operation parameters:

[0053] Y r- Operational age, the number of years from the target reservoir's current dam completion date;

[0054] Y d - Assessment period, the number of years between the last dam safety assessment of the target reservoir and the completion of the dam;

[0055] P m - Monthly inspection scores for target reservoir dams are scored by the reservoir inspection officer based on the standardized management regulations for small reservoir projects in the region where the reservoir group is located. When m=0, it is the daily inspection score;

[0056] F p -The maximum water level of the target reservoir during the forecast period;

[0057] F o - Current water level in front of the dam of the target reservoir;

[0058] F m - The highest historical flood level in front of the dam that the target reservoir can safely pass through the flood season. For newly built reservoir dams, the initial value is replaced by the dam design high water level multiplied by a safety factor of 0.8, until the highest historical flood level of the newly built dam that can safely pass through the flood season exceeds the design high water level;

[0059] L r - Target reservoir amplitude change in front of the dam within 1 hour;

[0060] L h -The fastest one-hour fluctuation of the water level in front of the dam during the safe operation of the target reservoir;

[0061] I r - Real-time monitoring data from typical monitoring stations at the target reservoir's dam, with deformation monitoring data prioritized for concrete dams and seepage deformation monitoring data for earth-rockfill dams;

[0062] I h -The historical highest safety value of the typical monitoring station for the target reservoir dam. For newly built reservoir dams, its initial value is replaced by the design threshold multiplied by a safety factor of 0.8 until the historical highest safety value of the monitoring station exceeds the design threshold.

[0063] The evaluation index database table is used to store the reservoir group dam safety assessment data output by the model driving module. All of them are dimensionless values, including the following factors and indicators:

[0064] H f -Basic health factors;

[0065] H y -Current annual dam health factor;

[0066] H m -The health factor of the current month, when m=0, it is the health factor of the day;

[0067] E p - Dam safety environmental factors of the target reservoir;

[0068] E o -Real-time safety environment factors of the dam of the target reservoir;

[0069] D r -The real-time dispatching factor of the dam of the target reservoir;

[0070] B r -Real-time monitoring factors of the dam of the target reservoir;

[0071] S p - Medium- to short-term dam safety concern index of the target reservoir;

[0072] S o -Dam immediate attention index of the target reservoir;

[0073] S DB -Real-time dam safety concern index of the target reservoir;

[0074] Model-driven module

[0075] The engine has built-in near-expiry index models (1 to 7 days) (applicable to 7 to 1 day before the target date), spot index models (within 24 hours) (applicable to within 24 hours of the same day) and real-time index models (within 1 hour) (applicable to within 1 hour). It uses regular inspections, automatic encryption calculations and manual adjustments to drive the model to calculate the evaluation indicators of each target dam.

[0076] The near-term index model calculates the short-term and medium-term safety concern index S of the target dam based on formula (1) p :

[0077] Formula (1)

[0078] The specific calculation process is as follows: Determine the basic health factor H according to the most recent safety assessment level of the target dam f ; According to the dam safety assessment period Y d 、Operation period Y r and basic health factor H f , use the interpolation method to calculate the current year's dam health factor H y , multiplied by the monthly inspection score P m Calculate the dam's current monthly health factor H m ; Calculate the maximum water level F of the target reservoir during the forecast period using the hydrological model based on the medium- and short-term weather forecast p , and the highest historical flood level F in front of the dam where the target dam can safely pass the flood season m Compared with the target dam safety environment factor E in the forecast period, p; Use the safety environment factor E of the target dam p Divide by the current month's dam health factor H m , calculate the short- to medium-term safety concern index S of the target dam p .

[0079] Further: The target reservoir dams with the most recent safety assessment grades of Class I, Class II, and Class III have corresponding basic health factors H f The values ​​are 0.9, 0.8 and 0.6 respectively; the above short-term and medium-term weather forecast can be used with 7-day, 3-day and 1-day weather forecasts, and the corresponding 7-day, 3-day and 1-day safety concern index S of the target dam is calculated. 7 、S 3 and S 1 The above hydrological model is preferably a distributed VIC model or a semi-distributed TOPMODEL model suitable for large-scale calculations;

[0080] The immediate index model calculates the immediate safety concern index S of the target dam based on formula (2) o :

[0081] Formula (2)

[0082] The real-time index model calculates the real-time safety concern index S of the target dam based on formula (3): DB :

[0083] Formula (3)

[0084] The specific calculation process of the spot index model and the real-time index model is as follows: the current water level in front of the target dam F o Replace the highest water level of the reservoir F p Substitute the above model and calculate the real-time safety environment factor E of the target dam in turn o and real-time attention index S o ; Use the target dam’s water level fluctuation L in 1 hour r Divide by the fastest one-hour fluctuation of the water level in front of the target dam during safe operation history, L h , calculate the real-time dispatch factor D of the target dam r ; Using real-time monitoring data from typical monitoring stations of the target dam r , divided by the historical highest safety value I of the monitoring site h , calculate the target dam real-time monitoring factor B r ; Use real-time attention index S o , real-time scheduling factor D r , Real-time monitoring of factor B r The product of the three is used to calculate the real-time safety concern index S of the target dam. DB .

[0085] (3) Intelligent interaction module

[0086] It includes an intelligent supervision unit, an intelligent early warning unit and an intelligent dispatching unit built into the engine, and interacts with reservoir inspection personnel, technical personnel, administrative personnel and supervisors at all levels of provinces, cities, counties and river basins through digital billboards, GIS platforms and mobile apps.

[0087] The intelligent supervision unit engine automatically detects the health factors, environmental factors, scheduling factors and monitoring factors of each dam in the evaluation index database. When a negative number, zero or greater than 1 appears, it further checks the corresponding dynamic database table. If there is an abnormality in the supervision index, statistics and notifications are made by basin or administrative jurisdiction, forming a closed loop of supervision and management. The basic prompt rules for abnormal supervision indicators include: d - Reservoirs older than five years indicate the need for safety assessment; L r , I r 、F o -No value, indicating that the monitoring instrument is malfunctioning; P m - No value indicates that the inspection is not in place, and if it is not within the range of 0 to 1, it indicates that the inspection report is abnormal; H f - is equal to 0.6, it is suggested to remove the danger and strengthen the reinforcement, such as m - less than 0.6, prompting to organize special appraisal as soon as possible; F o - When the water level exceeds the corresponding design level in the static database, an over-design water level operation prompt will be issued. The prompt rules for abnormalities in the above basic regulatory indicators will be gradually expanded as the engine application data accumulates.

[0088] The intelligent early warning unit engine automatically detects the impending, immediate and real-time attention indicators of each dam in the evaluation index database, and sorts them by the nine major river basins in the country (Yangtze River Basin, Yellow River Basin, Pearl River Basin, Haihe River Basin, Huaihe River Basin, Songliao River Basin, Southeast River Basin, Southwest River Basin, Inland River Basin) and provincial administrative regions, and issues three-level warnings of "red-orange-yellow" in a graded manner. The medium- and short-term safety attention index S p The initial warning value is 1.2, and the real-time safety concern index of the target reservoir is S DB The initial warning value is 1.5.

[0089] Furthermore, the 92,000 small reservoirs in the country can be divided into 9 forecast areas according to the nine major river basins in the country. Each 10,000-level forecast area has 10 1,000-level forecast areas, and each 1,000-level forecast area has 10 100-level forecast areas. The medium- and short-term safety concern index S of the reservoirs in the entire area can be calculated on a rolling basis during the flood season. p and real-time safety concern index S DBRanked from largest to smallest, the top 111 reservoirs are selected for attention, namely one "one in 10,000", ten "one in 1,000", and 100 "one in 100" risk reservoirs. The current global low dam failure standard is one in 10,000. Historical dam failures vary in temporal and spatial distribution across different seasons and regions, so the highest risk can be controlled at 3 / 10,000, 3 / 1,000, and 3% respectively. This means the top 333 reservoirs are selected for key attention. On the GIS watershed map, blue circles with a scale of "large-medium-small" are used to indicate the 10,000, 1,000, and 100% risk levels. If the three warning levels (red-orange-yellow) have been reached, the corresponding warning color will be filled in the blue circle.

[0090] The intelligent scheduling unit uses the inverse operation of the engine model-driven module to achieve optimized scheduling: for dams with a safety assessment of Class III, the engine automatically optimizes scheduling during the flood season with the lowest single-reservoir safety concern index; for cascade reservoirs with water resources and power generation requirements, the engine automatically optimizes scheduling during the flood season with the maximum storage water volume under an acceptable safety concern warning. In addition, the engine supports manual optimization scheduling.

[0091] Furthermore, for the same reservoir, restricted operation and pre-discharge flood-prepared scheduling methods can be adopted to reduce risks; for cascade reservoirs in the same basin, the short-term and medium-term safety concern index S of upstream and downstream reservoirs can be adjusted by using the joint scheduling method of the reservoir group. p The distribution of target values ​​means raising the water level by intercepting and storing flood water in upstream safe reservoirs, lowering the maximum water level in downstream dangerous reservoirs, balancing the temporal and spatial risks of the entire river basin, and meeting the overall flood safety standards.

[0092] Example 1: There are four small reservoirs in a river basin. Heavy rain is forecasted in the next seven days. The calculation results of this engine system are shown in the following table:

[0093]

[0094] (1) Reservoir 2 is a newly built dam. The design water level of 24.7 meters multiplied by 0.8 is used as the historical highest flood level for evaluation, that is, 19.76 meters. The flood level is expected to be 22.2 meters after 7 days, and the safety concern index is 1.38, which exceeds the initial warning value of 1.2. The new reservoir adopts restrictive measures to timely lower the water level to 19 meters. After draining water to the downstream reservoir 3, the 7-day safety concern index of reservoir 2 is reduced to 1.15, which meets the flood requirements.

[0095] (2) Reservoir 4 is located downstream of Reservoir 3 and has been under construction for a long time. It is rated as a Class III dam with a 7-day safety threshold of 1.92 and a real-time attention level of 1.6, which is relatively dangerous. Reservoir 3 is a concrete dam and is rated as a Class I dam. It uses the horizontal deformation monitoring value as the monitoring factor, with a 7-day attention level of 1.08 and a real-time attention level of 0.88, which is extremely safe. To balance the load, Reservoir 3 intercepts the water, and the real-time water level rises by 5 meters. The 7-day safety attention level increases from 1.08 to 1.15, and the safety risk does not increase significantly. Reservoir 4 pre-discharges, and the real-time water level drops by 7 meters. The safety attention level after 7 days decreases from 1.92 to 1.41, and the safety risk is greatly reduced. However, it still requires high attention during the flood season and strengthens on-duty. It is recommended to remove hazards and reinforce it or downgrade it for scrapping.

[0096] It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the scope of protection of the present invention.

Claims

1. A small reservoir group safety attention engine system, characterized by: It is integrated by data interaction module, model driving module and intelligent interaction module; The data interaction module includes a static information library table, a dynamic database table, and an evaluation index library table built into the engine. The data interaction module is used to obtain dynamic and static data of the reservoir group outside the engine, and uses an interface call method to interact with the regional or river basin reservoir group operation management platform, business system, and perception system for data; The model driving module includes an engine built-in impending index model, a spot index model and a real-time index model, and uses the reservoir group dynamic data to calculate the evaluation index of each target dam; The intelligent interaction module includes an intelligent supervision unit, an intelligent early warning unit and an intelligent scheduling unit built into the engine. The intelligent interaction module uses the static data and the evaluation indicators of each target dam to provide intelligent supervision, intelligent early warning and intelligent scheduling services to the outside of the engine; The engine has a built-in static information database table for storing static information on the dam group, including name, type, elevation, width, geological conditions, anti-seepage form, and reservoir code, name, administrative division, watershed, water system, and design water level; The dynamic database table is used to store the reservoir dam operation data required for engine calculation, all of which adopt international units, including the following operation parameters: Y r - Operational age, the number of years from the target reservoir's current dam completion date; Y d - Assessment period, the number of years between the last dam safety assessment of the target reservoir and the completion of the dam; P m - Monthly inspection scores for target reservoir dams are scored by the reservoir inspection officer based on the standardized management regulations for small reservoir projects in the region where the reservoir group is located. When m=0, it is the daily inspection score; F p -The maximum water level of the target reservoir during the forecast period; F o - Current water level in front of the dam of the target reservoir; F m -The highest historical flood level in front of the dam at which the target reservoir can safely pass the flood season; L r - Target reservoir amplitude change in front of the dam within 1 hour; L h -The fastest one-hour fluctuation of the water level in front of the dam during the safe operation of the target reservoir; I r - Real-time monitoring data from typical monitoring stations at the target reservoir's dam, with deformation monitoring data prioritized for concrete dams and seepage deformation monitoring data for earth-rockfill dams; I h -The highest historical safety value of the dam of the target reservoir at the typical monitoring station; The evaluation index database table is used to store the reservoir group dam safety assessment data output by the model driving module, which are all dimensionless values ​​and include the following factors and indicators: H f - Basic health factor; the target reservoir dam is assessed as a Class I dam, Class II dam, or Class III dam according to the Reservoir Dam Safety Assessment Guidelines, and its corresponding basic health factor H f The values ​​are 0.9, 0.8 and 0.6 respectively; H y -Current annual dam health factor; H m -The health factor of the current month, when m=0, it is the health factor of the day; E p - Dam safety environmental factors of the target reservoir; E o -Real-time safety environment factors of the dam of the target reservoir; D r -The real-time dispatching factor of the dam of the target reservoir; B r -Real-time monitoring factors of the dam of the target reservoir; S p - Medium- to short-term dam safety concern index of the target reservoir; S o -Dam immediate attention index of the target reservoir; S DB -Real-time dam safety concern index of the target reservoir; The engine has a built-in expiration index model, which calculates the short-term and medium-term safety concern index S of the target dam based on formula (1): p : Formula (1) The instant index model calculates the instant safety concern index S of the target dam based on formula (2): o : Formula (2) The real-time index model calculates the real-time safety concern index S of the target dam based on formula (3): DB : Formula (3); The engine has a built-in intelligent supervision unit. The engine automatically detects the health factors, environmental factors, scheduling factors and monitoring factors of each dam in the reservoir group in the evaluation index database. When a negative number, zero or greater than 1 appears, the corresponding dynamic database table is further checked. If there is any abnormality in the supervision indicators, statistics and responsibilities are notified by basin or administrative jurisdiction, forming a closed loop of supervision and management. The intelligent early warning unit's engine automatically detects the impending, immediate, and real-time attention indicators of each dam in the reservoir group in the evaluation index database, sorts them by the nine major river basins and provincial administrative regions, and issues three-level warnings of "red-orange-yellow"; The intelligent scheduling unit uses the inverse operation of the engine model driving module to achieve optimized scheduling: for dams with safety assessments of Class III, the engine uses the lowest single-reservoir safety concern index as the automatic optimization scheduling target during the flood season; for cascade reservoirs with water resources and power generation requirements, the maximum storage water volume under an acceptable safety concern warning is used as the automatic optimization scheduling target during the flood season. The engine supports manual optimization scheduling.

2. The small reservoir group safety attention engine system according to claim 1 is characterized by: The basic prompt rules for abnormal regulatory indicators include: d - Reservoirs older than five years indicate the need for safety assessment; L r , I r 、F o -No value, indicating that the monitoring instrument is malfunctioning; P m - No value indicates that the inspection is not in place, and if it is not within the range of 0 to 1, it indicates that the inspection report is abnormal; H f - is equal to 0.6, it is suggested to remove the danger and strengthen the reinforcement, such as m - less than 0.6, prompting to organize special appraisal as soon as possible; F o -When the corresponding design water level in the static database is exceeded, an over-design water level operation prompt will be issued; the basic prompt rules for abnormal regulatory indicators will be gradually expanded as the engine application data accumulates.

3. The small reservoir group safety attention engine system according to claim 1 is characterized by: For newly built reservoirs and dams, the highest historical flood level F in front of the dam for the target reservoir to safely pass the flood season is m The initial value is replaced by the dam design high water level multiplied by the safety factor 0.8, until the highest water level in the history of safe flood season of the newly built dam exceeds the design high water level.

4. The small reservoir group safety attention engine system according to claim 1 is characterized by: For newly built reservoir dams, the historical highest safety value I of the typical monitoring station of the target reservoir dam is h The initial value is replaced by the design threshold multiplied by a safety factor of 0.8 until the highest historical safety value of the monitoring station exceeds the design threshold.

5. The small reservoir group safety attention engine system according to claim 1 is characterized by: The medium- and short-term safety concern index S of the target reservoir's dam p The initial warning value is 1.2, and the real-time safety concern index of the target reservoir is S DB The initial warning value is 1.5.

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