A virtual-real twin preplan driven interactive decision method for flood defense

Abstract

The application provides a flood defense interactive decision method driven by virtual-real twin contingency plans, comprising the following steps: analyzing a flood control situation of a basin based on a flood control scene, and judging whether there is a flood hidden danger; if not, a normal deduction state is executed; if yes, a real-time mutual feedback deduction state is executed. The application innovatively proposes a real-time mutual feedback deduction of "reality-scene-contingency", through a time progression mode, combining the reality scene of the current situation of each device detection, model deduction of each level hydropower station, flood control section, reservoir and real-time water and rain weather, using the deduction scene of water and rain weather forecast data, dispatching scheme and flood control situation analysis, to generate a dispatching scheme which is verified by hydrodynamic simulation, has good effect risk evaluation, and meets the standard of flood control effect.

Description

Technical Field

[0001] This invention relates to the field of flood defense and emergency management technology, specifically to a flood defense interactive decision-making method driven by virtual and real twin plans. Background Technology

[0002] Floods are among the most common and destructive natural disasters globally. Traditional flood emergency management relies primarily on post-disaster responses; however, this reactive approach often fails to effectively mitigate losses. Furthermore, traditional flood defense decision-making methods largely depend on empirical judgment and historical data, which presents certain limitations.

[0003] As the number of water projects under joint dispatch and operation plans increases, the scope of water conservancy dispatch has gradually extended from the upstream to the middle and upper reaches of the main stream and tributaries; the dispatch objects have gradually expanded from reservoir groups to various types of water projects such as drainage pumping stations, flood storage and detention areas, and water diversion projects; and the dispatch time has extended from flood season dispatch to the entire process of pre-flood drawdown, flood season flood control, post-flood water storage, year-round water supply, and emergency response. Flood simulations are becoming increasingly complex, dispatch decisions are becoming more refined, and the demand for real-time dispatch feedback systems is becoming increasingly strong.

[0004] However, the integration and automation of flood simulation systems are currently low, and the human-computer interaction lacks humanization, which limits the ability to respond quickly to floods. Moreover, most systems are based on numerical models such as hydrology and hydrodynamics, which involve huge amounts of data. The formulation of real-time forecasting and scheduling schemes suffers from poor timeliness. Using flow numerical visualization technology to achieve real-time high-speed simulation of floods still presents a huge challenge. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a flood defense interactive decision-making method driven by virtual and real twin plans, which can effectively solve the above problems.

[0006] The technical solution adopted in this invention is as follows:

[0007] This invention provides a flood defense interactive decision-making method driven by virtual and real twin plans, comprising the following steps:

[0008] Step S1: Obtain the hydrological characteristics of the study watershed; determine the flood control cross-section based on the hydrological characteristics of the study watershed; set the initial value of the flood control simulation period S of the study watershed to 1; set the scheduling scheme D corresponding to the flood control simulation period S. s The initial value is empty; obtain the hydrological characteristics of each flood control section at the beginning of the flood control simulation period S to form the flood control scenario Scene0;

[0009] Step S2: Analyze the flood control situation of the basin based on the flood control scenario Scene0, and determine whether there is a potential flood hazard; if not, proceed to step S3; if yes, proceed to step S4.

[0010] Step S3, enter the normal simulation state:

[0011] Step S3.1: Based on the flood control scenario Scene0 and the conventional simulation state scheduling target S0, formulate the conventional simulation scheduling scheme D. S，0 ;

[0012] Step S3.2, based on the conventional simulation scheduling scheme D S，0 Perform routine state simulations of flood evolution and construct the routine simulation scheduling scheme D to execute the simulation. S，0 The subsequent flood control scenario Scene'0 is used to analyze the flood control situation in the basin and determine whether there is a potential flood hazard; if not, the flood control scenario Scene'0 is updated using the flood control scenario Scene'0; let scheduling scheme D... S =Conventional simulation scheduling scheme D S，0 S = S + 1, return to step S3.1; if so, proceed to step S4;

[0013] Step S4, enter the real-time mutual feedback simulation state:

[0014] Step S4.1: Let the variable i = 1 for the number of real-time mutual feedback simulations; determine the scheduling target S for the i-th real-time mutual feedback simulation. i ;

[0015] Step S4.2, based on the flood control scenario Scene0 and the scheduling target S during the i-th real-time feedback simulation. i M scheduling plans corresponding to the flood scheduling simulation period S at the i-th real-time feedback simulation are formulated, denoted as: D S，i，k k = 1, 2, ..., M;

[0016] Step S4.3, based on each scheduling plan D S，i，k Real-time feedback simulations of flood evolution are conducted to evaluate the effectiveness and risks of various dispatch plans, and the optimal dispatch plan is selected as the flood defense scheme D from among them. S，i ;

[0017] Step S4.4, construct and implement the flood defense scheme D S，i Post-flood control scene i Based on the flood control scenario i Conduct a flood control situation analysis of the watershed and determine whether there are any potential flood risks; if not, then adopt a flood control scenario.i Update the flood control scenario Scene0; Instruct the scheduling scheme D S =D S，i If S = S + 1, return to step S3.1; otherwise, proceed to step S4.5.

[0018] Step S4.5, regarding the flood defense scheme D S，i Conduct an effectiveness evaluation to determine whether the flood defense plan D should be implemented. S，i Does the subsequent flood control effect meet the expected flood control objectives? If so, then adopt the flood control scenario. i Update the flood control scene Scene0; let D S =D S，i If S = S + 1, return to step S4.1; otherwise, proceed to step S4.6.

[0019] Step S4.6, based on the scheduling target S during the i-th real-time mutual feedback simulation. i Determine the scheduling target for the (i+1)th real-time mutual feedback simulation; let i = i+1, and return to step S4.2.

[0020] Preferably, in step S1, the hydrological characteristics of each flood control section at the beginning of the flood control simulation period S are based on the forecast hydrological characteristics of each flood control section, including the flow and water level of the flood control section.

[0021] Preferably, in step S2, the basin flood control situation is analyzed based on the flood control scenario Scene0, and it is determined whether there are potential flood risks. Specifically:

[0022] Read the flow rate and water level of each flood control section in the flood control scenario Scene0, and determine whether the following judgment formula is satisfied:

[0023]

[0024] Among them: Q j，t Q represents the flow rate of flood control section j during time period t of the flood control simulation cycle S; t = 1, 2, ..., T, where T represents the number of time periods in the flood control simulation cycle S; j = 1, 2, ..., m, where m represents the number of flood control sections in the study basin; warn_j Z represents the warning flow rate at flood control section j; j，t Z represents the water level at flood control section j during time period t of the flood control simulation cycle S; warn_j The warning water level represents the flood control section j;

[0025] If the discrimination formula is satisfied, there is no flood risk; otherwise, there is a flood risk.

[0026] Preferably, in step S3.1, based on the flood control scenario Scene0 and the conventional simulation state scheduling target S0, a conventional simulation scheduling scheme D is formulated. S，0 Specifically:

[0027] Based on the obtained flood control simulation period S, starting time t0, the water and rainfall forecast data, and the current time t * Based on the measured data of watershed rainfall and engineering conditions, the flood control scenario Scene0 and the conventional simulation state scheduling objective S0 are used to formulate a conventional simulation scheduling scheme D. S，0 .

[0028] Preferably, functions f1, f2, f3, and f4 are set:

[0029] f1 is the function that minimizes water shortage losses in the watershed;

[0030]

[0031] W t D represents the water shortage in the water supply area during the flood control simulation period S in time period t; t P represents the water demand of the water supply area during time period t in the flood control simulation cycle. t The water supply of all hydropower stations during the flood control simulation period S in time period t;

[0032] f2 is the objective function for ecological water volume in the river channel;

[0033]

[0034] W ex (t) represents the amount of water exceeding the ecological flow threshold during time period t in the flood control simulation cycle S; Q out_l，t To study the outflow of the first-stage hydropower station in the basin during time period t; K min (t) represents the lower bound of the ecological flow threshold range for the watershed during the study period t; K max (t) represents the upper bound of the ecological flow threshold range for the watershed during the study period t;

[0035] f3 is the objective function that maximizes power generation efficiency;

[0036]

[0037] Where: N l，t To study the average output of the l-th stage hydropower station in the basin during time period t, l = 1, 2, ..., n, where n is the total number of hydropower stations in the basin; Δt is the number of hours included in time period t; k is the output coefficient; H l，t To study the head of the first-stage hydropower station in the basin during time period t; Z up_l，t To study the water level of the first-stage hydropower station in the basin during time period t; Zdown_l，t To study the downstream tailrace water level of the first-stage hydropower station in the basin during time period t; H min_l and H max_l Q represents the minimum and maximum water levels of the first-level hydropower station when considering flood risks; min_l and Q max_l , which are the minimum and maximum outflow values ​​of the Class I hydropower station when considering flood risks;

[0038]

[0039] Where: a l b j c j These are the weights for the first objective, the second objective, and the third objective, respectively.

[0040] This represents the highest operating water level of the first-level hydropower station during the flood control simulation cycle S.

[0041] and These are the maximum and minimum allowable water levels for the Class I hydropower station during the flood control simulation period S, respectively.

[0042] Q j，t The flow rate at flood control section j during time period t of the flood control simulation cycle S; Q min_j ≤Q j，t ≤Q max_j Q min_j and Q max_j These are the lower and upper limits of the allowable flow rate at the flood control section j, respectively.

[0043] For the excess flow at the flood control section j of the hydropower station after regulation and storage in time period t, when Q j，t Not exceeding the upper limit of the overcurrent flow rate Q max_j hour, =0; when Q j，t Exceeding the upper limit of the overcurrent flow Q max_j hour, Q j，t，ce The excess flow at the flood control section j during time period t, without regulation by the hydropower station;

[0044] The conventional simulation state scheduling target S0 is: S0 = {f1, f2, f3};

[0045] The scheduling target S during the i-th real-time mutual feedback simulation i ={f1, f2, f3, f4}.

[0046] Preferably, setting boundary constraints includes:

[0047] (1) Water balance equation: V l，t =V l，t-1 +(Q in_l，t-1 -Q out_l , -1 )Δt

[0048] Where: V l，t V represents the reservoir capacity of the first-level hydropower station during time period t; l，t-1 The reservoir capacity of the first-level hydropower station in time period t-1;

[0049] Q in_l，t-1 and Q out_l，t-1 , , are the inflow and outflow of the L-th hydropower station in time period t-1, respectively; Δt is the number of hours contained in time period t;

[0050] (2) Tailwater function of the hydropower station: Z down_l，t =h l (Q out_l，t )

[0051] Among them: Z down_l，t The downstream tailrace water level of the L-th stage hydropower station at time period t; h l (Q out_l，t ) is the relationship function between the outflow from the reservoir and the downstream tailrace level of the l-th hydropower station in time period t;

[0052] (3) Hydropower station water level-storage capacity function:

[0053] Among them: Z up_l，t The water level of the L-th stage hydroelectric power station during time period t; This is the function relating water level and reservoir capacity for the first-level hydropower station.

[0054] (4) Head equation: H l，t =Z up_l，t -Z down_l，t

[0055] Among them: H l，t The head of the first-level hydroelectric power station in time period t;

[0056] (5)Output equation: N l，t =kQ out_l，t H l，t

[0057] Where: N l，t Let Q be the average output of the l-th stage hydropower station during time period t, where l = 1, 2, ..., n, and n is the total number of hydropower stations in the study basin; k is the output coefficient; Q out_l，t The outflow from the reservoir of the L-level hydropower station during time period t;

[0058] The conventional deduction state scheduling objective S0 = {f1, f3, f3} and the boundary constraints form the conventional deduction state scheduling model;

[0059] The scheduling target S during the i-th real-time mutual feedback simulation i ={f1, f2, f3, f4} and the boundary constraints form a real-time feedback deduction state scheduling model.

[0060] Preferably, the scheduling scheme based on the conventional deduction scheme D S，0 Perform routine state simulations of flood evolution and construct the routine simulation scheduling scheme D to execute the simulation. S，0 The subsequent flood control scenario, Scene'0, is as follows:

[0061] Based on the conventional deduction and scheduling scheme D S，0 Using the outflow from the reservoir at each level of hydropower station in time period t as the decision variable, the conventional deductive state scheduling model is solved to obtain the result when executing the conventional deductive scheduling scheme D. S，0 Subsequently, the outflow Q of each hydropower station in the basin during the time interval t of the flood control simulation period S was studied. out_l，t ;

[0062] Based on the current time t * The study uses measured data of watershed hydrology, rainfall, and engineering conditions, as well as the time-by-time outflow Q of each hydropower station in the watershed during the flood control simulation period S. out_l，t Flood simulations were performed on the study basin to obtain the flow rate and water level at each flood control section, and then the conventional simulation scheduling scheme D was executed. S，0 Scene 0, depicting the flood control scenario.

[0063] Preferably, the method based on each scheduling plan D S，i，k Real-time feedback simulations of flood evolution are conducted to evaluate the effectiveness and risks of various dispatch plans, specifically:

[0064] Based on the aforementioned scheduling plan D S，i，k Using the outflow from the reservoir at each level of hydropower station in time period t as the decision variable, the real-time feedback simulation state scheduling model is solved to obtain the results when the scheduling plan D is executed. S，i，k Subsequently, the outflow Q of each hydropower station in the basin during the time interval t of the flood control simulation period S was studied. out_l，t ;

[0065] Based on the current time t * The study uses measured data of watershed hydrology, rainfall, and engineering conditions, as well as the time-by-time outflow Q of each hydropower station in the watershed during the flood control simulation period S. out_l，t Flood simulation was performed on the study basin to obtain the flow rate and water level at each flood control section;

[0066] The effectiveness and risks of the aforementioned scheduling plan are evaluated based on the flow rate and water level at each flood control section.

[0067] Preferably, in step S4.5, the following discrimination formula is used to determine the flood defense scheme D. S，i Conduct an effectiveness evaluation to determine whether the flood defense plan D should be implemented. S，i Does the subsequent flood control effect meet the expected flood control objectives?

[0068]

[0069] Among them: Q exp_j The expected maximum flow rate at flood control section j; Z exp_j The expected highest water level at flood control section j;

[0070] If the discrimination formula is satisfied, the flood control effect meets the expected flood control target; otherwise, it does not meet the expected flood control target.

[0071] The flood defense interactive decision-making method driven by virtual-real twin plans provided by this invention has the following advantages:

[0072] This invention innovatively proposes a real-time feedback simulation of "reality-scenario-contingency plan". By using a time-progressive approach, it combines the current status of various hydropower stations, flood control sections, reservoirs, etc., at all levels, as detected by various equipment in the basin and derived by the model with the real-time water and rainfall conditions. Using water and rainfall forecast data, scheduling plans, and flood situation analysis, it generates a scheduling plan that has been verified by hydrodynamic simulation, has good effect and risk assessment, and meets the flood control standards. Attached Figure Description

[0073] Figure 1 A flowchart of a flood defense interactive decision-making method driven by virtual-real twin contingency plans provided by the present invention;

[0074] Figure 2 A diagram illustrating one implementation of a flood defense interactive decision-making method driven by virtual-real twin contingency plans provided by the present invention;

[0075] Figure 3 The real-time feedback flowchart of the flood defense interactive decision-making method provided by the present invention;

[0076] Figure 4 A diagram illustrating the nested scheduling relationships at different time scales in the flood defense interactive decision-making method provided by this invention.

[0077] Figure 5 This is a diagram illustrating the flood control and operation process of the Three Gorges Reservoir in 2020. Detailed Implementation

[0078] To make the technical problems solved, the technical solutions, and the beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the invention.

[0079] This invention is applied to the field of digital twin technology, and more specifically, it is a real-time feedback contingency plan simulation technology that connects virtual and real mapping, namely "reality-scenario-contingency plan". Subsequently, a demonstration system for simulation of basin-wide flood "virtual and real twin" scenarios is established using this method.

[0080] See Figure 1 This invention provides a flood defense interactive decision-making method driven by virtual and real twin plans, comprising the following steps:

[0081] Step S1: Obtain the hydrological characteristics of the study watershed; determine the flood control cross-section based on the hydrological characteristics of the study watershed; set the initial value of the flood control simulation period S of the study watershed to 1; set the scheduling scheme D corresponding to the flood control simulation period S. S The initial value is empty; obtain the hydrological characteristics of each flood control section at the beginning of the flood control simulation period S to form the flood control scenario Scene0;

[0082] In this step, the hydrological characteristics of each flood control section at the beginning of the flood control simulation period S are based on the predicted hydrological characteristics of each flood control section, including but not limited to the flow and water level of the flood control section.

[0083] In practical implementation, after obtaining the hydrological characteristics of the study basin, a realistic base map of the basin can be drawn to obtain a virtual model of the basin; dynamic monitoring and prediction are then performed in conjunction with real-time data, including: real-time monitoring of the current time t. * The study uses measured water and rainfall data from the basin to predict water and rainfall forecasts at the start time t0 of the flood control simulation cycle S in real time. This allows for the acquisition of hydrological characteristics of each flood control section at the beginning of the flood control simulation cycle S, including but not limited to the flow and water level of the flood control section, forming a flood control scenario Scene0. This enables the connection between the real-time water and rainfall data and the flood control scenario.

[0084] Step S2: Analyze the flood control situation of the basin based on the flood control scenario Scene0, and determine whether there is a potential flood hazard; if not, proceed to step S3; if yes, proceed to step S4.

[0085] In this step, based on the flood control scenario Scene0, a basin flood control situation analysis is performed, and it is determined whether there are potential flood risks. Specifically:

[0086] Read the flow rate and water level of each flood control section in the flood control scenario Scene0, and determine whether the following judgment formula is satisfied:

[0087]

[0088] Among them: Q j，t Q represents the flow rate of flood control section j during time period t of the flood control simulation cycle S; t = 1, 2, ..., T, where T represents the number of time periods in the flood control simulation cycle S; j = 1, 2, ..., m, where m represents the number of flood control sections in the study basin; warn_j Z represents the warning flow rate at flood control section j; j，t Z represents the water level at flood control section j during time period t of the flood control simulation cycle S; warn_j The warning water level represents the flood control section j;

[0089] If the discrimination formula is satisfied, there is no flood risk; otherwise, there is a flood risk.

[0090] Step S3, enter the normal simulation state:

[0091] Step S3.1: Based on the flood control scenario Scene0 and the conventional simulation state scheduling target S0, formulate the conventional simulation scheduling scheme D. S，0 ;

[0092] This step specifically involves: based on the obtained flood control and dispatch simulation period S's initial time t0 hydrological and rainfall forecast data, the current time t... * Based on the measured data of watershed rainfall and engineering conditions, the flood control scenario Scene0 and the conventional simulation state scheduling objective S0 are used to formulate a conventional simulation scheduling scheme D. S，0 This step establishes the connection between "reality, scenario, and contingency plan / scheduling scheme".

[0093] Step S3.2, based on the conventional simulation scheduling scheme D S，0 Perform routine state simulations of flood evolution and construct the routine simulation scheduling scheme D to execute the simulation. S，0 The subsequent flood control scenario Scene'0 is used to analyze the flood control situation in the basin and determine whether there is a potential flood hazard; if not, the flood control scenario Scene'0 is updated using the flood control scenario Scene'0; let scheduling scheme D... S =Conventional simulation scheduling scheme D S，0 S = S + 1, return to step S3.1; if so, proceed to step S4;

[0094] Step S4, enter the real-time mutual feedback simulation state:

[0095] Step S4.1: Let the variable i = 1 for the number of real-time mutual feedback simulations; determine the scheduling target S for the i-th real-time mutual feedback simulation. i ;

[0096] Step S4.2, based on the flood control scenario Ssene0 and the scheduling target S during the i-th real-time feedback simulation. i M scheduling plans corresponding to the flood scheduling simulation period S at the i-th real-time feedback simulation are formulated, denoted as: D S，i，k k = 1, 2, ..., M;

[0097] Step S4.3, based on each scheduling plan D S，i，k Real-time feedback simulations of flood evolution are conducted to evaluate the effectiveness and risks of various dispatch plans, and the optimal dispatch plan is selected as the flood defense scheme D from among them. S，i ;

[0098] Step S4.4, construct and implement the flood defense scheme D S，i Post-flood control scene i Based on the flood control scenario i Conduct a flood control situation analysis of the watershed and determine whether there are any potential flood risks; if not, then adopt a flood control scenario. i Update the flood control scenario Scene0; Instruct the scheduling scheme D S =D S，i If S = S + 1, return to step S3.1; otherwise, proceed to step S4.5.

[0099] Step S4.5, regarding the flood defense scheme D S，i Conduct an effectiveness evaluation to determine whether the flood defense plan D should be implemented. S，i Does the subsequent flood control effect meet the expected flood control objectives? If so, then adopt the flood control scenario. i Update the flood control scene Scene0; let D S =D S，i If S = S + 1, return to step S4.1; otherwise, proceed to step S4.6.

[0100] Step S4.6, based on the scheduling target S during the i-th real-time mutual feedback simulation. i Determine the scheduling target for the (i+1)th real-time mutual feedback simulation; let i = i+1, and return to step S4.2.

[0101] In step S4.5, the following discrimination formula is used to determine the flood defense scheme D. S，i Conduct an effectiveness evaluation to determine whether the flood defense plan D should be implemented. S，i Does the subsequent flood control effect meet the expected flood control objectives?

[0102]

[0103] Among them: Q exp_j The expected maximum flow rate at flood control section j; Z exp_j The expected highest water level at flood control section j;

[0104] If the discrimination formula is satisfied, the flood control effect meets the expected flood control target; otherwise, it does not meet the expected flood control target.

[0105] Therefore, in this invention, when the basin flood control situation is analyzed in step S2 and a potential flood hazard is detected, a real-time feedback simulation state is entered. Upon entering the real-time feedback simulation state, multiple scheduling plans are formulated based on the scheduling objectives and flood control scenarios during the real-time feedback simulation. The plan with the highest evaluation value is selected as the flood defense plan. After executing the flood defense plan, the basin flood control situation is further analyzed, and it is determined whether a potential flood hazard exists. If no potential flood hazard exists at this time, the flood defense plan becomes the final scheduling plan formulated for this flood scheduling simulation cycle, and the next flood scheduling simulation cycle begins with a normal simulation. The simulation process begins with assessing the flood control status. If a flood hazard persists, the simulation further determines whether the flood control effect of implementing the flood defense plan meets the expected flood control objectives. If it does, the flood defense plan remains the final scheduling plan for this flood control simulation cycle, but the next flood control simulation cycle will conduct a real-time feedback simulation. If the flood hazard does not meet the objectives, the scheduling objectives during the real-time feedback simulation will be revised, thereby revising the scheduling plan. This process is repeated multiple times until the flood hazard is eliminated or the flood control effect meets the expected flood control objectives, at which point the next flood control simulation cycle begins, and the scheduling plan for this flood control simulation cycle is determined.

[0106] In this invention, when performing conventional state simulations and real-time feedback simulations of flood evolution, it is necessary to use both a conventional simulation state scheduling model and a real-time feedback simulation state scheduling model.

[0107] The methods for establishing the conventional simulation state scheduling model and the real-time mutual feedback simulation state scheduling model are as follows:

[0108] (a) Set up functions f1, f2, f3, and f4:

[0109] f1 is the function that minimizes water shortage losses in the watershed;

[0110]

[0111] W t D represents the water shortage in the water supply area during the flood control simulation period S in time period t; t P represents the water demand of the water supply area during time period t in the flood control simulation cycle.t The water supply of all hydropower stations during the flood control simulation period S in time period t;

[0112] f2 is the objective function for ecological water volume in the river channel;

[0113]

[0114] W ex (t) represents the amount of water exceeding the ecological flow threshold during time period t in the flood control simulation cycle S; Q out_l，t To study the outflow of the first-stage hydropower station in the basin during time period t; K min (t) represents the lower bound of the ecological flow threshold range for the watershed during the study period t; K max (t) represents the upper bound of the ecological flow threshold range for the watershed during the study period t;

[0115] f3 is the objective function that maximizes power generation efficiency;

[0116]

[0117] Where: N l，t To study the average output of the l-th stage hydropower station in the basin during time period t, l = 1, 2, ..., n, where n is the total number of hydropower stations in the basin; Δt is the number of hours included in time period t; k is the output coefficient; H l，t To study the head of the first-stage hydropower station in the basin during time period t; Z up_l，t To study the water level of the first-stage hydropower station in the basin during time period t; Z down_l，t To study the downstream tailrace water level of the first-stage hydropower station in the basin during time period t; H min_l and H max_l Q represents the minimum and maximum water levels of the first-level hydropower station when considering flood risks; min_l and Q max_l , which are the minimum and maximum outflow values ​​of the Class I hydropower station when considering flood risks;

[0118]

[0119] Where: a l b j c j These are the weights for the first objective, the second objective, and the third objective, respectively.

[0120] This represents the highest operating water level of the first-level hydropower station during the flood control simulation cycle S.

[0121] and These are the maximum and minimum allowable water levels for the Class I hydropower station during the flood control simulation period S, respectively.

[0122] Q j，t The flow rate at flood control section j during time period t of the flood control simulation cycle S; Q min_j ≤Q j，t ≤Q max_j Q min_j and Q max_j These are the lower and upper limits of the allowable flow rate at the flood control section j, respectively.

[0123] For the excess flow at the flood control section j of the hydropower station after regulation and storage in time period t, when Q j，t Not exceeding the upper limit of the overcurrent flow rate Q max_j hour, =0; when Q j，t Exceeding the upper limit of the overcurrent flow Q max_j hour, Q j，t，ce The excess flow at the flood control section j during time period t, without regulation by the hydropower station;

[0124] The conventional simulation state scheduling target S0 is: S0 = {f1, f2, f3};

[0125] The scheduling target S during the i-th real-time mutual feedback simulation i ={f1, f2, f4, f4}.

[0126] (ii) Setting boundary constraints includes:

[0127] (1) Water balance equation: V l，t =V l,t-1 +(Q in_l,t-1 -Q out_l,t-1 )Δt

[0128] Where: V l，t V represents the reservoir capacity of the first-level hydropower station during time period t; l，t-1 The reservoir capacity of the first-level hydropower station in time period t-1;

[0129] Q in_l，t-1 and Q out_l，t-1 , , are the inflow and outflow of the L-th hydropower station in time period t-1, respectively; Δt is the number of hours contained in time period t;

[0130] (2) Tailwater function of the hydropower station: Z down_l，t =h l (Q out_l，t )

[0131] Among them: Z down_l，tThe downstream tailrace water level of the L-th stage hydropower station at time period t; h l (Q out_l，t ) is the relationship function between the outflow from the reservoir and the downstream tailrace level of the l-th hydropower station in time period t;

[0132] (3) Hydropower station water level-storage capacity function:

[0133] Among them: Z up_l，t The water level of the L-th stage hydroelectric power station during time period t; This is the function relating water level and reservoir capacity for the first-level hydropower station.

[0134] (4) Head equation: H l，t =Z up_l，t -Z down_l，t

[0135] Among them: H l，t The head of the first-level hydroelectric power station in time period t;

[0136] (5)Output equation: N l，t =kQ out_l，t H l，t

[0137] Where: N l，t Let Q be the average output of the l-th stage hydropower station during time period t, where l = 1, 2, ..., n, and n is the total number of hydropower stations in the study basin; k is the output coefficient; Q out_l，t The outflow from the reservoir of the L-level hydropower station during time period t;

[0138] (iii) The conventional deduction state scheduling objective S0 = {f1, f2, f3} and the boundary constraints form a conventional deduction state scheduling model;

[0139] The scheduling target S during the i-th real-time mutual feedback simulation i ={f1, f2, f3, f4} and the boundary constraints form a real-time feedback deduction state scheduling model.

[0140] (iv) The conventional simulation scheduling scheme D S，0 Perform routine state simulations of flood evolution and construct the routine simulation scheduling scheme D to execute the simulation. S，0 The subsequent flood control scenario, Scene'0, is as follows:

[0141] Based on the conventional deduction and scheduling scheme D S，0 Using the outflow from the reservoir at each level of hydropower station in time period t as the decision variable, the conventional deductive state scheduling model is solved to obtain the result when executing the conventional deductive scheduling scheme D. S，0 Subsequently, the outflow Q of each hydropower station in the basin during the time interval t of the flood control simulation period S was studied.out_l，t ;

[0142] Based on the current time t * The study uses measured data of watershed hydrology, rainfall, and engineering conditions, as well as the time-by-time outflow Q of each hydropower station in the watershed during the flood control simulation period S. out_l，t Flood simulations were performed on the study basin to obtain the flow rate and water level at each flood control section, and then the conventional simulation scheduling scheme D was executed. S，0 Scene 0, depicting the flood control scenario.

[0143] (v) The above is based on each scheduling plan D S，i，k Real-time feedback simulations of flood evolution are conducted to evaluate the effectiveness and risks of various dispatch plans, specifically:

[0144] Based on the aforementioned scheduling plan D S，i，k Using the outflow from the reservoir at each level of hydropower station in time period t as the decision variable, the real-time feedback simulation state scheduling model is solved to obtain the results when the scheduling plan D is executed. S，i，k Subsequently, the outflow Q of each hydropower station in the basin during the time interval t of the flood control simulation period S was studied. out_l，t ;

[0145] Based on the current time t * The study uses measured data of watershed hydrology, rainfall, and engineering conditions, as well as the time-by-time outflow Q of each hydropower station in the watershed during the flood control simulation period S. out_l，t Flood simulations were performed on the study basin to obtain the flow rate and water level at each flood control section; based on the flow rate and water level at each flood control section, the effectiveness and risks of the aforementioned scheduling plan were evaluated.

[0146] This invention provides a flood defense interactive decision-making method driven by virtual and real twin plans, which has the following characteristics:

[0147] This invention introduces the concept of flood warning and dispatch status, including conventional simulation status and real-time feedback simulation status. The results of basin flood control situation analysis affect the regulation of these two statuses and are also one of the main decision-making conditions for the verification of flood defense plans. It innovatively proposes a real-time feedback simulation of "reality-scenario-plan". Through a time-progressive approach, it combines the current status of various hydropower stations, flood control sections, reservoirs, etc., at all levels, as detected by various equipment in the basin and derived by the model with the real-time water and rainfall conditions. Using water and rainfall forecast data, dispatch plans, and flood control situation analysis, it generates a dispatch plan that has been verified by hydrodynamic simulation, has good effect and risk assessment, and meets the flood control standards.

[0148] The plan-driven interactive decision-making method provided by this invention improves the efficiency and accuracy of flood emergency response through real-time feedback and optimization, and provides a more efficient solution for dealing with complex flood risks in the future.

[0149] This invention dynamically selects flood control schemes under different conditions, enabling the selection of the optimal scheme from multiple schemes based on real-time water and rainfall information when a flood forecast arrives, thereby maximizing flood control.

[0150] When selecting a flood control scheme, the main criteria for classification and selection are based on actual changes in water and rainfall conditions and forecasts. The specific selection steps include: acquiring water and rainfall data in real time; selecting the optimal control scheme from multiple control plans based on the acquired water and rainfall data and forecasts; and dynamically adjusting the selected control scheme based on measured data and evaluation results.

[0151] For each flood warning, there is a corresponding set of dispatching schemes, which contains multiple schemes under different dispatching conditions. Based on the flood warning and real-time hydrological and rainfall data, the dispatching scheme with the highest evaluation value is selected from the set of schemes as the final execution scheme. This includes: for each dispatching scheme in the set, evaluating its impact on flood control engineering capacity, protection sections and dikes, as well as its potential impact on watershed losses; summarizing these evaluation indicators as the scheme's evaluation value; and finally selecting the scheme with the highest evaluation value as the execution scheme.

[0152] When a flood is forecast, the system can quickly obtain a set of corresponding dispatching schemes based on real-time hydrological and rainfall information, and select the optimal scheme from them. This invention provides an efficient and flexible technical solution for flood defense.

[0153] In the field of flood control, this invention enables flexible adjustment of dispatching schemes according to actual conditions, which is crucial for ensuring the safety of life and property. During the flood warning phase, the swift implementation of effective dispatching measures is key to flood control efforts. Examples of this invention demonstrate how to flexibly switch between conventional dispatching and real-time feedback simulations based on real-time flood monitoring data and forecast information, ensuring timely responses under different circumstances and improving the timeliness and effectiveness of flood control.

[0154] The specific embodiments of the present invention will be described in further detail with reference to examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the invention.

[0155] Combination Figures 2 to 5This invention has been practically applied in the 2020 flood simulation of the Yangtze River Basin. Taking the Dongting Lake area as an example, it uses an intelligent adaptation method of mutual feedback between flood control engineering scheduling plans and simulation scenarios to simulate flood evolution. Then, the effectiveness of the flood control emergency plan is evaluated and the risk situation is analyzed, thereby obtaining the lowest-risk scheduling scheme. Taking the formulation of the 2020 Yangtze River Basin flood defense scheduling plan as an example, the interactive simulation method provided by this invention includes two states: a normal state and a real-time mutual feedback simulation state, which is based on... Figure 4 The diagram shows nested execution of schedules at different time scales. For example... Figure 5 This shows the daily simulated status of the middle and lower reaches of the Yangtze River during the Three Gorges Reservoir's operation.

[0156] From July 5th to July 9th, the system performed routine daily calculations, hydrodynamic simulations, and evaluations of scheduling effectiveness. The evaluation results showed no flood risk alarms within the foreseeable 5-7 days. Therefore, the current scheduling plan was continued, and the system remained in a normal state.

[0157] From July 7th to 10th, the system evaluated the daily dispatch plans and found that the dispatch effects did not meet the expected goals and flood risk alarms were triggered. The system then switched to real-time feedback simulation mode. Based on current and forecast water and rainfall conditions, the system proposed new dispatch objectives and output a set of dispatch plans in conjunction with the flood control scenario. Subsequently, hydrodynamic simulations, effectiveness and risk assessments were performed on the dispatch plans, and the optimal dispatch plan was determined as the flood defense scheme.

[0158] After obtaining the flood defense plan, it was incorporated into the scenario data to calculate the outflow from the Three Gorges Reservoir and conduct hydrodynamic simulation analysis of the basin's flood control situation. No flood risks were identified after revising the flood defense plan, so it was readjusted to a normal state and implemented according to the new dispatch plan.

[0159] From July 7th to 11th, the system evaluated the effectiveness of the daily dispatch plan, finding that the dispatch effect did not meet the expected goals and that a flood risk alarm had been triggered. The system then switched to real-time feedback simulation mode. Using the same steps, the system derived the optimal flood defense plan as the dispatch plan. This plan was then applied to the scenario data to calculate the outflow from the Three Gorges Reservoir and perform flood simulations based on hydrodynamics, revealing that a flood risk still existed. At this point, the real-time feedback simulation mode was maintained, and the plan was evaluated to determine if it had achieved the expected goals. If the implementation of the dispatch plan achieved the dispatch objectives, a newly revised dispatch plan was executed, and the system remained in real-time feedback simulation mode.

[0160] From July 7th to 12th, the flood control situation was assessed based on measured data. If flood warnings were still in effect, real-time feedback simulations were maintained, and operations similar to those implemented on July 11th were executed. If flood risks persisted and the expected targets were not met, the existing dispatch plan was revised, dispatch objectives were changed, and a new set of dispatch plans was selected, formulated, and retested until the expected flood control targets were met. The plan was then implemented, and real-time feedback simulations continued.

[0161] From July 13th to 30th, the above operations were repeated. Flood risk warnings remained, so the dispatch plan was modified daily and real-time feedback simulations were maintained.

[0162] From July 7th to 31st, when the system tested the plan, it found no flood hazards and returned to normal status, which also indicates that the previous No. 2 and No. 3 floods have been eliminated.

[0163] Then, the above method is used daily to progressively analyze and calculate, and the scheduling plan is tested in real time. This enables daily checking and correction of the scheduling plan, reduces the large-scale work of plan formulation and selection, and highly integrates "reality-scenario-plan".

[0164] This invention provides a flood defense interactive decision-making method driven by virtual and real twin plans, which has the following advantages:

[0165] This invention features a flexible time scheduling mechanism: By adjusting the flood control simulation cycle S, it can flexibly adapt to the scheduling needs of different flood control simulation cycles S, enabling dynamic formulation of scheduling plans and improving their adaptability and convenience. It also features all-weather flood defense monitoring: Combining routine conditions with real-time feedback simulation conditions, this invention achieves full-process monitoring of flood defense, ensuring high alert under any circumstances and enhancing the real-time nature and effectiveness of flood defense. Furthermore, it employs a feedback-based contingency plan formulation method: By simulating and analyzing the scheduling results, this invention proposes a feedback-based contingency plan formulation method. This method ensures that the formulated plans are closer to actual flood conditions, improving their practicality and accuracy. Finally, it features data linkage and real-time response: Through the coordinated action of reality, scenarios, and contingency plans, this invention achieves data sharing and real-time updates. This mechanism allows scheduling plans to closely follow actual needs and adapt to real-world flood conditions, improving the timeliness and accuracy of the scheduling plans.

[0166] This invention not only improves the efficiency of flood control and dispatching plan formulation but also enhances the reliability and practicality of the plans. Through the application of virtual-real twin technology, this invention provides an innovative decision support tool for the field of flood defense, strengthening real-time monitoring and response capabilities to flood situations. It effectively addresses complex and ever-changing flood conditions, providing strong technical support for flood control and disaster reduction efforts.

[0167] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A flood defense interactive decision-making method driven by virtual and real twin plans, characterized in that, Includes the following steps: Step S1: Obtain the hydrological characteristics of the study watershed; determine the flood control cross-section based on the hydrological characteristics of the study watershed; set the initial value of the flood control simulation period S of the study watershed to 1; set the scheduling scheme D corresponding to the flood control simulation period S. S The initial value is empty; obtain the hydrological characteristics of each flood control section at the beginning of the flood control simulation period S to form the flood control scenario Scene0; Step S2: Analyze the flood control situation of the basin based on the flood control scenario Scene0, and determine whether there is a potential flood hazard; if not, proceed to step S3. If so, proceed to step S4; Step S3, enter the normal simulation state: Step S3.1: Based on the flood control scenario Scene0 and the conventional simulation state scheduling target S0, formulate the conventional simulation scheduling scheme D. S，0 ; Step S3.2, based on the conventional simulation scheduling scheme D S，0 Perform routine state simulations of flood evolution and construct the routine simulation scheduling scheme D to execute the simulation. S，0 The subsequent flood control scenario Scene'0 is used to analyze the flood control situation in the basin and determine whether there is a potential flood hazard; if not, the flood control scenario Scene'0 is updated using the flood control scenario Scene'0; let scheduling scheme D... S =Conventional simulation scheduling scheme D S，0 S = S + 1, return to step S3.1; if so, proceed to step S4; Step S4, enter the real-time mutual feedback simulation state: Step S4.1, let the variable i = 1 for the number of real-time mutual feedback simulations; Determine the scheduling target S during the i-th real-time mutual feedback simulation. i ; Step S4.2, based on the flood control scenario Scene0 and the scheduling target S during the i-th real-time feedback simulation. i M scheduling plans corresponding to the flood scheduling simulation period S at the i-th real-time feedback simulation are formulated, denoted as: D S，i，k k = 1, 2, ..., M; Step S4.3, based on each scheduling plan D S，i，k Real-time feedback simulations of flood evolution are conducted to evaluate the effectiveness and risks of various dispatch plans, and the optimal dispatch plan is selected as the flood defense scheme D from among them. S，i ; Step S4.4, construct and implement the flood defense scheme D S，i Post-flood control scene i ; Based on the flood control scenario Scene i Conduct a flood control situation analysis of the watershed and determine whether there are any potential flood risks; if not, then adopt a flood control scenario. i Update the flood control scenario Scene0; Instruct the scheduling scheme D S =D S，i S = S + 1, return to step S3.1; If so, proceed to step S4.5; Step S4.5, regarding the flood defense scheme D S，i Conduct an effectiveness evaluation to determine whether the flood defense plan D should be implemented. S，i Does the subsequent flood control effect meet the expected flood control objectives? If so, then adopt the flood control scenario. i Update the flood control scene Scene0; let D S =D S，i If S = S + 1, return to step S4.1; otherwise, proceed to step S4.

6. Step S4.6, based on the scheduling target S during the i-th real-time mutual feedback simulation. i Determine the scheduling objective for the (i+1)th real-time mutual feedback simulation; Let i = i + 1, and return to step S4.

2.

2. The flood defense interactive decision-making method driven by virtual-real twin plans according to claim 1, characterized in that, In step S1, the hydrological characteristics of each flood control section at the beginning of the flood control simulation period S are based on the forecast hydrological characteristics of each flood control section, including the flow and water level of the flood control section.

3. The flood defense interactive decision-making method driven by virtual-real twin plans according to claim 1, characterized in that, In step S2, based on the flood control scenario Scene0, a basin flood control situation analysis is performed, and it is determined whether there are potential flood risks. Specifically: Read the flow rate and water level of each flood control section in the flood control scenario Scene0, and determine whether the following judgment formula is satisfied: Among them: Q j，t Q represents the flow rate of flood control section j during time period t of the flood control simulation cycle S; t = 1, 2, ..., T, where T represents the number of time periods in the flood control simulation cycle S; j = 1, 2, ..., m, where m represents the number of flood control sections in the study basin; warn_j Z represents the warning flow rate at flood control section j; j，t Z represents the water level at flood control section j during time period t of the flood control simulation cycle S; warn_j The warning water level represents the flood control section j; If the discrimination formula is satisfied, there is no flood risk; otherwise, there is a flood risk.

4. The flood defense interactive decision-making method driven by virtual-real twin plans according to claim 1, characterized in that, In step S3.1, based on the flood control scenario Scene0 and the conventional simulation state scheduling target S0, a conventional simulation scheduling scheme D is formulated. S，0 Specifically: Based on the obtained flood control simulation period S, starting time t0, the water and rainfall forecast data, and the current time t * Based on the measured data of watershed rainfall and engineering conditions, the flood control scenario Scene0 and the conventional simulation state scheduling objective S0 are used to formulate a conventional simulation scheduling scheme D. S，0 .

5. The flood defense interactive decision-making method driven by virtual-real twin plans according to claim 1, characterized in that, Set functions f1, f2, f3, and f4: f1 is the function that minimizes water shortage losses in the watershed; W t D represents the water shortage in the water supply area during the flood control simulation period S in time period t; t P represents the water demand of the water supply area during the flood control simulation period S in time period t; t The water supply of all hydropower stations during the flood control simulation period S in time period t; f2 is the objective function for ecological water volume in the river channel; W ex (t) represents the amount of water exceeding the ecological flow threshold during time period t in the flood control simulation cycle S; Q out_l，t To study the outflow of the first-stage hydropower station in the basin during time period t; K min (t) represents the lower bound of the ecological flow threshold range for the watershed during the study period t; K max (t) represents the upper bound of the ecological flow threshold range for the watershed during the study period t; f3 is the objective function that maximizes power generation efficiency; H min_l ≤H l，t ≤H max_l Q min_l ≤Q out_l，t ≤Q max_l Where: N l，t To study the average output of the l-th stage hydropower station in the basin during time period t, l = 1, 2, ..., n, where n is the total number of hydropower stations in the basin; Δt is the number of hours included in time period t; k is the output coefficient; H l，t To study the head of the first-stage hydropower station in the basin during time period t; Z up_l，t To study the water level of the first-stage hydropower station in the basin during time period t; Z down_l，t To study the downstream tailrace water level of the first-stage hydropower station in the basin during time period t; H min_l and H max_l Q represents the minimum and maximum water levels of the first-level hydropower station when considering flood risks; min_l and Q max_l , which are the minimum and maximum outflow values ​​of the Class I hydropower station when considering flood risks; Where: a l b j c j These are the weights for the first objective, the second objective, and the third objective, respectively. This represents the highest operating water level of the first-level hydropower station during the flood control simulation cycle S. and These are the maximum and minimum allowable water levels for the Class I hydropower station during the flood control simulation period S, respectively. Q j，t The flow rate at flood control section j during time period t of the flood control simulation cycle S; Q min_j ≤Q j，t ≤Q max_j Q min_j and Q max_j These are the lower and upper limits of the allowable flow rate at the flood control section j, respectively. For the excess flow at the flood control section j of the hydropower station after regulation and storage in time period t, when Q j，t Not exceeding the upper limit of the overcurrent flow rate Q max_j hour, =0; when Q j，t Exceeding the upper limit of the overcurrent flow Q max_j hour, Q j，t，ce The excess flow at the flood control section j during time period t, without regulation by the hydropower station; The conventional simulation state scheduling target S0 is: S0 = {f1, f2, f3}; The scheduling target S during the i-th real-time mutual feedback simulation i ={f1, f2, f3, f4}.

6. The flood defense interactive decision-making method driven by virtual-real twin plans according to claim 5, characterized in that, Setting boundary constraints includes: (1) Water balance equation: V l，t =V l，t-1 +(Q in_l，t-1 -Q out_l，t-1 )Δt Where: V l，t V represents the reservoir capacity of the first-level hydropower station during time period t; l，t-1 The reservoir capacity of the first-level hydropower station in time period t-1; Q in_l，t-1 and Q out_l，t-1 , , are the inflow and outflow of the L-th hydropower station in time period t-1, respectively; Δt is the number of hours contained in time period t; (2) Tailwater function of the hydropower station: Z down_l，t =h l (Q out_l，t ) Among them: Z down_l，t The downstream tailrace water level of the L-th stage hydropower station at time period t; h l (Q out_l，t ) is the relationship function between the outflow from the reservoir and the downstream tailrace level of the l-th hydropower station in time period t; (3) Hydropower station water level-storage capacity function: Among them: Z up_l，t The water level of the L-th stage hydroelectric power station during time period t; This is the function relating water level and reservoir capacity for the first-level hydropower station. (4) Head equation: H l，t =Z up_l，t -Z down_l，t Among them: H l，t The head of the first-level hydroelectric power station in time period t; (5)Output equation: N l，t =kQ out_l，t H l，t Where: N l，t Let Q be the average output of the l-th stage hydropower station during time period t, where l = 1, 2, ..., n, and n is the total number of hydropower stations in the study basin; k is the output coefficient; Q out_l，t The outflow from the reservoir of the L-level hydropower station during time period t; The conventional deduction state scheduling objective S0 = {f1, f2, f3} and the boundary constraints form the conventional deduction state scheduling model; The scheduling target S during the i-th real-time mutual feedback simulation i ={f1, f2, f3, f4} and the boundary constraints form a real-time feedback deduction state scheduling model.

7. The flood defense interactive decision-making method driven by virtual-real twin plans according to claim 6, characterized in that, The conventional deduction and scheduling scheme D S，0 Perform routine state simulations of flood evolution and construct the routine simulation scheduling scheme D to execute the simulation. S，0 The subsequent flood control scenario, Scene'0, is as follows: Based on the conventional deduction and scheduling scheme D S，0 Using the outflow from the reservoir at each level of hydropower station in time period t as the decision variable, the conventional deductive state scheduling model is solved to obtain the result when executing the conventional deductive scheduling scheme D. S，0 Subsequently, the outflow Q of each hydropower station in the basin during the time interval t of the flood control simulation period S was studied. out_l，t ; Based on the current time t * The study uses measured data of watershed hydrology, rainfall, and engineering conditions, as well as the time-by-time outflow Q of each hydropower station in the watershed during the flood control simulation period S. out_l，t Flood simulations were performed on the study basin to obtain the flow rate and water level at each flood control section, and then the conventional simulation scheduling scheme D was executed. S，0 Scene 0, depicting the flood control scenario.

8. A flood defense interactive decision-making method driven by virtual-real twin plans according to claim 6, characterized in that, The basis for each scheduling plan D S，i，k Real-time feedback simulations of flood evolution are conducted to evaluate the effectiveness and risks of various dispatch plans, specifically: Based on the aforementioned scheduling plan D S，i，k Using the outflow from the reservoir at each level of hydropower station in time period t as the decision variable, the real-time feedback simulation state scheduling model is solved to obtain the results when the scheduling plan D is executed. S，i，k Subsequently, the outflow Q of each hydropower station in the basin during the time interval t of the flood control simulation period S was studied. out_l，t ; Based on the current time t * The study uses measured data of watershed hydrology, rainfall, and engineering conditions, as well as the time-by-time outflow Qou of each hydropower station in the watershed during the flood control simulation period S. t_l，t Flood simulation was performed on the study basin to obtain the flow rate and water level at each flood control section; The effectiveness and risks of the aforementioned scheduling plan are evaluated based on the flow rate and water level at each flood control section.

9. A flood defense interactive decision-making method driven by virtual-real twin plans according to claim 6, characterized in that, In step S4.5, the following discrimination formula is used to determine the flood defense scheme D. S，i Conduct an effectiveness evaluation to determine whether the flood defense plan D should be implemented. S，i Does the subsequent flood control effect meet the expected flood control objectives? Among them: Q exp_j The expected maximum flow rate at flood control section j; Z exp_j The expected highest water level at flood control section j; If the discrimination formula is satisfied, the flood control effect meets the expected flood control target; otherwise, it does not meet the expected flood control target.

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