Reservoir flood control scheme library area inundation risk map construction method

Abstract

The application discloses a method for constructing a reservoir flood control scheduling scheme reservoir area submergence risk atlas, and comprises the following steps: basic data collection and arrangement; construction of a reservoir area real-time water surface line simulation model with multiple reservoir inlet points; generation of reservoir trunk and branch stream reservoir inlet flow and flood control scheduling control parameter combination working conditions; simulation of reservoir area real-time water surface lines under each combination working condition and statistics of reservoir area submergence indexes; establishment of a multivariate joint probability distribution function of reservoir trunk and branch stream reservoir inlet flow, flood control scheduling control parameters and reservoir area submergence indexes; construction of a conditional probability conversion model; and production of a reservoir area submergence risk atlas. The correlation among the reservoir trunk and branch stream reservoir inlet flow, the flood control scheduling scheme control parameters and the reservoir area submergence indexes is fully utilized, which is favorable for reducing the uncertainty of traditional reservoir area water surface line prediction, reducing the time cost of complex hydrology and hydrodynamic calculation, and improving the robustness and timeliness of reservoir real-time flood control scheduling decision.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of reservoir operation risk assessment, and relates to a reservoir flood control operation scheme reservoir area submergence risk atlas construction method. BACKGROUND

[0002] Reservoirs that undertake downstream flood control tasks use the reserved flood control storage capacity of the reservoir area to block flood peaks and ensure downstream flood control safety when floods arrive. During the design phase of the reservoir, the design flood standard for reservoir submergence treatment and the sedimentation period are selected to carry out reservoir flood operation and backwater calculation. Based on certain normal reservoir water levels, wind wave climbing values, ship wave effects, and reservoir perimeter landslides and landslides, the reservoir submergence impact treatment range is determined, and the reservoir area resident relocation and land expropriation boundaries are measured and set. During the construction phase of the reservoir, the design results are used to organize and implement the relocation of rural, town, and industrial and mining enterprises within the submergence impact range, and the expropriation of farmland, gardens, forests, and grasslands to ensure the safe and effective operation of the reservoir's flood control function. Therefore, under normal circumstances, the reservoir needs to drop the dam front water level to the flood control limit water level before the flood arrives. At this time, if the flood level does not exceed the design flood standard for reservoir submergence treatment, there is generally no submergence risk in the reservoir area.

[0003] Whether submergence occurs in the reservoir area and the degree of submergence during the reservoir flood control operation process mainly depends on the combination of the inflow and the reservoir outflow, the dam front water level, and other flood control operation control parameters. Currently, under the dual stress of climate change and human activity, extreme climate events increase, and the underlying surface conditions change, making the probability of inflow exceeding the reservoir land expropriation standard (such as 5-year return period) or even the resident relocation standard (such as 20-year return period) increase, and the reservoir area may face certain submergence losses. In addition, when encountering continuous compound floods, the reservoir continuously blocks floods, and the reservoir water level continuously rises, the dam front water level is high when the next flood peak appears, which may also cause temporary submergence in the reservoir area. During real-time operation, the reservoir operation department needs to evaluate the impact of different flood control operation schemes on engineering safety, downstream flood routing, and reservoir submergence based on the inflow, make scientific and rapid decisions on reservoir storage and release strategies during the temporary period, and reasonably control the outflow and dam front water level. Under the premise of ensuring engineering safety, the upstream and downstream flood control pressures are considered, and the loss of people's life and property is minimized or reduced as much as possible.

[0004] The traditional reservoir flood control scheduling scheme reservoir submergence risk assessment method is to construct a high-precision reservoir hydrological and hydrodynamic model, simulate the reservoir water surface line change process under different flood control scheduling schemes under the assumption of inflow conditions, and compare with the demarcated resident relocation and land expropriation limit, statistically analyze the submergence influence range and degree index, and estimate the reservoir submergence loss. However, due to the existence of rainfall, flood forecast and model uncertainty, the accuracy of the water surface line prediction is restricted to a certain extent; at the same time, the reservoir generally has multiple inflow points, and the reservoir flood evolution and distribution along the way are complex, the operation scale is large, the time is long, and the decision efficiency is affected. SUMMARY

[0005] The technical problem to be solved by the present application is to provide a reservoir flood control scheduling scheme reservoir submergence risk atlas construction method, a large number of reservoir water surface line numerical simulation experiment samples under different inflow flow and flood control scheduling scheme control parameter combination working conditions are obtained offline, and a probability conversion model among the reservoir inflow flow and the discharge flow, the dam front water level and the corresponding submergence index of the flood control scheduling control parameters is constructed by using the multi-dimensional joint distribution theory, the possibility and severity of the reservoir submergence caused by the preset flood control scheduling scheme under a certain inflow condition are evaluated, and thus the reservoir flood control scheduling scheme reservoir submergence risk atlas is constructed, so as to reduce the uncertainty of the reservoir water surface line prediction, reduce the time cost of the complex hydrological and hydrodynamic calculation, and improve the robustness and timeliness of the real-time flood control scheduling decision of the reservoir.

[0006] To solve the above technical problems, the technical scheme adopted by the present application is: a reservoir flood control scheduling scheme reservoir submergence risk atlas construction method, comprising the following steps:

[0007] Step 1, basic data acquisition and arrangement;

[0008] Step 2, constructing a real-time water surface line simulation model of a reservoir area with multiple inflow points;

[0009] Step 3, generating a combination working condition of the reservoir trunk and branch inflow flow and the flood control scheduling control parameters;

[0010] Step 4, using the model constructed in step 2, traversing and simulating the real-time water surface line of the reservoir area under each combination working condition generated in step 3, and statistically analyzing the reservoir submergence index under each combination working condition;

[0011] Step 5, establishing a multi-element joint probability distribution function of the reservoir trunk and branch inflow flow, the flood control scheduling control parameters and the reservoir submergence index;

[0012] Step 6, constructing a conditional probability conversion model between the reservoir trunk and branch inflow flow, the flood control scheduling control parameters and the reservoir submergence index, and making a reservoir submergence risk atlas.

[0013] In step 1, the basic data includes the reservoir's characteristic water level, water level-reservoir capacity curve, discharge capacity curve, topography of the river section along the reservoir area and distance from the dam, location and elevation of land acquisition boundary markers, location and elevation of resident relocation boundary markers, statistics on the number of submerged objects at different elevations in the reservoir area, and minimum discharge flow data of the reservoir; synchronous flood data and frequency distribution statistics of the main and tributary inflow control stations in the reservoir area, water level and flow processes of the reservoir area's control hydrological stations for measured flood events since the reservoir's construction, and the corresponding discharge flow and hydrological and operational data of the water level in front of the dam.

[0014] In step 2, constructing a real-time water surface line simulation model of the reservoir area with multiple inflow points includes the following steps:

[0015] Step 2-1, for the collected S The river sections along the reservoir area are numbered sequentially from downstream to upstream. Topographical data and distance from the dam are collected for each section to divide the river into segments. Section 1 is generally the section where the dam site is located. S The No. 1 section is generally the section where the main inflow point is located;

[0016] Step 2-2: Establish a one-dimensional hydrodynamic model of the reservoir area. Use the measured flood level and flow process of the reservoir area's controlling hydrological station and the corresponding reservoir flood control scheduling process discharge flow and upstream water level data to calibrate the roughness of each section by river segment.

[0017] Steps 2-3: Initialize the water level and flow rate at each cross-section, using the first... S Using the flow rate at section 1 as the upper boundary and the water level or flow rate at section 1 as the lower boundary, the water level is calculated section by section to obtain the real-time water surface line of the reservoir area.

[0018] In steps 2 and 3, based on the characteristics of flood evolution, river topography, and available data, a one-dimensional steady flow or unsteady flow hydrodynamic model for the reservoir area is selected.

[0019] In step 3, generating the combined operating conditions of the reservoir's main and tributary inflows and flood control scheduling parameters includes the following steps:

[0020] Step 3-1: Based on the synchronous flood data and frequency distribution statistical parameters of the main and tributary inflow control stations in the reservoir area, the master-slave station method is used to randomly generate... N Group of tributary inflow and outflow combinations ,in For the main stream i Group inbound flow For the first k The first tributary i Group inbound flow;

[0021] Step 3-2, set the reservoir's flood control limit water level. ZFCL Up to flood control high water level Z FSL The water level range between the two values ​​is determined by the step size Δ. Z Discretize the data and use Bootstrap resampling technology to generate... N Water level in front of the dam Z i ( i =1,2,..., N ), and in turn for each group Z i At the minimum discharge flow rate of the reservoir Water level in front of the dam Z i Corresponding discharge capacity Within the value range, a set of outflow rates is randomly generated. ;

[0022] Step 3-3, N Inflow of water into the main and tributary reservoirs and flood control scheduling and control parameter scheme Perform a random combination without replacement to obtain N Combined working conditions .

[0023] In step 3-2, to reduce sampling error and to closely reflect flood control scheduling practices, .

[0024] In step 4, the reservoir inundation indicators include the land acquisition line inundation indicator and the resident relocation line inundation indicator. By comparing the real-time water level line of the reservoir with the land acquisition line or resident relocation line, a set of indicators U={ can be statistically estimated to reflect the scope and degree of reservoir flood control scheduling inundation impact. U 1, U 2,..., U J}

[0025] In step 5, the data obtained from steps 3 and 4... N The calculation of the water surface line boundary conditions and corresponding inundation index statistical samples in the reservoir area is based on the maximum entropy principle. This is achieved by solving the probability distribution that maximizes the joint information entropy of the random variables while maintaining the main statistical characteristics of the system. This distribution serves as the inflow rate Q of the reservoir's main tributaries and the water level in front of the dam. Z Downflow The joint probability distribution density function of the random variable system composed of the reservoir inundation index U. Obtaining the joint probability density function of a system of random variables is described as the following mathematical programming problem:

[0026] Objective function: wherein is the joint information entropy of the random variable system X; f (x) is the joint probability distribution function of the random variable system; R is the Euclidean space with the same dimension as the number of system variables;

[0027] Constraint conditions: ;

[0028] wherein g m (x) and EX [ g m (x)] are the first m = 1, 2,..., n M known functions of the random variable system X and the corresponding mathematical expectation values; g m (x) uses the low-order origin moments, sample moments or moment product functions of each random variable to maintain the expected value, variance, skewness coefficient, correlation statistics of the random variable system;

[0029] To ensure the normalization and normalization of the probability density function, the following constraints also need to be met:

[0030] ;

[0031] By reasonably setting the number of constraint conditions, the Lagrange multiplier method is used to solve the above constrained maximum value optimization problem to estimate the shape, scale and location parameters of f (x) and then obtain f (x).

[0032] In step 6, according to the size of the reservoir inflow forecast during the facing period and the height of the real-time water level in front of the dam, the reservoir inundation risk value atlas or reservoir inundation risk early warning atlas is selected to be constructed; When the forecast inflow is large or the water level in front of the dam is high, the reservoir inundation risk is difficult to avoid, and the reservoir inundation risk value atlas is selected to be constructed, including the following steps:

[0033] According to the downstream flood control demand during the facing period, the reservoir trunk stream inflow forecast value Q=q and the preset flood control scheduling control parameter Z = z , are given, and is subjected to bounded multiple integration to obtain the conditional probability distribution density function of the reservoir inundation index during the facing period ; In combination with the recognized standard and artificial experience, the risk consequence severity level corresponding to different reservoir inundation index threshold values is divided; The conditional probability distribution density function By performing multiple integrations in continuous space, the cumulative probability of inundation index thresholds for different reservoir areas is obtained, and the risk occurrence probability levels are classified. By combining the risk occurrence probability and the severity level of consequences corresponding to the inundation index thresholds for different reservoir areas, the risk value is calculated, and the inundation risk value map of the reservoir area is obtained.

[0034] When the predicted inflow is not large or the water level in front of the dam is not high, and the risk of reservoir inundation can be avoided or mitigated, the reservoir inundation early warning map is constructed, including the following steps:

[0035] Based on the reservoir inundation risk control objectives, and given the inundation index U=u for the period in which the reservoir is expected to be flooded, By performing bounded multiple integrations, we obtain the conditional probability distribution density function of the combined operating conditions of the reservoir's main and tributary inflows and flood control scheduling parameters during the given time period. Based on the downstream flood control needs during the current period, the reservoir discharge flow rate is assumed to be... Calculate the inflow rates of different reservoirs and tributaries under the condition Q=q. The cumulative probability of the water level in front of the dam is not lower than a certain acceptable risk level. Z The upper bound of the integral is used as the critical warning water level to avoid or mitigate reservoir inundation, thus obtaining the reservoir inundation risk warning map.

[0036] The main beneficial effects of this invention are as follows:

[0037] By fully utilizing the correlation between the inflow of water into the reservoir and its tributaries, the control parameters of the flood control scheduling scheme, and the inundation index of the reservoir area, a joint probability distribution and conditional probability transformation model was constructed. This model helps to reduce the uncertainty of inputs and models in the process of calculating the inundation index of the reservoir area from the inflow of water into the reservoir and the control parameters of the flood control scheduling scheme. Furthermore, it can inversely obtain the critical control conditions that can avoid or mitigate the inundation of the reservoir area, thereby improving the robustness and flexibility of flood control scheduling decisions.

[0038] By acquiring a large number of real-time water surface line simulation samples of the reservoir area offline, which are computationally cumbersome and time-consuming, and constructing a reservoir inundation risk map, we can integrate and quickly provide reservoir inundation risk information under different combinations of working conditions, saving valuable flood control scheduling decision-making time.

[0039] The method for obtaining the joint probability distribution density function of a random variable system based on the maximum entropy principle does not require prior assumptions about the a prior distribution. It can optimize the parameters of the joint distribution as a whole by utilizing various statistical characteristics of the original simulation data, and has a strong statistical foundation. Attached Figure Description

[0040] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0041] Figure 1 This is a flowchart of the present invention.

[0042] Figure 2 This is a schematic diagram comparing the outer boundary of the reservoir water surface line with the land acquisition line and the resident relocation line during the flood season of this invention.

[0043] Figure 3 This is a schematic diagram of the reservoir flood process simulation results of the present invention.

[0044] Figure 4 This is a schematic diagram of the reservoir inundation risk value map of the present invention.

[0045] Figure 5 This is a schematic diagram of the reservoir flooding risk early warning map of the present invention. Detailed Implementation

[0046] like Figures 1-5 A method for constructing a reservoir inundation risk map under a reservoir flood control scheduling scheme includes the following steps:

[0047] Step 1: Basic data collection and processing, including reservoir characteristic water levels, water level-reservoir capacity curves, discharge capacity curves, topography of river sections along the reservoir area and distance from the dam, location and elevation of land acquisition boundary markers, location and elevation of resident relocation boundary markers, statistics on the number of submerged objects at different elevations in the reservoir area, minimum discharge flow, and other reservoir characteristic data; long-series synchronous flood data and frequency distribution statistics of the reservoir's main and tributary inflow control stations, water level and flow processes of measured floods since the reservoir's construction at the reservoir's control hydrological stations, and corresponding reservoir flood control scheduling discharge flow, dam front water levels, and other hydrological and scheduling operation data.

[0048] Among them: the topographic data of the river section along the reservoir area and the distance from the dam refers to the location of the latest measured cross section along the reservoir area and the distance from the starting point of each node of the cross section, the riverbed elevation, etc.; the statistical data of the number of submerged objects at different elevations in the reservoir area can be obtained by visiting the reservoir area after the reservoir is built, conducting on-site visits and investigations, or by interpreting satellite and aerial photos of the reservoir area.

[0049] Step 2: Construct a real-time water surface line simulation model of the reservoir area with multiple inflow points. Specifically, this step includes the following sub-steps:

[0050] Step 2.1, for the collected S The river sections along the reservoir area are numbered sequentially from downstream to upstream. Topographical data and distance from the dam are collected for each section to divide the river into segments. Section 1 is generally the section where the dam site is located. S Section number 1 is generally the section where the main stream flows into the reservoir.

[0051] Step 2.2, based on spatial topological relationships, divide the reservoir area into... KThe tributary rivers are connected to the river channel in turn as concentrated lateral inflow, and the hydraulic characteristics of the cross section of each tributary inflow point are generalized according to the parameters of the most adjacent cross sections upstream and downstream of the inflow point.

[0052] Step 2.3, a one-dimensional hydrodynamic model of the reservoir area is established, the measured water level-flow process of the control hydrological station in the reservoir area during the flood season and the corresponding reservoir flood control scheduling discharge and dam front water level data are used to calibrate the roughness of each cross section in each river section.

[0053] Specifically, the one-dimensional constant flow or unsteady flow hydrodynamic model of the reservoir area can be selected and established according to the characteristics of flood evolution, river terrain conditions, and data mastery.

[0054] To establish the one-dimensional constant flow hydrodynamic model of the reservoir area, the cross section of the reservoir area is usually taken as a representative of the hydraulic characteristics along the way, the inflow and outflow processes and the dam front water level process are simplified, and the local head loss and the non-uniformity coefficient of flow velocity are ignored. Based on the theory of constant non-uniform gradually varied flow, the hydrodynamic model of the reservoir area is constructed.

[0055] To establish the one-dimensional unsteady flow hydrodynamic model of the reservoir area, the Preissmann four-point implicit difference format is used to discretize the Saint-Venant equation set, and the chasing method is used to solve the equation set, which can realize the continuous simulation of the water surface line of the reservoir area.

[0056] Step 2.4, the water level and flow of each cross section are initialized, the flow of the No. S cross section is taken as the upper boundary, and the water level or flow of the No. 1 cross section is taken as the lower boundary, and the water level is calculated cross section by cross section to obtain the real-time water surface line of the reservoir area.

[0057] Step 3, generate the combination of reservoir trunk and tributary inflow and flood control scheduling control parameters. Specifically, this step includes the following sub-steps:

[0058] Step 3.1, according to the long series of synchronous flood data and frequency distribution statistical parameters of the reservoir trunk and tributary inflow control stations, the master-slave station method is used to randomly generate N combination of trunk and tributary inflow , wherein is the No. i trunk inflow, is the No. k trunk inflow. i

[0059] Specifically, the master-slave station method generally takes the trunk inflow control station with large control basin area and significant backwater influence on the reservoir area as the master station, and takes each tributary inflow station as the slave station. First, the master station flood is randomly simulated, and then the slave station flood is indirectly generated from the master station flood by maintaining the main statistical characteristics of the slave station flood and the zero-order cross correlation of the master station and slave station flood in space. ​

[0060] Step 3.2, set the reservoir's flood control limit water level. Z FCL Up to flood control high water level Z FSL The water level range between the two values ​​is determined by the step size Δ. Z Discretize the data and use Bootstrap resampling technology to generate... N Water level in front of the dam Z i ( i =1,2,..., N ), and in turn for each group Z i At the minimum discharge flow rate of the reservoir Water level in front of the dam Z i Corresponding discharge capacity Within the value range, a set of outflow rates is randomly generated. .

[0061] Specifically, when the water level in front of the reservoir dam is at [ Z FCL , Z FSL Within the specified interval, the reservoir can play a flood control role downstream through flood control scheduling; Bootstrap resampling technology, through […]. Z FCL , Z FSL The feasible values ​​of the water level in front of the dam within the interval are sampled repeatedly with replacement and equal probability to achieve random generation of the water level in front of the dam; in order to reduce sampling error and to closely reflect flood control scheduling practice, it is required that... .

[0062] Step 3.3, will N Inflow of water into the main and tributary reservoirs and flood control scheduling and control parameter scheme Perform a random combination without replacement to obtain N Combined working conditions .

[0063] Step 4: Using the model constructed in Step 2, traverse and simulate the real-time water surface lines of the reservoir area under each combination of working conditions generated in Step 3, and statistically analyze the reservoir inundation index under each combination of working conditions.

[0064] Specifically, reservoir inundation indicators include land acquisition line inundation indicators and resident relocation line inundation indicators. By comparing the real-time water level line of the reservoir with the land acquisition line or resident relocation line, and combining this with statistics on the quantity of inundated objects at different elevations in the reservoir, a set of indicators U={ can be quantitatively calculated and reflects the scope and degree of reservoir flood control scheduling inundation impact. U 1, U2,..., U J}

[0065] in: U j ( j =1,2,..., J This includes, but is not limited to, quantitative indicators such as the inundation mileage, average inundation depth, and maximum inundation freeboard under various combined working conditions, or physical quantitative indicators such as the population affected by the inundation area, the area of ​​inundated farmland, and economic losses.

[0066] Step 5, obtained from steps 3 and 4 above. N The boundary conditions for calculating the water surface line of the reservoir area and the corresponding statistical samples of inundation indicators are used. Based on the principle of maximum entropy, the probability distribution that maximizes the joint information entropy of the random variables while keeping the main statistical characteristics of the random variable system unchanged is solved. This distribution serves as the inflow rate Q of the reservoir's main tributaries and the water level in front of the dam, as described in this invention. Z Downflow The joint probability distribution density function of the random variable system composed of the reservoir inundation index U. Specifically, obtaining the joint probability distribution density function of a system of random variables can be described as the following mathematical programming problem:

[0067] Objective function: ;

[0068] In the formula: The joint information entropy of the random variable system X; f (x) is the joint probability distribution function of the system of random variables; R is the Euclidean space with the same dimension as the number of system variables.

[0069] Constraints: ;

[0070] In the formula: g m (x) and EX [ g m (x)] are respectively the first m =1,2,..., M A function of a known random variable system X and its corresponding expected value. g m (x) Use the low-order raw moments, sample moments, or moment products of each random variable to preserve the statistical characteristics of the random variable system, such as expectation, variance, skewness coefficient, and correlation.

[0071] For example, in conjunction with the random variable system described in this invention, some typical constraints can be described as follows:

[0072] ;

[0073] ;

[0074] ;

[0075] ;

[0076] In particular, to ensure the normalization and normalization of the probability density function, the following constraints also need to be met:

[0077] .

[0078] By reasonably setting the number of constraint conditions, the Lagrange multiplier method is used to solve the above constrained maximum optimization problem to estimate the shape, scale and location of f (x) parameters, and then obtain f (x).

[0079] Specifically, the form of (x) described by the Lagrange multiplier f is as follows:

[0080] , where .

[0081] The more the number of general constraints, the higher the accuracy of the joint distribution construction, but the number of distribution parameters (Lagrange multipliers) to be estimated is also more, and the number of samples required for estimating parameters is also more.

[0082] Step 6, construct the conditional probability conversion model between the reservoir trunk and branch inflow, flood control scheduling control parameters and reservoir inundation indicators, and make reservoir inundation risk atlas.

[0083] Specifically, according to the size of the forecast reservoir inflow in the period, the height of the real-time dam water level, etc., the reservoir inundation risk value atlas or the reservoir inundation risk early warning atlas can be selected to be constructed. Specifically:

[0084] When the forecast inflow is large or the dam water level is high, the reservoir inundation risk is difficult to avoid, and the reservoir inundation risk value atlas can be selected to be constructed, including the following steps: according to the downstream flood control demand in the period, the reservoir trunk and branch inflow forecast value Q=q and the preset flood control scheduling control parameter Z = z , , the bounded multiple integral of is carried out to obtain the conditional probability distribution density function of the reservoir inundation indicator in the period ; combining the recognized standard and artificial experience, dividing the risk consequence severity level corresponding to the threshold of different reservoir inundation indexes; obtaining the conditional probability distribution density function carrying out continuous spatial multiple integrals, obtaining the cumulative probability of different reservoir inundation index thresholds, and dividing the risk occurrence possibility level; comprehensively considering the risk occurrence possibility and the consequence severity level corresponding to the threshold of different reservoir inundation indexes, calculating the risk value, and obtaining the reservoir inundation risk value atlas.

[0085] For example, Table 1 lists a reference risk value level division standard.

[0086] Table 1 Risk Value Level Standard

[0087]

[0088] For example, Table 2 and Table 3 respectively list a reference risk occurrence possibility and risk consequence severity level division standard.

[0089] Table 2 Risk Occurrence Possibility Level Standard

[0090] Grade 1 2 3 4 5 Qualitative Description Extremely low, almost impossible to occur Low, difficult to occur Medium, occasional occurrence High, likely to occur Extremely high, frequent occurrence Probability Interval 0.00001～0.001 0.001～0.1 0.1～0.5 0.5～0.9 0.9～1.0

[0091] Table 3 Risk Consequence Severity Level Standard

[0092] Grade Submersion Area Population Affected Submersion Farmland Area Economic Loss 1 Below 50,000 people Below 100,000 mu Below 5 million yuan 2 50,000-100,000 people 100,000-200,000 mu 500-1,000 million yuan 3 100,000-200,000 people 200,000-500,000 mu 1,000-5,000 million yuan 4 200,000-500,000 people 500,000-1,000,000 mu 5,000-10 billion yuan 5 More than 500,000 people More than 1,000,000 mu More than 10 billion yuan

[0093] When the forecasted reservoir inflow is not large or the water level before the dam is not high, and the reservoir inundation risk can be avoided or reduced, a reservoir inundation early warning atlas can be constructed, including the following steps: according to the reservoir inundation risk control target, giving the reservoir inundation index U = u in the face period, obtaining the conditional probability distribution density function carrying out bounded multiple integrals, obtaining the conditional probability distribution density function of the combination working condition of the reservoir trunk and branch inflow and the flood control scheduling control parameter in the face period ; according to the downstream flood control demand in the face period, assuming the reservoir outflow , and trying to calculate the integral upper limit of the water level before the dam with the cumulative probability not lower than a certain acceptable risk level under the condition of different reservoir trunk and branch inflow Q = q, as the critical early warning water level for avoiding or reducing reservoir inundation, and obtaining the reservoir inundation risk early warning atlas. Z

[0094] Specifically, in real-time scheduling, according to the reservoir trunk and branch inflow forecast, if the water level before the dam is close to or higher than the corresponding critical early warning water level of each level, early warning needs to be issued in time, and certain risk countermeasures need to be taken, including close monitoring, taking measures to reduce the water level, and switching to flood control scheduling, etc.

[0095] ​Taking a control reservoir A in the main stream of the Yangtze River as an example, a flood control scheduling scheme reservoir inundation risk atlas is constructed, and the specific implementation manner is as follows:

[0096] According to step 1, collect and organize the basic data of A reservoir. The flood control limit water level of A reservoir is 145 m, the normal storage water level is 175 m, the flood control high water level is 175 m, and the flood control storage capacity is 221.5 billion m 3 ; The land expropriation standard is 5 years, and the backwater end is DTB section; The resident relocation standard is 20 years, and the backwater end is DZT; CT is the main stream control station, the main tributary control station is WL, and the reservoir area along the way control hydrological station also includes YJW, MD, WJT, CS, WG, ZJYZ, ST, QXC, ZX, WX, FJ, WS, BD, ZG, etc.

[0097] In 2020, the largest reservoir flood since the construction of A reservoir occurred in the flood season, and A reservoir played an important role in flood control. The reservoir water level continued to rise, and the reservoir flood control situation was once tense. Figure 2 The contrast diagram of the reservoir water surface line envelope line and the land expropriation line and the resident relocation line of A reservoir in the flood season of 2020 is shown. As shown in the figure, there is a part of the time period, the real-time water surface line of the reservoir exceeds the land expropriation line at the section above QXC station, and some sections even exceed the resident relocation line, causing temporary inundation of the reservoir area.

[0098] According to step 2, a real-time water surface line simulation model of A reservoir with multiple reservoir points is constructed. Based on the latest survey of 319 sections of terrain from the main stream control station CT to the dam, a one-dimensional unsteady flow hydrodynamic model of the reservoir area with 1 main stream (control station CT) and 1 main tributary (control station WL) is constructed, a total of 2 reservoir points, and the discharge and dam water level change process of 6 measured flood processes and corresponding flood control scheduling in the flood season since 2012 are used as the upper and lower boundaries to calibrate the model parameters. Figure 3 The simulation result diagram of QXC station in the flood process of A reservoir in July-August 2020 is shown. As shown in the figure, the water level process simulated by the constructed real-time water surface line model of the reservoir area can well coincide with the measured water level process.

[0099] According to step 3, the combination of A reservoir dry and branch flow and flood control scheduling control parameter combination is generated. CT station is the main station, WL station is the slave station, and 100000 groups of dry and branch flow combination N are randomly generated ; Δ Z =0.01m discrete A reservoir [145m,175m] water level value interval.

[0100] According to step 4, the real-time water surface line of the A reservoir area under each combined working condition is simulated, and the inundation indexes of the reservoir area under each combined working condition are counted. In order to more popularly and intuitively illustrate the embodiment of the present application, the present embodiment of the present application only takes the maximum inundation superhigh H As a representative inundation index, the maximum value of the difference between the backwater elevation of each section of the simulated reservoir water surface line and the backwater elevation of the connecting line of the most adjacent upstream and downstream boundary piles of the land acquisition line or the resident relocation line at the section is taken.

[0101] Table 4 lists the maximum inundation superhigh indexes of the reservoir water surface line relative to the resident relocation line under some combined working conditions. As can be seen from Table 4, the sensitive inundation river section of the A reservoir area is mainly located between the ST and DZT sections, and the maximum inundation superhigh usually occurs at the CS section.

[0102] Table 4 maximum inundation superhigh indexes of the reservoir water surface line relative to the resident relocation line under some combined working conditions

[0103]

[0104] According to step 5, based on the joint information entropy and the maximum entropy principle, a multivariate joint probability distribution function of the A reservoir main stream CT, the main tributary WL inflow, the dam front water level, the discharge flow and the maximum inundation superhigh H of the reservoir area is established. .

[0105] According to step 6, a conditional probability conversion model of the A reservoir main stream CT, the main tributary WL inflow, the dam front water level, the discharge flow and the maximum inundation superhigh H of the reservoir area is constructed, and a reservoir inundation risk quantity value atlas and a reservoir inundation risk early warning atlas are made.

[0106] In order to simplify and intuitively illustrate the construction effect of the A reservoir area inundation risk quantity value atlas, the present embodiment of the present application first fixes the facing time period Q out = q out , Q WL = q WL boundary, and focuses on Q CT and Z two elements which have the most significant influence on the reservoir backwater, sets different working condition combinations q CT and z , respectively obtains ; combined with the mapping relationship between the different maximum inundation superhigh amplitudes of the CS section and the inundation physical quantities of the reservoir at different elevations, the inundation risk consequence severity corresponding to different superhigh maximum inundation superhigh thresholds is divided; and the inundation risk consequence severity corresponding to different superhigh maximum inundation superhigh thresholds is obtained from The cumulative probability corresponding to different maximum inundation freeboard thresholds is calculated by integration to classify the likelihood of inundation risk occurrence; the risk value is calculated to obtain the inundation risk value spectrum of Reservoir A during the time period, as shown in the figure. Figure 4 As shown.

[0107] To simplify and intuitively illustrate the construction effect of the inundation risk early warning map for Reservoir A, this embodiment of the invention takes the control objective of avoiding inundation at any cross section of the reservoir area during the specified time period as an example, i.e., given... H =0, thus obtaining Similarly, different assumptions are made. Q out = q out , Q WL = q WL Trial calculations are different q CT Under the conditions The cumulative probability of the water level in front of the dam is not lower than a certain acceptable risk level. Z The upper bound of the integral is used as the critical warning water level to avoid or mitigate reservoir inundation, resulting in a reservoir inundation risk warning map for the A reservoir area during the facing period, as shown below. Figure 5 As shown.

[0108] The above analysis shows that by using the method described in this invention, a large number of numerical simulation experimental samples of reservoir water surface lines can be obtained offline. By fully utilizing the correlation between the inflow of water into the reservoir and its tributaries, the control parameters of the flood control scheduling scheme, and the inundation indicators of the reservoir area, the deterministic transformation process of calculating the real-time water surface line of the reservoir area and then statistically analyzing the inundation indicators based on the inflow and outflow of water into the reservoir and the water level boundary in front of the dam is replaced by a conditional probability transformation process based on a multivariate joint probability distribution. This helps to reduce the uncertainty of inputs and models during the calculation process, and can also reversely obtain the critical conditions for controlling the inundation risk of the reservoir area, providing richer decision-making information, saving the time cost of complex hydrodynamic calculations, and improving the robustness and timeliness of flood control scheduling.

[0109] The above embodiments are merely preferred technical solutions of the present invention and should not be considered as limitations on the present invention. The embodiments and features described in these embodiments can be arbitrarily combined without conflict. The scope of protection of the present invention should be limited to the technical solutions described in the claims, including equivalent substitutions of the technical features described in the claims. That is, equivalent substitutions and improvements within this scope are also within the scope of protection of the present invention.

Claims

1. A method for constructing a reservoir inundation risk map for a reservoir flood control scheduling scheme, characterized in that, Includes the following steps: Step 1: Basic data collection and organization; Step 2: Construct a real-time water surface line simulation model of the reservoir area with multiple inflow points; Step 3: Generate the combined operating conditions of the reservoir's main and tributary inflows and flood control scheduling parameters; Step 4: Using the model constructed in Step 2, traverse and simulate the real-time water surface line of the reservoir area under each combination of working conditions generated in Step 3, and statistically analyze the reservoir inundation index under each combination of working conditions. Step 5: Establish a multivariate joint probability distribution function of the inflow of the main and tributary reservoirs, flood control scheduling parameters, and reservoir inundation indicators; Step 6: Construct a conditional probability transformation model between the inflow of water into the reservoir and its tributaries, flood control scheduling parameters and reservoir inundation indicators, and create a reservoir inundation risk map; In step 1, the basic data includes the reservoir's characteristic water level, water level-reservoir capacity curve, discharge capacity curve, topography of the river section along the reservoir area and distance from the dam, location and elevation of land acquisition boundary markers, location and elevation of resident relocation boundary markers, statistics on the number of submerged objects at different elevations in the reservoir area, and minimum discharge flow data of the reservoir; synchronous flood data and frequency distribution statistics of the main and tributary inflow control stations in the reservoir area, water level and flow processes of the reservoir area's control hydrological stations for measured flood events since the reservoir's construction, and hydrological and operational data on the discharge flow and upstream water level of the corresponding reservoir during the entire flood control scheduling process; In step 2, constructing a real-time water surface line simulation model of the reservoir area with multiple inflow points includes the following steps: Step 2-1, for the collected S The river sections along the reservoir area are numbered sequentially from downstream to upstream. Topographical data and distance from the dam are collected for each section to divide the river into segments. Section 1 is the section where the dam site is located. S Section No. 1 is the section where the main inflow point is located; Step 2-2: Establish a one-dimensional hydrodynamic model of the reservoir area. Use the measured flood level and flow process of the reservoir area's controlling hydrological station and the corresponding reservoir flood control scheduling process discharge flow and upstream water level data to calibrate the roughness of each section by river segment. Steps 2-3: Initialize the water level and flow rate at each cross-section, using the first... S The upper boundary is the flow rate at section 1, and the lower boundary is the water level or flow rate at section 1. The water level is calculated section by section to obtain the real-time water surface line of the reservoir area. In step 3, generating the combined operating conditions of the reservoir's main and tributary inflows and flood control scheduling parameters includes the following steps: Step 3-1: Based on the synchronous flood data and frequency distribution statistical parameters of the main and tributary inflow control stations in the reservoir area, the master-slave station method is used to randomly generate... N Group of tributary inflow and outflow combinations ,in For the main stream i Group inbound flow For the first k The first tributary i Group inbound flow; Step 3-2, set the reservoir's flood control limit water level. Z FCL Up to flood control high water level Z FSL The water level range between the two values ​​is determined by the step size Δ. Z Discretize the data and use Bootstrap resampling technology to generate... N Water level in front of the dam Z i ( i =1,2,..., N ), and in turn for each group Z i At the minimum discharge flow rate of the reservoir Water level in front of the dam Z i Corresponding discharge capacity Within the value range, a set of outflow rates is randomly generated. ; Step 3-3, will N Inflow of water into the main and tributary reservoirs and flood control scheduling and control parameter scheme Perform a random combination without replacement to obtain N Combined working conditions .

2. The method for constructing a reservoir inundation risk map according to claim 1, characterized in that: in In steps 2 and 3, based on the characteristics of flood evolution, river topography, and available data, a one-dimensional steady flow or unsteady flow hydrodynamic model for the reservoir area is selected.

3. The method for constructing a reservoir inundation risk map according to claim 1, characterized in that: in In step 3-2, to reduce sampling error and to closely reflect flood control scheduling practices, .

4. The method for constructing a reservoir inundation risk map according to claim 1, characterized in that: in In step 4, the reservoir inundation indicators include land acquisition line inundation indicators and resident relocation line inundation indicators. By comparing the real-time water level line of the reservoir with the land acquisition line or resident relocation line, a set of indicators U={ can be statistically estimated to reflect the scope and degree of reservoir flood control scheduling inundation impact. U 1, U 2,..., U J } 5. The method for constructing a reservoir inundation risk map according to claim 1, characterized in that: in In step 5, the data obtained from steps 3 and 4... N The calculation of the water surface line boundary conditions and corresponding inundation index statistical samples in the reservoir area is based on the maximum entropy principle. This is achieved by solving the probability distribution that maximizes the joint information entropy of the random variables while maintaining the main statistical characteristics of the system. This distribution serves as the inflow rate Q of the reservoir's main tributaries and the water level in front of the dam. Z Downflow The joint probability distribution density function of the random variable system composed of the reservoir inundation index U. Obtaining the joint probability density function of a system of random variables is described as the following mathematical programming problem: Objective function: In the formula: The joint information entropy of the random variable system X; f (x) is the joint probability distribution function of the system of random variables; R is the Euclidean space with the same dimension as the number of system variables; Constraints: ; In the formula: g m (x) and EX [ g m (x)] are respectively the first m =1,2,..., M A function of a known random variable system X and its corresponding expected value; g m (x) Use the low-order raw moments, sample moments, or moment product functions of each random variable to preserve the expected value, variance, skewness coefficient, and correlation statistical characteristics of the random variable system; To ensure the normalization and standardization of the probability density function, the following constraints must also be satisfied: ； By appropriately setting the number of constraints, the Lagrange multiplier method is used to solve the constrained maximization problem to estimate the optimal value. f The shape, scale, and position parameters of (x) are then used to obtain... f (x).

6. The method for constructing a reservoir inundation risk map according to claim 1, characterized in that: in In step 6, based on the predicted inflow rate and real-time water level in front of the dam during the expected time period, either a reservoir inundation risk value map or a reservoir inundation risk early warning map is selected. When the predicted inflow rate is large or the water level in front of the dam is high, making it difficult to avoid the reservoir inundation risk, a reservoir inundation risk value map is selected, including the following steps: Based on the downstream flood control demand during the expected period, given the predicted inflow values ​​of the reservoir's main and tributary inflows Q=q and the preset flood control scheduling parameters... Z = z , ,right By performing bounded multiple integrals, we obtain the conditional probability distribution density function of the reservoir inundation index for the facing period. Combining recognized standards and human experience, the severity levels of risk consequences corresponding to different reservoir inundation index thresholds are classified; based on the conditional probability distribution density function... By performing multiple integrations in continuous space, the cumulative probability of inundation index thresholds for different reservoir areas is obtained, and the risk occurrence probability levels are classified. By combining the risk occurrence probability and the severity level of consequences corresponding to different inundation index thresholds for different reservoir areas, the risk value is calculated, and the reservoir inundation risk value map is obtained. When the predicted inflow is not large or the water level in front of the dam is not high, and the risk of reservoir inundation can be avoided or mitigated, the reservoir inundation early warning map is constructed, including the following steps: Based on the reservoir inundation risk control objectives, and given the inundation index U=u for the period in which the reservoir is expected to be flooded, By performing bounded multiple integrations, we obtain the conditional probability distribution density function of the combined operating conditions of the reservoir's main and tributary inflows and flood control scheduling parameters during the given time period. Based on the downstream flood control needs during the current period, the reservoir discharge flow rate is assumed to be... Calculate the inflow rates of different reservoirs and tributaries under the condition Q=q. The cumulative probability of the water level in front of the dam is not lower than a certain acceptable risk level. Z The upper bound of the integral is used as the critical warning water level to avoid or mitigate reservoir inundation, thus obtaining the reservoir inundation risk warning map.

Images