Method for determining designed flood hygrograph of river-through lake

Abstract

The invention discloses a river-through lake design flood hydrograph determination method, and belongs to the technical field of hydraulic engineering design, and the method comprises the steps: S1, collecting the historical flood data of each river entering the lake, including the flood hydrographs of different years, and the basic data of a reservoir on each river entering the lake; s2, preprocessing the data in the step S1, and setting a fault-tolerant mechanism; s3, for the reservoirs on the lake-entering rivers, adjusting and calculating the flood by adopting a water balance method to obtain the flood process of the lake-entering rivers adjusted by the reservoirs; s4, establishing joint probability distribution based on a Copula function; s5, generating a flood hydrograph; according to the method for determining the design flood hydrograph of the river-through lake provided by the invention, the influence of the flood and reservoir regulation of the river entering the lake can be comprehensively considered, and the correlation of the flood characteristic variables is accurately described based on the Copula function; a lake design flood hydrograph which is more practical can be generated, the flood risk handling capacity of a project is improved, and regional safety and stability are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy project design, and in particular to a method for determining the design flood hydrograph of a lake connected to a river. Background Art

[0002] In the basin system of large lakes connected to rivers, the flood problem is of crucial importance. Taking Dongting Lake as an example, it has four rivers flowing into the lake, namely the Xiangjiang River, Zishui River, Yuanjiang River, and Lishui River. At the same time, three distributaries of the Yangtze River, namely the Songzi River, Taiping River, and Ouchi River, also flow into it, and its outflow returns to the Yangtze River at the Chenglingji section. The catchment area of such lakes is vast, and the confluence area of the large rivers flowing into the lake is also very large. Moreover, the diversion flow of the large rivers flowing into the lake is related to the water surface height of the diversion point, making the flood situation extremely complex. Accurately determining the design flood hydrograph of a lake connected to a river is of great significance for flood control and disaster reduction, water conservancy project planning, and rational allocation of water resources in the lake basin.

[0003] Traditional flood calculation methods, such as using single-variable probability distributions to describe flood characteristic quantities, ignore the correlation between various characteristic quantities and are difficult to accurately reflect the true characteristics of floods. When hydrological models are applied to flood calculation in small basins, problems such as parameter transplantation and lack of calibration with measured data often lead to difficulties in ensuring the calculation accuracy. Therefore, it is urgent to explore a more scientific and effective method for determining the design flood hydrograph of a lake connected to a river.

[0004] As a tool that can effectively describe the correlation of multiple variables, the Copula function has been widely used in the field of flood simulation. It can connect the marginal distributions of multiple random variables to construct a joint distribution, thereby more comprehensively describing the relationship between multiple characteristic quantities in the flood process. Based on this, the present invention proposes a method for determining the design flood hydrograph of a lake connected to a river using the Copula function, aiming to improve the accuracy and reliability of flood simulation. Summary of the Invention

[0005] The object of the present invention is to provide a method for determining the design flood hydrograph of a lake connected to a river, so as to overcome the defects that traditional methods cannot accurately reflect the correlation of multiple variables and the influence of reservoir regulation. The present invention collects multi-source flood data, combines the water balance method to simulate the reservoir regulation effect, constructs the joint distribution of flood characteristic variables based on the Copula function, and uses Monte Carlo simulation to generate the design flood hydrograph, thereby improving the accuracy and reliability of flood simulation.

[0006] To achieve the above object, the present invention provides a method for determining the design flood hydrograph of a lake connected to a river, including the following steps:

[0007] S1. Collect historical flood data of rivers entering the lake, including the process lines of water level and flow over time, as well as the reservoir capacity curve, flood discharge capacity curve and dispatch records; at the same time, sort out the water level-flow relationship and basin topography and meteorological data of the diversion outlets of large rivers. The data must be complete and verified to ensure the accuracy of the simulation.

[0008] S2, preprocessing the data in step S1 and setting a fault tolerance mechanism;

[0009] S3. For each reservoir on the rivers entering the lake, the water balance method is used to adjust and calculate the flood, and the flood process of each river entering the lake after the reservoir is adjusted is obtained;

[0010] S4, establish joint probability distribution based on Copula function;

[0011] S5. Generation of flood process lines.

[0012] Preferably, in step S2, the historical flood process line collected in step S1 is checked for data points in the time series, and if there is data missing, a linear interpolation method is used for processing, specifically including:

[0013] For a time point t with missing data in the flood process line of a river entering the lake, find the two adjacent time points t1 and t2 and their corresponding flood flow values ​​X1 and X2, and t1 <t<t2,通过公式 The estimated flood flow at time t is calculated to fill in the missing data. For some continuously changing data in the reservoir basic data (such as the data of reservoir capacity changing with water level), if the data interval is too large, the interpolation method is also used to encrypt the data points to improve the accuracy and continuity of the data.

[0014] The fault tolerance mechanisms that are set include:

[0015] (1) Data missing processing: If missing values ​​are found in historical flood data or reservoir basic information, the missing data of short periods of time in the flood process line can be supplemented by linear interpolation of data from adjacent time points; for data with a large number of missing values, historical data of similar rivers or reservoirs in the same basin can be used for estimation and filling, and proper marking and explanation should be made.

[0016] (2) Outlier detection and processing: Identify outliers in flood data through statistical analysis methods. For outliers, first check their source. If it is a recording error, correct it; if it is a reasonable outlier caused by a special flood event, record it separately and take its particularity into account in subsequent analysis.

[0017] (3) Data consistency check: Compare the logical relationships between the flood data of each incoming river and between the flood data and the basic reservoir information to check for any contradictions. If inconsistencies are found, trace the data sources, verify and correct them. If the correct data cannot be determined, mark the relevant data and handle it using the principle of conservative estimation in subsequent calculations.

[0018] Preferably, the specific steps of step S3 include:

[0019] S31. Based on the various data collected in S1, determine the calculation time interval Δt. The time interval should not be too long to avoid ignoring important changes in the flood process, nor too short to avoid excessive calculation. Usually, 1 hour, 3 hours, etc. can be selected as the calculation time interval.

[0020] S32. Define the starting time t1 of the calculation, and determine the initial water storage V1, incoming flow Q1, and outgoing flow q1 of the reservoir at this time. The initial water level can be obtained from the previous monitoring data or relevant information, and then the initial water storage can be obtained through the storage capacity curve. The incoming flow can be obtained from the flood data of the incoming rivers. If there are no available measured data for the outgoing flow, it can be estimated according to the reservoir operation rules and previous operation conditions.

[0021] S33. Within each calculation time interval, based on the principle of water balance, that is, the difference between the incoming water volume and the outgoing water volume is equal to the change in the reservoir water storage, use the water balance equation to calculate the water storage of the reservoir. Where Q1 and Q2 are the incoming flows at time t1 and t2, with the unit of m 3 / s; q1 and q2 are the outgoing flows at time t1 and t2, with the unit of m 3 / s; V1 and V2 are the reservoir capacities at time t1 and t2.

[0022] S34. According to the reservoir operation rules and the current water storage, calculate the outgoing flow q2 at time t2 in combination with the flood discharge capacity curve.

[0023] S35. Based on the calculated water storage V2 and outgoing flow q2 at time t2, update the state information of the reservoir to provide a basis for the next moment's calculation.

[0024] S36. Repeat steps S33 - S35 until the calculation of the entire flood process is completed, obtaining the change processes of the incoming flow, outgoing flow, and reservoir water storage after reservoir regulation for each calculation time interval.

[0025] S37. Organize the inflow discharges after reservoir regulation for each time period obtained, arrange them in chronological order, and form the flood process data series of each river flowing into the lake. These data can reflect the regulation effect of the reservoir on the floods of the rivers flowing into the lake and provide more realistic basic data for the subsequent establishment of the joint probability distribution of the floods encountered by each river flowing into the lake.

[0026] Preferably, the specific steps of step S4 include:

[0027] S41. Select flood characteristic variables from the flood processes of each river flowing into the lake after reservoir regulation, including the peak flood Q and the flood volume W.

[0028] S42. Determine the marginal distribution function for each selected flood characteristic variable.

[0029] S43. Select a suitable Copula function. Commonly used Copula functions can generally be divided into elliptical, quadratic, and Archimedean types. Archimedean Copula functions include symmetric and asymmetric types.

[0030] S44. Substitute the marginal distribution functions of each characteristic variable into the selected Copula function and determine the parameters to obtain the joint distribution function of the flood characteristic variables of each river flowing into the lake.

[0031] Preferably, the distribution functions of the peak flood Q and the flood volume W in step S42 are:

[0032]

[0033] Among them, q0 and w0 respectively represent the given values of the peak flood and the flood volume in a time period. According to the marginal distribution probability theorem, the two-dimensional discrete frequency calculation formula is:

[0034]

[0035] Among them, a, β, and a0 are respectively shape, scale, and location parameters used to measure flood characteristics, and Γ is the gamma function.

[0036] Preferably, step S43 adopts a symmetric Archimedean Copula function, which has a simple structure, few parameters, and is convenient to solve.

[0037] Preferably, step S44 specifically includes:

[0038] S441. Fit the distribution functions of the peak flood Q and the flood volume W according to the measured floods.

[0039] S442. Substitute the distribution functions of the peak flood Q and the flood volume W into the expression of the Archimedean Copula function and solve the parameters by the maximum likelihood method.

[0040] S443. Select the optimal function type through goodness-of-fit tests (such as the K-S test) to determine the Copula function form.

[0041] Preferably, the expression of the Archimedean Copula function in step S442 is:

[0042]

[0043] where, is the generator of the Archimedean Copula function, and α is the parameter of the Archimedean Copula function, t is the marginal distribution value of the flood peak Q and the flood volume W, is the inverse function of.

[0044] Preferably, the specific steps of step S5 include:

[0045] S51. After knowing the joint distribution of the flood characteristic variables, conduct stochastic simulation using the Monte Carlo simulation method;

[0046] S52. Select a typical flood hydrograph, longitudinally magnify it according to the flood peak and flood volume parameters simulated in S41 to obtain a flood sequence, and conduct statistical analysis based on the flood sequence to obtain the design flood characteristic values under different return periods, thereby determining the design flood hydrograph entering the lake.

[0047] Preferably, step S51 specifically includes:

[0048] Randomly draw a flood peak value according to the probability distribution of the flood peak flow;

[0049] Use the generated flood peak value and its joint distribution with the flood volume to randomly generate the corresponding flood volume value to complete one simulation;

[0050] Repeat the above steps multiple times to generate multiple sets of correlated flood peak and flood volume values.

[0051] Therefore, the present invention adopts the above method for determining the design flood hydrograph of a connected lake, and has the following beneficial effects:

[0052] (1) By collecting multi-source data and considering reservoir regulation, ensure that the construction of the flood hydrograph is based on a detailed and practical basis;

[0053] (2) Use the Copula function to construct the joint distribution, effectively consider the correlation between flood characteristic variables, and improve the simulation accuracy;

[0054] (3) Adopt Monte Carlo simulation and typical flood magnification to generate multiple sets of flood sequences and determine characteristic values, providing strong support for flood control and other decisions.

[0055] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Description of the Drawings

[0056] Figure 1 It is a flowchart of a method for determining the design flood hydrograph of a river-connected lake of the present invention;

[0057] Figure 2 It is a flowchart of obtaining the flood hydrographs of each river flowing into the lake after reservoir regulation of the present invention;

[0058] Figure 3 It is a flowchart of establishing a joint probability distribution based on the Copula function of the present invention;

[0059] Figure 4 It is a flowchart of obtaining the joint distribution function of the flood characteristic variables of each river flowing into the lake of the present invention;

[0060] Figure 5 It is a flowchart of flood hydrograph generation of the present invention. Detailed Embodiments

[0061] The following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0062] Please refer to Figures 1 - 5 , a method for determining the design flood hydrograph of a river-connected lake. Taking a certain river-connected lake as an example, it includes the following steps:

[0063] S1. Collect the historical flood data of each river flowing into the lake, including the flood hydrographs (data of water level and flow rate varying with time) in different years, as well as the basic information of the reservoirs on each river flowing into the lake, such as the reservoir capacity curve, flood discharge capacity curve, annual operation plans, and actual operation records, etc., so as to accurately simulate the regulation effect of the reservoir on floods; in addition, it is also necessary to sort out the water level-flow rate relationship data of the diversion outlets of large rivers, as well as the topographic, meteorological and other relevant information within the confluence area of the large rivers flowing into the lake. This information is crucial for analyzing the flood situation of the large rivers diverting and flowing into the lake and understanding the flood formation mechanism of the entire basin.

[0064] S2. Preprocess the data in step S1 and set a fault tolerance mechanism, specifically including:

[0065] For the historical flood hydrographs collected in step S1, check the data points in the time series. If there are data missing situations, linear interpolation method is used for processing, specifically including:

[0066] For a time point \(t\) with missing data in the flood hydrograph of a certain river flowing into the lake, find two adjacent time points \(t_1\), \(t_2\) and their corresponding flood discharge values \(X_1\), \(X_2\), where \(t_1 < t < t_2\). Calculate the estimated flood discharge value at time \(t\) using the formula to fill in the missing data. For some continuously varying data in the basic reservoir data (such as the data of reservoir storage capacity varying with water level), if there is a large data interval, interpolation method is also used to densify the data points to improve the accuracy and continuity of the data.

[0067] The set fault tolerance mechanism specifically includes:

[0068] (1) Missing data processing: If missing values are found in the historical flood data or the basic reservoir data, for the short-term missing data in the flood hydrograph, linear interpolation method of adjacent time point data can be used for supplementation; for the data with more missing values, historical data of similar rivers or reservoirs in the same basin can be referred to for estimation and filling, and marks should be made for explanation.

[0069] (2) Outlier detection and processing: Identify outliers in the flood data through statistical analysis methods. For outliers, first check their sources. If it is a recording error, it should be corrected; if it is a reasonable outlier caused by a special flood event, it should be recorded separately and its particularity should be considered in subsequent analysis.

[0070] (3) Data consistency check: Compare the logical relationships between the flood data of each river flowing into the lake, and between the flood data and the basic reservoir data to check whether there are contradictions. If inconsistencies are found, trace the data sources, verify and correct them. If the correct data cannot be determined, mark the relevant data and adopt the principle of conservative estimation in subsequent calculations.

[0071] S3. For the reservoirs on each river flowing into the lake, use the water balance method to conduct flood regulation calculations to obtain the flood hydrographs of each river flowing into the lake after reservoir regulation. The specific steps include:

[0072] S31. According to various data collected in S1, determine that the calculation time interval \(\Delta t\) is 1 hour;

[0073] S32. Define the starting time \(t_1\) of the calculation, and determine the initial reservoir storage volumes \(V_1\), \(V_2\), the inflow discharges \(Q_1\), \(Q_2\) and the outflow discharges \(q_1\), \(q_2\) of the reservoir at this time;

[0074] S33. In each calculation time interval, based on the water balance principle, that is, the difference between the inflow water volume and the outflow water volume is equal to the change in the reservoir storage volume, use the water balance equation to calculate the reservoir storage volume; where \(Q_1\), \(Q_2\) are the inflow discharges at time \(t_1\) and \(t_2\) of the time interval, with the unit of \(m\) 3 / s; q1 and q2 are the out - flow rates at time t1 and t2, with the unit of m 3 / s; V1 and V2 are the reservoir storage capacities at time t1 and t2;

[0075] S34. According to the reservoir operation rules and the current water storage V1, calculate the out - flow rate q2 at time t2 by combining with the flood - discharge capacity curve;

[0076] S35. Update the reservoir status information according to the calculated water storage V2 and out - flow rate q2 at time t2; Take V2 as the initial water storage V1 for the next calculation period, and q2 as the initial out - flow rate q1 for the next calculation period. Meanwhile, the inflow rate Q1 for the next calculation period can be obtained through time - series analysis or forecasting models of the flood data of the incoming rivers.

[0077] S36. Repeat steps S33 - S35 until the calculation of the entire flood process is completed, and obtain the variation processes of the inflow rate, out - flow rate, and reservoir water storage after reservoir regulation for each calculation period;

[0078] S37. Organize the out - flow rates after reservoir regulation for each period obtained, arrange them in chronological order, and form the flood process data sequences of each incoming river. These data can reflect the regulation effect of the reservoir on the floods of the incoming rivers, and provide more realistic basic data for establishing the joint probability distribution of the floods encountered by each incoming river later.

[0079] S4. Establish a joint probability distribution based on the Copula function. The specific steps include:

[0080] S41. Select the peak - flow rate Q and the 3 - day and 7 - day flood volumes W as flood characteristic variables from the flood processes of each incoming river after reservoir regulation;

[0081] S42. For each selected flood characteristic variable, determine the marginal distribution function; Through the goodness - of - fit test, it is determined that the peak - flow rate conforms to the P - III distribution, the 3 - day flood volume conforms to the Log - Logistic distribution, and the 7 - day flood volume conforms to the Weibull distribution. Their distribution functions are respectively:

[0082]

[0083] Among them, q0 and w0 respectively represent the given values of the peak - flow and the period flood volume. According to the marginal distribution probability theorem, the two - dimensional discrete - type frequency calculation formula is:

[0084]

[0085] Among them, a, β, and a0 are the shape, scale, and location parameters respectively, used to measure the flood characteristics, and Γ is the gamma function.

[0086] S43. The symmetric Archimedean Copula function is adopted, which has a simple structure, few parameters, and is convenient to solve.

[0087] S44. Substitute the marginal distribution functions of each characteristic variable into the selected Copula function and determine the parameters to obtain the joint distribution function of the flood characteristic variables of each river flowing into the lake, specifically including:

[0088] S441. Fit the distribution functions of the flood peak Q and the flood volume W according to the measured floods.

[0089] S442. Substitute the distribution functions of the flood peak Q and the flood volume W into the expression of the Archimedean Copula function, and solve the parameters by the maximum likelihood method; the expression of the Archimedean Copula function is:

[0090]

[0091] Among them, is the generator of the Archimedean Copula function, and α is the parameter of the Archimedean Copula function, t is the marginal distribution value of the flood peak Q and the flood volume W, is the inverse function of.

[0092] S443. Select the optimal function type through the goodness-of-fit test (such as the K-S test) to determine the Copula function form.

[0093] S5. Generation of the flood hydrograph, the specific steps include:

[0094] S51. After knowing the joint distribution of the flood characteristic variables, use the Monte Carlo simulation method for random simulation, specifically including:

[0095] Randomly extract a flood peak value according to the probability distribution of the flood peak discharge;

[0096] Use the generated flood peak value and its joint distribution with the flood volume to randomly generate the corresponding flood volume value to complete one simulation;

[0097] Repeat the above steps multiple times to generate multiple groups of correlated flood peak and flood volume values (the combination of flood peak discharge, 3-day flood volume, and 7-day flood volume).

[0098] S52. Select a typical flood hydrograph (such as a certain large flood hydrograph in history), and use the same ratio amplification method or the sub-period same-frequency control amplification method for vertical amplification according to the flood peak and flood volume parameters simulated by S41. For example, when amplifying by the flood peak control, the amplification ratio (Q d is the simulated flood peak discharge, Q p(which is the peak flow of the typical flood), magnify the flow at each moment of the typical flood hydrograph to obtain multiple flood sequences, and conduct statistical analysis based on the flood sequences to obtain the design flood characteristic values such as the peak flow, 3-day flood volume, 7-day flood volume, etc. under different return periods, so as to determine the flood hydrograph of the lake.

[0099] Therefore, the present invention adopts the above method for determining the design flood hydrograph of a lake communicating with the river, fully considering the correlation between the floods of the inflowing rivers and the influence of factors such as reservoir regulation and diversion of large rivers. By establishing a joint probability distribution and stochastic simulation, it can generate the design flood hydrograph of the lake more accurately and statistically obtain the corresponding flood characteristic values.

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that they can still modify or equivalently replace the technical solutions of the present invention, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for determining the design flood hydrograph of a river-connected lake, characterized in that It includes the following steps: S1. Collect the historical flood data of each river flowing into the lake, including the flood hydrographs of different years and the basic information of the reservoirs on each river flowing into the lake; S2. Preprocess the data in step S1 and set a fault tolerance mechanism; S3. For the reservoirs on each river flowing into the lake, use the water balance method to adjust and calculate the flood, and obtain the flood hydrographs of each river flowing into the lake after reservoir regulation; S4. Establish a joint probability distribution based on the Copula function; S5. Generation of flood hydrographs.

2. The method for determining the design flood hydrograph of a river-connected lake according to claim 1, wherein In step S2, for the historical flood hydrographs collected in step S1, check the data points in the time series. If there are missing data, use the linear interpolation method to process them. Specifically, it includes: For a time point t with missing data in the flood hydrograph of a certain river flowing into the lake, find two adjacent time points t1 and t2 and their corresponding flood flow values X1 and X2, where t1 < t < t2. Calculate the estimated flood flow value at time t through the formula to fill in the missing data.

3. The method for determining the design flood hydrograph of a lake connected to a river according to claim 1, wherein, The specific steps of step S3 include: S31. According to the various data collected in S1, determine the calculation time interval Δt; S32. Define the starting time t1 of the calculation, and determine the initial water storage V1, the inflow Q1 and the outflow q1 of the reservoir at this time; S33. During each calculation period, use the water balance equation to calculate the water storage volume of the reservoir; where, Q1 and Q2 are the inflow discharges at time t1 and t2, with the unit of m 3 / s; q1 and q2 are the outflow discharges at time t1 and t2, with the unit of m 3 / s; V1 and V2 are the reservoir capacities at time t1 and t2; S34. According to the reservoir operation rules and the current water storage, calculate the outflow at time t2 in combination with the flood discharge capacity curve; S35. Update the state information of the reservoir according to the calculated water storage and outflow at time t2; S36. Repeat steps S33 - S35 until the calculation of the entire flood process is completed, and obtain the change processes of the inflow, outflow and reservoir water storage of each river flowing into the lake after reservoir regulation in each calculation time interval; S37. Organize the inflows of each river flowing into the lake after reservoir regulation obtained in each time interval to form the flood hydrograph data series of each river flowing into the lake.

4. A method for determining the design flood hydrograph of a river-connected lake according to claim 1, characterized in that, The specific steps of step S4 include: S41. Select flood characteristic variables from the flood hydrographs of each river flowing into the lake after reservoir regulation, including the peak flood Q and the flood volume W; S42. For each selected flood characteristic variable, determine the marginal distribution function; S43. Select a suitable Copula function; S44. Substitute the marginal distribution functions of each characteristic variable into the selected Copula function and determine the parameters to obtain the joint distribution function of the flood characteristic variables of each river flowing into the lake.

5. The method for determining the design flood hydrograph of a river-connected lake according to claim 4, characterized in that The distribution functions of the peak flood Q and the flood volume W in step S42 are: Among them, q0 and w0 respectively represent the given values of the peak flood and the flood volume in a time period. According to the marginal distribution probability theorem, its two-dimensional discrete frequency calculation formula is: Among them, a, β, and a0 are shape, scale, and position parameters respectively, used to measure flood characteristics, and Γ is the gamma function.

6. The method for determining the design flood hydrograph of a river-connected lake according to claim 4, characterized in that Step S43 uses a symmetric Archimedean Copula function.

7. The method for determining the design flood hydrograph of a lake connected to a river according to claim 4, characterized in that, The specific steps of step S44 include: S441. Fit the distribution functions of the peak flood Q and the flood volume W according to the measured floods; S442. Substitute the distribution functions of the peak flood Q and the flood volume W into the expression of the Archimedean Copula function, and use the maximum likelihood method to solve the parameters; S443. Select the optimal function type through the goodness-of-fit test to determine the Copula function form.

8. The method for determining the design flood hydrograph of a lake connected to a river according to claim 7, characterized in that, The expression of the Archimedean Copula function in step S442 is: Among them, is the generator of the Archimedean Copula function, and α is the parameter of the Archimedean Copula function, t is the marginal distribution value of the peak flood Q and the flood volume , is the inverse function of.

9. The method for determining the design flood hydrograph of a lake connected to a river according to claim 1, wherein The specific steps of step S5 include: S51. After knowing the joint distribution of the flood characteristic variables, use the Monte Carlo simulation method for random simulation; S52. Select a typical flood hydrograph, vertically magnify it according to the peak flood and flood volume parameters simulated in S41 to obtain a flood series, conduct statistical analysis based on the flood series, obtain the design flood characteristic values under different return periods, and thus determine the design flood hydrograph into the lake.

10. The method for determining the design flood hydrograph of a river-connected lake according to claim 9, wherein, Step S51 specifically includes: Randomly extract a peak flood value according to the probability distribution of the peak flood discharge; Using the generated peak flood value and its joint distribution with the flood volume, randomly generate the corresponding flood volume value to complete one simulation; Repeat the above steps multiple times to generate multiple groups of correlated peak flood and flood volume values.

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