A method for configuring a flood control water level in a flood season based on a composition of most unfavorable flood areas

Abstract

The application discloses a flood season control water level configuration method based on a most unfavorable flood area composition. The method comprises the following steps: obtaining a joint distribution fitting of each subarea flood volume of a cascade reservoir; presetting a mathematical model of the most unfavorable flood area composition, and obtaining the most unfavorable flood area composition according to the mathematical model and the joint distribution fitting; and obtaining a running period design flood and a flood season flood control water level configuration condition of a downstream of the cascade reservoir based on the most unfavorable flood area composition. According to the method, the most unfavorable flood area composition is constructed for the downstream of the cascade reservoir, the running period design flood of the reservoir is deduced and the flood season flood control water level is determined according to the most unfavorable flood area composition, the sufficiency and the balance of the flood season flood control water level configuration are improved, the flood control risk is reduced, and the flood resources can be efficiently utilized.

Description

Technical Field

[0001] This application relates to the technical field of water conservancy, and in particular to a method for configuring flood control water levels based on the composition of the most unfavorable flood areas. Background Technology

[0002] Design floods are crucial for the planning, design, construction, and operation management of water conservancy and hydropower projects. For downstream sections with large upstream reservoirs, the "Specification for Calculating Design Floods of Water Conservancy and Hydropower Projects SL44-2006" (hereinafter referred to as the "Specification") recommends using the flood region composition method to derive the design flood at the corresponding design frequency, including the typical year method, the same frequency method, and the discrete summation method. The typical year method is simple and quick to apply, but it is heavily influenced by subjective human factors. The same frequency method implicitly assumes that the upstream flood and the downstream design section flood are fully correlated, failing to consider the uneven spatiotemporal distribution of floods, and the number of scheme combinations increases exponentially with the number of zones (reservoirs), making calculations complex and introducing significant uncertainty. The discrete summation method suffers from the risk of distortion during independence conversion, and the peak discharge frequency still differs somewhat from the section design frequency.

[0003] Yan Baowei et al. proposed a most probable regional composition method, using the Archimedes Copula function to construct the joint distribution of flood volume and solve for the flood regional composition with the highest probability density, providing a new approach for calculating the regional composition of design floods. Liu Zhangjun et al. derived the general formula for calculating the most probable regional composition method based on the Copula function and applied it to the Qingjiang cascade reservoirs. Patent document CN111709147A discloses a method for calculating the regional composition of design floods based on hydrological failure mechanisms. It selects an appropriate Copula function to construct the joint probability distribution function of upstream reservoir cross-sections and interval flood volumes, uses the peak flow frequency distribution method with reference to the discrete summation method, calculates the probability of hydrological failure, and derives the regional composition of the design flood at a specified cross-section. Patent document CN115203984A discloses a flood regional composition design method and system based on the characteristics of multiple flood sources. It determines the flood distribution method and reconstructs the flood regional composition by calculating the regional composition paradigm set of floods in each zone and the deviation rate of the first normal form coefficient.

[0004] The above-mentioned technologies have overlooked the unfavorable composition of flood-prone areas, and the sufficiency and balance of flood control level configuration in the downstream of reservoirs during the flood season based on their design floods still need to be improved. Summary of the Invention

[0005] In view of this, this application provides a flood season control water level configuration method based on the composition of the most unfavorable flood areas, which can improve the sufficiency and balance of flood control water level configuration during the flood season.

[0006] This application provides a method for configuring flood control water levels based on the composition of the most unfavorable flood areas during the flood season, including:

[0007] Obtain the joint distribution fit of flood volume in each zone of the cascade reservoirs;

[0008] A mathematical model of the composition of the most unfavorable flood areas is pre-set, and the composition of the most unfavorable flood areas is obtained by fitting the mathematical model and the joint distribution.

[0009] Based on the composition of the most unfavorable flood area, the operational design flood and flood control level configuration of the downstream of the cascade reservoirs are obtained.

[0010] Optionally, the mathematical model is implemented using equation (5).

[0011]

[0012]

[0013]

[0014]

[0015] In the formula, x1 represents the inflow flood volume of the upstream reservoir, and y represents the inflow flood volume of the upstream reservoir. i F represents the flood volume of 1 to n uncontrolled downstream sections. X (x1) is the cumulative distribution function of the upstream reservoir, F i (y i Let D be the cumulative distribution function of the downstream uncontrolled intervals from 1 to n. R This poses a risk and consequence to flood-prone areas. This represents the corresponding flood volume for the i-th uncontrolled interval in the same frequency composition method.

[0016] Optionally, the composition of the most unfavorable flood region is obtained by fitting the mathematical model and the joint distribution, specifically as follows:

[0017] The mathematical model is solved using a genetic algorithm until it converges.

[0018] Optionally, obtaining the joint distribution fit specifically includes:

[0019] Based on measured flow data from downstream sections, reservoir sections, uncontrolled sections, and reservoir operation data, the marginal distribution of the annual maximum flood was obtained.

[0020] The marginal distribution is fitted using a P-III type curve, and the joint distribution is fitted using a Vine Copula function. Optionally, the marginal distribution of the annual maximum flood is obtained using a P-III type curve, as shown in equation (1).

[0021]

[0022] In the formula, α is the shape parameter of the flood volume, β is the scale parameter of the flood volume, and γ is the location parameter of the flood volume.

[0023] Optionally, the Vine Copula function is a C-type structure function or a D-type structure function;

[0024] The C-type structure function is represented by equation (2), and the D-type structure function is represented by equation (3).

[0025]

[0026]

[0027] In equations (2) and (3), f k (·) represents the marginal distribution of the flood volume in the k-th interval fitted by a P-III type curve; F k (·) is f k (·) is the corresponding cumulative distribution function; c(·,·) is the total derivative of the corresponding Pair Copula.

[0028] Optionally, the joint distribution fitting is implemented using the joint distribution probability density function represented by equation (4).

[0029]

[0030] In the formula, x i For the relevant variables in the joint distribution, f i (x i Let F be the probability density function of the variable. i (x i ) is the cumulative distribution function, and c(·) is the total derivative of the fitted Vine Copula function.

[0031] Optionally, obtaining the marginal distribution of the annual maximum flood includes:

[0032] Based on the principle of water balance, the measured flow data of downstream sections, reservoir sections, uncontrolled sections, and reservoir operation data are restored to obtain the natural flow sequence.

[0033] The annual maximum flood sequence is obtained by sampling the natural flow sequence annually.

[0034] The marginal distribution is obtained using a P-III type curve based on the annual maximum flood sequence.

[0035] Optionally, based on the composition of the most unfavorable flood zone, the flood control level configuration downstream of the cascade reservoirs during the flood season is obtained, including:

[0036] Based on the composition of the most unfavorable flood area and the original design flood hydrograph of the design section, the most unfavorable design flood process is obtained;

[0037] Based on the most unfavorable design flood process, the flood control level configuration during the flood season is obtained.

[0038] Optionally, the most unfavorable design flood process is obtained, specifically including:

[0039] Based on the original design flood hydrograph of the design section, the flood process of each flood area is obtained;

[0040] Based on the flood process in each flood region, reservoir flood regulation calculation and river channel calculation are used to progressively extrapolate to the downstream section to obtain the unfavorable design flood process, and the flood season control water level of the downstream reservoir is configured through trial and error.

[0041] The method disclosed in this application constructs the composition of the most unfavorable flood zone downstream of the cascade reservoir, and derives the design flood for the reservoir operation period and determines the flood control control water level during the flood season based on the composition of the most unfavorable flood zone. This improves the sufficiency and balance of flood control water level configuration during the flood season, reduces flood risk, and enables efficient utilization of flood resources. Attached Figure Description

[0042] The technical solution and other beneficial effects of this application will become apparent from the following detailed description of specific embodiments in conjunction with the accompanying drawings.

[0043] Figure 1 A flowchart illustrating an exemplary embodiment of a method for configuring flood season control water levels based on the composition of the most unfavorable flood zones is shown.

[0044] Figure 2 This illustration shows a specific scenario operation diagram of an exemplary embodiment providing a flood control level configuration method based on the composition of the most unfavorable flood areas during the flood season;

[0045] Figure 3 A schematic diagram and a simplified diagram of a watershed design cross section and an upstream reservoir group provided by an exemplary embodiment are shown.

[0046] in, Figure 3 In the middle section, A1, A2, and A3 represent upstream cascade reservoirs, and their flood volumes are represented by X1, X2, and X3, respectively; B1, B2, and B3 represent uncontrolled sections, and their flood volumes are represented by Y1, Y2, and Y3, respectively; C represents the design section, and its flood volume is represented by Z; the arrows indicate the direction of water flow.

[0047] Figure 4 The example shows a comparison of flood distribution schemes obtained by different regional composition methods such as the same frequency, most likely, and most unfavorable regions for design section C and downstream reservoir sections A2 and A3, respectively, provided by an exemplary embodiment.

[0048] Figure 5 An exemplary embodiment is shown, which provides a method for obtaining the most unfavorable design flood process line for the operation period of a cascade reservoir with respect to the design section C by using different regional composition methods such as the same frequency, most likely, and most unfavorable. Detailed Implementation

[0049] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application are described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0050] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules is not necessarily limited to those explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices. The naming or numbering of steps appearing in this application does not imply that the steps in the method flow must be performed in the chronological / logical order indicated by the naming or numbering. The execution order of named or numbered process steps can be changed according to the desired technical purpose, as long as the same or similar technical effect is achieved. The division of units in this application is a logical division. In practical applications, there may be other division methods. For example, multiple units may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the coupling or direct coupling or communication connection between units shown or discussed may be through some interface, and the indirect coupling or communication connection between units may be electrical or other similar forms, which are not limited in this application. Furthermore, the units or sub-units described as separate components may or may not be physically separated, may or may not be physical units, or may be distributed among multiple circuit units. Some or all of the units can be selected to achieve the purpose of the solution in this application according to actual needs.

[0051] Please refer to Figure 1 , Figure 1A flowchart illustrating an exemplary embodiment of a flood season flood control level configuration method based on the composition of the most unfavorable flood zones is provided. This method includes:

[0052] 102, obtain the joint distribution fitting of flood volume in each zone of the cascade reservoir.

[0053] As an exemplary implementation, obtaining a joint distribution fit specifically includes:

[0054] Based on measured flow data from downstream sections, reservoir sections, uncontrolled sections, and reservoir operation data, the marginal distribution of the annual maximum flood was obtained.

[0055] The marginal distribution is fitted using a P-III type curve, and the joint distribution is fitted using a Vine Copula function. As an exemplary implementation, the marginal distribution of the annual maximum flood is obtained by:

[0056] Based on the principle of water balance, the measured flow data of downstream sections, reservoir sections, uncontrolled sections, and reservoir operation data are restored to obtain the natural flow sequence.

[0057] The annual maximum flood sequence is obtained by sampling the natural flow sequence annually.

[0058] The marginal distribution is obtained using a P-III type curve based on the annual maximum flood sequence.

[0059] It should be added that the annual maximum flood sequence can be, but is not limited to, the annual maximum 3-day, 7-day, 15-day, and 30-day flood volumes, etc.

[0060] Here, the marginal distribution of the annual maximum flood is obtained using a P-III type curve, as represented by equation (1).

[0061]

[0062] In the formula, α is the shape parameter of the flood volume, β is the scale parameter of the flood volume, and γ is the location parameter of the flood volume.

[0063] The Vine Copula function mentioned above is a C-type structure function or a D-type structure function;

[0064] The C-type structure function is represented by equation (2), and the D-type structure function is represented by equation (3).

[0065]

[0066]

[0067] In equations (2) and (3), f k(·) represents the marginal distribution of the flood volume in the k-th interval fitted by a P-III type curve; F k (·) is f k (·) is the corresponding cumulative distribution function; c(·,·) is the total derivative of the corresponding Pair Copula.

[0068] As an exemplary example, the joint distribution fitting is implemented using the joint distribution probability density function represented by equation (4).

[0069]

[0070] In the formula, x i For the relevant variables in the joint distribution, f i (x i Let F be the probability density function of the variable. i (x i Let be the cumulative distribution function, and c(·) be the total derivative of the fitted Vine Copula function.

[0071] 104. A mathematical model of the composition of the most unfavorable flood areas is pre-set, and the composition of the most unfavorable flood areas is obtained by fitting the mathematical model and the joint distribution.

[0072] Here, the mathematical model is implemented through equation (5).

[0073]

[0074]

[0075]

[0076]

[0077] In the formula, x1 represents the inflow flood volume of the upstream reservoir, and y represents the inflow flood volume of the upstream reservoir. i F represents the flood volume of 1 to n uncontrolled downstream sections. X (x1) is the cumulative distribution function of the upstream reservoir, F i (y i Let D be the cumulative distribution function of the downstream uncontrolled intervals from 1 to n. R This poses a risk and consequence to flood-prone areas. This represents the corresponding flood volume for the i-th uncontrolled interval in the same frequency composition method.

[0078] As an exemplary implementation, the composition of the most unfavorable flood region is obtained based on the mathematical model and the joint distribution fitting, specifically as follows:

[0079] The mathematical model is solved using a genetic algorithm until it converges.

[0080] It should be added that, during the process of solving the problem using the genetic algorithm, the composition of the most unfavorable flood zone is represented as (x1, y1, y2, ..., y n Encode it.

[0081] 106. Based on the composition of the most unfavorable flood area, obtain the operational design flood and flood control level configuration of the downstream of the cascade reservoir.

[0082] As an exemplary example, based on the composition of the most unfavorable flood zone, the flood control level configuration downstream of the cascade reservoirs during the flood season is obtained, including:

[0083] Based on the composition of the most unfavorable flood area and the original design flood hydrograph of the design section, the most unfavorable design flood process is obtained;

[0084] Based on the most unfavorable design flood process, the flood control level configuration during the flood season is obtained.

[0085] Here, we obtain the most unfavorable design flood process, which specifically includes:

[0086] Based on the original design flood hydrograph of the design section, the flood process of each flood area is obtained;

[0087] Based on the flood process in each flood region, reservoir flood regulation calculations and river channel calculations are used to progressively extrapolate to the downstream section to obtain the unfavorable design flood process.

[0088] As a widely demonstrated approach, the specific operation of the flood control level configuration during the flood season based on the most unfavorable design flood process can be as follows: Since the most unfavorable design flood is affected by the upstream reservoir regulation, the composition of the most unfavorable area of ​​each section is reduced relative to the original design value. Under the premise of maintaining the flood control standard unchanged, the flood control level of the reservoir during the flood season can be appropriately raised.

[0089] The operational process of configuring the flood control water level in this application will now be described in a relatively broad application scenario. It should not be misunderstood that although the following application scenario involves some sub-steps not appearing in the basic solution of this application (i.e., the technical solution corresponding to the independent claim), these sub-steps should not be considered as the most fundamental constituent sub-steps affecting the technical effect of this application.

[0090] This application method includes the following steps:

[0091] S1: Collect measured flow data for the research watershed. For example... Figure 2As shown in the example, upstream of the designed cross-section C, there are three large reservoir projects: A1, A2, and A3, which separate three uncontrolled areas: B1, B2, and B3. Measured runoff data for the above six areas and the designed cross-section, as well as operational data for the three reservoirs, are required. The data are then processed using the water balance principle to obtain the natural flood sequence for each area and cross-section. Since the catchment area is relatively small, the 7-day flood volume is used as the control, and the maximum 7-day flood volume of the annual maximum flood is statistically analyzed. The maximum 7-day flood volumes of the three reservoirs, the three uncontrolled areas, and the downstream cross-section are represented by random variables X1, X2, X3, Y1, Y2, Y3, and Z, respectively. Figure 2 As shown.

[0092] The above variables were fitted using P-III type curves, and the shape, scale, and location parameters were calibrated by visually estimating the fitting method to obtain the marginal distribution of the maximum 7-day flood volume in each zone:

[0093]

[0094] In the formula, α is the shape parameter of the flood volume, β is the scale parameter of the flood volume, and γ is the location parameter of the flood volume.

[0095] S2: By organizing the composition of flood volume in each sub-region during the same flood event, and using Archimedes Copula function family, binary t-Copula, and normal Copula as Pair Copulas, and combining the AIC Akaike Information Criterion to select the VineCopula with the highest goodness of fit, the joint distribution of flood volume in each sub-region can be obtained:

[0096]

[0097] In the formula, x i For the relevant variables in the joint distribution, f i (x i Let F be the probability density function of the variable. i (x i Let be the cumulative distribution function, and c(·) be the total derivative of the fitted Vine Copula function.

[0098] Based on the distribution of flood volume at the edge, the composition of flood-prone areas is determined using the same-frequency composition method, and a mathematical model is established for the composition of the most unfavorable flood-prone areas of the cascade reservoirs in the basin:

[0099]

[0100]

[0101]

[0102]

[0103] In the formula, x1 represents the inflow flood volume of the upstream reservoir, and y represents the inflow flood volume of the upstream reservoir. i F represents the flood volume of 1 to n uncontrolled downstream sections. X (x1) is the cumulative distribution function of the upstream reservoir, F i (y i Let D be the cumulative distribution function of the downstream uncontrolled intervals from 1 to n. R This poses a risk and consequence to flood-prone areas. This represents the corresponding flood volume for the i-th uncontrolled interval in the same frequency composition method.

[0104] A genetic algorithm is used to solve the problem. The genetic algorithm population size is set to 200, and the number of generations is set to 500. The initial parameter values ​​are given according to the preliminary hydrological reports of each cascade reservoir. The flood zone composition of the design section C and the sections of reservoirs A2 and A3 can then be obtained as follows: Figure 3 As shown. Figure 3 The study presents flood distribution schemes obtained by using the same frequency regional composition method, the most likely regional composition method, and the most unfavorable regional composition method for different cross sections. It is clear that the most unfavorable composition method allocates more flood volume to the downstream area.

[0105] S3: After obtaining the most unfavorable flood distribution scheme for each zone, the flood process for each zone can be derived based on the flood hydrograph of the design section during the construction period. The outflow from Reservoir A1 is superimposed with the flood in section B1 and calculated to Reservoir A2. Then, using the same method, the outflows from Reservoirs A2 and A3, along with the corresponding uncontrolled floods, are calculated from top to bottom to the design section C. This yields the design flood process for the operational period, as follows: Figure 4 As shown.

[0106] Since the flood in the uncontrolled section is not regulated by the reservoir, the magnitude of the most unfavorable design flood at section C is larger compared to other methods. However, it is still significantly reduced compared to the original design flood during the planning and construction period, and the flood process is relatively flat. For the two downstream reservoirs A2 and A3, the design flood is also significantly reduced. After calculating the design flood for the reservoir section during the operating period using the same steps, the flood control water level during the flood season can be appropriately raised through trial and error, while ensuring the original flood control standard, in order to obtain a higher hydropower head and improve the utilization rate of flood resources.

[0107] The above description is merely a preferred embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for configuring flood control water levels based on the composition of the most unfavorable flood areas during the flood season, characterized in that, include: Obtain the joint distribution fit of flood volume in each zone of the cascade reservoirs; A mathematical model of the composition of the most unfavorable flood areas is pre-set, and the composition of the most unfavorable flood areas is obtained by fitting the mathematical model and the joint distribution. Based on the composition of the most unfavorable flood area, the operational design flood and flood control level configuration of the downstream of the cascade reservoirs are obtained; Obtaining the joint distribution fit specifically includes: Based on measured flow data from downstream sections, reservoir sections, uncontrolled sections, and reservoir operation data, the marginal distribution of the annual maximum flood was obtained. The marginal distribution was fitted using a P-III type curve, and the joint distribution was fitted using a Vine Copula function. The probability density function of the marginal distribution of the annual maximum flood is obtained using a P-III type curve, as shown in equation (1). Equation (1); In the formula, α The shape parameters of the flood volume, β The scale parameter for flood volume, γ Location parameters for flood volume; The Vine Copula function is a C-type structure function or a D-type structure function; The C-type structure function is represented by equation (2), and the D-type structure function is represented by equation (3). Equation (2); Equation (3); In equations (2) and (3), The marginal distribution of the flood volume in the kth interval is fitted by a P-III type curve. for The corresponding cumulative distribution function; This is the total derivative of the corresponding Pair Copula; The joint distribution fitting is implemented using the joint distribution probability density function represented by equation (4). Equation (4); In the formula, x i For the relevant variables of the joint distribution, f i ( x i Let ) be the probability density function of the variable. F i ( x i ) is the cumulative distribution function. The total derivative of the fitted Vine Copula function; The mathematical model is implemented through equation (5). Equation (5); Equation (6); In the formula, x 1. The inflow of floodwater into the upstream reservoir. y i This refers to the flood volume in 1 to n uncontrolled downstream sections. F X ( x 1) is the cumulative distribution function of the upstream reservoir. F i ( y i Let be the cumulative distribution function of the downstream 1 to n uncontrolled intervals. D R This poses a risk and consequence to flood-prone areas. In the same frequency composition method, the first i The corresponding flood volume in each uncontrolled area.

2. The method according to claim 1, characterized in that, The composition of the most unfavorable flood zone is obtained based on the mathematical model and the joint distribution fitting, specifically as follows: The mathematical model is solved using a genetic algorithm until it converges.

3. The method according to claim 1, characterized in that, The acquisition of the marginal distribution of the annual maximum flood includes: Based on the principle of water balance, the measured flow data of downstream sections, reservoir sections, uncontrolled sections, and reservoir operation data are restored to obtain the natural flow sequence. The annual maximum flood sequence is obtained by sampling the natural flow sequence annually. The marginal distribution is obtained using a P-III type curve based on the annual maximum flood sequence.

4. The method according to claim 1, characterized in that, Based on the composition of the most unfavorable flood areas, the flood control level configuration downstream of the cascade reservoirs during the flood season is obtained, including: Based on the composition of the most unfavorable flood area and the original design flood hydrograph of the design section, the most unfavorable design flood process is obtained; Based on the most unfavorable design flood process, the flood control level configuration during the flood season is obtained.

5. The method according to claim 4, characterized in that, The most unfavorable design flood process is obtained, specifically including: Based on the original design flood hydrograph of the design section, the flood process of each flood region is obtained by amplifying it according to the flood volume distribution scheme of the corresponding most unfavorable flood region. Based on the flood process in each flood region, reservoir flood regulation calculation and river channel calculation are used to progressively extrapolate to the downstream section to obtain the unfavorable design flood process, and the flood season control water level of the downstream reservoir is configured through trial and error.

Images