Configuration method of slope regulation measures based on flood regulation capacity and water consumption control

Abstract

The present invention discloses a method for configuring slope regulation measures based on flood regulation capacity and water consumption control, comprising the following steps: S1, collecting and sorting basin precipitation data; S2, constructing an optimization configuration model based on the balance between flood regulation capacity improvement and slope water consumption control; S3, initialization settings; S4, using a genetic algorithm to calculate the optimal comprehensive benefit of slope regulation; S5, judging whether the maximum number of iterations has been reached, if so, ending the iteration, outputting data, and completing the calculation; otherwise, returning to step S4 and recalculating. The optimization configuration model of the present invention can solve the balance relationship between flood regulation capacity improvement and slope water consumption control, that is, taking the maximum flood regulation capacity and the minimum slope water consumption as constraint targets, to achieve maximum comprehensive benefits.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy engineering, in particular to the technical field of flood regulation and water conservation, and specifically to a method for optimizing the configuration of slope regulation measures based on the balance between improving flood regulation and water conservation capacity and controlling slope water consumption. Background Art

[0002] Ecological engineering prevention and control has become an important measure to deal with flood disasters in river basins. The scientific configuration of slope regulation measures for the rainfall-runoff process is the key. Under extreme precipitation, slope regulation measures such as forest and grass vegetation engineering and natural restoration engineering have an impact on slope runoff, sand production and soil moisture. On the one hand, they can reduce flood peaks, prolong flood processes and reduce flood damage; on the other hand, the arrangement of slope vegetation construction measures will produce a certain amount of water consumption and reduce runoff entering the river. The scientific configuration of slope regulation measures is an important means to balance flood prevention and disaster reduction and slope water production and consumption. At present, most related studies focus on the impact of indicators such as slope and vegetation coverage on single targets such as slope flood regulation capacity or slope water consumption, while there are few studies on the coupling changes of slope flood regulation capacity and water consumption process under extreme precipitation. Based on this, it is necessary to propose an optimization configuration method based on the balance between flood regulation capacity improvement and slope water consumption control, in order to achieve basin flood prevention and disaster reduction and reasonable allocation of water resources. Summary of the invention

[0003] The purpose of the present invention is to propose a slope regulation and storage measures optimization configuration method based on the balance between the improvement of flood regulation and storage capacity and the control of slope water consumption, which can solve the balance relationship between the improvement of flood regulation and storage capacity and the control of slope water consumption, that is, to maximize the comprehensive benefits with the maximum flood regulation and storage capacity and the minimum slope water consumption as the constraint target. Different from the existing research focusing on the impact of indicators such as slope and vegetation coverage on single targets such as slope flood regulation and storage capacity or slope water consumption, this method realizes flood prevention and disaster reduction in the basin and the rational allocation of water resources.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is:

[0005] A method for configuring slope storage measures based on flood storage capacity and water consumption control comprises the following steps:

[0006] S1. Collect and organize basin precipitation data;

[0007] S2. Construct an optimal configuration model based on the balance between flood storage capacity improvement and slope water consumption control, including the following steps:

[0008] S2-1. Flood regulation and storage target: The maximum value of the control unit water storage rate and flood peak reduction rate index is used as the flood regulation and storage capacity FR i The representation of the improvement target is as follows:

[0009] FR i,Max =Max(WS i ,FPR i ) (1)

[0010] in,

[0011]

[0012] Where WS i is the water storage rate of unit i; FPR i is the flood peak reduction rate of unit i; P i is the precipitation in unit i, mm; R i is the total flow rate of unit i, mm; f represents R i Functional relationship with precipitation, slope, and vegetation coverage; S i is the slope of unit i; V i is the vegetation coverage of unit i; FP b,i is the peak flow of unit i without slope vegetation construction measures, m 3 / s; FP v,i is the peak flow of unit i with slope vegetation construction measures, m 3 / s;

[0013] S2-2, water consumption control target: the slope vegetation water demand and transpiration are minimized as the slope water consumption control target WC i The characterization is as follows:

[0014]

[0015] in,

[0016] WD i =WD g,i +WD f,i =g(V i ) (6)

[0017]

[0018] Where, WD i is the water requirement of vegetation in unit i, mm; WD g,i is the water requirement of grassland unit i, mm; WD f,i is the water demand of forest land unit i, mm; g represents WD i Functional relationship with vegetation coverage, V i is the vegetation coverage of unit i, ET i is the transpiration of vegetation in unit i, mm; Indicates ET i Functional relationship with vegetation coverage;

[0019] S2-3, based on the multi-objective optimization configuration of slope storage measures, the flood storage capacity is maximized and the slope water consumption is minimized, and the multi-objective function is converted into a single objective function, the target of which is the comprehensive benefit index CE i CE is obtained through the game relationship between flood storage and slope water consumption i The maximum value of the corresponding slope and coverage is the optimal solution, and the calculation formula of the comprehensive benefit index is:

[0020]

[0021] in,

[0022] ω1+ω2=1,ω1>0,ω2>0 (9)

[0023] In the formula, CE i is the comprehensive benefit index of slope regulation measures for unit i; FR i is the flood storage capacity index of the slope storage measure of unit i; is the mean value of flood storage capacity of different unit slope storage measures; WC i is the water consumption control index of the slope regulation and storage measures of unit i; is the mean value of water consumption control for different unit slope regulation measures; ω1 and ω2 represent weight values, which are determined based on simulation experiments;

[0024] S3, initialization settings;

[0025] S4. Calculate the optimal comprehensive benefit of slope regulation measures using a genetic algorithm: The genetic algorithm calculates the fitness of each individual, and evaluates the performance of the individual according to the standard. Individuals with high fitness represent better solutions. The individuals are set as slope slope and coverage, and the target is the comprehensive benefit index of slope regulation measures;

[0026] S5. Determine whether the maximum number of iterations has been reached. If so, end the iteration, output the data, obtain the slope and coverage corresponding to the optimal comprehensive benefit of the slope storage measures, and complete the calculation; otherwise, return to step S4 and recalculate.

[0027] Among them, the step S1 collects and organizes the basin precipitation data: collects the observation data of the rain gauges and hydrological stations in the basin, and selects the rainfall events that reach the flood level as typical precipitation data.

[0028] Further, step S2-3 includes the following operations:

[0029] (a) The maximum flood storage capacity of the control unit, that is, the maximum value of the water storage rate and flood peak reduction rate index is used as the first criterion to determine the flood storage capacity of the slope storage measures;

[0030] (b) Coordinate the flood control capacity and water consumption control of various slope control measures to establish a comprehensive benefit index; determine the most suitable slope and vegetation coverage based on the size of the comprehensive benefit index; and conduct "secondary configuration" to determine the zoning and classification optimization plan based on the total slope control capacity threshold of the control unit.

[0031] Furthermore, the initialization setting in step S3 includes: setting the slope S i =0°, the boundary condition is 0°≤S i ≤90°, calculation step length ΔS i =1°; vegetation coverage V i =0, the boundary condition is 0≤V i ≤100%, calculation step length ΔV i =1%.

[0032] Furthermore, the step S4 genetic algorithm includes: 1) initialization: creating an initial population; each individual in the population represents a potential solution, the individual is set with a slope gradient and a vegetation coverage, and the individual is represented by a chromosome; 2) fitness evaluation: calculating the fitness of each individual to determine their quality; the fitness function evaluates the performance of the individual according to the goal of the problem, and individuals with high target fitness of the problem represent better solutions, and the goal of the problem is a comprehensive benefit index of slope regulation measures; 3) selection: based on the fitness value, selecting a number of individuals from the current population as parents for the next generation of reproduction; 4) crossover: combining the selected parent individuals through a crossover operation to generate new offspring individuals; 5) mutation: performing mutation operations on offspring individuals, randomly modifying gene values ​​at certain positions of the chromosome, simulating the mutation process in biological evolution, and ensuring that the population has diversity; 6) replacement: replacing the generated new individuals with individuals in the original population to form a new generation of population; 7) repetition: repeating the process of evaluation, selection, crossover and mutation until the termination condition is met, and the termination condition is reaching the maximum number of iterations.

[0033] The beneficial effect of adopting the above technical solution is: by constructing an optimization configuration model, combining genetic algorithms with actual observations and other methods, with the maximum flood storage capacity and the minimum slope water consumption as the constraint targets, the balance between improving flood storage capacity and controlling slope water consumption is solved, and the goal of maximizing the comprehensive benefits of flood control and disaster reduction in the basin and rational allocation of water resources is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0035] Figure 1 It is a schematic diagram of the model construction process of the method of the present invention. DETAILED DESCRIPTION

[0036] Example 1

[0037] A method for configuring slope storage measures based on flood storage capacity and water consumption control comprises the following steps:

[0038] S1. Collect and organize basin precipitation data: collect observation data from rain gauges and hydrological stations in the basin, and select rainfall events that reach flood levels as typical precipitation data.

[0039] S2. Construct an optimal configuration model based on the balance between flood storage capacity improvement and slope water consumption control, including the following steps:

[0040] S2-1. Flood regulation and storage target: The maximum value of the control unit water storage rate and flood peak reduction rate index is used as the flood regulation and storage capacity FR i The representation of the improvement target is as follows:

[0041] FR i,Max =Max(WS i ,FPR i ) (1)

[0042] in,

[0043]

[0044] R i =f(P i ,S i ,V i ) (3)

[0045]

[0046] Where WS i is the water storage rate of unit i; FPR i is the flood peak reduction rate of unit i; P i is the precipitation in unit i, mm; R i is the total flow rate of unit i, mm; f represents R i Functional relationship with precipitation, slope, and vegetation coverage; S i is the slope of unit i; V i is the vegetation coverage of unit i; FP b,i is the peak flow of unit i without slope vegetation construction measures, m 3 / s; FP v,i is the peak flow of unit i with slope vegetation construction measures, m 3 / s;

[0047] S2-2, water consumption control target: the slope vegetation water demand and transpiration are minimized as the slope water consumption control target WC i The characterization is as follows:

[0048]

[0049] in,

[0050] WD i =WD g,i +WD f,i =g(V i ) (6)

[0051]

[0052] Where, WD i is the water requirement of vegetation in unit i, mm; WD g,i is the water requirement of grassland unit i, mm; WD f,i is the water demand of forest land unit i, mm; g represents WD i Functional relationship with vegetation coverage; V i is the vegetation coverage of unit i; ET i is the transpiration of vegetation in unit i, mm; Indicates ET i Functional relationship with vegetation coverage;

[0053] S2-3, based on the multi-objective optimization configuration of slope regulation and storage measures, the flood regulation and storage capacity is maximized and the slope water consumption is minimized. The multi-objective function is converted into a single objective function, the goal of which is a comprehensive benefit index. CE is obtained through the game relationship between flood regulation and storage and slope water consumption. i The maximum value of , the corresponding slope and coverage are the optimal solutions.

[0054] (a) The maximum flood storage capacity of the control unit, that is, the maximum value of the water storage rate and flood peak reduction rate index is used as the first criterion to determine the flood storage capacity of the slope storage measures;

[0055] (b) Coordinate the flood control capacity and water consumption control of various slope control measures to establish a comprehensive benefit index; determine the most suitable slope and vegetation coverage based on the size of the comprehensive benefit index; and perform "secondary configuration" to determine the zoning and classification optimization plan based on the total slope control capacity threshold of the control unit (determined by formulas (1)-(4)).

[0056] The calculation formula of comprehensive benefit index is:

[0057]

[0058] in,

[0059] ω1+ω2=1,ω1>0,ω2>0 (9)

[0060] In the formula, CEi is the comprehensive benefit index of slope regulation measures for unit i; FR i is the flood storage capacity index of the slope storage measure of unit i; is the mean value of flood storage capacity of different unit slope storage measures; WC i is the water consumption control index of the slope regulation and storage measures of unit i; is the mean value of water consumption control of different unit slope regulation measures; ω1 and ω2 represent weight values;

[0061] S3. Initialization setting: Set the slope S i =0°, the boundary condition is 0°≤S i ≤90°, calculation step length ΔS i =1°; vegetation coverage V i =0, the boundary condition is 0≤V i ≤100%, calculation step length ΔV i =1%.

[0062] S4. Calculate the optimal comprehensive benefit of slope regulation measures using a genetic algorithm: The genetic algorithm calculates the fitness of each individual, and evaluates the performance of the individual according to the standard. Individuals with high fitness represent better solutions. The individuals are set as slope slope and coverage, and the target is the comprehensive benefit index of slope regulation measures;

[0063] The genetic algorithm includes: 1) initialization: creating an initial population; each individual in the population represents a potential solution, and the individual in the present invention is set with a slope gradient and a vegetation coverage; the individual is usually represented by a chromosome (which can be a binary, real number or other data structure. The initialization method can be randomly generated or generated according to a specific rule); 2) fitness evaluation: calculating the fitness of each individual to determine their quality; the fitness function evaluates the performance of the individual according to the goal of the problem, and the individual with a high target fitness of the problem represents a better solution. The goal of the problem in the present invention is a comprehensive benefit index of slope regulation measures; 3) selection: based on the fitness value, select a number of individuals from the current population as parents for the next generation of reproduction (common selection methods include roulette selection, tournament selection and ranking selection, etc.); 4) crossover: the selected parent individuals are combined through a crossover operation (or recombination) to produce new offspring individuals. (This usually involves exchanging part of the genetic information of the parent chromosomes to simulate gene recombination in biological genetics); 5) Mutation: perform mutation operations on the offspring individuals, randomly modify the gene values ​​at certain positions of the chromosome, simulate the mutation process in biological evolution, and ensure the diversity of the population; 6) Replacement: replace the newly generated individuals (offspring) with the individuals in the original population (parent generation) to form a new generation of population (there are many replacement strategies, including full replacement and partial replacement); 7) Repetition: repeat the process of evaluation, selection, crossover and mutation until the termination condition is met. The termination condition described in the present invention is reaching the maximum number of iterations.

[0064] S5, determine whether the maximum number of iterations has been reached, if so, end the iteration, output the data, obtain the slope and coverage corresponding to the optimal comprehensive benefit of the slope regulation and storage measures, and complete the calculation; otherwise, return to step S4 and recalculate. Taking the comprehensive benefit of the slope regulation and storage measures as the final indicator, the slope of the Pihe River Basin is optimized according to the method of this embodiment to 28° and the vegetation coverage is 60%.

[0065] The above description is only proposed as an implementable technical solution of the present invention, and is not intended to be a single limitation on the technical solution itself.

Claims

1. A method for configuring slope storage measures based on flood storage capacity and water consumption control, characterized in that: The following steps are involved: S1. Collect and organize basin precipitation data; S2. Construct an optimal configuration model based on the balance between flood storage capacity improvement and slope water consumption control, including the following steps: S2-1. Flood regulation and storage target: The maximum value of the control unit water storage rate and flood peak reduction rate index is used as the flood regulation and storage capacity FR i The representation of the improvement target is as follows: FR i,Max =Max(WS i ,FPR i ) (1) in, R i =f(P i ,S i ,V i ) (3) Where WS i is the water storage rate of unit i; FPR i is the flood peak reduction rate of unit i; P i is the precipitation in unit i, mm; R i is the total flow rate of unit i, mm; f represents R i Functional relationship with precipitation, slope, and vegetation coverage; S i is the slope of unit i; V i is the vegetation coverage of unit i; FP b,i is the peak flow of unit i without slope vegetation construction measures, m 3 / s; FP v,i is the peak flow of unit i with slope vegetation construction measures, m 3 / s; S2-2, water consumption control target: the slope vegetation water demand and transpiration are minimized as the slope water consumption control target WC i The characterization is as follows: in, WD i =WD g,i +WD f,i =g(V i ) (6) Where, WD i is the water requirement of vegetation in unit i, mm; WD g,i is the water requirement of grassland unit i, mm; WD f,i is the water demand of forest land unit i, mm; g represents WD i Functional relationship with vegetation coverage; V i is the vegetation coverage of unit i; ET i is the transpiration of vegetation in unit i, mm; Indicates ET i Functional relationship with vegetation coverage; S2-3, based on the multi-objective optimization configuration of slope storage measures, the flood storage capacity is maximized and the slope water consumption is minimized, and the multi-objective function is converted into a single objective function, the target of which is the comprehensive benefit index CE i CE is obtained through the game relationship between flood storage and slope water consumption i The maximum value of the corresponding slope and coverage is the optimal solution, and the calculation formula of the comprehensive benefit index is: in, ω1+ω2=1,ω1>0,ω2>0 (9) Where, CE i is the comprehensive benefit index of slope regulation measures for unit i; FR i is the flood storage capacity index of the slope storage measure of unit i; is the mean value of flood storage capacity of different unit slope storage measures; WC i is the water consumption control index of the slope regulation and storage measures of unit i; is the mean value of water consumption control of different unit slope regulation measures; ω1 and ω2 represent weight values; S3, initialization settings; S4. Calculate the optimal comprehensive benefit of slope regulation measures using a genetic algorithm: The genetic algorithm calculates the fitness of each individual, and evaluates the performance of the individual according to the standard. Individuals with high fitness represent better solutions. The individuals are set as slope slope and coverage, and the target is the comprehensive benefit index of slope regulation measures; S5. Determine whether the maximum number of iterations has been reached. If so, end the iteration, output the data, obtain the slope and coverage corresponding to the optimal comprehensive benefit of the slope storage measures, and complete the calculation; otherwise, return to step S4 and recalculate.

2. The method for configuring slope storage measures based on flood storage capacity and water consumption control according to claim 1 is characterized in that: The step S1 collects and organizes the basin precipitation data: collects the observation data of the rain gauges and hydrological stations in the basin, and selects the rainfall events reaching the flood level as typical precipitation data.

3. The method for configuring slope storage measures based on flood storage capacity and water consumption control according to claim 1 is characterized in that: Step S2-3 includes the following operations: (a) The maximum flood storage capacity of the control unit, that is, the maximum value of the water storage rate and flood peak reduction rate index is used as the first criterion to determine the flood storage capacity of the slope storage measures; (b) Coordinate the flood control and water consumption control of various slope control measures and establish comprehensive benefit indicators; determine the most suitable slope and vegetation coverage based on the size of the comprehensive benefit indicators; and conduct "secondary configuration" to determine the zoning and classification optimization plan based on the total slope control and storage capacity threshold of the control unit.

4. The method for configuring slope storage measures based on flood storage capacity and water consumption control according to claim 1 is characterized in that: The step S3 initialization setting includes: setting the slope S i =0°, the boundary condition is 0°≤S i ≤90°, calculation step length ΔS i =1°; vegetation coverage V i =0, the boundary condition is 0≤V i ≤100%, calculation step length ΔV i =1%.

5. The method for configuring slope storage measures based on flood storage capacity and water consumption control according to claim 1 is characterized in that: The step S4 genetic algorithm includes: 1) initialization: creating an initial population; each individual in the population represents a potential solution, the individual is set with a slope gradient and a vegetation coverage, and the individual is represented by a chromosome; 2) fitness evaluation: calculating the fitness of each individual to determine their quality; the fitness function evaluates the performance of the individual according to the goal of the problem, and the individual with a high target fitness of the problem represents a better solution, and the goal of the problem is a comprehensive benefit index of slope regulation measures; 3) selection: based on the fitness value, selecting a number of individuals from the current population as parents for the next generation of reproduction; 4) crossover: combining the selected parent individuals through a crossover operation to generate new offspring individuals; 5) mutation: performing a mutation operation on the offspring individuals, randomly modifying the gene value at certain positions of the chromosome, simulating the mutation process in biological evolution, and ensuring that the population has diversity; 6) replacement: replacing the generated new individuals with the individuals in the original population to form a new generation of population; 7) repetition: repeating the process of evaluation, selection, crossover and mutation until the termination condition is met, and the termination condition is reaching the maximum number of iterations.

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