CN-121998152-A - Canal system optimized water distribution method, medium, equipment and product

CN121998152ACN 121998152 ACN121998152 ACN 121998152ACN-121998152-A

Abstract

The invention discloses a canal system optimized water distribution method, medium, equipment and product, which relate to the technical field of agricultural irrigation, and the method comprises the steps of constructing a canal system optimized water distribution model by taking water distribution starting time, water distribution duration and water distribution flow of all levels of canal systems as decision variables, taking the total water shortage of crops in an irrigation area, the excessive irrigation water quantity of crops in the irrigation area and the lost water quantity of the water distribution as objective functions, taking water diversion flow constraint, channel water distribution capacity constraint, irrigation time constraint and water balance constraint as constraint conditions, and solving the canal system optimized water distribution model by adopting DCNSGAIII. The model of the invention can adapt to the incoming water flow which dynamically changes and effectively process complex constraint.

Inventors

LIU CHAO
LI JIANCHEN
HU CHUNTAO
YAO HONG
LIANG QINGZHONG
LI XINCHUAN

Assignees

中国地质大学（武汉）

Dates

Publication Date: 20260508
Application Date: 20251130

Claims (10)

1. A canal system optimized water distribution method is characterized by comprising the following steps: S1, taking water distribution starting time, water distribution duration and water delivery and distribution flow of all levels of canal systems as decision variables, taking the total water shortage of crops in an irrigation area, the excessive irrigation water quantity of crops in the irrigation area and the lost water quantity of the water delivery and distribution as objective functions, and taking diversion flow constraint, canal water delivery capacity constraint, irrigation time constraint and water balance constraint as constraint conditions to construct a canal system optimized water distribution model; S2, adopting DCNSGAIII to solve a canal system optimized water distribution model.
2. A method of optimizing water distribution in a canal system according to claim 1, wherein the total amount of water shortage of crops in a irrigated area is expressed as: Wherein, the Indicating the total water shortage amount of crops in the irrigation area, U represents the number of all main channels in the irrigated area, Representing the number of branch channels of the nth main channel, Representing a canal The water demand of the irrigation area, A jth branch channel representing a jth main channel, Indicating the length of a water distribution period, Representing a canal The water flow rate of the water delivery at the tail end, Representing a canal The number of water delivery and distribution time periods, Representing a canal The water distribution of the irrigation area is smaller than the water demand of the irrigation area, Representing a canal The water distribution amount of the irrigation area is large the water demand of the irrigation area is equal to or higher than that of the irrigation area; The amount of excess irrigation water for the crops in the irrigation area is expressed as: Wherein, the Indicating the surplus irrigation water quantity of crops in the irrigation area, Representing a canal The water distribution of the irrigation area is larger than the water demand of the irrigation area, Representing a canal The water distribution amount of the irrigation area is small the water demand of the irrigation area is equal to or higher than that of the irrigation area; The water loss of the water delivery and distribution is expressed as: Wherein, the Represents the lost water quantity of canal system water delivery and distribution, The channel number of the nth main channel is represented, Indicating the time when the water distribution of the nth main channel begins, Represents the water delivery and distribution time of the nth main channel, Representing the water delivery loss flow of the ith channel section of the ith main channel in the period t, Representing a canal Is characterized by that the water-conveying and water-distributing loss flow quantity, Represents the water flow rate of the ith canal section of the ith main canal at the end of the period t, A represents the canal bed soil permeability coefficient of all channels, m represents the canal bed soil permeability index of all channels, Representing the length of the ith channel section of the ith main channel, Representing a canal Is a length of (c).
3. A canal system optimized water distribution method according to claim 1, characterized in that, The diversion flow constraint is as follows: wherein U represents the number of all main channels in the irrigation area, Representing the water flow of the 1 st channel of the u-th main channel at the end of the period t, Representing the water delivery loss flow of the 1 st channel section of the nth main channel in the period t, Representation of Incoming water flow from the source upstream of the time period; the channel water delivery capacity constraint is: Wherein, the Representing the water flow rate of the ith channel of the ith main channel at the end of the period t, Representing the water delivery loss flow of the ith channel section of the ith main channel in the period t, Representing the design flow of the ith channel section of the ith main channel, Representing a canal The water flow rate of the water delivery at the tail end, Representing a canal Is characterized by that the water-conveying and water-distributing loss flow quantity, Representing a canal Design flow rate of the end; The irrigation time constraint is: Wherein, the Indicating the time when the water distribution of the nth main channel begins, The water delivery and distribution time of the nth main channel is represented, T is the maximum water distribution time period number of the irrigation area, Canal The time at which water distribution is started, Representing a canal A number of water delivery and distribution time periods; The water balance constraint is: Wherein, the Representing the water flow of the (i+1) th channel of the (u) th main channel at the end of the period t, Representing the water delivery loss flow of the (i+1) th channel section of the (u) th main channel in the period t, Representing a canal Whether water is being distributed or not at the time t, Time-indicating canal Water is distributed at the time t; Time-indicating canal No water is distributed at the time t, Representing the number of branch channels of the nth main channel, The number of channels of the nth main channel is shown.
4. The method for optimizing water distribution in a canal system according to claim 1, wherein the concrete steps of solving the model for optimizing water distribution in a canal system by DCNSGAIII are as follows: (1) Setting a population coding and decoding strategy and initializing algorithm parameters; (2) Randomly initializing parent populations For the population Calculating an objective function and constraint conditions according to each water distribution scheme; (3) Entering iteration, constraint boundary of the t-th iteration Dynamically changing with iteration rounds, generating offspring population by selecting, crossing and mutating operations ; (4) For offspring population Calculating objective function and constraint condition, and comparing it with parent population Combining to form a combined population ; (5) According to constraint boundaries Will combine the population Divided into feasible solution sets And unfeasible solution set If (3) , Is that The number of solutions in (a), N is the population number, pair Non-dominant ranking and reference point-based pruning strategy, from which N schemes are selected as parent populations If (3) Will be All added to parent population In (1) to The constraint violation degree of all solutions in the solution is sequenced, and the optimal solution is selected Put in the proposal In (a) and (b); (6) And (3) checking whether the maximum iteration times are reached, if so, outputting a final pareto optimal solution set, otherwise, returning to the step (3) to continue iteration.
5. A method of optimizing water distribution in a canal system according to claim 4, wherein the coding strategy is as follows: the water delivery and distribution flow is an M-bit real number string, and the water distribution starting time and the water distribution duration are an M-bit integer string; Wherein M is the total number of canal systems in the irrigation area, U is the number of all main canals in the irrigation area, Representing the number of branch channels of the nth main channel.
6. The canal system optimized water distribution method according to claim 4, wherein a repair strategy is adopted for the constraint of the water delivery capacity of the canal and the constraint of the irrigation time, and if the individual violates the constraint, the relevant variables are adjusted to meet the constraint condition; the dynamic constraint processing strategy of DCNSGAIII is adopted for diversion flow constraint and water balance constraint, and the method is specifically expressed as follows: Wherein, the Respectively represent the total water shortage amount of crops in irrigation areas excess irrigation water quantity for crops in irrigation area and the water loss amount of the water delivery and distribution, Represents the constraint boundary of the ith constraint and the t-th iteration, Representing the degree of constraint violation, the calculation formula is as follows: where q represents the number of constraints, Representing the degree of constraint violation of x on its ith constraint, A constraint vector representing x on its ith constraint; Wherein, the And Is a constant, cp is a parameter that controls the decreasing trend of the dynamic constraint boundary, Is a value close to zero.
7. A method of optimizing water distribution in a canal system according to claim 6, characterized in that the non-dominant ordering and reference point based pruning strategy is specifically as follows: Given two schemes And If, in the current time state, Is superior to The following conditions need to be satisfied: (1) It is a possible solution to the problem that, Is not a viable solution; (2) And Are all not feasible solutions, but Is less than ; (3) And Are all feasible solutions, but in Upper part Is less than or equal to any one of the objective function values Is set according to the objective function value of (1); To collect feasible solutions Dividing into different non-dominant grades A clipping strategy based on a reference point is adopted for And performing a cutting operation.
8. A computer-readable storage medium, in which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the method according to any of the claims 1-7.
9. An electronic device comprising a processor and a memory, the processor being interconnected with the memory, wherein the memory is configured to store a computer program comprising computer readable instructions, the processor being configured to invoke the computer readable instructions to perform the method of any of claims 1-7.
10. A computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the method of any of claims 1-7.

Description

Canal system optimized water distribution method, medium, equipment and product Technical Field The invention relates to the technical field of agricultural irrigation, in particular to a canal system optimized water distribution method, medium, equipment and product. Background Agricultural irrigation water demand is large, but agricultural irrigation water efficiency is low. The unreasonable canal system water distribution scheme leads to waste of water resources and exacerbates the contradiction between water supply and demand in irrigation areas. Therefore, the establishment of a reasonable canal system water distribution scheme has important significance for improving the efficiency of agricultural irrigation water and promoting sustainable development of irrigation areas. With the development of information technology and artificial intelligence, channel optimization of water distribution has become an important content for intelligent management of agricultural irrigation areas. The main task of optimizing water distribution of the canal system is to scientifically determine the water distribution time and flow of each level of canal based on the maximum overflow capacity of the canal, combining the actual water demand of crops and the water supply condition of a irrigated area, and under the condition of the physical characteristics of the fixed canal system, to convey agricultural irrigation water to farmlands so as to meet the growth demands of the crops. In recent years, research on canal optimization water distribution models has been significantly advanced, and the models are changed from single-objective to multi-objective. The current research often uses minimum water loss, minimum total water shortage in irrigation areas, minimum diversion time difference of rotation irrigation groups and the like as objective functions, and combines a plurality of constraint conditions such as water balance constraint, agricultural irrigation time constraint and the like to construct a canal system scheduling model. Feng Tao and the like, and the water supply benefit of the water user is maximum, the total water shortage amount of the irrigation area is minimum, and the COD discharge amount of the irrigation area is minimum, thereby maximally reducing the water shortage amount of agricultural irrigation. Ma Jianqin and the like aim at minimizing the sum of the water shortage rate of the irrigation area period and the water loss of the canal system, and the result shows that the sum of the water shortage rate of the irrigation area period is reduced by 13.6 percent compared with an empirical method, and the water loss of the canal system is reduced by 6.3 percent. A great deal of water resource loss exists in the water delivery and distribution process, so that accurate calculation and minimization of water delivery loss amount are particularly important. Current canal system optimization water distribution models are increasingly refined in the characterization of water delivery losses. Li Mo et al consider the effect of superior channel splitting on the water loss flow in the water loss calculation. With the increasing complexity of canal-based optimized water distribution models, intelligent optimization algorithms capable of handling multi-objective constraint problems become critical. A reasonable intelligent optimization algorithm can generate a scheduling scheme meeting the agricultural irrigation requirement through an efficient search mechanism. The solution of the water distribution model mainly comprises two types, wherein the first type is a single-target optimization algorithm comprising a genetic algorithm, a particle swarm algorithm, a longicorn swarm optimization algorithm, an ant colony algorithm and a gray wolf algorithm. The second category is multi-objective Optimization algorithms such as multi-objective particle swarm Optimization (MOPSO), non-dominant order genetic algorithm II (Non-dominated Sorting Genetic Algorithm II, NSGAII), non-dominant order genetic algorithm III (Non-dominated Sorting Genetic Algorithm III, NSGAIII), and the like. Compared with the traditional method, the water distribution time is reduced by 1.2 days, the water delivery loss is reduced by 6.84%, and the water utilization efficiency is improved. Lu Xiaoyue, and the like, a irrigation area branch and bucket canal optimized water distribution model which aims at minimum channel water delivery loss and minimum water distribution time difference in an irrigation group is established, and a multi-target particle swarm algorithm is adopted for solving. Li Jiayang and the like construct a water distribution model by taking the minimum leakage loss of the two-stage canal system and the minimum fluctuation of water flow as objective functions, and solve the water distribution model by adopting an improved self-adaptive genetic algorithm. Compared with the manual formulation method and the baseline algorithm, the algori