Method for regulating water delivery in a canal system based on flow stability of control section

Abstract

The application discloses a canal system water delivery allocation method based on flow stability of quantity control section, and is specifically implemented according to the following steps: step 1, collecting characteristic data of a canal system of an irrigation area; step 2, constructing a canal system water delivery allocation model; and step 3, solving the canal system water delivery allocation model constructed in step 2 by using a genetic algorithm, and outputting optimal water distribution flow, water distribution starting time, water distribution ending time and continuous water distribution duration of each lower-level channel. The application solves the problems of frequent flow fluctuation of a quantity control section of an irrigation water delivery canal system, large water quantity error and distorted measurement result in the existing canal system water delivery allocation method.

Description

Technical Field

[0001] This invention belongs to the field of irrigation canal system water conveyance scheduling technology, specifically involving a canal system water conveyance scheduling method based on the stability of flow through the flow control section. Background Technology

[0002] Water allocation in irrigation canal systems is a core component for achieving precise water distribution and efficient water-saving operation in irrigation districts. The quality of the water allocation scheme directly determines the stability of water delivery in the main canals of large and medium-sized irrigation districts, the accuracy of water metering, and the overall water use management effectiveness of the irrigation district. Currently, canal system water allocation primarily aims to ensure the water demand of canals at all levels, and allocation optimization usually focuses on shortening water distribution time, reducing water loss, and minimizing the intensity of gate operation.

[0003] However, existing canal water conveyance and allocation methods suffer from frequent fluctuations in the flow process at various control sections, leading to increased water measurement errors and distorted metering results. These problems are particularly pronounced in irrigation districts with high rates of inter-regional water conveyance and rotational irrigation, making it difficult to meet the requirements of modern irrigation districts for accurate water measurement, stable water conveyance, and refined water supply management. Summary of the Invention

[0004] The purpose of this invention is to provide a canal water conveyance allocation method based on the stability of flow through the flow control section, which solves the problems of frequent flow fluctuations, large water measurement errors, and distorted measurement results in existing canal water conveyance allocation methods.

[0005] The technical solution adopted in this invention is a canal water conveyance and allocation method based on the stability of flow at the flow control section, which is implemented according to the following steps: Step 1: Collect characteristic data of the irrigation district canal system; Step 2: Construct a canal system water conveyance and allocation model; Step 3: Use a genetic algorithm to solve the canal system water allocation model constructed in Step 2, and output the optimal water allocation flow rate, water allocation start time, water allocation end time and continuous water allocation duration for each lower-level canal.

[0006] The invention is further characterized by: Step 1 is as follows: Step 1.1: Obtain the topological structure relationship of each level of canal system, including the hierarchical relationship of each level of canal, the number and number of water outlets corresponding to each level of canal, the control gates, water diversion gates, water discharge gates associated with each canal section, and the binding relationship of water measuring equipment; Step 1.2: Obtain the flow capacity of each channel, the length of each channel, the roughness of each channel, the flow capacity of each gate, the water demand of each channel, the water distribution time, and the location station number.

[0007] Step 2 is as follows: Step 2.1, calculate the water distribution duration; Step 2.2: The difference between the outflow rate and the target flow rate at each time period during the entire water distribution period is taken as the objective function. The optimization objective is to minimize the objective function of the flow control section to ensure that the water flow at each flow control section remains stable throughout the water distribution process. Step 2.3, determine the constraints.

[0008] Step 3 specifically involves: Step 3.1, Population Initialization: Step 3.2, assess population fitness; Step 3.3: Use a tournament selection strategy to screen the parent population; Step 3.4: Perform gene recombination on the screened parent population using a two-point crossover strategy; Step 3.5: Use a uniform mutation strategy to expand the global search range, perform gene mutation on all offspring individuals generated by crossover, generate a new generation of population and update the iteration count; Step 3.6: Compare the current generation number with the preset maximum total number of iterations to determine if the iteration is terminated.

[0009] Step 1.2 defines the current-carrying capacity of each channel level, including the minimum safe current flow, maximum limiting current flow, design rated current flow, and current-carrying capacity of a specific section. (m) 3 / s; The length of each level of channel includes the complete length of the channel and the length of individual channel segments, in km; The flow capacity of each gate, including control gates, diversion gates, and discharge gates, is uniformly collected, showing the complete adjustment range of the minimum controllable flow and the maximum fully open flow of the gates under the condition of the highest design operating water level upstream of the gates. 3 / s; The water demand of each level of canal is calculated according to the irrigation control zone of each level of canal. The net irrigation water demand of crops in each zone is calculated and then the losses due to canal leakage, evaporation, and wastewater are added to calculate the corresponding gross irrigation water demand, in 10,000 m³. 3 ; The water distribution duration is the total cycle time (in hours) of a complete water distribution cycle for each level of canal irrigation group. Location stationing includes the starting station and ending station of the entire canal at all levels, the starting and ending station of each independent canal section, and the stationing corresponding to water outlets, gates, structures, and cross-sectional changes, in km.

[0010] Step 2 is as follows: Step 2.1, calculate the water distribution duration. ; , (1) In the formula, For water diversion, For water distribution point collection, This is the start time for water distribution. This is the end time of water distribution; Step 2.2: The difference between the outflow rate and the target flow rate at each time period during the entire water distribution period is taken as the objective function. The optimization objective is to minimize the objective function of the flow control section to ensure that the water flow at each flow control section remains stable throughout the water distribution process, thereby reducing the frequency of water measurement in the irrigation area and improving accuracy. (2) In the formula, The objective function is... The main canal's volume control section set; for Within the time period The actual flow rate at each flow control section, m 3 / s; For the first The target flow rate of each flow control section during the entire water distribution period, m 3 / s; Calculate the first during the entire water distribution period Target flow rate at each flow control section Take the average flow rate of the corresponding control section; , (3) calculate Within the time period The actual flow rate of each flow control section It is determined by superimposing the flow rates of all downstream channels supplying water through the corresponding flow control section within a known time period; , (4) In the formula, For the water distribution flow of the channel, express During the period of time, through the first The lower-level channels for water distribution are collected at each water control section; Step 2.3, determine the constraints; The constraints include channel flow capacity constraints, flow balance constraints, water volume constraints, time sequence constraints, and non-negativity constraints.

[0011] Step 2.3 specifically involves: Step 2.3.1: Distribute the water flow rate of each channel within the allowable range. Boundary information serves as a constraint on channel flow capacity; , (5) In the formula, Indicates channel Minimum allowable overcurrent, m 3 / s; Indicates channel Maximum allowable overcurrent, m 3 / s; Step 2.3.2: The sum of the flow rates of the lower-level channels operating simultaneously during any time period in the water distribution process is taken as the water delivery flow rate of the upper-level channel, which serves as a flow balance constraint. , (6) In the formula, This indicates that the superior channel is in Traffic during a given time period, m 3 / s; express The lower-level channels that are in water distribution mode during the specified period; Step 2.3.3: The product of the water distribution flow rate and the water distribution duration of each channel is used as the allocated water volume, which serves as the water volume constraint. , (7) In the formula, Indicates channel Distributed water volume, 10,000 m³ 3 0.36 is the conversion factor for water volume units; Step 2.3.4: The water distribution period for each channel is completed within the total water distribution duration, and the water distribution end time is not earlier than the start time, which serves as a timing constraint. , (8) , (9) , (10); Step 2.3.5, the non-negative constraint includes the water distribution flow rate of each channel. Water distribution end time; water distribution start time; , , , (11) In the formula, the water distribution flow rate of each channel is... Water distribution start time Water distribution end time ; Step 2.3.6: Determine the time constraint for water flow propulsion; Estimating the water flow propulsion wave velocity using wave velocity theory for: (12) In the formula, The average flow velocity across the cross section is expressed in m / s. The acceleration due to gravity is m / s². 2 ; The cross-sectional area of ​​the water passage is m. 2 , Width of the water surface, in meters; The water flow is diverted from the upstream branch point. Proceed to the downstream water diversion point transport time for: (13) In the formula, The length of the channel section between two adjacent water outlets, in meters (m). Step 2.3.7: Determine the maximum water distribution flow constraint for a single water distribution outlet; When the water level in the forebay at the water distribution outlet rises to the highest achievable level, the water distribution flow rate is: (14) In the formula, The maximum flow rate that can be diverted by the branch outlet after the control gate is adjusted, m 3 / s; For flow coefficient; Width of the water distribution outlet, in meters (m); The maximum forebay water depth reached at the diversion outlet after the control gate regulation, in meters; The actual maximum diversion flow at the water distribution point is taken as the smaller of the upper limit of the hydraulic control gate and the design flow of the branch canal, ensuring that the water level requirement of the water distribution point for the forebay during the water distribution process is: , (15) In the formula, For the first The design flow rate of the branch canal is m 3 / s.

[0012] Step 3 specifically involves: Step 3.1, Population Initialization: Set an iteration counting variable and assign an initial value, and pre-set the maximum total number of iterations of the algorithm in combination with the scale of irrigation district scheduling; randomly generate the first generation population chromosome matrix in the decision variable space; construct chromosomes using real number encoding, with each chromosome corresponding to a complete irrigation district water allocation scheduling scheme, and store three types of continuous decision variables in segments: water allocation flow rate of each level of channel, water allocation start time, and water allocation end time. Step 3.2, assess population fitness; Using the minimization of flow fluctuation at the flow control section as the objective function, and combining the various engineering constraints in step 2.3, a penalty coefficient is introduced to construct the constraint violation as a penalty term, which is coupled with the objective function to form a composite fitness function, used to balance the optimization accuracy and engineering feasibility of the water distribution scheme. The smaller the flow fluctuation and the lower the degree of constraint violation, the better the fitness. Violating schemes will be penalized and downweighted, reducing the probability of optimal inheritance. By calculating the objective value and constraint penalty of each individual in the population, the composite fitness value is obtained, thereby completing the individual ranking and quantitatively evaluating the comprehensive advantages and disadvantages of each water distribution scheduling scheme. Step 3.3: Use a tournament selection strategy to screen the parent population; A fixed number of individuals are randomly selected from the population and their composite fitness values ​​are compared. Only individuals with better fitness are retained to enter the offspring candidate population. Step 3.4: Perform gene recombination on the screened parent population using a two-point crossover strategy; Two parent chromosomes are randomly selected, two gene splitting nodes are determined, and all gene segments between the two nodes are exchanged to generate a brand new offspring chromosome. Step 3.5: Use a uniform mutation strategy to expand the global search range, perform gene mutation on all offspring individuals generated by crossover, generate a new generation of population and update the iterative count; apply a uniform random perturbation within a controllable range to the real-valued decision variables within the chromosome to ensure that the variable values ​​do not exceed the engineering physical boundary. Step 3.6: Compare the current generation number with the preset maximum total number of iterations to determine if the iteration is terminated; If the current generation reaches the preset maximum number of iterations, then all individuals in the population are traversed, the chromosome with the best composite fitness value is selected, and after decoding the chromosome, the optimal water distribution flow, water distribution start and end time, and water distribution duration scheduling parameters for each level of channel are output. The water delivery flow process curve of each main canal control section is output in time period, and the optimization ends. If the maximum number of iterations is not reached, return to step 3.2 and repeat the fitness calculation and evolution operation on the newly generated population to complete the genetic iteration optimization.

[0013] The beneficial effects of this invention are as follows: This invention is based on a canal water conveyance and allocation method with stable flow at the flow control section. With the aim of improving the accuracy of water measurement in irrigation areas, it breaks through the traditional mode of relying on engineering facilities to stabilize the water conveyance process. It moves the control of flow stability at the flow control section to the stage of water allocation scheme formulation, optimizes the water conveyance and allocation strategy from the source, reduces the flow fluctuation and measurement deviation in the canal system caused by the allocation scheme, and provides scheme support for stable water conveyance and accurate flow control in the canal system. It has strong practicality. Attached Figure Description

[0014] Figure 1 This is a simplified diagram of the application scenario of the model in Embodiment 6 of the present invention; Figure 2 This describes the flow change process at the main canal flow control section 1 in embodiment 6 of the present invention. Figure 3 This describes the flow change process at the main canal flow control section 2 in the application area of ​​Embodiment 6 of the present invention. Figure 4 This describes the flow change process at the main canal flow control section 3 in the application area of ​​Embodiment 6 of the present invention. Figure 5 This describes the flow change process at the main canal flow control section 4 in embodiment 6 of the present invention. Figure 6 This describes the flow change process at the main canal flow control section 5 in embodiment 6 of the present invention. Figure 7 This describes the flow change process at the main canal flow control section 6 in embodiment 6 of the present invention. Detailed Implementation

[0015] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0016] Example 1 This invention provides a canal water conveyance and allocation method based on the stability of flow at the flow control section, which is implemented according to the following steps: Step 1: Collect characteristic data of the irrigation district canal system; Step 2: Construct a canal system water conveyance and allocation model; Step 3: Use a genetic algorithm to solve the canal system water allocation model constructed in Step 2, and output the optimal water allocation flow rate, water allocation start time, water allocation end time and continuous water allocation duration for each lower-level canal.

[0017] Example 2 This invention provides a canal water conveyance and allocation method based on the stability of flow at the flow control section, which is implemented according to the following steps: Step 1: Collect characteristic data of the irrigation district canal system; Step 1.1: Obtain the topological structure relationship of each level of canal system, including the hierarchical relationship of each level of canal, the number and number of water outlets corresponding to each level of canal, the control gates, water diversion gates, water discharge gates associated with each canal section, and the binding relationship of water measuring equipment; Step 1.2: Obtain the flow capacity of each channel, the length of each channel, the roughness of each channel, the flow capacity of each gate, the water demand of each channel, the water distribution time, and the location station number.

[0018] Step 2: Construct a canal system water conveyance and allocation model; Step 3: Use a genetic algorithm to solve the canal system water allocation model constructed in Step 2, and output the optimal water allocation flow rate, water allocation start time, water allocation end time and continuous water allocation duration for each lower-level canal.

[0019] Example 3 This invention provides a canal water conveyance and allocation method based on the stability of flow at the flow control section, which is implemented according to the following steps: Step 1: Collect characteristic data of the irrigation district canal system; Step 1.1: Obtain the topological structure relationship of each level of canal system, including the hierarchical relationship of each level of canal, the number and number of water outlets corresponding to each level of canal, the control gates, water diversion gates, water discharge gates associated with each canal section, and the binding relationship of water measuring equipment; Step 1.2: Obtain the flow capacity of each channel, the length of each channel, the roughness of each channel, the flow capacity of each gate, the water demand of each channel, the water distribution time, and the location station number.

[0020] Step 2: Construct a canal system water conveyance and allocation model; Step 2.1, calculate the water distribution duration. Step 2.2: The difference between the outflow rate and the target flow rate at each time period during the entire water distribution period is taken as the objective function. The optimization objective is to minimize the objective function of the flow control section to ensure that the water flow at each flow control section remains stable throughout the water distribution process. Step 2.3, determine the constraints.

[0021] Step 3: Use a genetic algorithm to solve the canal system water allocation model constructed in Step 2, and output the optimal water allocation flow rate, water allocation start time, water allocation end time and continuous water allocation duration for each lower-level canal.

[0022] Example 4 This invention provides a canal water conveyance and allocation method based on the stability of flow at the flow control section, which is implemented according to the following steps: Step 1: Collect characteristic data of the irrigation district canal system; Step 1.1: Obtain the topological structure relationship of each level of canal system, including the hierarchical relationship of each level of canal, the number and number of water outlets corresponding to each level of canal, the control gates, water diversion gates, water discharge gates associated with each canal section, and the binding relationship of water measuring equipment; Step 1.2: Obtain the flow capacity of each channel, the length of each channel, the roughness of each channel, the flow capacity of each gate, the water demand of each channel, the water distribution time, and the location station number.

[0023] Step 2: Construct a canal system water conveyance and allocation model; Step 2.1, calculate the water distribution duration; Step 2.2: The difference between the outflow rate and the target flow rate at each time period during the entire water distribution period is taken as the objective function. The optimization objective is to minimize the objective function of the flow control section to ensure that the water flow at each flow control section remains stable throughout the water distribution process. Step 2.3, determine the constraints; Step 3: Use a genetic algorithm to solve the canal system water allocation model constructed in Step 2, and output the optimal water allocation flow rate, water allocation start time, water allocation end time and continuous water allocation duration for each lower-level canal.

[0024] Step 3.1, Population Initialization: Step 3.2, assess population fitness; Step 3.3: Use a tournament selection strategy to screen the parent population; Step 3.4: Perform gene recombination on the screened parent population using a two-point crossover strategy; Step 3.5: Use a uniform mutation strategy to expand the global search range, perform gene mutation on all offspring individuals generated by crossover, generate a new generation of population and update the iteration count; Step 3.6: Compare the current generation number with the preset maximum total number of iterations to determine if the iteration is terminated.

[0025] Example 5 This invention provides a canal water conveyance and allocation method based on the stability of flow at the flow control section, which is implemented according to the following steps: Step 1: Collect characteristic data of the irrigation district canal system; Step 1.1: Obtain the topological structure relationship of each level of canal system, including the hierarchical relationship of each level of canal, the number and number of water outlets corresponding to each level of canal, the control gates, water diversion gates, water discharge gates associated with each canal section, and the binding relationship of water measuring equipment; Step 1.2: Obtain the flow capacity of each channel, the length of each channel, the roughness of each channel, the flow capacity of each gate, the water demand of each channel, the water distribution time, and the location station number.

[0026] The current carrying capacity of each channel level includes the minimum safe current carrying capacity, the maximum limit current carrying capacity, the design rated current carrying capacity, and the current carrying capacity of certain sections of each channel, in m. 3 / s; The length of each level of channel includes the complete length of the channel and the length of individual channel segments, in km; The flow capacity of each gate, including control gates, diversion gates, and discharge gates, is uniformly collected, showing the complete adjustment range of the minimum controllable flow and the maximum fully open flow of the gates under the condition of the highest design operating water level upstream of the gates. 3 / s; The water demand of each level of canal is calculated according to the irrigation control zone of each level of canal. The net irrigation water demand of crops in each zone is calculated and then the losses due to canal leakage, evaporation, and wastewater are added to calculate the corresponding gross irrigation water demand, in 10,000 m³. 3 ; The water distribution duration is the total cycle time (in hours) of a complete water distribution cycle for each level of canal irrigation group. Location stationing includes the starting station and ending station of the entire canal at all levels, the starting and ending station of each independent canal section, and the stationing corresponding to water outlets, gates, structures, and cross-sectional changes, in km.

[0027] Step 2: Construct a canal system water conveyance and allocation model; Step 2.1, calculate the water distribution duration. ; , (1) In the formula, For water diversion, For water distribution point collection, This is the start time for water distribution. This is the end time of water distribution.

[0028] Step 2.2: The difference between the outflow rate and the target flow rate at each time period during the entire water distribution period is taken as the objective function. The optimization objective is to minimize the objective function of the flow control section, so as to ensure that the water flow at each flow control section remains stable throughout the water distribution process, thereby reducing the frequency of water measurement in the irrigation area and improving accuracy.

[0029] (2) In the formula, The objective function is... The main canal's volume control section set; for Within the time period The actual flow rate at each flow control section, m 3 / s; For the first The target flow rate of each flow control section during the entire water distribution period, m 3 / s; Calculate the first during the entire water distribution period Target flow rate at each flow control section Take the average flow rate of the corresponding control section; , (3) calculate Within the time period The actual flow rate of each flow control section It is determined by superimposing the flow rates of all downstream channels supplying water through the corresponding flow control section within a known time period; , (4) In the formula, For the water distribution flow of the channel, express During the period of time, through the first The lower-level channels for water distribution are collected at each water control section.

[0030] Step 2.3, determine the constraints; The constraints include channel flow capacity constraints, flow balance constraints, water volume constraints, time sequence constraints, and non-negativity constraints.

[0031] Step 2.3.1: Distribute the water flow rate of each channel within the allowable range. Boundary information serves as a constraint on channel flow capacity; , (5) In the formula, Indicates channel Minimum allowable overcurrent, m 3 / s; Indicates channel Maximum allowable overcurrent, m 3 / s.

[0032] Step 2.3.2: The sum of the flow rates of the lower-level channels operating simultaneously during any time period in the water distribution process is taken as the water delivery flow rate of the upper-level channel, which serves as a flow balance constraint. , (6) In the formula, This indicates that the superior channel is in Traffic during a given time period, m 3 / s; express The lower-level channels that are in water distribution mode during the specified period.

[0033] Step 2.3.3: The product of the water distribution flow rate and the water distribution duration of each channel is used as the allocated water volume, which serves as the water volume constraint. , (7) In the formula, Indicates channel Distributed water volume, 10,000 m³ 3 0.36 is the conversion factor for water volume units; Step 2.3.4: The water distribution period for each channel is completed within the total water distribution duration, and the water distribution end time is not earlier than the start time, which serves as a timing constraint. , (8) , (9) , (10) Step 2.3.5, the non-negative constraint includes the water distribution flow rate of each channel. Water distribution end time; water distribution start time; , , , (11) In the formula, the water distribution flow rate of each channel is... Water distribution start time Water distribution end time .

[0034] Step 2.3.6: Determine the time constraint for water flow propulsion; Estimating the water flow propulsion wave velocity using wave velocity theory for: (12) In the formula, The average flow velocity across the cross section is expressed in m / s. The acceleration due to gravity is m / s². 2 ; The cross-sectional area of ​​the water passage is m. 2 , The width of the water surface is in meters (m).

[0035] The water flow is diverted from the upstream branch point. Proceed to the downstream water diversion point transport time for: (13) In the formula, The length of the channel section between two adjacent water outlets is in meters (m).

[0036] Step 2.3.7: Determine the maximum water distribution flow constraint for a single water distribution outlet; When the water level in the forebay at the water distribution outlet rises to the highest achievable level, the water distribution flow rate is: (14) In the formula, The maximum flow rate that can be diverted by the branch outlet after the control gate is adjusted, m 3 / s; For flow coefficient; Width of the water distribution outlet, in meters (m); The maximum forebay water depth reached at the diversion outlet after the control gate regulation is expressed in meters (m).

[0037] The actual maximum diversion flow at the water distribution point is taken as the smaller of the upper limit of the hydraulic control gate and the design flow of the branch canal, ensuring that the water level requirement of the water distribution point for the forebay during the water distribution process is: , (15) In the formula, For the first The design flow rate of the branch canal is m 3 / s.

[0038] This invention, while taking into account the conventional constraints of canal system water distribution, adds constraints on water flow advancement time and maximum water distribution flow at a single branch point. This allows the executable irrigation area water distribution scheme to match the temporal process of actual water flow in the canal system, optimizes the constraint system of the canal system water conveyance and allocation model, and effectively avoids practical engineering problems such as water conveyance timing imbalance and branch point overflow.

[0039] Step 3: Use a genetic algorithm to solve the canal system water allocation model constructed in Step 2, and output the optimal water allocation flow rate, water allocation start time, water allocation end time and continuous water allocation duration for each lower-level canal.

[0040] Step 3.1, Population Initialization: Set an iteration count variable and assign an initial value, and pre-set the maximum total number of iterations of the algorithm in conjunction with the scale of irrigation district scheduling; randomly generate the chromosome matrix of the first generation population in the decision variable space.

[0041] Chromosomes are constructed using real-number encoding, with each chromosome corresponding to a complete irrigation district water allocation and scheduling scheme. Chromosome genes are segmented to store three types of continuous decision variables: water allocation flow rate at each level of channel, water allocation start time, and water allocation end time.

[0042] Step 3.2, assess population fitness; Using minimizing the flow fluctuation at the flow control section as the objective function, and combining the engineering constraints from step 2.3, a penalty coefficient is introduced to construct the constraint violation as a penalty term, which is coupled with the objective function to form a composite fitness function. This function is used to balance the optimization accuracy and engineering feasibility of the water distribution scheme. The smaller the flow fluctuation and the lower the degree of constraint violation, the better the fitness. Violating schemes will be penalized and downgraded, reducing the probability of optimal inheritance. By calculating the objective value and constraint penalty of each individual in the population, the composite fitness value is obtained, thereby completing the individual ranking and quantitatively evaluating the comprehensive advantages and disadvantages of each water distribution scheduling scheme.

[0043] Step 3.3: Use a tournament selection strategy to screen the parent population; A fixed number of individuals are randomly selected from the population and their composite fitness values ​​are compared. Only individuals with better fitness are retained to enter the offspring candidate population. This reduces the probability of premature convergence and local optimization in the algorithm and ensures the stable retention of high-quality water allocation and scheduling schemes within the population.

[0044] Step 3.4: Perform gene recombination on the screened parent population using a two-point crossover strategy; Two parent chromosomes are randomly selected, two gene splitting nodes are determined, and all gene segments between the two nodes are exchanged to generate new offspring chromosomes; a crossover probability is set to expand the population search diversity while retaining high-quality genes.

[0045] Step 3.5: Use a uniform mutation strategy to expand the global search range, perform gene mutation on all offspring individuals generated by crossover, generate a new generation of population and update the iteration count; Apply a uniform random perturbation within a controllable interval to the real-valued decision variables within the chromosome to ensure that the variable values ​​do not exceed the engineering physical boundaries.

[0046] Step 3.6: Compare the current generation number with the preset maximum total number of iterations to determine if the iteration is terminated.

[0047] If the current generation reaches the preset maximum number of iterations, then all individuals in the population are traversed, the chromosome with the best composite fitness value is selected, and after decoding the chromosome, the optimal water distribution flow, water distribution start and end time, and water distribution duration scheduling parameters for each level of channel are output. The water delivery flow process curve of each main canal control section is output in time period, and the optimization ends. If the maximum number of iterations is not reached, return to step 3.2 and repeat the fitness calculation and evolution operation on the newly generated population to complete the genetic iteration optimization.

[0048] The canal system water allocation model constructed in this invention belongs to a multivariable, multi-constraint coupled nonlinear optimization model. Traditional gradient-based optimization algorithms are prone to converge to local optima and are difficult to obtain the global optimal water allocation scheme. This invention realizes global optimization by genetic algorithm.

[0049] Example 6 This embodiment selects the Xiaokaihe Irrigation District as the implementation object. Located in northern Shandong Province, on the left bank of the lower reaches of the Yellow River, the Xiaokaihe Irrigation District lies between 117°42′~118°04′ east longitude and 37°17′~38°03′ north latitude, in the heart of the Yellow River Delta High-Efficiency Ecological Economic Zone. The irrigation district supplies water to five counties (districts): Bincheng District, Huimin County, Yangxin County, Zhanhua District, and Wudi County, covering 15 townships and 390 natural villages, serving a total population of 330,800. The effective irrigated area of ​​the irrigation district is 660,000 mu (approximately 44,000 hectares), and it is a typical long-distance, multi-stage canal system water conveyance structure.

[0050] This invention is a canal water conveyance and allocation method based on flow stability at the flow control section, and is implemented according to the following steps: Step 1: Collect data on the irrigation canal system; Collect parameters such as elevation, topological relationship, canal section length, canal roughness, and flow capacity of canals at all levels in the irrigation district; Statistical analysis of the flow regulation ranges of each water distribution point, control gate, and discharge gate; Based on the planting structure and growth period quota of the irrigation area, the net irrigation water demand of each irrigation unit is calculated, and the gross irrigation water demand of each canal is obtained by adding the water conveyance loss. Determine the regular irrigation cycle of the irrigation district and the division of each irrigation group, and compile all basic parameters such as channel station numbers, measurement control section locations, and equipment binding relationships.

[0051] Table 1 shows the information on the branch canals of the Xiaokaihe Irrigation District.

[0052] Step 2: Construct a canal system water conveyance and allocation model; The total water allocation scheduling cycle is set as T, and the six key cross-regional water control sections of the main canal of the irrigation area are used as the set of control points for the optimization objective function. The minimum safe flow, maximum limit flow, and design flow parameters of the canal are assigned based on the engineering data of each canal section. Calculate the water flow wave velocity and water flow propagation time at adjacent water outlets under different water conveyance conditions based on channel cross-section parameters; The maximum diversion flow rate of each diversion gate is calculated by combining the gate size and maximum backwater depth of each diversion point, and the upper limit of the actual maximum diversion flow rate of each diversion point is determined by combining the design flow rate of the branch canal.

[0053] The objective function is to minimize the sum of squared errors between the flow rate and the average target flow rate at each time section. The model is coupled with channel flow constraints, water balance constraints, water supply and demand constraints, water distribution timing constraints, and non-negativity constraints. At the same time, the model incorporates the timing correction constraint of water flow advancement time and the dual upper limit constraint of the maximum water distribution flow rate at the water distribution point to construct a complete and stable canal system water conveyance and allocation model.

[0054] Step 3: Using the Geatpy intelligent optimization toolbox on the Python platform, a genetic algorithm is used to solve the canal system water allocation model constructed in Step 2, and output the optimal water distribution flow, water distribution start time, water distribution end time and continuous water distribution duration for each lower-level canal.

[0055] The optimized water distribution scheme obtained in step 3 is compared and verified with the traditional on-demand water distribution scheme.

[0056] Traditional water distribution schemes only meet the total water demand and conventional flow constraints, without considering the timing of water flow and the goal of maintaining stable flow. This results in large fluctuations in flow rate at the control sections during scheduling, significant flow rate abrupt changes during time-sharing water supply switching, and high metering errors. This invention, through optimization of the stable flow target and dual-constraint control of timing and flow rate, effectively smooths the water flow process across different time periods, significantly reduces the standard deviation of flow rate at the control sections, and ensures improved water metering accuracy.

[0057] Based on the actual needs of daily operation and management in the irrigation district, four models were used: a top-down supply and demand matching scheduling model (Model 1), a bottom-up on-demand allocation scheduling model (Model 2), a scheduling model with the shortest global water distribution duration as the optimization objective (Model 3), and the canal system water conveyance allocation model of this invention (Model 4). These four models were used to simulate the canal system water conveyance process. During the simulation, time-series flow data of six key flow control sections in the irrigation district were extracted simultaneously. The dynamic changes of the complete flow at each section under different scheduling modes were compared and analyzed, and the water conveyance stability and water metering adaptability of various schemes were quantitatively evaluated.

[0058] like Figure 1 As shown, this is a simplified diagram of the application scenario of the model in Example 6. Figures 2-7 As shown, the temporal flow variation processes of six key flow control sections in the irrigation area are illustrated under four different canal system allocation modes. The different allocation schemes exhibit significant differences in their control effects on the canal system flow process. Specifically, under the traditional top-down and bottom-up allocation models, the flow dynamic response at each flow control section is drastic, with high frequency and large amplitude of flow fluctuations throughout the water distribution process, resulting in poor water conveyance stability. The optimized allocation model, aiming to minimize the water distribution duration, can mitigate flow fluctuations to some extent compared to the traditional allocation mode. However, this method does not incorporate cross-sectional flow stability into the constraints, and continuous and random flow oscillations still exist during the water distribution process, making it difficult to meet the requirements for stable flow measurement. Compared to the three existing allocation methods, this invention's canal system water conveyance allocation model based on stable flow at flow control sections can effectively suppress flow disturbances throughout the water distribution process, ensuring that each flow control section maintains a stable and uniform flow state during the main water distribution periods. The slight drop in flow rate only occurred at the end of the water distribution phase. This is a normal hydraulic response during the termination of water distribution and a reasonable change resulting from the natural decrease in canal water flow as the irrigation area's water distribution task gradually concludes. It is not an abnormal flow fluctuation and does not affect the stable metering effect of the overall water distribution process. The results show that the canal water distribution method based on stable flow at the flow control section, and the canal water distribution model based on stable flow at the flow control section, with the goal of stable flow at the flow control section, can significantly improve the stability of the canal water distribution process, with small measurement errors and accurate metering results, providing reliable technical support for precise water measurement and stable water distribution in irrigation areas.

Claims

1. A canal system water conveyance and allocation method based on flow stability at flow control sections, characterized in that, The specific steps are as follows: Step 1: Collect characteristic data of the irrigation district canal system; Step 2: Construct a canal system water conveyance and allocation model; Step 3: Use a genetic algorithm to solve the canal system water allocation model constructed in Step 2, and output the optimal water allocation flow rate, water allocation start time, water allocation end time and continuous water allocation duration for each lower-level canal.

2. The canal system water conveyance and allocation method based on flow stability at the flow control section according to claim 1, characterized in that, Step 1 is as follows: Step 1.1: Obtain the topological structure relationship of each level of canal system, including the hierarchical relationship of each level of canal, the number and number of water outlets corresponding to each level of canal, the control gates, water diversion gates, water discharge gates associated with each canal section, and the binding relationship of water measuring equipment; Step 1.2: Obtain the flow capacity of each channel, the length of each channel, the roughness of each channel, the flow capacity of each gate, the water demand of each channel, the water distribution time, and the location station number.

3. The canal water conveyance and allocation method based on flow stability at the flow control section according to claim 2, characterized in that, Step 2 is as follows: Step 2.1, calculate the water distribution duration; Step 2.2: The difference between the outflow rate and the target flow rate at each time period during the entire water distribution period is taken as the objective function. The optimization objective is to minimize the objective function of the flow control section to ensure that the water flow at each flow control section remains stable throughout the water distribution process. Step 2.3, determine the constraints.

4. The canal water conveyance and regulation method based on flow stability at the flow control section according to claim 3, characterized in that, Step 3 specifically involves: Step 3.1, Population Initialization: Step 3.2, assess population fitness; Step 3.3: Use a tournament selection strategy to screen the parent population; Step 3.4: Perform gene recombination on the screened parent population using a two-point crossover strategy; Step 3.5: Use a uniform mutation strategy to expand the global search range, perform gene mutation on all offspring individuals generated by crossover, generate a new generation of population and update the iteration count; Step 3.6: Compare the current generation number with the preset maximum total number of iterations to determine if the iteration is terminated.

5. The canal system water conveyance and allocation method based on flow stability at the flow control section according to claim 4, characterized in that, Step 1.2 defines the current-carrying capacity of each channel level, including the minimum safe current flow, maximum limiting current flow, design rated current flow, and current-carrying capacity of certain sections. (m) 3 / s; The length of each level of channel includes the complete length of the channel and the length of individual channel segments, in km; The flow capacity of each gate, including control gates, diversion gates, and discharge gates, is uniformly collected, showing the complete adjustment range of the minimum controllable flow and the maximum fully open flow of the gates under the condition of the highest design operating water level upstream of the gates. 3 / s; The water demand of each level of canal is calculated according to the irrigation control zone of each level of canal. The net irrigation water demand of crops in each zone is calculated and then the losses due to canal leakage, evaporation, and wastewater are added to calculate the corresponding gross irrigation water demand, in 10,000 m³. 3 ; The water distribution duration is the total cycle time (in hours) of a complete water distribution cycle for each level of irrigation canal group. Location stationing includes the starting and ending stationings of all levels of canals, the starting and ending stationings of each independent canal section, and the stationings corresponding to water outlets, gates, structures, and cross-sectional changes, in km.

6. The canal system water conveyance and allocation method based on flow stability at the flow control section according to claim 5, characterized in that, Step 2 is as follows: Step 2.1, calculate the water distribution duration. ; ， （1） In the formula, For water diversion, For water distribution point collection, This is the start time for water distribution. This is the end time of water distribution; Step 2.2: The difference between the outflow rate and the target flow rate at each time period during the entire water distribution period is taken as the objective function. The optimization objective is to minimize the objective function of the flow control section to ensure that the water flow at each flow control section remains stable throughout the water distribution process, thereby reducing the frequency of water measurement in the irrigation area and improving accuracy. （2） In the formula, The objective function is... The main canal's volume control section set; for Within the time period The actual flow rate at each flow control section, m 3 / s; For the first The target flow rate of each flow control section during the entire water distribution period, m 3 / s; Calculate the first during the entire water distribution period Target flow rate at each flow control section Take the average flow rate of the corresponding control section; ， （3） calculate Within the time period The actual flow rate of each flow control section It is determined by superimposing the flow rates of all downstream channels supplying water through the corresponding flow control section within a known time period; ， （4） In the formula, For the water distribution flow of the channel, express During the period of time, through the first The lower-level channels for water distribution are collected at each water control section; Step 2.3, determine the constraints; The constraints include channel flow capacity constraints, flow balance constraints, water volume constraints, time sequence constraints, and non-negativity constraints.

7. The canal system water conveyance and allocation method based on flow stability at the flow control section according to claim 6, characterized in that, Step 2.3 specifically involves: Step 2.3.1: Distribute the water flow rate of each channel within the allowable range. Boundary information serves as a constraint on channel flow capacity; ， （5） In the formula, Indicates channel Minimum allowable overcurrent, m 3 / s; Indicates channel Maximum allowable overcurrent, m 3 / s; Step 2.3.2: The sum of the flow rates of the lower-level channels operating simultaneously during any time period in the water distribution process is taken as the water delivery flow rate of the upper-level channel, which serves as a flow balance constraint. ， （6） In the formula, This indicates that the superior channel is in Traffic during a given time period, m 3 / s; express The lower-level channels that are in water distribution mode during the specified period; Step 2.3.3: The product of the water distribution flow rate and the water distribution duration of each channel is used as the allocated water volume, which serves as the water volume constraint. ， （7） In the formula, Indicates channel The allocated water volume, in ten thousand cubic meters 3 0.36 is the conversion factor for water volume units; Step 2.3.4: The water distribution period for each channel is completed within the total water distribution duration, and the water distribution end time is not earlier than the start time, which serves as a timing constraint. ， （8） ， （9） ， （10）； Step 2.3.5, the non-negative constraint includes the water distribution flow rate of each channel. Water distribution end time; water distribution start time; , , ， （11） In the formula, the water distribution flow rate of each channel is... Water distribution start time With the end time of water distribution ; Step 2.3.6: Determine the time constraint for water flow propulsion; Estimating the water flow propulsion wave velocity using wave velocity theory for: （12） In the formula, The average flow velocity across the cross section is expressed in m / s. The acceleration due to gravity is m / s². 2 ; The cross-sectional area of ​​the water passage is m. 2 , Width of the water surface, in meters; The water flow is diverted from the upstream branch point. Proceed to the downstream water diversion point transport time for: （13） In the formula, The length of the channel section between two adjacent water outlets, in meters; Step 2.3.7: Determine the maximum flow rate constraint for a single water distribution point; When the water level in the forebay at the water distribution outlet rises to the highest achievable level, the water distribution flow rate is: （14） In the formula, The maximum flow rate that can be diverted by the branch outlet after the control gate is adjusted is m. 3 / s; For flow coefficient; Width of the water distribution outlet, in meters (m); The maximum forebay water depth reached at the diversion outlet after the control gate regulation, in meters; The actual maximum diversion flow at the water distribution point is taken as the smaller of the upper limit of the hydraulic control gate and the design flow of the branch canal, ensuring that the water level requirement of the water distribution point for the forebay during the water distribution process is: ， （15） In the formula, For the first The design flow rate of the branch canal is m 3 / s.

8. The canal system water conveyance and allocation method based on flow stability at the flow control section according to claim 7, characterized in that, Step 3 specifically involves: Step 3.1, Population Initialization: Set an iteration counting variable and assign an initial value, and pre-set the maximum total number of iterations of the algorithm in combination with the scale of irrigation district scheduling; randomly generate the first generation population chromosome matrix in the decision variable space; construct chromosomes using real number encoding, with each chromosome corresponding to a complete irrigation district water allocation scheduling scheme, and store three types of continuous decision variables in segments: water allocation flow rate of each level of channel, water allocation start time, and water allocation end time. Step 3.2, assess population fitness; Using the minimization of flow fluctuation at the flow control section as the objective function, and combining the various engineering constraints in step 2.3, a penalty coefficient is introduced to construct the constraint violation as a penalty term, which is coupled with the objective function to form a composite fitness function, used to balance the optimization accuracy and engineering feasibility of the water distribution scheme. The smaller the flow fluctuation and the lower the degree of constraint violation, the better the fitness. Violating schemes will be penalized and downweighted, reducing the probability of optimal inheritance. By calculating the objective value and constraint penalty of each individual in the population, the composite fitness value is obtained, thereby completing the individual ranking and quantitatively evaluating the comprehensive advantages and disadvantages of each water distribution scheduling scheme. Step 3.3: Use a tournament selection strategy to screen the parent population; A fixed number of individuals are randomly selected from the population and their composite fitness values ​​are compared. Only individuals with better fitness are retained to enter the offspring candidate population. Step 3.4: Perform gene recombination on the screened parent population using a two-point crossover strategy; Two parent chromosomes are randomly selected, two gene splitting nodes are determined, and all gene segments between the two nodes are exchanged to generate a brand new offspring chromosome; Step 3.5: Use a uniform mutation strategy to expand the global search range, perform gene mutation on all offspring individuals generated by crossover, generate a new generation of population and update the iterative count; apply a uniform random perturbation within a controllable range to the real-valued decision variables within the chromosome to ensure that the variable values ​​do not exceed the engineering physical boundary. Step 3.6: Compare the current generation number with the preset maximum total number of iterations to determine if the iteration is terminated; If the current generation reaches the preset maximum number of iterations, then all individuals in the population are traversed, the chromosome with the best composite fitness value is selected, and after decoding the chromosome, the optimal water distribution flow, water distribution start and end time, and water distribution duration scheduling parameters for each level of channel are output. The water delivery flow process curve of each main canal control section is output in time period, and the optimization ends. If the maximum number of iterations is not reached, return to step 3.2 and repeat the fitness calculation and evolution operation on the newly generated population to complete the genetic iteration optimization.

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