Slope cropland collecting tank layout optimization method based on irrigation and storage matching constraint

Abstract

The invention discloses a slope cropland water collecting tank layout optimization method based on irrigation and storage matching constraint, and relates to the technical field of agricultural water conservancy projects, and the method comprises the steps: unifying objects: generating a time period water demand curve and an event storage sequence, explicitly deducting evaporation, leakage and deposition, forming an effective irrigation water amount, and determining a minimum effective water head; constructing an irrigation and storage matching constraint family: uniformly acting the water supply reliability of the key window period, the flow abandoning allowable level and the minimum effective water head on the effective irrigation water amount, and generating a feasible region and a non-feasible boundary; progressive solving: determining service domain mapping in the feasible region, solving the pool level and the pool capacity by combining the shortest transmission and distribution path with the minimum effective water head, and calculating the minimum nominal pool capacity; and solidification implementation: deriving a seasonal rule curve and a pre-discharge water-carrying strategy from the optimal solution, setting a flood overflow triggering condition, and giving a front sand setting scheme, a lining scheme and a monitoring point position to realize design and operation linkage delivery.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of agricultural water conservancy, in particular to a slope farmland catchment pool layout optimization method based on irrigation and storage matching constraints. BACKGROUND

[0002] In a Chinese invention patent with the application publication number CN109376902A, a slope farmland ridge and furrow layout optimization method for crop water demand process is disclosed. First, according to the precipitation data and the crop growth period, a typical crop dry year is determined. Then, according to the crop water demand, evaporation data and precipitation data, the key field precipitation is determined. Based on this, the relevant parameters of the ridge and furrow layout are determined by comparing the theoretical ridge and furrow storage maximum value with the key field precipitation and the relationship between the infiltration amount and the evaporation amount during the rainfall period, combining the slope farmland water balance formula. This method fully considers the crop water demand, focuses on the precipitation characteristics of the crop dry year, can significantly improve the rainwater utilization rate in arid and semiarid areas, and improves the crop yield.

[0003] In the production scene of slope farmland rainwater utilization and supplemental irrigation, small catchment pools are often arranged to intercept runoff and supply water in the critical growth period. Existing projects often follow the general pond specification and experience scheduling, runoff estimation mainly uses the event method or empirical runoff coefficient, and site selection mainly depends on static indicators such as catchment area, slope, and construction convenience. Although the single body is checked sufficiently, the pool group cooperation is not paid enough attention. The common method does not align the time period water demand curve and the event storage sequence in the same time resolution, and the evaporation, leakage and sedimentation losses are often corrected after the operation period. The minimum effective water head and the pipe network path are not coupled enough, the service domain mapping is random, and it is difficult to form a traceable pool position-pool capacity-service domain integrated logic. The overflow trigger condition, water quality and sediment control, and monitoring point are also disconnected from the design, resulting in frequent abandoned flow, high energy consumption, rapid capacity attenuation, and unverifiable operation rules.

[0004] However, irrigation and storage lack calculable irrigation and storage matching constraints, which leads to the time and space mismatch formed in the layout stage to be exposed in the operation period. It is caused by the natural inconsistency between the time structure and the spatial accessibility of the event storage sequence formed by the short duration peak of the slope farmland rainfall and the time period water demand curve composed of the critical window period of crop water use. It occurs in the design which only determines the pool position and pool capacity according to the average inflow or the maximum catchment scale in a year, without taking the effective irrigable water volume as a unified object, without constructing the candidate solution feasible region with the critical window period water supply reliability and the abandoned flow allowable level, and without constraining the service domain mapping and the shortest delivery path with the minimum effective water head. The consequence is that in the scene where strong convective rain and land fragmentation coexist, individual pools frequently overflow and abandon flow while the window period is short of water, the self-flowing proportion decreases, leading to the increase of non-conventional pumping and leakage risks, the pre-sedimentation scheme and the lining scheme lagging behind, causing rapid capacity attenuation, seasonal rule curve difficult to execute, and the overall water supply reliability and operation economy declining simultaneously. SUMMARY

[0005] (I) Technical problems solved In view of the deficiencies of the prior art, the present application provides a slope farmland catchment pool layout optimization method based on irrigation and storage matching constraints, which forms effective irrigable water volume by including generation period water demand curve and event storage sequence, explicitly deducting evaporation, seepage and sedimentation, and determining the minimum effective water head; the key window period water supply reliability, the allowable level of flow rejection and the minimum effective water head uniformly act on the effective irrigable water volume to generate the feasible region and the unfeasible boundary; the service domain mapping is determined in the feasible region, and the pool site and pool capacity are obtained by solving the minimum effective water head with the shortest delivery path, and the minimum nominal pool capacity is calculated; the seasonal rule curve and the pre-discharge water carrying strategy are derived from the optimal solution, the overflow trigger condition is set, and the pre-sedimentation scheme, the lining scheme and the monitoring point are given, and the design operation linkage delivery is realized; thereby solving the technical problems recorded in the background art.

[0006] (II) Technical solutions In order to achieve the above object, the present application is implemented by the following technical solutions: a slope farmland catchment pool layout optimization method based on irrigation and storage matching constraints, comprising: generating a period water demand curve and an event storage sequence, defining effective irrigable water volume by evaporation, seepage and sedimentation reduction, extracting terrain elevation data and irrigated land block elevation, determining whether the minimum effective water head is reachable, and forming unified time resolution basic data for pool site-pool capacity-service domain solution; The key window period water supply reliability, the allowable level of flow rejection and the minimum effective water head constitute the irrigation and storage matching constraint family, and uniformly act on the effective irrigable water volume; according to the period water demand curve and the event storage sequence, the candidate solution feasible region is generated and the unfeasible boundary is marked; In the candidate solution feasible region, the pool site-pool capacity-service domain is progressively solved: first, the service domain mapping is determined according to the key window period water use intensity and the block adjacency relationship, then the pool site and pool capacity are determined by the minimum effective water head and the shortest delivery path, the minimum nominal pool capacity is calculated and the optimal solution set is formed; The seasonal rule curve and the pre-discharge water carrying strategy are derived from the optimal solution set, the upper and lower limits of the target water level of each pool are determined according to the minimum nominal pool capacity and the water level-storage capacity function, and the overflow trigger condition is set; the pool site-pool capacity-service domain and the seasonal rule curve form an implementation file.

[0007] Further, the period water demand curve is generated according to crop evapotranspiration and crop coefficient in a unified time step, and is marked on the growth period according to the key window period weight kernel; The event storage sequence is obtained by rainfall intensity, infiltration and runoff time distribution transformation; evaporation, seepage and sedimentation reduction are deducted hour by hour and recorded corresponding to the effective irrigable water volume.

[0008] Further, the accessibility of the minimum effective water head is determined by the difference between the terrain equipotential difference and the elevation of the irrigated plot. When the equipotential difference between the pool body and the plot is not less than the minimum effective water head, it is recorded as accessible, and a reachable mapping set is formed, which serves as the upper limit set of the subsequent service domain mapping.

[0009] Further, the key window period water supply reliability is defined by the satisfaction ratio of the effective irrigable water volume to the water demand curve in the key window period set. The allowable level of flow abandonment is defined by the proportion of the cumulative volume after deducting the loss from the event storage sequence in the evaluation time domain, and the candidate solution feasible region is generated accordingly.

[0010] Further, the candidate solution feasible region needs to satisfy the inclusion relationship of the reachable mapping set and the threshold constraints of the lower limit of the key window period water supply reliability and the upper limit of the allowable level of flow abandonment. And the infeasible boundary is marked when the reliability hits the bottom, the flow abandonment hits the top, or the minimum effective water head is insufficient, and the failure reason of the corresponding pool plot boundary is recorded.

[0011] Further, the service domain mapping is minimized by taking the path impedance composed of the water head margin and the shortest delivery path as the target in the reachable mapping set, and the coverage constraint that each irrigated plot is covered by at least one pool body is applied; the service domain mapping is composed of pool plot boundaries that satisfy the minimum effective water head.

[0012] Further, the minimum nominal pool capacity is calculated by the upper bound of the cumulative surplus, and in the evaluation time domain, the event storage sequence is sequentially deducted by the service domain demand, evaporation loss, seepage loss, and the reduction of the dynamic accumulation effective coefficient summarized by the service domain mapping, and the upper bound of the non-negative cumulative surplus is taken as the lower bound of the capacity of each pool body.

[0013] Further, the screening of the preferred solution set takes the composite target of the normalized path impedance total amount and the inflow connectivity indicator as the minimization criterion, and the pool site selection is completed within the candidate solution feasible region and with the service domain mapping as the fixed input, while the pre-sedimentation scheme requirement is marked for channels with peak significant inflow time distribution.

[0014] Further, the target water level lower limit of the seasonal rule curve is determined by the proportion of the cumulative gap between the service domain demand and the effective irrigable water volume in the key window period to the minimum nominal pool capacity, and is inverted to a water level sequence through the water level-storage function, which is used to describe the lower track of the target water level of each pool.

[0015] Furthermore, the upper limit of the target water level is determined by the buffer ratio synthesized from the allowable diversion level and the inflow connectivity indicator, and an overflow trigger condition is set at the upper limit of the target water level; when the measured water level exceeds the upper limit of the target water level, the pre-discharge water-carrying strategy will return water in the order of the service domain mapping and the shortest transmission and distribution path.

[0016] (III) Beneficial Effects This invention provides a method for optimizing the layout of water collection ponds on sloping farmland based on irrigation and water storage matching constraints, which has the following beneficial effects: By explicitly including losses in the effective irrigation volume and combining topographic elevation data with the elevation of the irrigated plots to determine whether the minimum effective head is achievable, unit conversion errors and information fragmentation are eliminated, directly supporting subsequent comparisons and retrieval, and significantly improving the matching accuracy and availability of time-period water demand curves and event database sequences.

[0017] Constructing a family of irrigation and storage matching constraints and generating feasible and infeasible boundaries for candidate solutions makes the reliability of water supply and the allowable level of water diversion during critical windows verifiable criteria. Simultaneously linking overflow triggering conditions, combinations that cannot meet window demand or have systemic oversupply risks are eliminated in advance, reducing the uncertainty of subsequent engineering iterations and reviews.

[0018] Within the feasible domain of candidate solutions, service domain mapping is prioritized for decision-making, and the pool location and capacity are determined by combining the shortest transport path and the minimum effective head. This ensures that the combination of pool location, pool capacity, and service domain is optimal in both dynamic and geometric aspects. In conjunction with the calculation of the minimum nominal pool capacity, the nominal reservoir capacity is avoided from being artificially high, the gravity flow ratio is increased, and energy consumption and pipeline maintenance risks are reduced.

[0019] Based on the service domain demand summary and inflow characteristics, the target water level lower limit and target water level upper limit of the seasonal regular curve are derived, and a pre-release water carrying strategy is formulated accordingly. This gives the operation side a clear time sequence control boundary, which can suppress the flow abandonment by returning water to the upper limit in advance during the high water period, and ensure the available water volume by the lower limit during the critical window period. It also forms an executable field instruction with the overflow triggering conditions, monitoring points and compliance residuals.

[0020] By constructing a demand index for pre-sedimentation schemes based on inflow connectivity indicators and effective reservoir capacity ratios, and implementing it in conjunction with lining schemes, highly connected inflow channels can be configured with targeted sand interception and seepage prevention, delaying reservoir capacity decay, stabilizing the time-series supply capacity of effective irrigation water, reducing the operation and maintenance burden of dredging and water treatment, and ensuring the continuous availability of seasonal regular curves. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the process for optimizing the layout of water collection ponds on sloping farmland based on irrigation and water storage matching constraints according to the present invention. Detailed Implementation

[0022] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described, obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work are within the protection scope of the present application.

[0023] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described, obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work are within the protection scope of the present application. Figure 1 The present application provides a slope farmland catchment pool layout optimization method based on impoundment matching constraint, comprising, The step one period water demand curve and the event storage sequence are unified to the same time resolution and dimension, and the effective impoundable water volume is defined on the same data object level, and whether the minimum effective water head is reachable is determined from the terrain elevation data and the irrigated land block elevation, thereby providing the subsequent solution of the pool position-pool capacity-service domain with the basis input which can be directly called and has consistent name.

[0024] To this end, taking the land block index and the pool body index as the main line, the period water demand curve with key window period memory is first constructed on the demand side, then the event storage sequence is generated on the supply side according to the confluence time delay structure, then the effective impoundable water volume is defined in the explicit loss manner, and the accessibility criterion of the minimum effective water head is given by the terrain elevation data and the irrigated land block elevation.

[0025] Step one, the period water demand curve, the event storage sequence and the effective impoundable water volume are constructed on the same time axis and dimension, and the accessibility determination of the minimum effective water head is completed, thereby forming the basis data required for the solution of the pool position-pool capacity-service domain.

[0026] The windowing on the demand side and the pulsing on the supply side are the essential conflict of the slope farmland water resource redistribution, if they are not modeled in the same domain on the design side, any subsequent constraint will lack common reference objects, therefore, the period water demand curve is generated in the land block unit, and the event storage sequence is generated in the pool body unit within the same time resolution, so that they can be compared and measured at each time, thereby providing a solid premise for the subsequent definition of the effective impoundable water volume and the minimum effective water head determination; The period water demand curve is first constructed by convoluting the reference evapotranspiration and the crop coefficient with the key window period weight, and then the event storage sequence is obtained by time delay transformation of the difference between the rainfall and the infiltration with the confluence time distribution; both of them are expressed within the same time step and are immediately indexed, ensuring that they can be directly aligned and called.

[0027] To avoid breaking down critical window information into several static coefficients, a critical window option re-kernel is introduced at the plot scale. This allows the product of reference evapotranspiration and crop coefficient to be sampled and smoothed over time by the window, resulting in a time-specific water demand curve that reflects the overlapping effects of the windows. This processing replaces the empirically piecewise weighted list with a window kernel, reducing the stacking of adjustment factors and maintaining a continuous response to fertility progress and meteorological fluctuations. Therefore, numerically, it can be directly compared hourly with the event database sequence. Where: Water demand curve for a given time period Land Parcel Index Demand-side timing, ;Crop reference evapotranspiration Land Parcel Index Reference evaporation timing, Provides atmospheric evapotranspiration drive; crop coefficient Land Parcel Index Time-varying coefficient, Key Window Options Reassessment Land Parcel Index The window core, ,satisfy Weighted sampling and smoothing are applied to the neighborhood of the key window period in terms of time.

[0028] The water demand curve for each time period uses continuous convolution to express the impact of the critical window period, thus it has a sensitive response to the short-term evapotranspiration peak caused by concentrated heat and wind fields, so that subsequent constraints can be accurately targeted at the window period. The convolutional structure at the same time resolution reduces the artificial segmentation of weights, avoids misjudgment caused by unclear parameter references, and is conducive to directly embedding the demand side into the generation of the feasible region of candidate solutions.

[0029] Instead of approximating with a single runoff coefficient, the supply side describes the migration and convergence of slopes and channels using the confluence time distribution, thus expressing the time delay and diffusion of event generation and confluence without introducing redundant adjustment factors. At the pool scale, the difference between rainfall intensity and infiltration intensity is used as the source term, and a convolution transformation is performed through the confluence time distribution to form the event ingestion sequence for the pool, where: In the formula: the sequence of events entered into the database. Pool Index The order of entry into the warehouse Rainfall intensity Regional-scale rainfall time series Infiltration intensity Pool Index infiltration timing, Reduce supply-side runoff, affected by soil layer and previous water content; positive part operator Operators that take zero for negative values ​​are guaranteed to be physically nonnegative; Convergence Time Distribution : pool index : time distribution of the pool, : satisfying : expressing the time delay and dispersion of the confluence path.

[0030] In use, the event-in-pool sequence has the resolution capability for the rainfall duration, peak interval and upstream infiltration variation, avoids compressing various rain types into a single event quantity, improves the timing accuracy of matching, and the normalization condition of the confluence time distribution ensures that the period demand curve generated by convolution is comparable in dimension, which opens up the path for subsequent hourly difference and integral calculation.

[0031] After completing the same-domain expression of the demand side and the supply side, if the effective storage reduction caused by evaporation, leakage and sedimentation is not directly included in the same object, any subsequent constraint may be based on nominal inflow and nominal storage, leading to the disconnection between design and operation. Therefore, the effective irrigable water volume is defined within a unified time step, and whether the minimum effective water head is reachable is determined by the terrain elevation data and the elevation of the irrigated land block, so that the physical reachability and the dimension-unified available quantity are established at the same level.

[0032] First, define the effective irrigable water volume by explicit loss reduction, and then construct the reachability criterion of the minimum effective water head by terrain equipotential difference; the output of the two will be the only object and necessary condition for constructing constraints. To avoid postpositioning losses as empirical corrections, the effective storage reduction caused by evaporation, leakage and sedimentation is explicitly shown on the time axis, and the effective irrigable water volume is defined in the form of integral of unified time step, so that it becomes the only measurement object of subsequent constraints. This definition naturally accommodates the pulsatility of the event-in-pool sequence and the window property of the period demand curve, thereby achieving consistency in dimension and time.

[0033] ; In the formula: effective irrigable water volume : pool index In the time step : available volume, ; dynamic sedimentation effective coefficient : pool index : effective storage coefficient of the pool, ; time step : unified calculation step, : convert instantaneous flow to time step volume; evaporation loss : evaporation flux of pool index : pool index ; leakage loss : leakage flux of pool index : pool index : deduct bottom and lateral leakage; event-in-pool sequence : pool index : in-pool timing, ; In use, the effective irrigable water volume directly binds the supply end and the loss process as a single object, and all subsequent constraints only need to be directed at this object, without the need to convert between multiple objects, and the time step integral form makes the contribution of pulse storage to window demand and loss comparable on the same scale, thereby avoiding unit inconsistency when constructing constraints. The introduction of the dynamic accumulation effective coefficient does not depend on external empirical calibration, but is a physical proportional quantity entering the expression, which is convenient for updating with monitoring points during operation.

[0034] To screen out physically unreachable pool-ground mappings at an early stage of design, construct the equipotential difference with topographic elevation data and the elevation of the irrigated plot, and use the minimum effective water head as the criterion to generate the reachability indicator. This process can give preliminary screening results after aerial survey or mapping is completed without relying on complex energy loss models, saving search costs for subsequent pool-site-pool capacity-service domain solving, wherein: ; ; In the formula: topographic equipotential difference : pool index relative plot index equipotential difference; pool water surface elevation : pool index water surface elevation of the plot; irrigated plot elevation : plot index surface elevation; reachability indicator : binary indicator, , indicating whether the minimum effective water head is met; minimum effective water head : criterion threshold, , ensuring the minimum water head required for gravity-fed water supply and end-of-line working conditions; In use, the reachability indicator establishes a clear feasibility boundary for the pool-ground mapping in space, allowing the subsequent construction of constraints to directly exclude unreachable mappings. The static calculation of the equipotential difference has a low threshold in data availability and is naturally coupled with topographic elevation data and irrigated plot elevation, making it easy to quickly form a judgment after reconnaissance. When stored together with the effective irrigable water volume, the minimum effective water head can be used together with the key window period water supply reliability and the allowable level of abandoned flow to act on the same object when constructing constraints, reducing the uncertainty of cross-object coupling.

[0035] Step 2: Express the time period water demand curve and the event storage sequence on the object of effective irrigable water volume, and generate the candidate solution feasible region and infeasible boundary according to it, to ensure that the subsequent pool-site-pool capacity-service domain solving is performed under a unified criterion.

[0036] While the water demand curves for different time periods and the event inflow sequence have been established within a unified time step, it is impossible to eliminate obviously unusable combinations during the design phase without translating the water supply reliability and allowable flow diversion level during critical windows into hard criteria for effective irrigation capacity. Therefore, it is necessary to construct reliability constraints and flow diversion constraints with effective irrigation capacity as the sole object, based on the co-domain expressions of demand and supply. This will ensure that "whether demand can be met during critical windows" and "whether excessive flow diversion occurs during periods of abundant water" are both computationally verifiable conditions, thus providing a quantitative foundation for the feasible region of candidate solutions.

[0037] First, the water supply reliability during the critical window period is used to connect the water demand curve and the effective irrigation volume. Second, the allowable level of water diversion is used to measure the acceptable mismatch of the system when there is an oversupply. Both are defined by a unified time step integral and are synchronized with the reachability indicator to ensure that subsequent set construction does not involve object migration.

[0038] To avoid simplifying reliability to an annual statistical proportion and losing the time structure of critical windows, the critical window water supply reliability at the plot level is defined directly on the critical window set using an hourly comparison method.

[0039] Specifically, accessible land plots that cannot be mapped by gravity flow are removed, and only the effective irrigation capacity corresponding to those that can be mapped by gravity flow is summarized. This is then compared with the water demand curve for each time step, and the water supply reliability during the critical window is obtained in the form of time proportion.

[0040] Where: Water supply reliability during critical window period Land Parcel Index The percentage of time periods that meet the requirements. Key Window Set Land Parcel Index The key window of time is a time set; set measure : Duration of the critical window period Normalized denominator; indicator function Numerical representation of logical decisions Transform time-sequential satisfaction into integrable objects; Accessibility indicator Pool Index To index the land parcel Reachability markers, Supply is only counted when the minimum effective head is met; effective irrigable water volume Pool Index At time step Available volume; water demand curve for different time periods Land Parcel Index Water demand per unit time; time step : unified computation step size, : dimension conversion and integral window.

[0041] In use, the key window period water supply reliability is satisfied on a time-by-time basis as the criterion, avoiding the average to cover up the short-term water shortage; therefore, it can identify the window-sensitive combination in the design stage, filter through the reachable indicator, and only allow the supply that meets the minimum effective water head to enter the judgment, so as to ensure the physical feasibility of the reliability.

[0042] In order to avoid losing the supply and demand perspective at the system level by defining the abandoned flow as the engineering label of single pool overflow, the effective irrigable water volume of all pools and the time period water demand curve of all plots are summarized in the unified time step, the potential oversupply body quantity at the system level is defined, and the abandoned flow allowance level is described by its proportion in the total supply. This definition does not rely on the pool capacity curve which has not been determined, nor does it introduce additional adjustment factors, and it can give a constraint reference before layout solving, wherein: ; In the formula: abandoned flow allowance level : potential oversupply ratio, ; evaluation time domain : a set of times in the design period, a positive part operator : an operator that takes zero for negative values, non-negative, only accumulates oversupply part; In use, the abandoned flow allowance level measures the oversupply from the system perspective, and can be screened early without relying on the details of the single pool capacity, thereby speeding up the construction of the candidate solution feasible region. It is defined in the same domain as the key window period water supply reliability, which is convenient for jointly imposing constraints on the same object, reducing the boundary ambiguity caused by inconsistent criteria, considering the oversupply as a re-labeling of the effective irrigable water volume, which helps to interface with the engineering record of the overflow trigger condition, and forms a consistent caliber when annotating the boundary later. After establishing quantitative criteria in the reliability and abandoned flow dimensions, the spatial reachability caused by the minimum effective water head and the engineering level overflow trigger condition need to be included in the set expression, so that the candidate solution feasible region not only has time dimension criteria, but also has spatial and engineering restriction description. Only by unifying these restrictions at the set level, the subsequent pool-site-pool-capacity-service-domain solving can be searched within the explicit boundary, avoiding the generation of unachievable combinations.

[0043] First, the reachable mapping set that meets the minimum effective water head is constructed, and then the candidate solution feasible region and the infeasible boundary are defined in a set way, so that reliability, abandoned flow and reachability are combined in the same expression and impose conditions on the pool-site-pool-capacity-service-domain triplets.

[0044] To ensure the spatial accessibility is clear at the set level, the pool land mapping pair corresponding to the accessibility indicator is converged into the accessibility mapping set, which is the upper limit set of the service domain optional edge. This processing avoids repeated determination of the minimum effective head in subsequent solving, and the combination space of the service domain is physically bounded before entering the optimization: ; In the formula: the accessibility mapping set : The allowed pool land mapping pair set is a finite set; the accessibility indicator : As above, the determination of whether the minimum effective head is met.

[0045] When using, the determination of the minimum effective head is moved from the line-by-line check to the set construction stage, thereby reducing the search space and calculation cost of subsequent solving. The accessibility mapping set provides a natural edge set for the graph structure of the service domain, so that the spatial limitation of the candidate solution feasible region has a clear and fixed carrier, and the time constraints of the key window period water supply reliability and the allowable level of flow rejection are not conflicting, thereby realizing the orthogonal integration of time and space limitations.

[0046] To make the constraints uniform at the pool site-pool capacity-service domain triplet level, define the candidate solution feasible region in a set way, and define the infeasible boundary with the constraint saturation condition. Specifically, construct the solution space element containing the pool site-pool capacity-service domain triplet, and require it to meet the lower limit of the key window period water supply reliability, the upper limit of the flow rejection tolerance, and the service domain inclusion relationship, thereby forming the candidate solution feasible region; Then mark the infeasible boundary with the condition of reliability bottom or flow top, wherein: ; ; In the formula: the candidate solution feasible region : The triplet set that meets all constraints; the triplet : The pool site-pool capacity-service domain triplet is a Cartesian product, an abstract representation of a single scheme; the pool site set : One of the triplet components, a spatial coordinate or index set, positioning the pool position; implicitly in ; pool capacity vector : One of the triplet components, containing the pool capacity of each pool vector, , depicting the pool capacity scale; implicitly in ; service domain mapping : One of the triplet components, a subset of , defining the pool land water supply relationship, which is explicitly limited to ; the lower limit of the key window period water supply reliability : The reliability threshold of ; the upper limit of the flow rejection tolerance : The upper limit of the allowed flow rejection ratio, : The upper limit of the allowed flow rejection ratio, , limit oversupply scale; infeasible boundary : boundary set of constraint saturation, for set, mark boundary state for engineering review; closure : closure in the sense of set topology, for set, ensure the completeness of boundary definition.

[0047] In use, time constraints, space constraints and scale constraints are unified into the pool-site-pool capacity-service domain triple in a set manner to achieve one-time construction of the feasible region; the explicit expression of the infeasible boundary enables engineers to review solutions close to the boundary, improving the certainty and interpretability of scheme review; the coupling between set-triple-threshold provides a clear calling interface for subsequent progressive solving, reducing the cost of cross-step object mapping.

[0048] First, the priority decision of service domain mapping resolves the huge uncertainty of spatial combination, and then under the premise of maintaining the key window period water supply reliability and the satisfaction of the allowable level of flow rejection, the minimum effective water head and the shortest delivery path are used as the common criterion to determine the pool site and pool capacity, so that the pool site-pool capacity-service domain is progressively determined in the same evaluation coordinate system, and the explicit marking of the pre-sedimentation scheme requirement is formed at the high connectivity inflow channel.

[0049] Step three, in the candidate solution feasible region, the service domain is determined first, and then the pool site and pool capacity are determined in a sequential manner, and the progressive solution of pool site-pool capacity-service domain is completed, and the constraints of key window period water supply reliability, allowable level of flow rejection and minimum effective water head are maintained.

[0050] The candidate solution feasible region has unified time constraints, spatial accessibility and system oversupply boundary, but without prior stable service domain mapping, any optimization of pool site and pool capacity may repeatedly oscillate between large-scale combinations. Therefore, the time alignment of time period water demand curve and effective irrigable water volume is used as the criterion to optimize the service domain in the accessible mapping set, so that the supply source of each irrigated plot is physically accessible, path-wise feasible and window period-satisfiable; on this basis, the service domain is passed as a fixed input to the pool site and pool capacity determination link, thereby compressing the search space from the large Cartesian product of triplets to a subspace with clear boundary set.

[0051] First, normalize the shortest delivery path with head margin to form path impedance, and minimize the total path impedance in the accessible mapping set to obtain the service domain; then use the time-by-time supply-demand deviation function generated by the service domain to check the local balance of the window period, ensuring that the contribution of the service domain to the key window period water supply reliability is not underestimated or overestimated.

[0052] In the accessible mapping set, simply pursuing the shortest delivery path may be biased towards locations with low terrain but insufficient head margin; simply pursuing the head margin may result in a long path.

[0053] Therefore, the terrain equipotential difference and the minimum effective water head are used to form a water head margin, and the shortest delivery path is normalized by the water head margin to obtain a path impedance that takes into account the power reachability and the path cost; on this basis, the service domain is obtained in a set optimization manner, so that each irrigation plot is covered by a plurality of physically reachable pools, and the overall path impedance is minimized, wherein: ; ; In the formula: water head margin : pool index to plot index water head surplus; terrain equipotential difference : pool index and plot index equipotential difference; minimum effective water head : minimum water head threshold required by the gravity end; service domain mapping : set representation of pool plot water supply relationship, which is a subset of , defines which pool supplies water to which plot; optimal service domain mapping : optimal under the meaning of path impedance, providing a fixed input for subsequent pool site and pool capacity solution; shortest delivery path : shortest path length from pool index to plot index , geometric quantification of delivery cost; member indicator : if , take 1, otherwise take 0, , activate the selected mapping in the summation; reachable mapping set : pool plot mapping set that meets the minimum effective water head, upper limit set of service domain optional edges.

[0054] In use, the normalization of path impedance to water head margin prevents the service domain from sacrificing power reachability due to short path, thereby improving gravity proportion and water supply stability. The set optimization is completed within the reachable mapping set, ensuring that physical reachability is not damaged, avoiding repeated backtracking in the subsequent pool site and pool capacity optimization stage, and the optimal service domain mapping obtained is balanced in both geometric and dynamic dimensions, providing a stable and interpretable edge set for the solution of capacity and location.

[0055] Once the service domain is determined, it still needs to be checked whether the hourly supply and demand relationship in the key window period meets the microstructure of the reliability requirement. For this purpose, a hourly deviation function is constructed to measure whether the cumulative supply of each plot at any time step under the given service domain is sufficient to cover the demand; by analyzing the sign and duration of the hourly deviation function, it can be determined whether the marginal contribution of the service domain to the key window period water supply reliability meets the standard, and accordingly trigger the adjustment of the edge mapping, wherein: ; where: time-by-time deviation function Land Parcel Index At time step The supply and demand gap; Member Indicator Select the supply belonging to the service domain; to prevent individual plots from being excluded from any pool due to optimization bias, a coverage constraint should be added to the service domain solution for "path impedance minimization": Member Indicator :when Select 1 if the value is 1, otherwise select 0. The range of values ​​is... Effective irrigation capacity Pool Index Available volume time series; water demand curve for each time period Land Parcel Index Water demand per unit time; time step : Standardize the calculation step size The dimensions of volume and flow rate are bridged.

[0056] In practice, the hourly deviation function allows for the local quantification of the service domain's contribution to water supply reliability during critical windows, enabling edge set fine-tuning without altering the global threshold. The deviation function and effective irrigation capacity are expressed within the same domain, avoiding cross-object conversions and reducing misjudgments caused by unit inconsistencies. By analyzing the duration of negative values ​​in the deviation function, optimal service domain mapping can be maintained. While ensuring stability, we selectively replace individual paths with higher impedance to improve overall robustness.

[0057] Based on the optimal service domain mapping obtained by minimizing path impedance, and supplemented by local verification of the time-by-time deviation function, the service domain satisfies both dynamic reachability and provable time-by-time satisfaction during critical windows, providing a stable and physically compliant input for the boundary value solutions of pool location and capacity. After the service domain stabilizes, if capacity and location are not simultaneously determined in a unified evaluation coordinate system, situations may arise where nominal capacity is sufficient but gravity flow is insufficient, or path costs are too high, leading to increased energy consumption and maintenance risks.

[0058] Therefore, using the service domain as a fixed input, the minimum nominal pool capacity is first defined using the supremum of accumulated surplus. Then, the pool location is selected using the combined objective of path impedance and inflow connectivity, so that the final solution achieves a balance between engineering costs and operational controllability while satisfying the water supply reliability and flow rejection tolerance levels during critical windows. The minimum nominal pool capacity is first calculated using the supremum of accumulated surplus with explicit loss reduction. Then, the objective function for pool location selection is constructed using path impedance and inflow connectivity, completing the boundary value solution of the pool location-pool capacity-service domain triple.

[0059] The capacity is not specified by empirical proportion, but by the upper bound of the cumulative surplus in all windows under the service domain constraint. This process takes the event sequence, the period water demand curve, and the evaporation, leakage, and sedimentation reduction into the integral kernel at one time, and obtains the lower bound estimate of the nominal pool capacity; this lower bound is engineering implementable before any operation procedure is determined, and can be directly translated into the target capacity of civil design.

[0060] ; In the formula: the minimum nominal pool capacity : pool index The lower bound of the target capacity of , provides a quantitative index for civil design; Evaluation time domain : The time set of design calculation, the upper bound of the integral interval of the time set; the starting time : The integral starting point, a time scalar, the reference point of the cumulative process; the dynamic sedimentation effective coefficient : Pool index The effective storage ratio of Event sequence : The storage time sequence of pool index : The unit time water demand of plot index : The evaporation flux of pool index ; Leakage loss : The leakage flux of pool index : Unified calculation step size , the dimensional bridge of volume and flow; positive part operator : Take zero for negative values, non-negative, to ensure that the lower bound of the capacity is non-negative.

[0061] When used, the minimum nominal pool capacity is given by the upper bound of the cumulative surplus, independent of empirical coefficients, ensuring that the capacity setting is consistent with the time sequence structure of window demand, loss, and inflow, and that the lower bound is naturally compatible with the service domain mapping, making the capacity decision one-to-one corresponding to the service object, reducing the subsequent redistribution pressure in the operation phase. The dynamic sedimentation effective coefficient is explicitly introduced into the capacity calculation, so that the civil design has some reservation for the effective storage decay from the beginning, reducing the impact of the later dredging frequency on the stability of water supply.

[0062] Pool location selection requires a trade-off between path cost and inflow aggregation; higher aggregation leads to stronger demands for upstream sedimentation and energy dissipation. Therefore, using optimal service domain mapping as a constraint, a pool location-pool capacity-service domain triplet selection criterion is constructed, with the sum of total path impedance and inflow connectivity indicators as the objective, yielding the final solution. Inflow connectivity is characterized by the peak value of the confluence time distribution, thus indicating the upstream sedimentation scheme requirements corresponding to highly connected inflow channels, as detailed below: ; In the formula: the optimal triplet The optimal combination of pool slots, pool capacity, and service domain is a set of triples. Feasible region of candidate solutions The set of solutions that satisfy all constraints, limiting the search range; the shortest transport path. Path cost; Topographical Isopotamus Maximum power output. Minimum effective head. Same as above, dynamic threshold; inflow connectivity indicator. Pool Index Inflow aggregation indicators Characterizes the concentration of inflow peaks; confluence time distribution Pool Index Time distribution, , satisfying normalization; Perform data-intrinsic upper bound normalization on the path impedance term: ; and will Dimensionless composite quantity used as the target for pool location selection. Normalized path impedance. Dimensionless impedance, range of values Its function is to be with Aggregation on the same scale; generic index In the reachable mapping set The ordered pairs of pool bodies and plots traversed in the middle are used to form the scan index of the normalized denominator, and do not add new entities themselves.

[0063] When in use, the pool location selection criterion juxtaposes path impedance and inflow connectivity, thereby taking into account both transmission and distribution costs and front-end protection requirements without introducing redundant factors. The utilization of the peak value of the confluence time distribution enables high-connectivity channels to be automatically identified and matched with the requirement marking of the pre-sedimentation scheme, enhancing the engineering feasibility of the scheme. The mapping between the feasible region of the candidate solution and the optimal service region is used as a hard constraint to ensure that the final solution neither undermines the water supply reliability during the critical window period nor exceeds the allowable level of flow diversion.

[0064] After fixing the service domain, the minimum nominal pool capacity and the pool site selection are determined under the same target, so that the capacity and location are synchronized to align the service object and the inflow characteristics; the result can directly generate a parameter set for civil and hydraulic calculation, and provide clear boundary conditions for the subsequent derivation of seasonal rule curves.

[0065] Step four, service domain mapping With the minimum nominal pool capacity As input, the lower limit of the target water level and the upper limit of the target water level of the seasonal rule curve are constructed, and the pre-discharge water carrying strategy and the spillway triggering condition are given, while the requirements of the pre-settling scheme and the lining scheme are expressed as identifiable engineering requirements, and the compliance residual of the monitoring point is used as the verification quantity in the operation period, keeping consistent with the feasible region of the candidate solution .

[0066] Optimal triple The pool site-pool capacity-service domain has been determined, but if the "required minimum supply" and "required maximum overflow" in the time dimension are not explicitly expressed in the form of seasonal rule curves, the pre-discharge water carrying strategy cannot be implemented by the operation end; at the same time, the allowable level of abandoned flow and the inflow connectivity indicator cannot be translated into an upper limit buffer, so that a stable risk-avoiding residual capacity cannot be formed in the wet season. Therefore, starting from the comparison between demand accumulation and supply accumulation, the monotonicity of the water level-storage function is used to translate the volume into the lower limit of the target water level and the upper limit of the target water level, so as to deposit the time sequence criterion into an explicit operation curve.

[0067] First, define the lower limit of the target water level by summarizing the service domain demand, and then define the upper limit of the target water level by combining the allowable level of abandoned flow and the inflow connectivity, and give the pre-discharge water carrying strategy and the spillway triggering condition; both share the minimum nominal pool capacity and the monotonic mapping of the water level-storage function , ensuring the comparability of units and objects.

[0068] Under the premise that the service domain mapping has been stabilized, the service domain demand is summarized as the synthesized time sequence of the plot demand from the pool perspective, so as to derive the lower limit of the target water level from the "excess demand in the most unfavorable period within the future window". First, define the service domain demand summary: ; then take the set of recent window windows as the integral domain to get the volume buffer ratio and map it to the lower limit of the target water level: ; ; In the formula: cumulative gap volume : pool index The demand-supply gap in the interval , the value Criterion for volume gap in window Service domain demand summary : By Pool perspective demand obtained by summary, value range ; Unified time step : Volume-flow dimension bridge, value range ; Effective irrigable water volume : Volume per step, value range ; Minimum nominal pool capacity : Capacity lower bound, value range ; Target water level lower limit : Seasonal rule curve lower track, Water level-storage function , Monotonic increasing function of pool index , Mapping of water level and storage capacity ; For example, if the pool surface area function at different water levels is obtained , then:

[0069] Where is the pool bottom control elevation. First, fit the "water level-area" relationship (such as polynomial, piecewise shape-preserving cubic spline, etc.), and then integrate according to the above formula to obtain the "water level-storage" continuous function and ensure monotonicity, and the water level-storage function is obtained by integrating the water level-area function.

[0070] Inverse function : Monotonic mapping, is to make the "storage capacity→water level" mapping into a monotonic, reversible, and computable function. For example, use the "water level-storage table" to directly construct a piecewise linear inverse function; obtain discrete points and strictly increasing with , first locate the interval on the storage capacity axis , and then according to: , the corresponding water level is obtained.

[0071] In use, the target water level lower limit is defined as the proportion of "window most unfavorable demand excess", avoiding the dilution of key window risk by averaging, so as to form a clear water conservation bottom line at the operation end, taking the service domain demand summary as the core, ensuring consistency with the service domain mapping , reducing the uncertainty of redistribution during operation, and the monotonic mapping of the water level-storage function makes the volume lower limit directly translated into the water level lower limit, which is convenient for on-site water level control without real-time volume calculation.

[0072] In the wet period, the allowable level of spillway capacity Inflow connectivity indicator The target water level upper limit is jointly determined to keep the volume retained in the reservoir below the threshold that would trigger a systemic oversupply. Based on this, a pre-release water-carrying strategy is proposed, and the buffer ratio is defined as follows: Based on this, the upper limit of the target water level is obtained: Where: target water level upper limit Pool Index Upper limit water level; buffer ratio Pool Index The upper limit of the buffer ratio, To allow for additional volume to mitigate risks; Discharge allowable level The maximum allowable oversupply ratio. Global risk avoidance constraints; inflow connectivity indicator Pool Index The concentration of peak inflow, This measures the risk intensity of short-duration peaks. Adopt a uniform time step Dimensionless transformation:

[0073] Inflow connectivity indicator :through The normalized dimensionless peak concentration range This is the pool-side weight used as the upper limit buffer ratio. In use, the target water level upper limit combines the global allowable discharge level with the pool's inflow peak characteristics into a buffer ratio, forming an easily executable upper limit control. When the pool water level reaches [a certain value]... When the target water level is exceeded, a pre-release water-carrying strategy is triggered and mapped to the service domain. Priority will be given to supplying irrigation to the irrigated plots, while also considering the shortest transmission and distribution paths. With water head margin This allows risk avoidance and supply assurance to be unified under the same operational command.

[0074] Once the time-dimensional rule curves are clearly defined, it is still necessary to externalize the engineering requirements related to inflow connectivity and reservoir capacity decay into an implementation list, and provide compliance verification quantities for the operational period. If the requirements for pre-sedimentation and lining schemes are not expressed using unified indicators, design documents and operational verification will lack a common language; if water level compliance is not expressed using measurable residuals, monitoring points will struggle to fulfill their responsibilities as verification criteria. Therefore, sedimentation and water level compliance are presented with quantitative indicators, and the layout of monitoring points and compliance criteria are explained in an integrated manner.

[0075] First, a demand index for pre-sedimentation schemes is constructed based on inflow connectivity and effective reservoir capacity ratio. Then, a compliance residual is constructed based on the target water level range and the measured water level, which is used for threshold-based alarms and operational corrections at monitoring points. Both serve the quantitative ranking and on-map annotation of implementation requirements.

[0076] The combined effect of highly connected inflow channels and effective reservoir capacity reduction significantly shortens the dredging cycle. Therefore, a unified indicator should be used in the design phase to express the intensity of the demand for pre-sedimentation solutions. The demand index is defined as the product of the inflow connectivity indicator and the supremum of effective reservoir capacity loss, in order to prioritize the coupled risks of "peak concentration-reservoir capacity reduction." Where: Demand index for pre-sand settling scheme Pool Index The intensity of demand, Prioritization of pre-sedimentation schemes and maintenance channels; inflow connectivity indicator. Peak concentration characterization; evaluation in the time domain The time set during the design period is defined as the time set, taking the interval with the supremum; dynamic sedimentation effective coefficient. Pool Index The effective storage capacity ratio This expresses the impact of siltation on reservoir capacity; When used, the demand index expresses the combined intensity of the two types of risks with a single dimension, which facilitates marking on construction drawings with contour lines or levels, forming a clear deployment of the pre-sedimentation scheme, and can be correlated with the minimum nominal pool volume without introducing additional factors. Mapping with service domain The system can be linked to guide the sedimentation tank capacity ratio and the location of maintenance access, and can be presented on the same diagram as the flood spillway triggering conditions, so that operation and maintenance personnel can prioritize dredging and facility inspection of high-risk tanks before the flood season.

[0077] To provide a quantitative assessment of the monitoring points' compliance with the rule curve, a compliance residual is constructed using the lower and upper limits of the target water level. A positive residual indicates that the water level has exceeded the limit, requiring pre-release or backfilling measures, and a review of the lining scheme's effectiveness. Where: compliance residual Pool Index The amount that exceeds the limit, Quantitative indicators for triggering operational procedures and verifying the effectiveness of the lining scheme; target water level lower limit. Target water level upper limit Same as above, water control boundary of the interval; water surface elevation of the pool. Pool Index The measured water level, the observed measurements at the monitoring points; the positive part operator For operators that take zero for negative values, the value is non-negative to ensure that the residual is non-negative.

[0078] In use, the compliance residual links monitoring and control as the same value quantity, facilitating recording in operation log and comparing with seasonal rule curve, when residual is positive and trend is consistent with leakage loss When consistent, it can be determined that the lining scheme needs to be upgraded or overhauled, forming a clear coupling between "rule-facility-monitoring", and mapping to service domain When the supply or supply limit is executed in the inner plot, the pool body of the priority treatment can be selected according to the distribution of the compliance residual, and the configuration efficiency of the operation resource is improved.

[0079] Those skilled in the art can appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0080] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0081] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0082] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on a plurality of network units. According to actual needs, some or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0083] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for optimizing layout of a hillside field catchment basin based on a matching constraint of irrigation and storage, characterized in that: comprising, generating a time period water demand curve and an event storage sequence, defining effective irrigable water volume by evaporation, seepage and siltation reduction, extracting terrain elevation data and irrigated land block elevation, determining whether the minimum effective water head is reachable, forming unified time resolution basic data for pool-site-pool-capacity-service domain solution; forming a set of irrigation and storage matching constraints by key window period water supply reliability, allowable level of spillage and minimum effective water head, which uniformly act on the effective irrigable water volume; comparing the time period water demand curve and the event storage sequence, generating a candidate solution feasible region and marking the infeasible boundary; progressively solving the pool-site-pool-capacity-service domain in the candidate solution feasible region: first determining the service domain mapping according to the key window period water use intensity and land block adjacency, then determining the pool site and pool capacity by the minimum effective water head and the shortest delivery path, calculating the minimum nominal pool capacity and forming an optimal solution set; deriving seasonal rule curve and pre-discharge water carrying strategy from the optimal solution set, determining the upper and lower limits of each pool target water level according to the minimum nominal pool capacity and water level-storage capacity function, setting the overflow trigger condition; forming the implementation file by the pool-site-pool-capacity-service domain and the seasonal rule curve.

2. The slope field water collection pool layout optimization method according to claim 1, wherein: the time period water demand curve is generated according to crop evapotranspiration and crop coefficient in a unified time step, and is marked on the growth period by key window period weight kernel; the event storage sequence is obtained by rainfall intensity, infiltration and flow concentration time distribution transformation; evaporation, seepage and siltation reduction are deducted in time and recorded corresponding to the effective irrigable water volume.

3. The slope field water collection pool layout optimization method according to claim 2, wherein: the accessibility of the minimum effective water head is determined by the difference between the terrain equipotential difference and the irrigated land block elevation, and when the equipotential difference from the pool body to the land block is not less than the minimum effective water head, it is recorded as reachable, and a reachable mapping set is formed, which is used as the upper limit set of the subsequent service domain mapping.

4. The slope field water collection pool layout optimization method according to claim 3, wherein: the key window period water supply reliability is defined by the percentage of satisfaction of the effective irrigable water volume and the time period water demand curve in the key window period set; the spillage allowance level is limited by the proportion of potential oversupply volume to the cumulative volume after deducting the event storage sequence loss in the evaluation time domain, and the candidate solution feasible region is generated accordingly.

5. The slope field water collection pool layout optimization method according to claim 4, wherein: the candidate solution feasible region needs to meet the inclusion relationship of the reachable mapping set and the threshold constraints of the key window period water supply reliability lower limit and the spillage allowance level upper limit; and mark the infeasible boundary by the bottom of reliability, the top of spillage or the lack of minimum effective water head, and record the failure reason of the corresponding pool land boundary.

6. The slope field water collection pool layout optimization method according to claim 5, wherein: The service domain mapping is solved by minimizing the path impedance composed of the head margin and the shortest delivery path in the reachability mapping set, and imposing the coverage constraint that each irrigated plot is covered by at least one pool; the service domain mapping is only composed of pool edges that meet the minimum effective head.

7. The method of claim 6, wherein: The minimum nominal pool capacity is calculated by the cumulative surplus upper bound, and the event sequence is sequentially deducted by the service domain demand, evaporation loss, seepage loss and dynamic deposition effective coefficient in the evaluation time domain, and the upper bound of the non-negative cumulative surplus is taken as the capacity lower bound of each pool.

8. The method of claim 7, wherein: The screening of the preferred solution set takes the minimum criterion of the combined target of the normalized path impedance total amount and the inflow connectivity indicator, and completes the pool site selection within the candidate solution feasible region and with the service domain mapping as a fixed input, while generating the pre-settling scheme requirement note for the channel with a peak significant inflow time distribution.

9. The method of claim 8, wherein: The lower limit of the target water level of the seasonal rule curve is determined according to the proportion of the cumulative gap of the service domain demand and the effective irrigable water amount in the key window period to the minimum nominal pool capacity, and is inverted to the water level sequence through the water level-storage capacity function, which is used to describe the lower track of the target water level of each pool.

10. The method of claim 9, wherein: The upper limit of the target water level is determined by the buffer ratio of the combined target of the spillway capacity and the inflow connectivity indicator, and the overflow trigger condition is set at the upper limit of the target water level; the pre-discharge water-carrying strategy is sequentially directed back to supply according to the service domain mapping and the shortest delivery path when the measured water level exceeds the upper limit of the target water level.

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