A method and device for determining a water resource allocation scheme for a reservoir-pond dominant irrigation area

Abstract

The present application relates to the technical field of surface water resources optimal scheduling, and discloses a reservoir and pond leading type irrigation area water resources allocation scheme determination method and device, comprising: acquiring basic attribute data set and actual water supply operation characteristics of the irrigation area to be allocated, and determining three-dimensional coupling effect intensity index; dividing the irrigation unit through double-index threshold grading; based on the reservoir and pond as the low-cost main water source and the lake as the high-cost emergency water source, using the minimum lake water supplement amount to determine the standard, calculating the minimum lake water supplement amount of each irrigation unit under different working conditions, and constructing multiple pure local water source differentiated allocation schemes; based on the preset four-dimensional evaluation index system, using the entropy weight method and the TOPSIS method to evaluate the multiple pure local water source differentiated allocation schemes, and determining the target pure local water source differentiated allocation scheme, realizing stable water supply for broken farmland, minimization of lake water intake scale and reduction of irrigation area water supply operation cost.

Description

Technical Field

[0001] This invention relates to the field of surface water resource optimization and scheduling technology, specifically to a method and apparatus for determining water resource allocation schemes in reservoir-dominated irrigation districts. Background Technology

[0002] Low-mountain and hilly lakeside irrigation areas generally face typical complex water resource allocation contradictions, with regional water supply entirely dependent on local lakes and scattered small reservoirs, resulting in significant constraints. Existing water resource allocation in these areas faces multiple technical bottlenecks: fragmented farmland distribution and significant elevation differences between plots, leading to poor adaptability of unified water allocation; adjacent open, uncontrolled large lakes lack artificial control structures, resulting in extreme annual and intra-annual water level fluctuations, ineffective water intakes during dry seasons, and poor water intake stability; numerous and energy-intensive lake intake facilities, making large-scale, routine water intakes uneconomical; limited regional topography and geological conditions preventing the construction of large-scale water conservancy projects and large-scale water storage facilities; numerous existing small reservoirs located close to fields, but operating independently and fragmented for a long time, failing to fully utilize their water storage potential, and the region lacks external water supply.

[0003] Based on the aforementioned multiple technical bottlenecks, existing water resource allocation technologies have significant shortcomings and cannot adapt to such special and constrained scenarios: First, the water supply logic is reversed, generally prioritizing the use of lake water while ignoring the advantages of low-cost and close-range water supply from small reservoirs, failing to achieve cost reduction in lake water intake; second, the three-dimensional coupling constraints of fragmented terrain, water level fluctuations, and reservoir distribution are not quantified, and there are no targeted zoned water allocation and operational condition-specific scheduling strategies, resulting in persistent problems such as difficulty in water intake from fragmented farmland and numerous irrigation blind spots; third, there is no large-scale hub-adapted scheduling system, making it impossible to rely on distributed reservoir clusters to replace the regulation and storage functions of large-scale projects, and the ability to resist interference from water level fluctuations is weak; fourth, the scheme comparison only assesses conventional indicators such as irrigation guarantee rate and water supply volume, failing to take water supply cost, lake water intake reduction benefits, and reservoir resource revitalization rate as core evaluation indicators, resulting in poor economic efficiency and practicality in scheme selection.

[0004] In summary, the industry currently lacks a refined allocation and scientific comparison method for reservoir- and pond-based water resources that is suitable for situations where there is no external water transfer, no large-scale hubs, fragmented farmland, large fluctuations in lake water levels, and differences in water supply costs. Summary of the Invention

[0005] This invention provides a method and apparatus for determining water resource allocation schemes in reservoir-dominated irrigation areas, in order to solve multiple technical problems existing in the prior art, such as the difficulty of water intake in fragmented farmland in low hills and mountains, large fluctuations in water level and unstable water intake in uncontrolled lakes, high cost of lake water intake, insufficient regulation and storage capacity due to the lack of large water conservancy hubs, low utilization rate of local small reservoirs and ponds, and lack of external water source replenishment.

[0006] In a first aspect, the present invention provides a method for determining a water resource allocation scheme in a reservoir-dominated irrigation area, the method comprising: The basic attribute dataset and actual water supply operation characteristics of the irrigation district to be configured were obtained. This district features both low mountain and hilly terrain and lakeside depressions, and does not rely on external water transfers or large-scale water storage projects. Based on the basic attribute dataset and actual water supply operation characteristics, the supply-demand coupling constraint strength of the irrigation district to be configured was quantified, resulting in a three-dimensional coupling effect strength index. This index characterizes the linkage constraint relationship between topographic water intake, lake water level fluctuations, and reservoir regulation in the irrigation district. Using farmland fragmentation and average plot elevation difference as grading indicators, and based on the three-dimensional coupling effect strength index, the topographic fragmentation distribution characteristics of the irrigation district, and field water allocation suitability conditions, a dual-index threshold grading method was used to classify the irrigation district to be configured. The fragmented irrigated farmland across the entire region is divided into unit types, resulting in multiple irrigation units. Based on the water supply benchmark of reservoirs and ponds as low-cost main water sources and lakes as high-cost emergency supplementary water sources, the minimum lake supplementary water volume is calculated for each irrigation unit under different operating conditions using the minimum lake supplementary water volume verification standard. These different operating conditions include high water level conditions, normal water level conditions, and low water level conditions. Based on the multiple minimum lake supplementary water volumes for each irrigation unit, multiple differentiated pure local water source configuration schemes for the irrigation area to be configured are constructed. Based on a preset four-dimensional evaluation index system, the entropy weight method and the approximation ideal solution ranking method are used to evaluate the multiple differentiated pure local water source configuration schemes and determine the target differentiated pure local water source configuration scheme for the irrigation area to be configured.

[0007] The method for determining water resource allocation schemes in reservoir-dominated irrigation districts provided by this invention can accurately pinpoint the restricted boundaries of irrigation districts with limited water transfer, lack of large-scale hubs, low-mountain and hilly lakeside areas, and fragmented farmland by acquiring the basic conditions and water supply characteristics of the irrigation district to be configured. Furthermore, by quantifying the supply-demand coupling constraint intensity and obtaining a three-dimensional coupling effect intensity index, the method achieves an intuitive quantification of the strength of the contradictions among topography, lakes, and reservoirs, clarifying the core direction for irrigation district scheduling optimization. Furthermore, by using dual-index thresholds to classify irrigation units, the method can match the differences in land elevation and the spatial differences in fragmented farmland, eliminating irrigation adaptation deviations caused by uniform water allocation across the entire region, thereby achieving a basis for differentiated supply and demand calculations by region. Furthermore, based on the water supply benchmark of reservoirs as low-cost primary water sources and lakes as high-cost emergency replenishment sources, the method uses a minimum lake replenishment volume verification standard to calculate the minimum lake replenishment volume for each unit under different operating conditions, strictly implementing the reservoir-priority water supply logic. Simultaneously, by differentiating water level conditions, the method can accurately control the scale of lake water intake, reducing the amount of high-cost lake water intake at the source. Furthermore, by constructing multiple differentiated allocation schemes for purely local water sources, a scheme set covering three scheduling modes—traditional, balanced, and optimized—can be formed, providing a complete and comparable alternative scheduling system. Furthermore, by combining the entropy weight method and the approximate ideal solution ranking method, multiple differentiated allocation schemes for purely local water sources are evaluated and the optimal scheme is determined, taking into account multiple dimensions of needs such as economy, water supply, and engineering adaptation. Thus, through objective selection, the optimal water resource allocation scheme suitable for the irrigation district's endowment can be obtained. Therefore, by implementing this invention, for fragmented irrigation districts in low-mountain and hilly lakeside areas without external water transfer or large-scale water storage hubs, stable water supply to fragmented farmland, minimizing lake water intake, and reducing irrigation district water supply operation costs are achieved, filling the gap in refined water allocation technology for purely local and constrained irrigation districts.

[0008] In one optional implementation, based on the basic attribute dataset and actual water supply operation characteristics, the supply-demand coupling constraint strength of the irrigation district to be configured is quantified to obtain a three-dimensional coupling effect strength index of the irrigation district to be configured, including: Based on the basic attribute dataset and actual water supply operation characteristics, multiple coupling constraint factors are obtained according to preset screening criteria, including mechanism relevance, dimensional completeness, regional adaptability, data quantifiability, and indicator independence. The analytic hierarchy process (AHP) and entropy weight method are used to calculate the weight values ​​of multiple coupling constraint factors. Based on a preset three-dimensional indicator system, the comprehensive evaluation value of multiple indicators is calculated using the multiple coupling constraint factors and their weight values. The preset three-dimensional indicator system includes topographic water intake constraints, lake water source fluctuation constraints, and reservoir regulation capacity constraints. Based on the comprehensive evaluation value of multiple indicators, the three-dimensional coupling effect intensity index of the irrigation district to be configured is calculated.

[0009] The method for determining water resource allocation schemes in reservoir-dominated irrigation districts provided by this invention, by screening coupling constraint factors according to screening criteria, can eliminate indicators with overlapping information, irrelevant mechanisms, and unquantifiable characteristics, ensuring that the factors can fully represent the constraint relationships of the three systems and avoiding evaluation distortion. Furthermore, by combining the analytic hierarchy process (AHP) and entropy weight method to calculate factor weights, it can take into account both subjective engineering experience and the discrete characteristics of objective data, weakening the bias of human assignment and highlighting the influence ratio of core constraint factors. Furthermore, by calculating the comprehensive evaluation value of multiple indicators, it can quantify the degree of supply and demand constraints of topographic water intake, lake water level, and reservoir regulation in a single dimension. Furthermore, by calculating the three-dimensional coupling effect intensity index, it can quantitatively characterize the comprehensive contradiction level of the linkage constraint relationship among topographic water intake, lake water level fluctuation, and reservoir regulation, thereby intuitively distinguishing the intensity of irrigation district scheduling pressure. Therefore, by implementing this invention, the objective and hierarchical quantification of the three-dimensional coupling and constraint relationship of topography, lakes, and reservoirs is realized, thereby enabling accurate identification of the source and pressure level of core water supply contradictions in irrigation areas. This provides a quantitative basis for the design of zoned water allocation and differentiated scheduling schemes, and solves the defect of traditional technologies that cannot quantitatively characterize the coupling and constraint of multiple factors.

[0010] In one optional implementation, based on the water supply benchmark of reservoirs as low-cost primary water supply sources and lakes as high-cost emergency replenishment sources, and the minimum lake replenishment volume verification standard, the minimum lake replenishment volume for each irrigation unit under different operating conditions is calculated, including: Using reservoirs and ponds as the low-cost primary water supply source and lakes as the high-cost emergency replenishment water source as the water supply benchmark, the total water demand and total water supply of each irrigation unit under different operating conditions are calculated. The total water demand of each irrigation unit is determined by the total water demand for agricultural irrigation, domestic use, industry, and ecology. Based on the multiple total water demand and multiple total water supply of each irrigation unit, the water supply and demand gap of each irrigation unit under different operating conditions is calculated. Based on the minimum lake replenishment verification standard, the minimum lake replenishment of each irrigation unit under different operating conditions is determined according to the multiple water supply and demand gaps of each irrigation unit.

[0011] The method for determining water resource allocation schemes in reservoir-dominated irrigation districts provided by this invention calculates the total demand and supply of each unit under different operating conditions, enabling the differentiation of diverse water demands from agriculture, domestic use, industry, and ecology. Furthermore, by distinguishing between the stable water supply from reservoirs and the fluctuating water supply from lakes, it can accurately match the supply and demand boundaries at different water levels. Moreover, by calculating the water gap between supply and demand for each unit and operating condition, it can stratify differentiated water shortage characteristics, such as severe water shortages during the dry season in high-level fractured areas and water surpluses during the wet and normal water seasons in low-level units, and clearly define the spatial and temporal scope of water replenishment needs. Furthermore, by using a minimum lake water replenishment standard to determine the minimum lake water replenishment volume, it strictly limits the use of lake water replenishment only when reservoir supply is insufficient, ensuring that the replenishment scale only offsets the supply and demand gap and eliminating redundant and high-cost lake water intake. Therefore, by implementing this invention, a two-tiered refined supply and demand balance accounting mechanism based on zone and operating conditions was established. This mechanism then uses the low-cost water supply benchmark of reservoirs and ponds to constrain the upper limit of lake water intake, quantitatively minimizing the scale of lake water intake and reducing the long-term water supply operation and maintenance costs of irrigation districts from the perspective of supply and demand calculation.

[0012] In one optional implementation, based on a preset four-dimensional evaluation index system, the entropy weight method and the approximation ideal solution ranking method are used to evaluate multiple pure local water source differentiated configuration schemes, and to determine the target pure local water source differentiated configuration scheme for the irrigation district to be configured, including: Using the entropy weight method, multiple weight values ​​of multiple evaluation indicators in the preset four-dimensional evaluation index system are calculated; based on multiple evaluation indicators and multiple weight values, the comprehensive closeness value of each pure local water source differentiated configuration scheme is calculated using the approximation ideal solution ranking method; based on multiple comprehensive closeness values, the target pure local water source differentiated configuration scheme for the irrigation area to be configured is determined among multiple pure local water source differentiated configuration schemes.

[0013] The method for determining water resource allocation schemes in reservoir-dominated irrigation areas provided by this invention uses the entropy weight method to calculate the weights of evaluation indicators, which can weaken the interference of secondary indicators. Furthermore, by using the approximation-ideal solution ranking method to determine the comprehensive closeness of each scheme, the differences in the dimensions of multiple evaluation indicators can be uniformly eliminated, quantifying the gap between each scheme and the ideal optimal allocation scheme, and enabling a quantifiable comparison of the merits of the schemes. Furthermore, by using the comprehensive closeness of each scheme to screen the target allocation scheme, the bias of subjective selection can be objectively avoided, and the optimal scheduling scheme that balances water supply stability, economic low cost, and suitability for fragmented farmland scenarios can be selected. Therefore, by implementing this invention, by constructing a multi-dimensional objective selection system specifically adapted to constrained lakeside irrigation areas, the limitations of traditional scheme selection based solely on the single indicator of irrigation guarantee rate are broken, ensuring that the selected scheme meets the actual needs of engineering operation and maintenance cost reduction, revitalization of existing reservoirs, and suitability for fragmented land, and that the scheme is more practical for implementation.

[0014] In one alternative implementation, the method further includes: Different operating conditions of the irrigation district to be configured were simulated, and the effect of the differentiated configuration scheme of the target pure local water source was verified under the conditions of no large-scale hub and no external water transfer based on the simulation results. The verification results were obtained. Based on the verification results, the differentiated configuration scheme of the target pure local water source was optimized.

[0015] The method for determining water resource allocation schemes in reservoir-dominated irrigation districts provided by this invention simulates and verifies the application effect of differentiated allocation schemes for target pure local water sources under extreme water level scenarios of lake abundance, normal, and low water levels in different operating conditions of the irrigation district to be allocated. Then, the verification results are used to optimize the differentiated allocation schemes for target pure local water sources, eliminating the water supply adaptability defects under extreme water level conditions, ensuring the long-term stable operation of the scheme under conditions of large fluctuations in lake water levels and the absence of large-scale hub regulation, and improving the full-cycle adaptability of the scheduling scheme.

[0016] In one optional implementation, the minimum lake replenishment volume determination criteria include: pre-extraction judgment criteria, water intake volume threshold control criteria, operating condition adaptation constraint criteria, and overall optimal configuration criteria.

[0017] The method for determining water resource allocation schemes in reservoir-dominated irrigation areas provided by this invention forms a four-layer progressive constraint rule, which strictly controls the scale of lake water intake from four dimensions: initiation conditions, water intake upper limit, water level control, and overall planning. This systematically achieves the minimization of lake water intake and the improvement of the economic efficiency of irrigation area water supply.

[0018] In one alternative implementation, multiple differentiated configuration schemes for purely local water sources include: a traditional lake-dominated scheme, a lake-pond balanced configuration scheme, and a reservoir-pond-dominated minimum lake water intake optimization scheme.

[0019] The method for determining water resource allocation schemes in reservoir-dominated irrigation districts provided by this invention can clearly quantify the comprehensive optimization gains of the reservoir-dominated scheduling mode compared to the traditional and balanced modes by constructing a gradient-differentiated scheme, providing a complete and comparable sample of alternative schemes for optimal selection.

[0020] Secondly, the present invention provides a device for determining water resource allocation schemes in reservoir-dominated irrigation areas, the device comprising: The acquisition module acquires the basic attribute dataset and actual water supply operation characteristics of the irrigation district to be configured. This district features both low mountain and hilly terrain and lakeside depressions, and does not rely on external water transfers or large-scale water storage projects. The quantification module quantifies the supply-demand coupling constraint strength of the irrigation district based on the basic attribute dataset and actual water supply operation characteristics, obtaining a three-dimensional coupling effect strength index. This index characterizes the linkage constraint relationship between topographic water intake, lake water level fluctuations, and reservoir regulation. The classification module uses farmland fragmentation and average plot elevation difference as classification indicators. Based on the three-dimensional coupling effect strength index, the topographic fragmentation distribution characteristics of the irrigation district, and field water allocation suitability conditions, it uses a dual-indicator threshold classification method to classify the irrigation district to be configured. The fragmented irrigated farmland across the entire region is divided into unit types, resulting in multiple irrigation units. A calculation module is used to calculate the minimum lake replenishment volume for each irrigation unit under different operating conditions, based on the water supply benchmark of reservoirs as the low-cost main water source and lakes as the high-cost emergency replenishment source. These different operating conditions include high water level during abundant water season, normal water level during normal water season, and low water level during dry season. A construction module is used to construct multiple differentiated pure local water source configuration schemes for the irrigation area to be configured, based on the multiple minimum lake replenishment volumes for each irrigation unit. An evaluation module is used to evaluate the multiple differentiated pure local water source configuration schemes based on a preset four-dimensional evaluation index system, using the entropy weight method and the approximation ideal solution ranking method, and to determine the target differentiated pure local water source configuration scheme for the irrigation area to be configured.

[0021] Thirdly, the present invention provides a computer-readable storage medium storing computer instructions, which are used to cause a computer to execute the method for determining water resource allocation schemes in reservoir-dominated irrigation areas as described in the first aspect or any corresponding embodiment.

[0022] Fourthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the method for determining water resource allocation schemes in reservoir-dominated irrigation areas as described in the first aspect or any corresponding embodiment. Attached Figure Description

[0023] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating the method for determining water resource allocation schemes in reservoir-dominated irrigation districts according to an embodiment of the present invention. Figure 3 This is a technical flowchart of a method for water resource allocation and scheme comparison in reservoir-dominated irrigation areas based on the coupling of low hills and open, uncontrolled lakes, according to an embodiment of the present invention. Figure 4 This is an architecture diagram of the entropy weight-TOPSIS multidimensional scheme comparison and evaluation model according to an embodiment of the present invention; Figure 5 This is a structural block diagram of a device for determining water resource allocation schemes in reservoir-dominated irrigation areas according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0027] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0028] As an optional application scenario of this invention, the specific application environment architecture or specific hardware architecture on which the method for determining water resource allocation schemes in reservoir-dominated irrigation areas depends is described here. For example... Figure 1 As shown, the architecture system may include at least one terminal device and at least one server. Figure 1The system is illustrated in the example, which includes a computer 101, a mobile terminal 102, and a server 103, and the terminal devices such as the computer 101 and the mobile terminal 102 are connected to the server 103 through a network 110.

[0029] Specifically, the terminal device can be a smartphone, tablet, laptop, PDA, desktop computer, game console, smart TV, smart wearable device, in-vehicle terminal, VR (Virtual Reality) device, AR (Augmented Reality) device, etc. Server 103 can be a standalone physical server, a server cluster, a distributed system, or a cloud server providing cloud services. Network 110 can be a wired or wireless network, examples of which include, but are not limited to, the Internet, corporate intranet, local area network, wide area network, mobile communication network, and combinations thereof.

[0030] Low-mountain and hilly lakeside irrigation areas generally face typical complex water resource allocation contradictions, with regional water supply entirely dependent on local lakes and scattered small reservoirs, resulting in significant constraints: Firstly, farmland is characterized by significant fragmentation, with scattered plots and large differences in elevation between fields. There are no contiguous and regular irrigation units, and the traditional large-scale canal system and water distribution mode cannot adapt to spatial differences. This easily leads to problems such as insufficient water supply to high-lying plots, surplus water to low-lying plots, and incomplete irrigation coverage for scattered plots. As a result, the accuracy of water distribution is low and there is a lot of ineffective loss.

[0031] Secondly, the adjacent open, uncontrolled large lakes in the region have no artificial dams, water control, or storage facilities. The water level is completely dominated by natural hydrological conditions, with large annual fluctuations and extremely poor hydrological stability. During the dry season, the water level drops sharply, resulting in insufficient fixed water intake depth and exposed and ineffective water intake points. During the wet season, the water level rises, causing large fluctuations in the water intake head. The entire process results in poor water intake stability and high difficulty in water intake.

[0032] Third, lake water intake is a high-cost method, requiring fixed pumping stations, long-distance water conveyance systems, and water level adaptation equipment. Equipment maintenance, electricity consumption, and labor management costs remain high, and long-term large-scale lake water extraction will result in extremely poor economic efficiency for irrigation supply in the irrigation district. Current technology does not differentiate between low-cost reservoir water supply and high-cost lake water supply, and has long adopted a "lake-centric, reservoir-supplemented" scheduling model, leading to an unreasonable resource utilization structure and persistently high water supply costs. Fourth, due to topographical variations, complex geology, and limited construction space, the region cannot construct large-scale reservoirs or key water control projects, lacking a centralized water resource regulation platform. This makes it impossible to mitigate lake water level fluctuations and fill water supply gaps through large-scale projects, resulting in extremely low water resource regulation and tolerance.

[0033] Fifth, to meet the irrigation needs of scattered farmland, the region has long constructed a large cluster of distributed small reservoirs and ponds. These small reservoirs and ponds are close to the fields, have short water conveyance distances, low energy consumption for water intake, and low water supply costs, possessing natural advantages for localized, nearby water supply. However, existing scheduling technologies all rely on single lake water intake scheduling or independent, scattered operation of reservoirs and ponds, failing to coordinate and link small reservoirs and ponds across the entire region for peak-shaving and off-peak storage and release. Reservoirs and ponds are left empty during the wet season and unusable during the dry season, resulting in a serious waste of existing water storage resources and an inability to replace high-cost lake water intake to undertake the main water supply task. Simultaneously, the region has no external water source replenishment, and water supply relies entirely on local lakes and ponds, further exacerbating the rigid contradiction between supply and demand.

[0034] This invention provides a method for determining water resource allocation schemes in reservoir-dominated irrigation districts. The entire process utilizes only local reservoirs and lakes as surface water bodies. By constructing a coupled scheduling system that prioritizes reservoirs and supplements lakes, it achieves stable water supply to fragmented farmland, minimizes lake water intake, and significantly reduces the water supply cost of the irrigation district.

[0035] According to an embodiment of the present invention, a method for determining water resource allocation schemes in reservoir-dominated irrigation areas is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0036] This embodiment provides a method for determining water resource allocation schemes in reservoir-dominated irrigation districts, which can be used on the aforementioned mobile terminals, such as mobile phones and tablets. Figure 2 This is a flowchart of a method for determining water resource allocation schemes in reservoir-dominated irrigation districts according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps: Step S201: Obtain the basic attribute dataset and actual water supply operation characteristics of the irrigation district to be configured.

[0037] In one optional embodiment, the irrigation area to be configured has both low mountain and hilly terrain and lakeside low-lying features, and does not rely on external water transfer or have large-scale water storage and regulation projects.

[0038] Furthermore, the basic attribute dataset is a collection of purely local meteorological, hydrological, and engineering basic data for the irrigation area to be configured. It may include rainfall, evaporation, runoff, farmland fragmentation characteristics, plot elevation distribution, plot spatial dispersion, multi-year water level temporal variation of lakes, minimum water intake level of lakes during the dry season, spatial distribution of small reservoirs and ponds across the entire area, effective storage capacity of a single reservoir, total controllable storage capacity of reservoirs and ponds, irrigation area canal system connectivity topology, and crop water demand temporal data.

[0039] Furthermore, the actual water supply operation characteristics indicate that the low-mountain and hilly lakeside irrigation area is constrained by three inherent objective conditions: fragmented terrain, large natural fluctuations in lake water levels, and decentralized and independent regulation of reservoirs and ponds. This is compounded by the outdated traditional scheduling method of "lakes as the main source and reservoirs and ponds as a supplement." Over the long term, various dynamic operational contradictions, water intake and distribution shortcomings, and current water resource utilization patterns have continuously emerged during the irrigation water supply operation. 1) Water supply operation characteristics derived from fragmented terrain: The farmland is scattered and uneven, with significant differences in elevation between plots, making the existing large-scale unified canal system water distribution mode poorly adaptable; in operation, there has been a long-term problem of insufficient water supply to high-lying fragmented plots, surplus water to low-lying and flat plots, and irrigation blind spots in scattered small plots; the field water conveyance lines are messy, the ineffective water conveyance loss has been high for a long time, and the uniformity and accuracy of water distribution are insufficient; 2) Water supply operation characteristics derived from lake water level fluctuations: The adjacent open, uncontrolled lake has no regulating gates or dams, resulting in large annual and interannual fluctuations in water level; during the dry season, the drop in water level exposes the water intake and causes water intake to be interrupted and ineffective, resulting in a sharp drop in irrigation guarantee capacity; during the wet season, the water level rises, the water intake head increases, and the power consumption of pumping stations and equipment operation and maintenance costs remain high; the annual water intake of the lake is unstable and cannot stably undertake the main water supply task. 3) Small reservoirs and ponds are scattered along the fields and are independent of each other without a coordinated scheduling mechanism; during the wet season, the reservoirs and ponds are empty and cannot uniformly store the surplus water of the lakes; during the dry season, the reservoirs and ponds are depleted of water and there is no water to supplement irrigation; the natural advantage of reservoirs and ponds in providing low-cost water supply at close range has not been brought into play, and the existing water storage resources have been idle and wasted for a long time, and cannot replace the high-cost lake water intake to undertake the main water supply task.

[0040] In one optional embodiment, for a restricted irrigation area that simultaneously possesses the characteristics of low hills and lakeside landforms, fragmented topography, large fluctuations in uncontrolled lake water levels, dispersed reservoir layout, no external water supply, and no large-scale water storage hub, firstly, the target irrigation area is delineated, and the irrigation area is verified to meet the limiting conditions: low hills and lakeside landforms, fragmented farmland with large elevation differences, adjacent to open lakes without artificial regulation, dispersed distribution of reservoirs and ponds in the fields, no external water supply, no groundwater utilization plan, and inability to construct large-scale water conservancy hubs due to topographic and geological constraints; confirm that the irrigation area is fully compatible with the research scenario of "fragmented topography, fluctuating lake water levels, and dispersed reservoir storage", and exclude unmatched irrigation areas.

[0041] Secondly, focusing on six dimensions—topography, lakes, reservoirs, meteorology, engineering, and agriculture—and relying on hydrological monitoring records, topographic mapping results, water conservancy project survey data, and agricultural planting statistical reports, static underlying data are collected. These data include, for example, farmland fragmentation, distribution of plot elevation differences, multi-year water level time series of lakes, critical water depth for low-water intake, spatial distribution and effective storage capacity of reservoirs, canal system topology, rainfall and evaporation, and crop water requirement time series. Standardized static basic datasets are then formed.

[0042] Then, combining the collected static basic data, we retrieved the historical operation records of pumping stations, reservoirs, and canals in the irrigation area, supplemented by field visits and surveys of irrigation in the fields, and determined the actual water supply operation characteristics.

[0043] Finally, the basic attribute dataset can be cross-matched and verified with the actual water supply operation characteristics, and the static endowments of topography, lakes, and reservoirs can be used to corroborate the authenticity of the corresponding operational contradictions, eliminating invalid data that conflict with each other or are detached from the reality of the irrigation area.

[0044] Step S202: Based on the basic attribute dataset and actual water supply operation characteristics, the supply and demand coupling constraint strength of the irrigation area to be configured is quantified to obtain the three-dimensional coupling effect strength index of the irrigation area to be configured.

[0045] In one optional embodiment, the supply and demand coupling constraint intensity represents the intensity of the comprehensive supply and demand contradiction formed by the superposition and linkage of three objective conditions: the fragmented terrain water intake constraint, the natural water level fluctuation constraint of the lake, and the decentralized regulation and storage constraint of small reservoirs in the low mountain and hilly lakeside irrigation area. It is used to quantitatively characterize the overall scheduling pressure such as water shortage, high cost, and irrigation blind spots brought about by the coupling of water intake adaptation, water source stability, and regulation and storage capacity in the irrigation area.

[0046] Furthermore, the three-dimensional coupling effect intensity index is used to characterize the linkage and constraint relationship among topographic water intake, lake water level fluctuation, and reservoir regulation in the irrigation area to be configured. Furthermore, the value range of this three-dimensional coupling effect intensity index is 0~1. The larger the value, the more prominent the linkage and constraint effect among topography, lakes, and reservoirs, and the stronger the overall supply and demand contradiction and scheduling pressure in the irrigation area. This allows for a direct distinction between weak, medium, and strong coupling contradiction levels.

[0047] In one optional embodiment, the fragmented terrain of the irrigation area exacerbates the uneven water distribution caused by lake water level fluctuations. Furthermore, the dispersed and independent reservoirs cannot offset the dual water supply deficiencies caused by the terrain elevation differences and drastic lake water level changes. These three factors mutually constrain and overlap. In this embodiment, using a basic attribute dataset and actual water supply operation characteristics derived from fragmented terrain, lake water level fluctuations, and decentralized reservoir regulation as dual inputs, the supply-demand coupling constraint intensity of the irrigation area to be configured is quantified. This allows for precise identification of the source and severity of water supply contradictions in the irrigation area, avoiding the limitation of single-dimensional indicators failing to fully reflect complex water supply contradictions.

[0048] Step S203: Using farmland fragmentation and average plot elevation difference as grading indicators, and based on the three-dimensional coupling effect intensity index, the topographic fragmentation distribution characteristics of the irrigation area to be configured, and the field water distribution adaptation conditions, the dual-index threshold grading method is used to classify the fragmented irrigated farmland of the entire irrigation area to be configured into unit types, resulting in multiple irrigation units.

[0049] In one optional embodiment, the farmland fragmentation degree is used to quantify the degree of spatial dispersion and fragmentation of farmland in low-mountain and hilly irrigation areas, and can characterize the degree of fragmentation of plots, the spatial dispersion of plots, and the integrity of farmland contiguous areas. Furthermore, the higher the farmland fragmentation degree value, the more fragmented the farmland is, the less contiguous and regular the irrigation units are, the worse the adaptability of the unified canal system for water distribution, the easier it is to generate irrigation blind spots, and the greater the water conveyance loss.

[0050] Furthermore, the average elevation difference of a plot represents the average vertical drop of all cultivated land plots within each area of ​​the irrigation district, used to reflect the degree of topographic relief in the region. Moreover, the higher the average elevation difference of the plot, the more significant the vertical drop between fields, making it difficult for conventional large-scale water distribution to deliver water evenly, leading to a water imbalance problem of water shortage at high elevations and surplus water at low elevations.

[0051] Furthermore, the fragmented distribution characteristics of the terrain represent the inherent spatial distribution pattern of cultivated land in the low mountain and hilly lakeside irrigation area; the field water distribution adaptation conditions represent the degree of matching and adaptation between the existing irrigation water conveyance and distribution engineering mode and the regional terrain and cultivated land distribution, which is used to judge whether a set of water distribution methods can meet the field irrigation needs evenly and with low loss.

[0052] Furthermore, the dual-indicator threshold classification method represents a decision-making method that simultaneously selects two key indicators, sets multiple levels of critical values ​​(thresholds) for each, and classifies objects into different risk / level categories through two-dimensional combination judgment.

[0053] In this embodiment, the dual-index threshold grading method uses two independent topographic indicators—farmland fragmentation and average plot elevation difference—as the grading basis, and combines the numerical ranges of the two indicators to divide threshold intervals, thus classifying fragmented farmland across the entire area into different types. Furthermore, this method can take into account both the spatial fragmentation and vertical elevation differences of farmland, match the complex terrain characteristics of irrigation areas with varying elevations and scattered distribution, and avoid the one-sidedness of single-index grading.

[0054] In one alternative embodiment, the weak / medium / strong coupling level can be determined based on the three-dimensional coupling effect strength index, and then the severity of the grading threshold can be adjusted according to the coupling level: (1) Strong coupling (high CEI value, prominent supply and demand contradiction in the whole region): narrow the index classification range, improve the classification precision, subdivide more partition levels, and accurately distinguish the water distribution shortcomings caused by the difference in crushing height; (2) Coupling: Standard interval thresholds are used, and conventional three-level division is employed; (3) Weak coupling (low CEI value, low water supply pressure): relax the index grading range, simplify the zoning standards, and reduce the subdivision level of the zoning.

[0055] Furthermore, combining the precision rules determined by the coupling strength in the previous step, statistical analysis is performed on the two sets of data: the overall farmland fragmentation and the average elevation difference of the plots. By utilizing the normal distribution characteristics of the indicators, three levels of numerical thresholds—high, medium, and low—are defined, thereby forming a dual-indicator combination judgment rule of "farmland fragmentation + average elevation difference of plots".

[0056] Furthermore, based on a combination of two-level indicator thresholds, and considering the fragmented topographical distribution characteristics of the irrigation area and the field water allocation suitability conditions, cultivated land can be divided into three independent irrigation units: (1) High-level fragmented irrigation unit: The area has high degree of fragmentation of cultivated land and large average elevation difference between plots. The plot elevation difference is significant, and the vertical drop between fields is large, making it difficult to adapt to conventional unified water distribution. The uniformity of water conveyance and distribution is poor. The cultivated land is scattered and fragmented, and the connectivity between plots is weak. The conditions for large-scale contiguous irrigation are poor. It is the unit with the worst water distribution adaptability and the most prominent contradiction in water intake scheduling in the irrigation area.

[0057] (2) Intermediate transitional irrigation unit: The degree of fragmentation of cultivated land and the average elevation difference of plots in the region are at a moderate level. The topographic relief and degree of fragmentation of cultivated land are relatively moderate. There are no extreme water allocation shortcomings. The unified water allocation has certain limitations. The irrigation effect can be optimized by local regulation of reservoirs and ponds and regional water replenishment. It belongs to the transitional unit of irrigation area supply and demand contradiction.

[0058] (3) Low-lying, gently sloping irrigation units: These units have low farmland fragmentation and small average elevation differences between plots. The overall terrain is flat with minimal elevation variations, resulting in good farmland contiguousness, low irrigation water loss, excellent water distribution uniformity, strong adaptability to unified water allocation, and minimal difficulty in water intake scheduling.

[0059] Step S204: Based on the water supply benchmark of reservoirs and ponds as low-cost main water supply sources and lakes as high-cost emergency replenishment water sources, the minimum lake replenishment volume for each irrigation unit under different operating conditions is calculated using the minimum lake replenishment volume verification standard.

[0060] In one alternative embodiment, based on the constraints of no large-scale hubs and no external water transfer, a water supply benchmark is established with reservoirs and ponds as low-cost main water supply sources and lakes as high-cost emergency replenishment sources, while strictly limiting the scale of water intake from lakes under normal circumstances.

[0061] In one optional embodiment, the minimum lake replenishment standard means that lake replenishment will only be initiated after the local reservoir water source has been completely depleted, and the optimal lake water intake scale will be accurately determined. This may include: (1) Pre-water intake judgment criteria: Under each irrigation unit and each water level condition, the effective adjustable water volume of the small reservoirs in the unit shall be fully utilized. When the total water supply of the reservoirs can fully cover the irrigation water demand of the unit, lake water intake shall not be used; lake water replenishment shall only be initiated when the water supply capacity of the reservoirs cannot meet the water demand in the fields and a supply-demand gap occurs.

[0062] (2) Water withdrawal threshold control standard: The lake water replenishment shall not exceed the limit, with the only upper limit being to just balance the supply and demand gap and ensure the basic irrigation needs of the irrigation area, and redundant water withdrawal shall be eliminated. The water replenishment scale shall be strictly equal to the water supply and demand gap of the corresponding unit under the current operating conditions, so as to minimize the scale of lake water withdrawal.

[0063] (3) Operating condition adaptation constraint standard: The upper limit of water intake is determined in combination with the operating conditions of different water levels in the lake: the water intake capacity is sufficient during the high and normal water periods, and the water is replenished in full according to the theoretical gap; during the dry season, the water intake is constrained by insufficient water depth, poor water intake stability and high energy consumption cost. The minimum water replenishment volume is determined based on the minimum operating threshold of the existing water intake facilities, and priority is given to ensuring the core irrigation water.

[0064] (4) Optimal configuration standard for the whole area: taking into account the differences in water demand of high-level, medium-level and low-level irrigation units, priority is given to the use of reservoir clusters to regulate and absorb regional water shortages, and lake water intake is only used as a backup emergency water source. From the mechanism, the high energy consumption of lake water intake on a regular and large scale is minimized, and the economic efficiency and stability of irrigation area water supply are improved.

[0065] In one optional embodiment, different operating conditions used for differentiated calibration of dual-source water supply capacity may include: (1) High water level in lakes: The water level of the lake is at a high level throughout the year, the water depth is sufficient, the water head is low, the water intake efficiency is high, the energy consumption is relatively low, the water available for the lake is sufficient, and the lake water resources can be pumped to fill the entire reservoir. (2) Normal water level conditions of lakes: The water level of lakes is within the average range of the year, the water intake conditions are moderate, the water intake capacity is moderate, and it can only supplement a small water shortage in local irrigation units. (3) Low water level conditions in lakes: The water level in lakes is at its lowest point of the year. Insufficient water depth can easily cause the water intake to become exposed and fail. The water intake head increases significantly, energy consumption costs rise sharply, the efficiency of lake water intake is poor, and the amount of water that can be taken is greatly reduced. Only in extreme water shortages can water be taken in limited emergency situations.

[0066] Furthermore, the minimum lake replenishment volume represents the minimum amount of water that needs to be drawn from the lake to just fill the supply-demand gap and ensure basic irrigation when the water storage in the reservoirs within the irrigation unit is insufficient to cover the total water demand for the current period, under specific irrigation unit and lake water level conditions. Moreover, this water volume does not include redundant water intake; strictly controlling the scale of lake water intake can minimize the total amount of lake water intake in the irrigation area, thereby reducing water supply operating costs and investment in water diversion projects.

[0067] In one optional embodiment, irrigation reservoirs have the advantage of low-cost, nearby water supply, while the energy consumption and operation and maintenance costs of lake water intake are relatively high. At the same time, the water levels of lakes during high, low, and low seasons directly change the water intake capacity and cost, and there are differentiated water demand gaps in the fragmented zoning of arable land.

[0068] In this embodiment, the three types of irrigation units—high-level broken, mid-level transitional, and low-level flat—are used as the calculation carrier. Following the water supply benchmark of "reservoirs and ponds as the main body and lakes as the auxiliary body," and utilizing the four-layer progressive minimum lake water replenishment determination rule, the minimum lake water replenishment scale required for each irrigation unit under the three types of lake water level conditions (abundant, normal, and dry) can be calculated respectively. This enables the quantification of the optimal lake water intake upper limit for each zone and each hydrological period.

[0069] Step S205: Based on the minimum lake replenishment volume of each irrigation unit, construct multiple differentiated configuration schemes for pure local water sources in the irrigation area to be configured.

[0070] In one optional embodiment, multiple differentiated configuration schemes for purely local water sources may include: (1) Traditional lake-dominated scheme: water supply is mainly based on lake water intake, and small reservoirs are scattered and idle for backup; unified water intake and distribution throughout the region does not adapt to the characteristics of fragmented farmland and water level fluctuations. The scale of normal lake water intake is large and the water supply cost is high. During the dry season, water intakes fail and water supply to high-level fragmented plots is insufficient, and reservoir resources are not effectively utilized.

[0071] (2) Lake and pond balanced configuration scheme: Lake and pond coordinated water supply, unified water storage and balanced water replenishment in reservoirs and ponds, and moderate reduction of lake water intake scale; during the dry season, the water supply pressure is shared by reservoirs and ponds, which alleviates the water supply interruption and high cost problem to a certain extent, but the main water supply of reservoirs and ponds is not realized, the water intake reduction effect of lakes is limited, and the irrigation adaptability of fragmented plots is generally poor.

[0072] (3) Optimization scheme of minimum lake water intake dominated by reservoirs and ponds: Under high water level conditions, only the surplus water of the lakes is used to replenish and fill the reservoirs and ponds in the whole area, and no large-scale lake water intake irrigation is carried out, so as to maximize the storage of local water volume and reduce the cost of lake water intake; Under normal water level conditions, the whole area is mainly supplied by precise water supply in the reservoir clusters and ponds, and only a small amount of lake water is taken to supplement the local gap; Under low water level conditions, the inefficient lake water intake is shut down, and water supply is completely relied on the hierarchical scheduling of the reservoir clusters and ponds. High-level broken units are matched with high-level reservoirs and ponds, and low-level units are matched with nearby reservoirs and ponds to solve the problems of water intake failure at low water level and irrigation blind spots in broken plots. Only in extreme water shortage times is lake water taken in limited quantities for emergency use, so as to minimize the scale of lake water intake and the lowest water supply cost.

[0073] In one optional embodiment, based on the quantified results of the minimum lake water replenishment for each irrigation unit under the three water level conditions of abundant, normal and dry periods, and with the irrigation area using only local reservoirs and lakes as two types of surface water sources and without external water transfer or groundwater as a hard boundary, a gradient-differentiated complete water supply scheduling scheme can be built according to different lake and pond water intake priority logic and water intake control intensity.

[0074] For example, firstly, the theoretical minimum lake water extraction scale is determined for each scenario, and this is used as the quantitative constraint bottom line for scheme design.

[0075] Then, lock in the general preconditions for all solutions, which may include: no groundwater extraction throughout the process, no external water source replenishment, water supply relying solely on small regional reservoirs and open, uncontrolled lakes, adapting to restricted scenarios with no large-scale water conservancy hubs and fragmented farmland, and all solutions must not exceed the constraints of this water source and engineering.

[0076] Finally, three differentiated configuration schemes were constructed according to the primary and secondary logical gradient of lake and pond water supply. The schemes were supplemented with reservoir and pond storage and release sequence, zoned water allocation ratio, lake water intake start and stop conditions, and water replenishment upper limit control details under high, normal, and low water level conditions. After matching the differentiated water demand characteristics of high, medium, and low irrigation units, multiple final pure local water source differentiated configuration schemes were formed that are complete, implementable, and quantifiable.

[0077] Step S206: Based on the preset four-dimensional evaluation index system, the entropy weight method and the approximation ideal solution ranking method are used to evaluate multiple pure local water source differentiated configuration schemes and determine the target pure local water source differentiated configuration scheme for the irrigation area to be configured.

[0078] In one optional embodiment, the preset four-dimensional evaluation index system represents a multi-dimensional evaluation standard adapted to scenarios of fragmented irrigation areas near lakes in low hills and low mountains without external water transfer or large-scale hubs. It can include multiple core quantitative indicators, focusing on three major economic core indicators: lake water intake reduction rate, unit irrigation water supply cost, and reservoir load utilization rate. It also covers irrigation coverage rate of fragmented plots, low water level water supply guarantee rate, water level fluctuation adaptability, water intake stability, water transmission loss rate, irrigation guarantee rate, ecological water use guarantee rate, supply and demand gap fluctuation rate, and engineering adaptability.

[0079] Furthermore, the entropy weight method (EWM) represents an objective weighting method for calculating index weights based on the principle of information entropy.

[0080] Furthermore, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is a method for ranking the options in a multi-attribute decision problem by using the ideal and negative ideal solutions.

[0081] In one alternative embodiment, traditional schemes rely solely on a single irrigation index for selection, leading to subjective biases and failing to address the core needs of cost reduction, reservoir revitalization, and adaptation to fragmented farmland. This embodiment, however, evaluates multiple differentiated allocation schemes based solely on local water sources. Using a pre-defined four-dimensional evaluation index system, it employs a fusion of entropy weighting and an approximation-ideal-solution ranking method for quantitative evaluation. This eliminates subjective biases and ultimately selects the optimal water resource allocation scheme that balances low-cost water intake, high reservoir utilization, full coverage of fragmented land, and stable water supply under stable water level conditions.

[0082] The method for determining water resource allocation schemes in reservoir-dominated irrigation districts provided in this embodiment is aimed at fragmented irrigation districts in low-mountain and hilly areas near lakes that lack external water transfer and large-scale water storage hubs. It achieves stable water supply to fragmented farmland, minimizes the scale of water intake from lakes, and reduces the operating cost of water supply in irrigation districts, filling the gap in refined water allocation technology for purely local and limited irrigation districts.

[0083] In some optional implementations, step S202 above includes: Step S2021: Based on the basic attribute dataset and actual water supply operation characteristics, obtain multiple coupling constraint factors according to preset screening criteria.

[0084] In one optional embodiment, the preset screening criteria may include mechanism relevance, dimensional completeness, regional adaptability, data quantifiability, and indicator independence.

[0085] Among them, the mechanism relevance means that the candidate indicators must have a clear hydrological and engineering internal causal logic with the three types of water supply constraints: irrigation area topography water intake, lake water level fluctuations, and reservoir regulation. They must be able to directly explain the causes of the contradictions of difficult water intake, unstable water supply, and insufficient regulation in the irrigation area, and exclude irrelevant indicators that have no physical connection with the supply and demand coupling constraints.

[0086] Furthermore, dimensional integrity means that all the selected factors need to fully cover the three-dimensional subsystems of topographic water intake constraints, lake water source fluctuation constraints, and reservoir storage capacity constraints. Each subsystem is assigned at least one corresponding quantitative indicator, and there is no situation where a certain dimension is completely without an indicator representation. This can further ensure that the three-dimensional coupled evaluation system does not lack any core constraint dimension and fully characterizes the complex water supply contradictions in the irrigation area.

[0087] Furthermore, regional adaptability means fitting the specific characteristics of the target irrigation area: no external water source, no large-scale water conservancy hub, fragmented farmland in low hills, open and uncontrolled lakes, distributed small reservoir clusters, adapting to restricted irrigation area scenarios with purely local surface water sources.

[0088] Furthermore, quantifiable data indicates that the indicators have collectable, statistical, and monitorable measured values, which in turn enable the acquisition of continuous quantitative data through channels such as hydrological records, topographic mapping, water conservancy project surveys, and agricultural statistics.

[0089] Furthermore, indicator independence means that the constraint information reflected by each candidate indicator does not overlap, has no high linear correlation, and a single water supply bottleneck does not rely on multiple redundant indicators for repeated characterization, thus avoiding information redundancy. For example, the average elevation difference of a plot and the fragmentation of arable land respectively characterize two independent terrain features: vertical undulation and spatial fragmentation. Their information does not overlap, satisfying the independence requirement. Furthermore, for two highly correlated similar indicators describing the same problem, only one is retained.

[0090] Furthermore, each indicator corresponds to three types of constraint systems, which can accurately characterize the inherent mechanisms of regional topographic water intake constraints, lake water source fluctuation constraints, and existing reservoir storage capacity constraints. This fully constructs a three-dimensional coupled constraint evaluation system for irrigation district water supply systems, providing core indicator support for subsequent quantitative analysis of supply and demand contradictions and selection of differentiated scheduling schemes.

[0091] In one optional embodiment, multiple coupling constraints may include farmland fragmentation, average elevation difference of plots, annual water level fluctuation of lakes, guaranteed water depth for lake intake during dry season, number and density of small reservoirs and ponds, and the proportion of effective storage capacity of reservoirs and ponds in the entire region.

[0092] Among them, the annual water level variation of a lake represents the difference between the highest and lowest water levels throughout the year for an open, uncontrolled lake, and is used to characterize the severity of natural fluctuations in lake water levels within and between years. Furthermore, a sudden drop in water level during the dry season can easily cause the water intake to become exposed and fail, while a rise in water level during the wet season will significantly increase the water intake head and raise the energy consumption costs of pumping stations, directly exacerbating the core contradictions of unstable water intake and high water supply costs in the irrigation area. Therefore, the larger the annual water level variation of the lake, the worse the hydrological stability of the lake.

[0093] Furthermore, the guaranteed water depth for lake intake during the dry season represents the minimum critical water depth of the lake required to ensure stable water intake for fixed water intake facilities in the irrigation area. Moreover, if the actual water depth of the lake during the dry season is lower than this value, the water intake cannot receive water normally, the water intake system fails, and irrigation water supply is interrupted.

[0094] Furthermore, the guaranteed water depth for water intake during the dry season of the lake can quantify the hard constraints on water intake during the dry season. The higher the value, the greater the difficulty of water intake during the dry season and the more prominent the shortcomings of the lake's water supply. This is used to characterize the water supply risk of the lake during the dry season.

[0095] Furthermore, the number density of small reservoirs and ponds indicates the distribution of distributed small reservoirs and ponds within a unit irrigated area, reflecting the spatial density of reservoirs and ponds in the field. A higher density indicates more nearby water storage projects within the irrigation area, providing the basic conditions for low-cost zoned water supply from reservoirs and ponds; a lower density indicates a lack of nearby water storage facilities throughout the area, forcing reliance on high-cost lakes for water intake.

[0096] Furthermore, the effective storage capacity ratio of reservoirs and ponds in the whole region represents the total dispatchable water storage capacity of all small reservoirs and ponds in the region after deducting dead storage capacity and evaporation and seepage losses, as a percentage of the total annual irrigation water demand of the irrigation district. It can directly reflect the overall capacity of existing reservoirs and ponds to replace lake water supply. That is, the higher the ratio, the more irrigation water the reservoirs and ponds can bear and the greater the space for reducing lake water intake. A low ratio indicates that the local reservoirs and ponds have insufficient storage capacity and lake water must be drawn on a large scale to make up the gap.

[0097] In one optional embodiment, all quantifiable raw indicators are determined using the basic attribute dataset, and the water supply contradiction mechanism corresponding to each indicator is labeled in combination with the actual water supply operation characteristics. Then, candidate indicators that are intrinsically related to topographic water intake, lake water level, and reservoir regulation are preliminarily screened.

[0098] Furthermore, candidate indicators can be verified one by one against the five preset screening criteria. For example, indicators that are irrelevant to the mechanism, cannot fully cover the three-dimensional subsystem, do not match the scenario of no external water transfer or large hub in the irrigation area, have no measured statistical data, or have highly overlapping indicator information can be eliminated.

[0099] Furthermore, after multiple rounds of screening, the final six core coupling constraint factors can be determined.

[0100] Step S2022: Using the analytic hierarchy process (AHP) and the entropy weight method, calculate the weight values ​​of multiple factors for multiple coupling constraints.

[0101] In one alternative embodiment, the Analytic Hierarchy Process (AHP) represents a systematic decision-making method that combines qualitative and quantitative approaches to clarify complex problems, calculate weights, and select the optimal solution.

[0102] In one optional embodiment, firstly, the analytic hierarchy process (AHP) is used, combined with irrigation district engineering scheduling experience, to construct a pairwise comparison judgment matrix of factors. Then, by solving the matrix, the subjective weights of each coupled constraint factor can be obtained. Furthermore, the weight proportion of the core constraint factors—topography, lakes, and reservoirs—is prioritized for increase.

[0103] Secondly, the six coupling constraint factors are standardized by range to eliminate dimensions, and the dispersion of each index data is calculated by information entropy, so that objective entropy weights that are completely based on measured data can be obtained.

[0104] Finally, by integrating and correcting the subjective weights and objective entropy weights, a comprehensive weight value for each factor that balances engineering experience and measured data characteristics can be obtained. Furthermore, a higher weight value indicates a stronger driving effect of that factor on the supply-demand coupling contradiction in the irrigation district.

[0105] Step S2023: Based on the preset three-dimensional indicator system, calculate the comprehensive evaluation value of multiple indicators using multiple coupling constraint factors and multiple factor weight values.

[0106] In one optional embodiment, a preset three-dimensional index system represents a hierarchical evaluation framework constructed to match the triple water supply constraints of the low-mountain and hilly lakeside irrigation area. This framework consists of three coupled subsystems: topographic water intake constraints, lake water source fluctuation constraints, and reservoir storage capacity constraints. Furthermore, these three subsystems correspond to three core water supply shortcomings: fragmented farmland elevation differences, uncontrolled lake water level fluctuations, and idle distributed reservoirs. Through six corresponding quantitative coupling constraint factors, the framework can fully cover the three underlying constraints of the irrigation area: natural topography, lake hydrology, and existing water conservancy projects.

[0107] In one optional embodiment, the six coupling constraint factors can be grouped according to a three-dimensional index system and assigned to corresponding subsystems. Specifically, the topography subsystem includes farmland fragmentation and average elevation difference of plots; the lake subsystem includes annual water level fluctuations of lakes and guaranteed water depth for water intake during the dry season; and the reservoir subsystem includes the number and density of small reservoirs and the proportion of effective storage capacity of reservoirs across the entire region.

[0108] Furthermore, the standardized factor values ​​within each group are multiplied by their corresponding comprehensive weights and summed to obtain the comprehensive scores for topographic water intake constraints, lake water source fluctuation constraints, and reservoir regulation capacity constraints, respectively.

[0109] Step S2024: Calculate the three-dimensional coupling effect intensity index of the irrigation area to be configured based on the comprehensive evaluation values ​​of multiple indicators.

[0110] In an optional embodiment, by combining multiple comprehensive evaluation values ​​of the obtained indicators, the three-dimensional coupling effect intensity index of the irrigation area to be configured can be calculated using the following relationship (1):

[0111] In the formula: Indicates the intensity index of three-dimensional coupling effect; This indicates the comprehensive score for water intake constraints due to topographical features; This indicates the comprehensive score for the constraints imposed by fluctuations in lake water resources. This indicates the comprehensive score that reflects the constraints on the reservoir's water storage capacity.

[0112] Furthermore, The value ranges from 0 to 1. The larger the value, the more significant the coupling effect of mutual constraints and interactions of the three-dimensional system, and the stronger the supply and demand contradiction and scheduling pressure in the irrigation area.

[0113] In some optional implementations, step S204 above includes: Step S2041: Using reservoirs and ponds as the low-cost main water supply source and lakes as the high-cost emergency supplementary water source as the water supply benchmark, calculate the total water demand and total water supply of each irrigation unit under different operating conditions.

[0114] In one optional embodiment, the total water demand of each irrigation unit is determined by the total water demand for agricultural irrigation, domestic, industrial, and ecological purposes.

[0115] In one optional embodiment, reservoirs are used as a priority low-cost and stable water supply source, while lakes are used only as a high-cost water source for later replenishment. Thus, the adjustable water storage capacity of reservoirs is counted separately during the accounting process.

[0116] Furthermore, the Penman-Monteith formula can be used to calculate the potential evapotranspiration of crops, and then combined with the crop coefficient and effective rainfall to obtain the net irrigation quota. Further, by combining the unit cultivated land area and irrigation water use coefficient, the gross agricultural irrigation water volume can be calculated, as shown in the following relationship (2):

[0117] In the formula: Indicates the first The irrigation unit in the first Agricultural irrigation water demand under operating conditions; Indicates the first The cultivated land area of ​​each irrigation unit; This represents the net irrigation quota per unit area; This represents the irrigation water utilization coefficient of the irrigation district.

[0118] Furthermore, regional population, industry scale, and industry water consumption quotas can be used to calculate domestic and industrial water demand. Additionally, the Tennant method can be used to calculate ecological water use.

[0119] Furthermore, by adding up the total water demand for agricultural irrigation, domestic use, industry, and ecological purposes calculated above, we can obtain the total water demand for each irrigation unit under the corresponding operating conditions. .

[0120] Furthermore, the local available water supply consists of two parts: the adjustable water storage capacity of unit reservoirs and ponds, and the water extractable capacity of the working lakes. 1) Adjustable water storage capacity of reservoirs and ponds Based on the effective storage capacity of unit reservoirs, after deducting dead storage capacity and evaporation and seepage losses, the dispatchable water supply is obtained, which does not change with the fluctuation of lake water level, thus providing a stable water source.

[0121] 2) Available water volume under lake operating conditions Based on different water level constraints, the amount is significantly reduced during the dry season due to water depth limitations, while it is fully calculated based on water intake capacity during the normal and wet seasons, reflecting the fluctuating characteristics of lake water sources.

[0122] Furthermore, the total water supply of each irrigation unit under the corresponding operating conditions can be calculated using the following relationship (3):

[0123] In the formula: Indicates the first The irrigation unit in the first Total water supply under operating conditions.

[0124] Step S2042: Calculate the water supply and demand gap for each irrigation unit under different operating conditions based on the multiple total water demand and multiple total water supply for each irrigation unit.

[0125] In an alternative embodiment, the total water demand of each irrigation unit is combined. and multiple total water supply The water supply and demand gap for each irrigation unit under different operating conditions can be calculated, as shown in the following equation (4):

[0126] In the formula: Indicates the first The irrigation unit in the first The water supply and demand gap under operating conditions is further defined as follows: a value greater than 0 indicates a water shortage, and the larger the value, the more severe the water shortage; a value less than or equal to 0 indicates that the water supply and demand are balanced and there is no water shortage pressure.

[0127] Step S2043: Based on the minimum lake replenishment verification standard, determine the minimum lake replenishment for each irrigation unit under different operating conditions according to the multiple supply and demand gaps of each irrigation unit.

[0128] In one alternative embodiment, the water volume is first determined based on the supply-demand gap. Water shortage classification should be carried out. Specifically, if... This indicates a water supply shortage, requiring the use of lakes for replenishment; if If the water level is 0, it means there is a water surplus and no need to draw water from the lake.

[0129] Furthermore, using the minimum lake replenishment standard as a calculation constraint, for each irrigation unit... Water level conditions Based on the gap determination result, substitute it into the following relation (5):

[0130] In the formula: Indicates the first The irrigation unit in the first Minimum lake replenishment under operating conditions; Indicates the first The irrigation unit in the first The effective water supply of the reservoir under operating conditions.

[0131] Furthermore, if This indicates that the basic water availability of reservoirs and natural lakes has met the demand. That is, the minimum lake replenishment amount is taken as 0.

[0132] Furthermore, if This indicates that relying solely on reservoirs for water supply results in water shortages, and the theoretical minimum lake replenishment amount is equal to... This perfectly fills the water shortage gap that the reservoir cannot cover.

[0133] Furthermore, the theoretical calculation values ​​can be corrected by distinguishing between three types of working conditions: (1) High water level and normal water level conditions: The water replenishment value calculated by the formula is directly used to fully make up for the supply and demand gap; (2) Low water level conditions: Combined with the minimum operating threshold of water intake facilities, the water replenishment volume is reduced, the water replenishment scale is reduced, and priority is given to ensuring the core irrigation water of the high-level crushing unit, so as to form the corrected actual minimum lake water replenishment volume.

[0134] Furthermore, by performing quantitative calculations on a unit-by-unit and working-condition-by-working-condition basis, it is possible to accurately distinguish the differentiated supply and demand characteristics, such as severe water shortages in high-level fractured units during the dry season and water surpluses in low-level units during the normal and abundant seasons. This provides a quantitative basis for subsequent coordinated scheduling of reservoir clusters and scheduling schemes that minimize high-cost lake water intake.

[0135] In some optional implementations, step S206 above includes: Step S2061: Using the entropy weight method, calculate multiple weight values ​​of multiple evaluation indicators in the preset four-dimensional evaluation index system.

[0136] In one optional embodiment, the original quantitative data of all evaluation indicators in a preset four-dimensional evaluation indicator system are obtained.

[0137] Furthermore, range standardization is performed on both positive and negative evaluation indicators to eliminate differences in the dimensions and numerical ranges of different indicators.

[0138] Furthermore, the information entropy of each evaluation index is calculated, and the information entropy value is used to determine the degree of dispersion of the index data. Moreover, the higher the dispersion, the stronger the ability to distinguish between superior and inferior solutions, and a higher basic entropy weight is assigned to it.

[0139] Furthermore, the weights of the three-dimensional coupling factors obtained in step S202 can be integrated for secondary correction, and the weight ratio of the core indicators characterizing water supply economy, reservoir revitalization, and adaptation of fragmented land plots can be further increased.

[0140] Furthermore, by normalizing the corrected values, we can obtain the final objective weight values ​​for all evaluation indicators.

[0141] Step S2062: Based on multiple evaluation indicators and multiple weight values, the comprehensive approximation value of each pure local water source differentiated configuration scheme is calculated using the approximation ideal solution ranking method.

[0142] In one optional embodiment, the standardized index value is multiplied by the corresponding index weight to obtain a weighted evaluation matrix. Further, the positive ideal solution and the negative ideal solution are determined respectively.

[0143] Among them, the positive ideal solution represents the optimal level of all indicators, namely the theoretical scheme with the least water intake from the reservoir, the lowest water supply cost, the highest reservoir utilization rate, and full coverage of fragmented land; the negative ideal solution represents the worst of all indicators, namely the extreme shortcoming of the traditional lake-dominated scheme.

[0144] Furthermore, the Euclidean distances to the positive ideal solution and the negative ideal solution for each scheme are calculated separately. Then, the overall closeness of each scheme is calculated according to the TOPSIS standard formula.

[0145] Furthermore, the proximity score ranges from 0 to 1, with the closer the score is to 1, the closer the solution is to the optimal water resource allocation requirements of the irrigation area.

[0146] Step S2063: Based on multiple comprehensive proximity values, determine the target pure local water source differentiated configuration scheme for the irrigation area to be configured from multiple pure local water source differentiated configuration schemes.

[0147] In one optional embodiment, the overall similarity of the traditional lake-dominated scheme, the lake-pond balanced configuration scheme, and the reservoir-pond-dominated minimum lake water intake optimization scheme is ranked from largest to smallest. Then, based on the ranking results, the scheme corresponding to the maximum overall similarity is determined as the target optimal configuration scheme. In this embodiment, the reservoir-pond-dominated minimum lake water intake optimization scheme has the highest similarity and is therefore selected as the optimal configuration scheme for the irrigation area to be configured.

[0148] Furthermore, the suitability of the optimal solution can be verified. Specifically, it can be checked whether the solution meets the core management requirements of irrigation districts, namely, minimizing lake water intake, high utilization rate of reservoirs and ponds, full coverage of fragmented plots, and stable water supply during the dry season, and solutions that do not meet the suitability standards can be eliminated.

[0149] In some optional implementations, the above method further includes: Step a1: Simulate different operating conditions of the irrigation district to be configured, and verify the effect of the target pure local water source differentiated configuration scheme under the conditions of no large hub and no external water transfer based on the simulation results, and obtain the verification results.

[0150] In one optional embodiment, the hard constraints of the simulation are first determined: no external water transfer is introduced, no new large-scale water conservancy projects are built, no groundwater is used, and only two types of local water sources are used: distributed small reservoirs and ponds in the irrigation area and open, uncontrolled lakes. Further, three types of simulation conditions are built sequentially: high water level during abundant water season, normal water level during normal water season, and low water level during dry season, with the low water level during dry season being the extremely unfavorable verification condition.

[0151] Furthermore, the system loads all the scheduling rules for the target pure local water source differentiated configuration scheme: during the high-water season, it prioritizes the use of surplus lake water to fill the reservoirs and ponds throughout the region; during the normal water season, the reservoirs and ponds are mainly supplied by different zones with only a small amount of lake water to supplement the shortage; during the dry season, it shuts down inefficient lake water intake facilities; and it matches high and low-level irrigation units with corresponding reservoirs and ponds for graded water supply.

[0152] Furthermore, by combining the time-series data of water demand of each irrigation unit, adjustable storage capacity of reservoirs and ponds, and water intake of lakes under different operating conditions, long-term simulations are used to deduce the entire process of lake storage and release, zoned water distribution, and lake water intake throughout the entire cycle.

[0153] Furthermore, by referring to the preset four-dimensional evaluation index system, key verification data were quantitatively extracted from the simulation results, and the effectiveness of the target pure local water source differentiated configuration scheme under the conditions of no large-scale hub and no external water transfer was verified.

[0154] Key verification data may include irrigation coverage of fragmented plots, water intake success rate during dry season, total water intake scale of lakes in the whole area, unit irrigation water supply cost, utilization rate of small reservoir clusters, water supply guarantee rate at low water levels, water transmission ineffective loss rate, and irrigation guarantee rate of the whole area.

[0155] Furthermore, it is possible to focus on verifying whether there is a large-scale water shortage in the high-level broken irrigation units during the dry season, and whether the reduction in lake water intake has met the standards.

[0156] Furthermore, the advantages and existing shortcomings of the schemes under the three types of working conditions can be classified and integrated. For example, under the extreme working conditions of low water, the water supply guarantee of local plots is insufficient, the timing of cross-unit linkage regulation and storage of reservoirs and ponds is unreasonable, and the emergency water replenishment threshold of lakes is set too high. After fully summarizing the various quantitative verification indicators and problem list, the corresponding simulation verification results are generated.

[0157] Step a2: Based on the verification results, optimize the differentiated configuration scheme for the target pure local water source.

[0158] In one optional embodiment, based on the multi-condition simulation verification results and the list of shortcomings output in step a1, optimization is carried out to address the scheduling deficiencies exposed in scenarios without large-scale hubs or external water transfer restrictions. This involves adjusting scheduling parameters such as reservoir storage and release timing, zoned water allocation ratios, and lake replenishment initiation thresholds, and correcting any adaptation defects in the scheme. Furthermore, the scheme can also reduce lake water intake scale, improve reservoir utilization, enhance water supply stability in fragmented areas, and iteratively obtain a final, practical scheduling scheme adapted to the three-dimensional coupling constraints of the irrigation district.

[0159] For example, firstly, the optimization directions corresponding to different problems can be distinguished by comparing the verification results: (1) If high-level fractured units are short of water during the dry season: adjust the priority supply of high-level reservoirs to high-level units, refine the cross-unit linkage regulation and storage rules of reservoirs, and lower the emergency water replenishment activation threshold of dry lakes; (2) If the overall utilization rate of reservoirs and ponds is low: optimize the timing of lake water storage and filling during the high water season, maximize the storage of local water volume, and reduce water intake from normal lakes during the normal water season; (3) If the total amount of water taken from the lake is too high: tighten the control standard for the minimum water replenishment of each unit and strengthen the scheduling mechanism for the distribution of water shortage in the entire reservoir cluster; (4) If water loss is large and water distribution is uneven: refine the water distribution ratio of high and low level irrigation units in different time periods, and adjust the gravity / pump water supply sequence according to the plot elevation difference.

[0160] Secondly, without violating the core configuration principle of "reservoirs and ponds as the main focus, lakes as the secondary focus, and minimizing lake water intake", the core control parameters of the scheme can be iteratively adjusted. These parameters may include the reservoir and pond water storage scheduling cycle, the water allocation ratio of each unit, the start and stop conditions for lake water intake under different water level conditions, the upper limit of water replenishment during the dry season, and the rules for water exchange between reservoirs and ponds in different units.

[0161] Finally, the optimized scheme with corrected parameters is re-substituted into the multi-condition simulation model, and the simulation process of step a1 is repeated to verify whether the shortcomings have been eliminated and whether the core indicators such as lake water intake reduction, water supply cost, and irrigation coverage have been further improved.

[0162] Furthermore, if there are still obvious adaptation defects, the simulation-optimization iteration is carried out repeatedly until the operating effect under various working conditions meets the water supply control requirements of the irrigation area. Then, the final configuration scheme, which includes unit-based and working condition-based reservoir storage and discharge rules, lake limited water replenishment standards, and zoned water allocation sequence, is obtained and used as the benchmark execution scheme for long-term dynamic adaptive scheduling of the irrigation area.

[0163] In one example, a method for water resource allocation and scheme comparison in a reservoir-dominated irrigation district based on the coupling of low hills and open, uncontrolled lakes is provided. The entire process involves no groundwater extraction, recharge, or utilization, and no external water transfer is used. It utilizes only two types of surface water sources: local small reservoirs and open, uncontrolled lakes. The core allocation principle is "reservoirs as the main source, lakes as a supplement, and minimizing lake water intake." This method specifically addresses the technical challenges of fragmented farmland in low hills, large elevation differences, large water level fluctuations in open, uncontrolled lakes leading to difficulties in water intake, high lake water supply costs, terrain limitations preventing the construction of large-scale water conservancy projects, and a large number of scattered, low-utilization local small reservoirs. The method includes the following steps: Step 1: Construct a three-dimensional coupled evaluation system of terrain, lakes, and reservoirs to quantify the intensity of supply and demand coupling constraints.

[0164] 1.1 Collect purely local meteorological, hydrological and engineering basic data for the study area, including rainfall, evaporation, runoff, farmland fragmentation characteristics, distribution of plot elevation differences, spatial dispersion of plots, multi-year time series variation of lake water levels, minimum water intake level of lakes during the dry season, spatial distribution of small reservoirs and ponds throughout the area, effective storage capacity of individual reservoirs, total controllable storage capacity of reservoirs and ponds, topology of irrigation canal system connectivity, and time series data of crop water requirements.

[0165] 1.2 Screening of Core Coupled Constraint Factors. This study, considering the actual water supply characteristics of the low-mountain and hilly lakeside irrigation area—characterized by fragmented terrain, fluctuating lake levels, and decentralized reservoir regulation—selected factors based on core screening criteria: mechanistic relevance, dimensional completeness, regional adaptability, quantifiable data, and independent indicators. Priority was given to key indicators that directly reflect the water supply and demand contradictions in the irrigation area, align with the region's lack of large-scale water conservancy projects and external water sources, and possess clear physical mechanisms, readily available basic data, and no information overlap. Based on these principles, six core coupled constraint factors were ultimately selected: farmland fragmentation, average elevation difference between plots, annual lake level fluctuation, guaranteed water depth for lake intake during the dry season, density of small reservoirs, and the proportion of effective reservoir storage capacity across the entire region. Each indicator corresponds to three types of constraint systems, accurately characterizing the inherent mechanisms of regional topographical water intake constraints, lake water source fluctuation constraints, and existing reservoir storage capacity constraints. This comprehensively constructs a three-dimensional coupled constraint evaluation system for the irrigation area's water supply system, providing core indicator support for subsequent quantification of supply and demand contradictions and selection of differentiated scheduling schemes.

[0166] 1.3 The factor weight judgment matrix is ​​constructed using the analytic hierarchy process to obtain the subjective weight of each factor. The subjective bias is corrected by combining the entropy weight method. Priority is given to strengthening the weight of three core factors: farmland fragmentation, lake water level fluctuation, and reservoir storage capacity. This highlights the core characteristics of difficulty in water intake due to fragmentation, unstable water level fluctuation, and the alternative storage capacity of reservoirs.

[0167] 1.4 Constructing a three-dimensional coupling effect intensity evaluation model and calculating the coupling effect intensity index. This paper constructs a coupling effect intensity evaluation model for the irrigation district water supply system based on a three-dimensional index system of topographic water intake constraints, lake water source fluctuation constraints, and reservoir storage capacity constraints. First, the six core constraint factors are standardized by range processing to eliminate dimensional differences; then, the entropy weight method is used to objectively calculate the weights of each index, avoiding subjective assignment bias, and obtaining the comprehensive evaluation score of the three-dimensional subsystem. On this basis, a coupling coordination model is introduced to construct a three-dimensional coupling effect intensity calculation formula applicable to this irrigation district, quantifying the mutual constraints and synergistic effects among the topographic, lake, and reservoir subsystems.

[0168] The calculation process for the coupling effect strength index is as follows: (1) Indicator standardization. The positive and negative indicators are respectively processed by range standardization to obtain normalized indicator values, ensuring that the values ​​of each indicator are uniformly in the range of 0~1.

[0169] (2) Entropy weighting. The weights of each factor are calculated by the information entropy of the indicators, and the influence contribution of each constraint factor on the irrigation area water supply system is objectively reflected based on the degree of data dispersion.

[0170] (3) Subsystem comprehensive score. Calculate the comprehensive evaluation value of the topographic water intake constraint subsystem, the lake water source fluctuation constraint subsystem, and the reservoir regulation constraint subsystem respectively.

[0171] (4) Calculation of coupling strength index. The three-dimensional coupling effect strength index is solved by the three-system coupling degree formula, as shown in the above relationship (1). The value ranges from 0 to 1. The larger the value, the more significant the coupling effect of mutual constraints and interactions of the three-dimensional system, and the stronger the supply and demand contradiction and scheduling pressure in the irrigation area.

[0172] Step 2: Calculate water demand between fragmented farmland areas and calibrate the differences in water supply capacity of local lakes and ponds.

[0173] 2.1 Based on the degree of farmland fragmentation and the elevation difference between plots, the fragmented irrigation area is divided into high-level fragmented irrigation units, mid-level transitional irrigation units, and low-level gentle irrigation units (wherein, the coupling strength index is mainly used to judge the strength of the supply and demand contradiction and pressure in the irrigation area, thereby indicating the water resource allocation scheme that is more suitable; the specific division of units should be based on the actual terrain, and there is no uniform specific value), to achieve differentiated zoning water demand calculation and adapt to the spatial differences in water use of scattered plots. This invention uses farmland fragmentation and average elevation difference between plots as core classification indicators, combined with the fragmented distribution characteristics of the irrigation area topography and the field water allocation adaptation conditions, and adopts a dual-indicator threshold classification method to classify the fragmented irrigated farmland in the entire area into unit types. The specific quantitative classification rules are as follows: (1) High-level fragmented irrigation unit: The area has high degree of fragmentation of cultivated land and large average elevation difference between plots. The plot elevation difference is significant, and the vertical drop between fields is large, making it difficult to adapt to conventional unified water distribution. The uniformity of water conveyance and distribution is poor. The cultivated land is scattered and fragmented, and the connectivity between plots is weak. The conditions for large-scale contiguous irrigation are poor. It is the unit with the worst water distribution adaptability and the most prominent contradiction in water intake scheduling in the irrigation area.

[0174] (2) Intermediate transitional irrigation unit: The degree of fragmentation of cultivated land and the average elevation difference of plots in the region are at a moderate level. The topographic relief and degree of fragmentation of cultivated land are relatively moderate. There are no extreme water allocation shortcomings. The unified water allocation has certain limitations. The irrigation effect can be optimized by local regulation of reservoirs and ponds and regional water replenishment. It belongs to the transitional unit of irrigation area supply and demand contradiction.

[0175] (3) Low-lying and flat irrigation units: The area has low farmland fragmentation and small average elevation difference between plots. The terrain is generally flat with small elevation differences between plots, good farmland contiguousness, low irrigation water loss, good water distribution uniformity, strong adaptability to unified water distribution, and the lowest difficulty in water intake scheduling.

[0176] By combining measured data and the normal distribution characteristics of indicators in the study area, the natural breakpoint method is used to determine the grading threshold, so as to achieve accurate division of irrigation units in the whole area and provide a zoning basis for matching differentiated reservoir-lake linkage scheduling schemes for different units.

[0177] The total water demand for agricultural irrigation, domestic use, industry, and ecology is calculated by region. The water demand for agricultural irrigation is accurately calculated using the Penman-Monteith formula. The water demand for domestic use and industry is calculated based on the regional population size, socio-economic indicators, and water quotas. The calculation of ecological water use refers to the Tennant method.

[0178] 2.2 Three typical operating conditions are divided into lakes: high water level during periods of abundant water, normal water level during periods of normal water, and low water level during periods of drought. The dual water source supply capacity is calibrated differently based on these conditions. Based on the limited conditions of no large-scale hubs and no external water transfer, the water supply benchmark is established with reservoirs and ponds as the low-cost main water supply source and lakes as the high-cost emergency supplementary water source. The scale of water intake from lakes during normal periods is strictly limited.

[0179] 2.3 The supply and demand gap of local surface water resources is calculated by working condition and unit. Only when the water supply from reservoirs and ponds is completely insufficient to cover the water demand, the minimum lake water replenishment is determined on the premise of meeting the water supply demand of the irrigation area (the determination standard is based on meeting the demand of the irrigation area as the upper limit, and the lower limit is determined according to the actual water intake capacity; this is mainly for the recommended scheme in this paper, highlighting the economic efficiency of the recommended scheme), so as to minimize the lake water intake, reduce the scale of new water diversion projects, and reduce the total investment of the project.

[0180] This invention does not rely on external water sources for replenishment; the entire region's water supply depends solely on two types of local surface water sources: small reservoirs and lakes. To accurately reveal the differences in water supply contradictions across different topographical units and hydrological periods, a two-tiered approach, dividing irrigation units and lake water level conditions, is used to conduct refined calculations of the water resource supply and demand gap. The specific calculation process is as follows.

[0181] (1) Calculation unit and working condition division.

[0182] The calculation unit is divided into three types of irrigation units: high-level fracture, mid-level transition, and low-level flat. The hydrological conditions are divided into dry season, normal season, and high-water season according to the annual variation of lake water level, which correspond to three water intake states: inefficient, restricted, and efficient.

[0183] (2) Calculation of water demand by zone.

[0184] Based on the cultivated land area, crop irrigation system and irrigation guarantee rate of each irrigation unit, the net irrigation water demand of the unit field is calculated, and the gross water demand of the zone is obtained by combining the water conveyance utilization coefficient, as shown in the above formula (2).

[0185] (3) Calculation of available water volume in each zone (dual water source separation).

[0186] The local available water supply consists of two parts: the water storage capacity of unit reservoirs and ponds and the water intake capacity of working lakes. 1) Adjustable water storage capacity of reservoirs and ponds: Based on the effective storage capacity of unit reservoirs and ponds, after deducting dead storage capacity and evaporation and seepage losses, the dispatchable water supply is obtained, which does not change with the fluctuation of lake water level, thus providing a stable water source.

[0187] 2) Available water volume for lake operation: Based on different water level constraints, the amount is significantly reduced during the dry season due to water depth restrictions, while it is fully calculated based on water intake capacity during the normal and wet seasons, reflecting the fluctuating characteristics of lake water sources.

[0188] The formula for calculating the total water supply of a zone is shown in the above relationship (3).

[0189] (4) Calculate the supply and demand gap by dimension.

[0190] The supply-demand gap is the difference between the water demand of a region and the total available water supply. The core formula is shown in the above relationship (4).

[0191] To strictly implement the water supply allocation principle of "reservoirs and ponds as the main source, lakes as a supplement, and minimizing high-cost lake water intake," this paper establishes a minimum lake water replenishment standard based on the supply and demand gap calculation results for each irrigation unit and hydrological condition. Lake water replenishment will only be initiated after the local reservoir water source is completely depleted, accurately determining the optimal lake water intake scale. The specific standard is as follows: (1) Pre-water intake judgment criteria.

[0192] Under all irrigation units and water level conditions, priority should be given to fully utilizing the effective adjustable water storage capacity of the unit's small reservoirs. When the total water supply from the reservoirs can completely cover the unit's irrigation water demand, lake water intake will not be activated; lake water replenishment may only be activated when the reservoir water supply capacity cannot meet the field water demand and a supply-demand gap occurs.

[0193] (2) Water intake threshold control standards.

[0194] The amount of water replenished to the lake will not exceed the limit, with the sole upper limit being to just balance the supply and demand gap and ensure the basic irrigation needs of the irrigation area, eliminating redundant water withdrawal. The scale of water replenishment is strictly equal to the water resource supply and demand gap of the corresponding unit under the current operating conditions, thereby minimizing the scale of lake water withdrawal.

[0195] (3) Operating condition adaptation constraint standards.

[0196] The upper limit of water intake is determined by taking into account the constraints of different water levels and operating conditions of the lake: during the wet and normal water periods, the water intake capacity is sufficient and water is replenished in full according to the theoretical gap; during the dry season, due to the constraints of insufficient water depth, poor water intake stability and high energy consumption costs, the minimum water replenishment volume is determined based on the minimum operating threshold of the existing water intake facilities, and priority is given to ensuring the core irrigation water.

[0197] (4) Global optimal configuration standard.

[0198] Taking into account the differences in water demand among high-, medium-, and low-level irrigation units, priority is given to regulating and absorbing regional water shortages through the coordinated operation of reservoir clusters. Lake water intake is only used as a backup emergency water source. From a mechanism perspective, this approach minimizes the high-energy-consuming water intake from lakes on a regular and large scale, thereby improving the economic efficiency and stability of water supply in the irrigation area.

[0199] The calculation formula is shown in the above relationship (5).

[0200] (5) Result discrimination.

[0201] By performing quantitative calculations on a unit-by-unit and working condition-by-working-condition basis, we can accurately distinguish the differentiated supply and demand characteristics, such as severe water shortage in high-level fractured units during the dry season and water surplus in low-level units during the normal and abundant season. This provides a quantitative basis for subsequent coordinated scheduling of reservoir clusters and scheduling schemes that minimize high-cost lake water intake.

[0202] Step 3: Construct a set of differentiated water resource allocation schemes with reservoirs and ponds as the main drivers and lakes as limited supplementary sources.

[0203] Focusing on six major pain points—difficulty in obtaining water from fragmented farmland, unstable lake water levels, high lake water extraction costs, idle reservoirs and ponds, lack of large-scale water conservancy projects, and lack of external water transfer—and with the goal of meeting the irrigation district's water supply needs, three sets of differentiated allocation schemes for purely local water sources (set based on human experience) were constructed: Option 1 (Traditional Lake-Based Solution): Water supply is mainly based on lake water intake, with small reservoirs and ponds scattered and idle for backup; unified water intake and distribution across the entire area does not adapt to the characteristics of fragmented farmland and water level fluctuations. The scale of lake water intake is large and the water supply cost is high under normal circumstances. During the dry season, water intakes become ineffective and water supply to high-lying fragmented plots is insufficient, and reservoir resources are not effectively utilized.

[0204] Option 2 (Lake and Pond Balanced Allocation): Lakes and ponds provide coordinated water supply, with unified water storage and balanced water replenishment in reservoirs and ponds, and a moderate reduction in the scale of water intake from lakes. During the dry season, the water supply pressure is shared by reservoirs and ponds, which alleviates the problems of water supply interruption and high costs to a certain extent. However, the main water supply from reservoirs and ponds is not achieved, the effect of reducing water intake from lakes is limited, and the suitability for irrigation of fragmented plots is generally poor.

[0205] Option 3 (Reservoir-led Minimum Lake Water Intake Optimization Scheme): This is the core optimal solution of the invention, fully adaptable to constrained scenarios. Under high water level conditions, only the surplus water volume of lakes is used to replenish and fill all reservoirs and ponds in the entire area, without large-scale lake water intake for irrigation, maximizing the storage of local water volume and reducing lake water intake costs. Under normal water level conditions, the entire area is mainly supplied with precise water from reservoir clusters in different zones, with only a small amount of lake water taken to supplement local gaps. Under low water level conditions, inefficient lake water intakes are shut down, and water supply is entirely based on the hierarchical scheduling of reservoir clusters. High-level fragmented units are matched with high-elevation reservoirs and ponds, and low-level units are matched with nearby reservoirs and ponds, solving the problems of water intake failure at low water levels and irrigation blind spots in fragmented areas. Lake water is only taken in limited quantities for emergency use during extreme water shortages, minimizing the scale of lake water intake and reducing water supply costs.

[0206] Step 4: Compare and evaluate multi-dimensional solutions that are suitable for economic, efficiency, and stability.

[0207] 4.1 Construct a dedicated four-dimensional evaluation index system (used to evaluate the three sets of differentiated allocation schemes for pure local water sources constructed in step 3 above), which includes multiple core quantitative indicators, focusing on three major economic core indicators: lake water intake reduction rate, unit irrigation water supply cost, and reservoir load utilization rate. It also covers irrigation coverage rate of fragmented plots, low water level water supply guarantee rate, water level fluctuation adaptability, water intake stability, water transmission loss rate, irrigation guarantee rate, ecological water use guarantee rate, supply and demand gap fluctuation rate, and engineering adaptability.

[0208] 4.2 The entropy weight method is used to couple the three-dimensional coupling factor weights (the weights of the indicators in 4.1), giving priority to the core indicators of lake water intake reduction, water supply cost reduction, reservoir revitalization, and fragmented land plots. All indicators are normalized to eliminate dimensional differences.

[0209] 4.3 The TOPSIS model was used to calculate the overall closeness of each scheme. Based on the closeness ranking, the best scheme was selected, which has stable water supply, full irrigation coverage, minimal lake water intake, lowest water supply cost, and is suitable for scenarios without large hubs or external water transfer.

[0210] Step 5: Multi-condition simulation verification and dynamic adaptive scheduling of reservoir linkage.

[0211] 5.1 Simulate extreme water level conditions of lakes during periods of abundance, normal, and low water levels to verify the optimal scheme's success rate of water intake from fragmented farmland, reservoir water supply coverage, lake water intake reduction effect, and water supply cost optimization effect under conditions of no large-scale hubs and no external water transfer. Eliminate scheduling parameters with poor adaptability.

[0212] 5.2 Establish a dynamic monitoring and adaptive mechanism to collect data on lake water levels, reservoir storage capacity, and farmland water demand in real time. Dynamically adjust the timing of reservoir storage and release, the water supply ratio of different zones, and the limited water replenishment of lakes to maintain a long-term scheduling mode of "reservoirs as the main source and lakes as the minimum supplement" and adapt to the coupling constraints of fragmented terrain and water level fluctuations.

[0213] Furthermore, in an optional embodiment, the overall technical flow diagram is as follows: Figure 3 As shown; the architecture diagram of the Entropy Weight-TOPSIS multidimensional scheme comparison and evaluation model is as follows. Figure 4 As shown.

[0214] Based on the above examples, a specific implementation method for water resource allocation and scheme comparison in reservoir-dominated irrigation districts coupled with low hills and open, uncontrolled lakes is provided. This implementation method does not involve groundwater utilization or external water transfer, and is fully adaptable to restricted scenarios with no large-scale water conservancy projects, numerous scattered small reservoirs, fragmented farmland, large fluctuations in lake water levels, and high water extraction costs.

[0215] Specifically, a typical low-mountain and hilly lakeside irrigation area in southern China was selected as the application object. This area is a purely local water source irrigation area with no external water supply. The farmland is highly fragmented, with plots scattered and significant differences in elevation between fields, lacking centralized and contiguous irrigation units. It is adjacent to a large, open, uncontrolled lake without artificial regulation facilities, resulting in large natural fluctuations in water level. During the dry season, fixed water intakes are exposed and ineffective, requiring pumping stations for lake water intake, leading to high energy consumption and operation and maintenance costs. Due to topographical and geological limitations, the area cannot construct large-scale water conservancy projects or large-scale water storage projects. Numerous scattered small reservoirs and ponds are distributed throughout the area, close to the fields, with sufficient storage capacity, but they have long operated independently without coordinated management. Calculations show that the three-dimensional coupling effect intensity of the area is at a medium-to-strong coupling level, highlighting the contradictions of difficult water intake, high costs, and weak water storage.

[0216] S1. Evaluation of three-dimensional coupling effect.

[0217] Core basic data were collected on the characteristics of fragmented farmland, plot elevation differences, temporal fluctuations in lake water levels, and the capacity and distribution of small reservoirs in the study area. Six core coupling factors were selected and identified. Through weighted calculation using the analytic hierarchy process combined with the entropy weight method, the weight proportions of water intake constraints due to fragmentation, water level fluctuation risks, and reservoir substitution and regulation were strengthened. The regional coupling effect intensity index was calculated, the corresponding coupling level was determined, and the core optimization directions were identified as revitalizing existing reservoirs, reducing lake water intake, adapting fragmented farmland to different zones, and mitigating water level fluctuation risks.

[0218] S2. Zonal water demand calculation and lake / pond water supply capacity calibration.

[0219] Based on the fragmentation of cultivated land and the elevation difference between plots, the irrigation area is divided into three independent irrigation units: a high-level fragmented area, a mid-level transitional area, and a low-level flat area. The annual total water demand of the irrigation area is calculated for each unit. Lakes are categorized into three water level conditions: high, medium, and low. The coordinated water supply capacity of lakes and ponds is calibrated for each condition: under high water level conditions, lakes can replenish and fill all reservoirs and ponds, ensuring sufficient total water storage capacity; under medium water level conditions, reservoirs and ponds can cover the main water demand, with only minor local shortages; under low water level conditions, lake water intake is limited, and the overall water supply relies mainly on the water storage capacity of the reservoir cluster. Through supply and demand balance analysis, the core supply and demand gap in the high-level fragmented area during the dry season is accurately identified.

[0220] S3. Construct a set of differentiated configuration schemes.

[0221] Based on regional characteristics and supply-demand imbalances, three differentiated water resource allocation schemes are constructed: Traditional lake-based solutions involve large-scale, regular water extraction, low utilization rates of reservoirs and ponds, limited water intake during the dry season leading to insufficient water supply in high-lying fractured areas, low irrigation coverage of fractured plots, and high overall water supply costs.

[0222] The balanced allocation scheme of lakes and ponds: coordinated water supply from lakes and ponds, moderately reducing the proportion of water intake from lakes, increasing the utilization rate of reservoirs and ponds and the irrigation coverage rate of fragmented plots, and reducing water supply costs. However, it does not achieve the main water supply from reservoirs and ponds, and the effect of reducing volume and cost is limited.

[0223] The reservoir-led, minimum lake water intake optimization scheme: During the wet and dry seasons, the core function is to store and supply water from reservoirs and ponds, utilizing only surplus water from lakes to supplement reservoir storage; during the dry season, inefficient lake water intake facilities are shut down, relying entirely on reservoirs and ponds for tiered and zoned water supply, with limited lake water intake for emergency use in extreme water shortages. This scheme significantly improves the comprehensive utilization rate of reservoirs and ponds, substantially increases irrigation coverage on fragmented land, completely solves the problems of difficult water intake from fragmented farmland and unstable water supply due to water level fluctuations, and significantly reduces the overall water supply cost of the irrigation area.

[0224] S4. Quantitative comparison of multiple options.

[0225] The entropy weight-TOPSIS method was adopted to conduct a comprehensive evaluation based on core indicators such as lake water intake reduction rate, water supply cost, reservoir utilization rate, fragmented land coverage rate, and low water level guarantee rate. The comprehensive closeness of the three schemes was calculated and ranked, and the reservoir-dominated minimum lake intake optimization scheme was determined as the optimal configuration scheme.

[0226] S5, Multi-condition verification and dynamic scheduling optimization.

[0227] Through multi-water-level simulation verification, the optimal solution maintains a high success rate for water intake from fragmented farmland under different water level conditions (abundant, normal, and dry), with no large-scale irrigation blind spots, a significant reduction in lake water intake scale, and orderly storage and release of reservoirs and ponds throughout the region, fully utilizing existing resources. By establishing a dynamic monitoring and adjustment mechanism, the timing of reservoir water storage and the regional water allocation ratio are optimized in real time, maintaining a reservoir-dominated water supply mode in the long term and adapting to regional coupled water supply contradictions.

[0228] The implementation results show that the method presented in this example can effectively make up for the shortcomings in water storage and regulation in areas without large-scale water conservancy hubs, fully revitalize existing small reservoir resources, solve the problems of water access difficulties and unstable water supply caused by fragmented farmland in low hills and large fluctuations in lake water levels, significantly improve the efficiency of surface water resource utilization and irrigation guarantee capacity of irrigation areas, fully adapt to the construction conditions of restricted terrain and water resource management requirements, and has high engineering practicality and regional promotion value.

[0229] The water resource allocation and scheme comparison method for reservoir-dominated irrigation districts based on the coupling of low hills and open, uncontrolled lakes provided in this example has the following beneficial effects: Extremely adaptable to constrained scenarios. This invention is the first of its kind in hilly and lake irrigation areas with no external water transfer, no large-scale water conservancy projects, and purely local water sources. It relies solely on local reservoirs and lakes as surface water bodies throughout the entire process, accurately solving multiple superimposed technical bottlenecks and filling the technical gap in the refined allocation of water resources in such extremely constrained scenarios.

[0230] It overturns the traditional water supply logic. It innovatively establishes the core scheduling logic of "reservoirs and ponds as the main source and lakes as the supplementary source", giving full play to the advantages of small reservoirs and ponds in terms of proximity, low energy consumption and low cost, and significantly reducing the scale of water intake from high-cost lakes. This fundamentally solves the industry pain point of high water supply costs in irrigation areas, and can significantly reduce irrigation water supply costs.

[0231] Distributed systems replace centralized systems. Relying on a cluster of numerous small, scattered reservoirs and ponds for coordinated regulation and storage, distributed small-scale projects replace the regulation and storage functions of large-scale water conservancy hubs that cannot be built. This effectively mitigates the water supply risks caused by large fluctuations in the water levels of uncontrolled lakes, and completely solves the core problems of lake intake failure during the dry season, difficulty in obtaining water from fragmented farmland, and numerous irrigation blind spots, resulting in a significant increase in irrigation coverage of fragmented plots.

[0232] A dedicated evaluation system. An innovative dedicated evaluation system has been constructed, incorporating water intake reduction and cost control. This breaks away from the traditional single evaluation model that only focuses on total water supply and guarantee rate. It takes minimizing lake water intake, revitalizing reservoir resources, and low-cost water supply as the core selection criteria, making the solution decision more aligned with the actual operation and maintenance needs of the project, and highly practical.

[0233] It requires less new engineering investment. It revitalizes existing idle reservoirs and ponds in the region, reduces the scale of new water conservancy projects, and achieves efficient allocation of water resources simply by optimizing the scheduling method. It has a high rate of return on investment and achieves efficient, economical, and stable allocation of purely local water resources without any external water source supplementation. It has wide applicability.

[0234] This embodiment also provides a device for determining water resource allocation schemes in reservoir-dominated irrigation areas. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0235] This embodiment provides a device for determining water resource allocation schemes in reservoir-dominated irrigation areas, such as... Figure 5 As shown, the device includes: The acquisition module 501 is used to acquire the basic attribute dataset and actual water supply operation characteristics of the irrigation area to be configured. The irrigation area to be configured has both low mountain and hilly landforms and lakeside low-lying features, and does not rely on external water transfer or have large-scale water storage and regulation hub projects.

[0236] The quantification module 502 is used to quantify the supply and demand coupling constraint strength of the irrigation area to be configured based on the basic attribute dataset and actual water supply operation characteristics, and obtain the three-dimensional coupling effect strength index of the irrigation area to be configured. The three-dimensional coupling effect strength index is used to characterize the linkage constraint relationship between the topographic water intake, lake water level fluctuation and reservoir regulation of the irrigation area to be configured.

[0237] The partitioning module 503 is used to divide the fragmented irrigated farmland of the irrigation district to be configured into unit types based on the degree of farmland fragmentation and the average elevation difference of the plots as classification indicators, the three-dimensional coupling effect intensity index, the topographic fragmentation distribution characteristics of the irrigation district to be configured and the field water distribution adaptation conditions, and the dual-index threshold classification method, thereby obtaining multiple irrigation units.

[0238] The calculation module 504 is used to calculate the minimum lake water replenishment for each irrigation unit under different operating conditions based on the water supply benchmark of reservoirs as low-cost main water supply sources and lakes as high-cost emergency replenishment sources. The calculation module 504 is used to calculate the minimum lake water replenishment for each irrigation unit under different operating conditions based on the minimum lake water replenishment verification standard. The different operating conditions include high water level conditions during abundant water season, normal water level conditions during normal water season, and low water level conditions during dry season.

[0239] Module 505 is used to construct multiple differentiated configuration schemes for purely local water sources in the irrigation area to be configured, based on the multiple minimum lake replenishment volumes for each irrigation unit.

[0240] Evaluation module 506 is used to evaluate multiple pure local water source differentiated configuration schemes based on a preset four-dimensional evaluation index system, using the entropy weight method and the approximation ideal solution ranking method, and to determine the target pure local water source differentiated configuration scheme for the irrigation area to be configured.

[0241] The water resource allocation scheme determination device for reservoir-dominated irrigation areas provided in this embodiment of the invention can execute the water resource allocation scheme determination method for reservoir-dominated irrigation areas provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0242] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0243] The following is a detailed reference. Figure 6 This diagram illustrates a suitable structural design for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 601, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 602 or a program loaded from memory 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for the operation of the electronic device. The processor 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0244] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0245] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a memory 608, or installed from a ROM 602. When the computer program is executed by the processor 601, it performs the functions defined in the method for determining water resource allocation schemes in reservoir-dominated irrigation areas according to embodiments of the present invention.

[0246] Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention.

[0247] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that the computer, processor, microprocessor controller, or programmable hardware includes storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the method for determining water resource allocation schemes in reservoir-dominated irrigation areas shown in the above embodiments is implemented.

[0248] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0249] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for determining water resource allocation schemes in reservoir-dominated irrigation districts, characterized in that, The method includes: Obtain the basic attribute dataset and actual water supply operation characteristics of the irrigation district to be configured. The irrigation district to be configured has both low mountain and hilly landforms and lakeside low-lying features, and does not rely on external water transfer or have large-scale water storage and regulation projects. Based on the basic attribute dataset and the actual water supply operation characteristics, the supply and demand coupling constraint intensity of the irrigation area to be configured is quantified to obtain the three-dimensional coupling effect intensity index of the irrigation area to be configured. The three-dimensional coupling effect intensity index is used to characterize the linkage constraint relationship between the topographic water intake, lake water level fluctuation and reservoir regulation of the irrigation area to be configured. Using farmland fragmentation and average plot elevation difference as grading indicators, and based on the three-dimensional coupling effect intensity index, the topographic fragmentation distribution characteristics of the irrigation area to be configured, and the field water allocation adaptation conditions, the dual-index threshold grading method is used to classify the fragmented irrigated farmland of the entire irrigation area to be configured into unit types, resulting in multiple irrigation units. Based on the water supply benchmark of reservoirs and ponds as low-cost main water supply sources and lakes as high-cost emergency replenishment water sources, the minimum lake replenishment volume is calculated for each irrigation unit under different operating conditions using the minimum lake replenishment volume verification standard. The different operating conditions include high water level conditions during abundant water season, normal water level conditions during normal water season, and low water level conditions during dry season. Based on the minimum lake replenishment volume for each irrigation unit, construct multiple differentiated configuration schemes for purely local water sources for the irrigation district to be configured. Based on a pre-defined four-dimensional evaluation index system, the entropy weight method and the approximation ideal solution ranking method are used to evaluate multiple pure local water source differentiated configuration schemes and determine the target pure local water source differentiated configuration scheme for the irrigation area to be configured.

2. The method according to claim 1, characterized in that, Based on the aforementioned basic attribute dataset and the actual water supply operation characteristics, the supply-demand coupling constraint strength of the irrigation district to be configured is quantified to obtain the three-dimensional coupling effect strength index of the irrigation district to be configured, including: Based on the aforementioned basic attribute dataset and the actual water supply operation characteristics, multiple coupling constraint factors are obtained according to preset screening criteria. The preset screening criteria include mechanism correlation, dimensional integrity, regional adaptability, data quantifiability, and indicator independence. Using the analytic hierarchy process (AHP) and the entropy weight method, the weight values ​​of multiple factors for multiple coupling constraints are calculated. Based on a preset three-dimensional indicator system, multiple indicators are evaluated using the multiple coupling constraint factors and the multiple factor weights. The preset three-dimensional indicator system includes topographic water intake constraints, lake water source fluctuation constraints, and reservoir storage capacity constraints. Based on the comprehensive evaluation value of the multiple indicators, the intensity index of the three-dimensional coupling effect of the irrigation area to be configured is calculated.

3. The method according to claim 1, characterized in that, Based on the water supply benchmark of reservoirs and ponds as low-cost primary water supply sources and lakes as high-cost emergency replenishment sources, and the minimum lake replenishment volume verification standard, the minimum lake replenishment volume for each irrigation unit under different operating conditions is calculated, including: Based on the water supply benchmark of reservoirs and ponds as low-cost main water supply sources and lakes as high-cost emergency supplementary water sources, the total water demand and total water supply of each irrigation unit under different operating conditions are calculated. The total water demand of each irrigation unit is determined by the total water demand for agricultural irrigation, domestic, industrial and ecological purposes. Based on the multiple total water demand and multiple total water supply of each irrigation unit, calculate the water supply and demand gap of each irrigation unit under different operating conditions; Based on the minimum lake replenishment standard, the minimum lake replenishment for each irrigation unit under different operating conditions is determined according to the multiple supply and demand gaps in each irrigation unit.

4. The method according to claim 1, characterized in that, Based on a pre-defined four-dimensional evaluation index system, the entropy weight method and the approximation ideal solution ranking method are used to evaluate multiple differentiated configuration schemes for purely local water sources, and to determine the target differentiated configuration scheme for the irrigation district to be configured, including: Using the entropy weight method, calculate multiple weight values ​​for multiple evaluation indicators in the preset four-dimensional evaluation index system; Based on the multiple evaluation indicators and multiple weight values, the comprehensive approximation value of each pure local water source differentiated configuration scheme is calculated using the approximation ideal solution ranking method. Based on multiple comprehensive proximity values, the target pure local water source differentiated configuration scheme for the irrigation district to be configured is determined from multiple pure local water source differentiated configuration schemes.

5. The method according to claim 1, characterized in that, The method further includes: The different operating conditions of the irrigation district to be configured were simulated, and the effect of the target pure local water source differentiated configuration scheme under the conditions of no large hub and no external water transfer was verified based on the simulation results, and the verification results were obtained. Based on the verification results, the differentiated configuration scheme for the target pure local water source is optimized.

6. The method according to claim 1, characterized in that, The minimum lake replenishment volume assessment standards include: pre-extraction judgment standards, water intake threshold control standards, operating condition adaptation constraint standards, and overall optimal configuration standards.

7. The method according to claim 1, characterized in that, The various differentiated allocation schemes for purely local water sources include: the traditional lake-dominated scheme, the lake-pond balanced allocation scheme, and the reservoir-pond-dominated minimum lake water intake optimization scheme.

8. A device for determining water resource allocation schemes in reservoir-dominated irrigation areas, characterized in that, The device includes: The acquisition module is used to acquire the basic attribute dataset and actual water supply operation characteristics of the irrigation area to be configured. The irrigation area to be configured has both low mountain and hilly landforms and lakeside low-lying features, and does not rely on external water transfer or have large-scale water storage and regulation hub projects. The quantification module is used to quantify the supply and demand coupling constraint strength of the irrigation area to be configured based on the basic attribute dataset and the actual water supply operation characteristics, and obtain the three-dimensional coupling effect strength index of the irrigation area to be configured. The three-dimensional coupling effect strength index is used to characterize the linkage constraint relationship between the topographic water intake, lake water level fluctuation and reservoir regulation of the irrigation area to be configured. The segmentation module is used to classify the fragmented irrigated farmland of the irrigation area to be configured into multiple irrigation units by using the degree of farmland fragmentation and the average elevation difference of the plots as classification indicators, based on the three-dimensional coupling effect intensity index, the topographic fragmentation distribution characteristics of the irrigation area to be configured and the field water allocation adaptation conditions, and using the dual-index threshold classification method. The calculation module is used to calculate the minimum lake water replenishment for each irrigation unit under different operating conditions based on the water supply benchmark of reservoirs and ponds as low-cost main water supply sources and lakes as high-cost emergency replenishment sources. The calculation module is used to calculate the minimum lake water replenishment for each irrigation unit under different operating conditions, including high water level conditions during abundant water season, normal water level conditions during normal water season, and low water level conditions during dry season. A construction module is used to construct multiple differentiated configuration schemes for purely local water sources in the irrigation area to be configured, based on multiple minimum lake replenishment volumes for each irrigation unit. The evaluation module is used to evaluate multiple differentiated configuration schemes of pure local water sources based on a preset four-dimensional evaluation index system, using the entropy weight method and the approximation ideal solution ranking method, and to determine the target differentiated configuration scheme of pure local water sources for the irrigation area to be configured.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions, which are used to cause the computer to execute the method for determining the water resource allocation scheme of the reservoir-dominated irrigation area as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, The method includes computer instructions for causing a computer to execute the method for determining water resource allocation schemes in reservoir-dominated irrigation areas as described in any one of claims 1 to 7.

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