Cross-basin water saving amount transaction and scheduling optimization method

Abstract

The invention relates to an inter-basin water saving amount transaction and scheduling optimization method, which comprises the following steps of: performing dynamic contrast analysis on water saving behaviors and water resource response on the basis of historical water consumption behaviors, resource regulation and control records and meteorological basic data, judging the autonomy and continuity of the water saving behaviors, and obtaining the right-confirmable water saving amount; according to the watershed water resource tension degree, the water ecology sensitivity and the water transfer cost, a cross-watershed conversion rule is adopted, a conversion scale factor is set, and resource value transverse butt joint of water saving behaviors of different areas is achieved; calculating the flow attenuation, the regional bearing threshold and the water quality compatibility in the allocation path based on the water-saving amount obtained by the water-saving transaction, and determining the available transmission range and the sustainable allocation amount of the water-saving amount; and according to the distribution of the water-saving quotas and the corresponding value grades, carrying out combined screening according to the use priority, the basin compensation relationship and the space-time adaptation requirements, outputting a resource allocation scheme, and forming a cross-basin water-saving-quantity-driven water resource optimal allocation structure.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water conservancy and water resources management, in particular to a cross-basin water saving quantity transaction and dispatching optimization method. BACKGROUND

[0002] The current disclosed technology, such as a multi-reservoir, multi-line, and multi-water area cross-basin water transfer engineering joint dispatching rule optimization method (Chinese Patent CN116663740A), although proposes to construct a cross-basin water transfer multi-objective model through a simulation-optimization method, and introduces an analytic hierarchy process in the multi-reservoir, multi-line, and multi-water area joint dispatching rule to optimize the scheme, thereby improving the coordination efficiency and engineering operation benefit of the cross-basin water transfer system to a certain extent, but its method still has significant deficiencies and limitations in dealing with more complex and more fine-grained water resources management scenarios such as water saving behavior right transaction, ecological constraint allocation, and real-time dynamic correction. First, from the perspective of water transfer resource source mechanism, the patent focuses on the joint configuration of water reservoirs and lines and other engineering water sources as the water transfer resource scheduling target, and does not cover the tradable water resources generated by non-engineering, user-side water saving behaviors, ignoring the current reality that water saving rights and interests are becoming the mainstream trend in a water saving society. In actual application, especially in the user level of farmland water saving, industrial water saving, and other water saving achievements, have gradually possessed the characteristics of quantifiable, rightable, and tradable, if the dispatching system still relies only on traditional water supply engineering as the only source, it is difficult to realize the potential of water saving driven dispatching in modern water resources optimization, and also lacks a management mechanism to support the linkage of water saving incentives and ecological compensation.

[0003] Secondly, from the perspective of ecological sensitivity constraints and real-time scheduling adaptability, the optimization model used in this patent still mainly relies on traditional scheduling rules and simulation-optimization iteration. The ecological evaluation method is limited to static factors or outcome indicators, and does not fully consider the real-time response changes of ecological nodes in the scheduling path, such as water level disturbance, habitat stress, and water quality disturbance threshold. This method may not capture ecological disturbance in time or effectively feedback to scheduling strategy adjustment when facing water diversion tasks in ecologically sensitive areas such as wetland buffer zones, river restoration areas, and groundwater non-extraction zones, leading to imbalances in ecological functions and increased regional water body disturbance. This invention introduces ecological function zoning, downstream ecological compensation response rate, and upstream water source fluctuation derivative to build a more real-time and dynamic ecological threshold calculation mechanism, which can quantitatively predict the ecological scheduling tolerance and effectively improve the ecological adaptability. Thirdly, in terms of water diversion path loss identification and water quality adaptation mechanism, this patent only considers the scheduling chain cost and water quantity matching of reservoir-line-user terminal, but ignores the actual dynamic changes of water loss in the path and the water quality safety boundary problem between multiple uses (drinking, irrigation, and industry). Especially in long-distance water diversion projects, evaporation loss due to high temperature, leakage loss due to pipe network aging, and multi-node water use behavior interference during water diversion may occur, which cannot be modeled by one-time loss parameters, but require multi-source perception of real-time loss correction based on weather, pipe network operation status, and behavior feedback data. In addition, this technology lacks consideration of water quality adaptability and fails to establish a water quality allocation strategy like the one proposed in this invention, which includes use priority adaptation, water quality safety boundary checking, and conflict elimination. This may lead to waste of high-quality water sources for low-use, pollution of water bodies, and hidden dangers of misusing polluted water for ecological or drinking water purposes in actual applications.

[0004] Fourthly, from the perspective of feedback of fulfillment behavior and closed-loop optimization mechanism, although the patent proposes to realize multi-scheme optimization by simulation-optimization method and analytic hierarchy process, the execution link after the formation of the scheduling strategy is not built into a traceable fulfillment chain, and the user fulfillment behavior (such as water diversion error, water use deviation, path anomaly, and ecological index change) is not supported for archival management, credit evaluation or used for subsequent scheduling strategy learning. The decision mechanism is dominated by feedforward and lacks closed loop, which is not conducive to the self-learning and adaptive evolution of the scheduling strategy in a dynamic and complex water use environment. The present application establishes a whole-process fulfillment record mechanism after the completion of scheduling to record water flow, water quality change, ecological response and other information, forms a scheduling fulfillment archive, and writes data back to the database for credit rating and next round of strategy optimization. This closed-loop reinforcement design greatly improves the learning ability and scheduling stability of the system. Fifthly, in terms of scheduling efficiency and regional value evaluation mechanism, the patent emphasizes more on the improvement of resource allocation efficiency within the water supply project, and lacks a comprehensive evaluation and horizontal conversion mechanism for the economic value of different regional water-saving behaviors, water diversion cost and ecological pressure, which is not conducive to supporting the fair mutual recognition and water-saving incentive transfer of resource values among multiple river basins. SUMMARY

[0005] The purpose of the present application is to provide a cross-basin water-saving quantity transaction and scheduling optimization method, thereby solving some of the problems and deficiencies pointed out in the background art.

[0006] The present application solves the above-mentioned technical problems by adopting the following technical solution: a cross-basin water-saving quantity transaction and scheduling optimization method, comprising: based on historical water use behavior, resource regulation records and meteorological basic data, performing dynamic contrast analysis of water-saving behavior and water resource response, determining and determining the autonomy and continuity of water-saving behavior by analyzing the water use adjustment behavior of users under crop planting, water price change and climate conditions, and obtaining water-saving quantity that can be authorized;

[0007] On the basis of the water-saving quantity, according to the water resource shortage degree, water ecological sensitivity and water diversion cost of the basin, the cross-basin conversion rule is adopted to convert the water-saving quantity into the equivalent resource value of the target basin, and by setting a conversion proportion factor, the resource value of different regional water-saving behaviors is horizontally connected;

[0008] Based on the water-saving amount obtained by water-saving transaction, the water-saving amount is jointly screened according to time priority, water ecological constraint and space path condition, the flow attenuation, regional carrying threshold and water quality compatibility in the allocation path are calculated, and the available transmission range and sustainable allocation amount of the water-saving amount are determined;

[0009] According to the water-saving quota distribution and the corresponding value level, all dispatchable water sources are associated with the water-saving transaction results, combined and screened according to the use priority of the water-saving quota, the compensation relationship of the basin and the space-time adaptation requirement, and the resource allocation scheme including the dispatching order, the water transfer direction and the allocation level is output, and the channel capacity, the water source availability and the dispatching cost are comprehensively considered in the dispatching process to form the water-saving quantity driven water resource optimization allocation structure across the basins.

[0010] Further, the method for obtaining the water-saving quantity that can be confirmed includes:

[0011] The historical water consumption data and the water consumption environment background information of the user are acquired, the water-saving events with traceable behavior characteristics are identified by combining the water consumption fluctuation characteristics in the continuous time period, and the quantifiable water-saving results are confirmed based on the multi-period and consistent behavior; based on the spatial distribution of the water-saving results and the resource conditions of the source area, the water resource supply and demand pressure, the ecological sensitivity and the water transfer cost of the target area are referred to, the water-saving equivalent value conversion rule is set, and the value of the water-saving quantity is converted between different basins;

[0012] According to the water-saving quota generated by the water-saving value transaction, the feasible allocation range of the water-saving quota is determined by combining the dispatching demand, the time priority, the water body carrying capacity and the allocation channel capacity factors, and the available transmission path and the quota allocation scheme are screened;

[0013] Under the constraint condition of the water-saving quota, the resource matching logic is constructed by associating with the multi-source water supply resources, the dispatching scheme including the water transfer direction, the allocation order and the allocation ratio is output by comprehensively prioritizing according to the water-saving behavior credit, the transaction completion condition and the demand urgency of the target area; the dispatching scheme is corrected and allocated for execution by combining the channel passing capacity, the water source acquisition stability and the overall system dispatching cost in the actual execution condition.

[0014] Further, the identification process of the water-saving behavior includes setting a behavior trigger threshold, under the planting structure and meteorological conditions, when the user water consumption decreases continuously by more than the threshold and is significantly different from the surrounding area, the behavior record with strong water-saving intention is marked; after the water-saving quantity is confirmed, the digital behavior certificate corresponding to the user behavior track record is generated and bound with the water-saving quota as the basis for subsequent transaction qualification and resource quota.

[0015] Further, in the allocation path screening process of the water-saving quota, the ecological impact range parameter is set, and when a certain allocation path causes negative impact on the ecological nodes in the middle, the path is excluded; the determination of the dispatching order is based on the marginal substitution ability of the water-saving quota, and the resource flow direction of the dispatching efficiency is determined by comparing and prioritizing the unit water-saving cost and the unit water transfer cost of different basins.

[0016] Further, the scheduling scheme execution includes a feedback learning link, the actual water quantity, the implementation error and the regional water response data in the execution process are input into the historical behavior library for correcting the next round of water saving quota evaluation and scheduling priority strategy.

[0017] Further, the method for calculating the flow attenuation in the allocation path, the regional carrying threshold and the water quality compatibility comprises:

[0018] The water saving quota is obtained as an allocation resource, in the allocation process, for each allocation path, the actual loss source on the path is identified and tracked in stages in combination with the operation records and historical feedback data of each node along the transmission, and the effective reachable amount of the water saving quota is dynamically corrected;

[0019] Based on the ecological function zoning of the allocation target region, the historical operation extreme value and the ecological protection requirement, the water quantity corresponding to the allocation path is subjected to batch and continuity constraints; in view of the water body characteristics of different sources and target regions, multi-level adaptive checking comparison is performed according to the water quality indexes of each node, the use categories and the water environment carrying capacity of the water receiving area, and the allocation scheme leading to water pollution or function conflict is screened out.

[0020] Further, the water saving quota experienced in the allocation path is corrected in real time by integrating meteorological factors, water transmission pipe network operation state and water use behavior fluctuation multi-source data; at the same time, the regional ecological carrying threshold is dynamically calculated in combination with the ecological function zoning information, the downstream ecological response rate and the upstream water inflow fluctuation state, supporting high-precision allocation path selection and node allocation strategy formulation; a dynamic loss and ecological response comprehensive function is used for jointly calculating the real-time bearable water quantity of the allocation node:

[0021]

[0022] Wherein:

[0023] is the available ecological allocation water quantity on the node s at the moment t; α(s, t) is the initial water saving quota allocation value of the node s at the moment t; ε w (t) is a meteorological driving evapotranspiration loss coefficient, fitted based on air temperature, wind speed and humidity; γ r (t, s) is a water transmission leakage loss rate on the path s, calculated in combination with the pipe network pressure, material and slope; δ c (t) is a downstream ecological compensation response coefficient, representing the sensitivity of ecological restoration to flow change; Φ(t, s) is an upstream node water inflow time-varying function; is a representation of the upstream water source fluctuation rate, i.e. the time derivative of the inflow; Λ(t, s) is an ecological function area intensity factor, reflecting the ecological sensitivity and protection level of the node, derived from the basin zoning data;

[0024] The linkage between loss, compensation, and response in the allocation path is comprehensively characterized by time integral form;

[0025] Dynamic import This study describes the immediate impact of water source instability on downstream ecological thresholds, a mechanism not yet proposed in existing literature and engineering systems; a custom composite adjustment term is used. It enables dynamic adjustment of water-saving quotas without relying on linear or static correction factors; it introduces Λ(t,s) as an ecological sensitivity enhancement term, so that the allocation differences caused by ecological risk levels in different regions have a quantitative basis and have practical engineering guidance significance.

[0026] Furthermore, the adaptability verification includes combining the real-time water demand type and usage priority of the target node to implement multi-level usage adaptation of the allocated water volume, matching the water quality safety boundaries of different functional water uses such as drinking water, irrigation, and industry, and prioritizing the allocation of high-value uses.

[0027] Furthermore, for the high-risk ecological nodes, a simulation and prediction mechanism is introduced before allocation to assess in advance the impact of large-flow allocation on the regional water structure and ecological carrying capacity, and generate emergency allocation and adjustment plans; during the allocation execution process, a dynamic feedback module for water-saving quotas is set up to collect execution errors and node response information in real time, and adjust the next round of allocation path and node quota allocation based on the feedback.

[0028] Furthermore, after the allocation plan is implemented, the water flow direction, actual water volume, and ecological impact indicators of all participating nodes are recorded throughout the entire process to form an allocation performance file.

[0029] The beneficial effects of this invention are as follows: 1. By introducing mechanisms for user water use behavior identification, water-saving intention judgment, and multi-time period data comparison, quantitative identification and rights confirmation of water-saving behaviors are achieved; with the help of digital behavior credentials and value conversion rules, water-saving achievements possess cross-basin resource trading attributes, providing a legitimate data foundation for water rights transfer. 2. By comprehensively considering multiple parameters such as meteorological factors, water conveyance path losses, ecological carrying capacity thresholds, and water quality compatibility, the adjustable range and sustainable magnitude of water-saving quotas at different paths and nodes are dynamically calculated, significantly improving the scientific nature and response accuracy of scheduling, and avoiding the resource misallocation and path rigidity problems of traditional water diversion. 3. By introducing ecological function zoning parameters, downstream ecological response speed, and upstream water source fluctuations, the scheduling intensity, rhythm, and water quality path are adjusted in real time, taking into account both ecological protection red lines and water demand guarantees, significantly reducing the risk of water body disturbance or ecological degradation caused by blind water diversion.

[0030] Supports multi-level use matching check for different water use scenarios (drinking, irrigation, industry), prioritizes high-quality water sources to high-value uses, avoids high-quality low-use or mismatched pollution, and achieves maximum marginal benefit of water resource allocation. The whole process of dispatching forms a compliance file, records the flow of water, changes in water quality and ecological response indicators, and provides quantitative basis for water rights credit management, performance evaluation and ecological compensation; At the same time, combined with the feedback data to support the dynamic correction and optimization learning of the dispatching strategy, enhance the stability and adaptability of the long-term operation of the system. Through the value conversion mechanism and the dispatching priority sorting rule, the water saving achievements of multiple basins are included in the unified evaluation system, forming a water saving driven basin water resource integration mechanism, laying a technical foundation for large-scale water resource collaborative dispatching, cross-administrative district water right negotiation and ecological compensation mechanism. BRIEF DESCRIPTION OF DRAWINGS

[0031] Figure 1 The flow chart of the cross-basin water saving quantity transaction and dispatching optimization of the present application.

[0032] Figure 2 The function relationship diagram of the water saving quantity right confirmation and cross-basin dispatching system of the present application.

[0033] Figure 3 The function relationship diagram of the water saving quota dynamic allocation and ecological threshold determination of the present application.

[0034] Figure 4 The flow chart of the cross-basin water saving quota dispatching of the present application embodiment 1A basin Zhang.

[0035] Figure 5 The concise flow chart of the water saving quota allocation and ecological batch dispatching of the present application embodiment 2 Zhang. DETAILED DESCRIPTION

[0036] The specific embodiments of the present application will be described in detail below in combination with the drawings.

[0037] In combination with the drawings Figure 1The application cross-basin water-saving quantity transaction and dispatch optimization method, based on historical water use behavior data, regional resource regulation records and multi-source meteorological basic data, constructs a data support system for water-saving behavior recognition, integrates crop planting structure adjustment in recent years, farmer irrigation frequency change, water price execution policy and precipitation, temperature and other natural factors, extracts the actual water use change track of typical users under the background of non-extreme climate and non-compulsory policy intervention, and dynamically compares and analyzes the track with the historical behavior mean value under similar conditions, the regional reference value and the water requirement characteristics of typical crops, so as to eliminate the non-active behavior influence caused by natural water reduction, system anomaly or external instruction, and only keep the water-saving behavior samples with autonomous control characteristics; The behavior continuity index and water-saving amplitude stability weight are introduced in the analysis process, the water use behavior consistency of the user in the continuous planting season or the dispatch period is scored, the identified water-saving behavior is ensured to have repeatability and controllability, and then the water-saving total quantity formed in a specific time window is extracted based on the time series analysis result as the quantitative basis of water-saving results; At the same time, combined with the regulation response records of the unit user in the water resource management system, such as irrigation instruction response delay, water use quota execution situation and regulation cooperation degree, the initiative of the behavior is further attributed and classified, so as to ensure that only the water-saving quantity generated by the user's autonomous decision is confirmed as the water resource asset with the right, and finally the water-saving quantity index with clear information source, behavior traceability and quantifiable result is formed.

[0038] On the basis of the water-saving amount obtained by analyzing historical water use behavior and response, further work is carried out on the equivalent value conversion of water-saving resources across basins. By obtaining real-time and periodic water resource pressure conditions of each target basin, including regional annual total water use, groundwater level change rate, water resource availability, water resource development and utilization rate, water ecological warning index and ecological red line implementation pressure data in the basin, the water resource tightness degree of the target basin is comprehensively evaluated, and the tightness degree weight parameter reflecting the marginal value of water resources in the target basin is constructed in combination with the sensitive level of local ecological system, water environment restoration demand, water source replacement capacity and policy water transfer priority. At the same time, the cost structure information of the source basin is obtained, including unit water transfer energy consumption, water transfer distance, high difference loss, water right transaction intermediary cost and pipe network channel load condition, and a cost function factor reflecting the economic efficiency of water transfer is constructed. After the above multi-factor extraction is completed, according to the cross-basin conversion rule, each unit of water-saving amount in the source basin is converted according to the conversion proportion factor composed of the regional tightness ratio, ecological response coefficient and marginal cost proportion, and the equivalent resource value of the unit water-saving amount in the target basin is obtained. The equivalent value is expressed in the form of water resource value points, water right replacement amount or ecological compensation amount, so as to realize the horizontal value docking of water resource contribution formed by water-saving behavior in different basins. The conversion proportion factor has dynamic adjustment ability, which can correct the water-saving equivalent proportion according to the periodical climate deviation, water price mechanism adjustment, policy water transfer window period change, etc., so as to ensure that the water-saving achievements in different basins have equivalence, time sensitivity and regional adaptability in value evaluation.

[0039] After completing the right of water saving amount and value conversion, the system based on the water saving amount formed by the water saving transaction as the resource unit of dispatching and deployment, carries out the feasibility analysis and path screening of water saving amount deployment, determines the time priority of dispatching task according to the execution period and water demand level of target area confirmed by transaction, and preferentially includes the dispatching task with high timeliness or near ecological sensitive window period into the deployment plan, obtains the ecological protection red line, water ecological regulation target and water flow bearing limit of sensitive area between basins, constructs the corresponding water ecological constraint boundary for limiting the impact of deployed water amount on the original ecological system, and on this basis, combines the spatial structure characteristics of each candidate path, including path total length, node distribution density, region attribute and flow regulation capacity, carries out spatial screening on the available path, and carries out flow attenuation analysis on each candidate deployment path, including calculating evaporation and leakage based on real-time meteorological data and hydraulic conditions along the line, estimating the dynamic water loss in the path combined with the shunting, water taking and pressure regulating behavior of each node, and forming the effective delivery rate of the path; Then determine the regional ecological bearing capacity of the key nodes at the end and in the middle of the path, set the bearing threshold limit according to the historical maximum water transfer value, ecological environment fluctuation threshold and infrastructure load limit capacity, to ensure that the transferred water amount does not exceed the physical or ecological bearing range of the node; And further based on the water quality indexes between source water and target water body, including pH value, conductivity, pollutant concentration, use category and other key indexes, the paths causing ecological or use conflict are excluded through compatibility screening, and finally the available transmission range and sustainable deployment amount of water saving amount in each path are determined by comprehensively considering the time priority sorting, water ecological boundary constraint, path flow attenuation coefficient and water quality adaptability judgment result, to provide resource allocation boundary and path selection basis for dispatching decision.

[0040] After the right of water-saving quota is completed, the transmission feasibility is screened and the allocation range is determined, the system further optimizes the resource allocation based on the distribution characteristics of water-saving quota and its corresponding value level, including: extracting the spatial distribution of water-saving quota in each basin and node, and assigning the corresponding value level according to the conversion ratio in the previous water-saving value conversion process. The higher the value level, the stronger the water-saving behavior in the target area has the stronger water replacement ability and ecological restoration contribution; then, the water source information and water-saving transaction results are matched and associated, including the dispatching availability and response period of surface water, groundwater, water storage engineering and unconventional water sources, and reading the fulfillment order, redemption time limit, credit level and transaction quota of each participant in the water-saving transaction. The priority of water-saving quota and the transaction right index are combined to establish the water source allocation sequence dominated by water-saving quota, and the water transfer direction, policy index guidance and water resource tilt policy of ecological sensitive area in the cross-basin compensation relationship are integrated to set the water transfer priority relationship and quota stratification principle between multiple regions. Further considering the spatial distance, hydraulic connectivity, time window matching degree and other factors to construct the space-time adaptation weight matrix, the selected water transfer combination is screened and evaluated, and finally the resource allocation scheme including the specific dispatching sequence, water transfer direction and allocation level of each path or node is output. In the resource scheduling execution process, the system also analyzes the channel transportation capacity of the input and output path, the real-time available water source capacity of the water transfer node and the unit scheduling cost of different water transfer paths to ensure that the generated scheduling structure has technical executability, resource supply-demand balance and economic cost minimization benefit. Finally, a cross-basin water-saving resource joint allocation structure driven by water-saving quota, guided by transaction value and optimized by scheduling feedback is formed, realizing efficient integration of scheduling resources and dynamic coordination of water ecological system.

[0041] Combining the drawings Figure 2The method for obtaining traceable water saving amount includes the following technical processes: obtaining historical water consumption data of a user in multiple periods, and synchronously calling water consumption environment background information of the region where the user is located, the background information including crop planting structure, water price change record, irrigation system, policy intervention frequency, and meteorological data, etc., then constructing a time series water consumption trajectory, extracting the fluctuation characteristics of the user's water consumption in continuous periods, combining the regional mean value and the reference sample to attribute the user's water consumption behavior, identifying water saving events with traceable behavior characteristics, the events need to have non-climate driven, non-exceptional interruption, and continuous and autonomous behavior attributes, and after consistency analysis, it is confirmed that it is a traceable water saving behavior, and the corresponding water saving result is formed by the water saving amount, and then according to the distribution position of the water saving result in space and the resource characteristics of the source region, referring to the key factors such as the water resource shortage index, the water ecological sensitivity level and the unit water transfer marginal cost of the target region, the cross-basin water saving value conversion relationship is established, the water saving result is value converted through the establishment of dynamic equivalent conversion rules, the resource value of water saving amount is realized in different basins, then after the water saving value is confirmed and traded, the corresponding water saving amount is formed, and on the basis of the amount, the emergency degree of dispatching task, target time window, water body ecological carrying boundary and allocation path waterway capacity are combined to jointly screen all the allocation paths, calculate the flow attenuation rate, water quality adaptability and transmission feasibility of each path, select the feasible allocation path and node level quota allocation scheme, on the basis of which, the matching logic of multi-source water supply resources is constructed according to the use priority of water saving amount, the transaction performance record of water saving subject and the demand urgency level of target region, and the priority sorting list is generated through multi-dimensional weight ordering algorithm, and the preliminary dispatching scheme including water transfer direction, allocation order and node allocation proportion is output, finally the preliminary scheme is feedback corrected and resource optimized allocated in combination with the channel passing capacity in actual operation stage, water source time-varying acquisition capacity and unit execution cost of dispatching path.

[0042] The process of identifying water-saving behaviors involves structuring user water usage data and behavioral background data over multiple years or periods. A basic water consumption prediction model is then established by combining this data with information such as local planting structure, crop type water usage standards, soil type, and irrigation methods. Based on this model, a behavior trigger threshold is set. This threshold is a water-saving judgment boundary calculated based on the upper and lower limits of the minimum water requirement fluctuation for typical crops under normal meteorological conditions. When a user's actual water consumption decreases beyond this threshold for several consecutive periods without changing crop types or experiencing extreme weather disturbances, and this behavior differs significantly from the water consumption changes of similar users in the surrounding area or the regional average—meaning the user's water consumption decline trend did not occur synchronously with climate anomalies or a unified water-saving policy context—the system will mark this behavior as having water-saving characteristics. Behavioral events demonstrating a clear intention to conserve water are included in the water-saving behavior identification results. Once water savings are confirmed, the system traces the user's identity, crop structure, time period, spatial location, and upstream and downstream relationships corresponding to the water-saving behavior, generating a uniquely coded digital behavior certificate. The certificate includes the water-saving behavior triggering factor, confirmation path, accounting benchmark, behavior timeliness, and description of changes in water use structure, serving as a traceable digital identifier for the water-saving behavior. The certificate is then linked to the water-saving quota in the transaction system to ensure that the water-saving behavior has a clear source and basis for confirmation when entering the water-saving transaction and resource allocation process. Subsequently, in water rights allocation, water-saving incentive distribution, priority allocation of water resources, and dynamic water price compensation, resource quotas and transaction rights can be determined based on this behavior certificate.

[0043] The water-saving quota allocation path screening process includes ecological impact assessment operation on each optional allocation path. The ecological impact range parameters are set in the scheduling system. The parameters are constructed according to the ecological protection level of the region along the line, the water function regionalization, the ecological water demand cycle, the species habitat sensitivity and the hydrological connectivity importance. The path matching analysis is carried out for all ecological nodes passed by the water transfer path. The system comprehensively judges the disturbance threshold of water flow disturbance intensity, water quality change risk and water quantity fluctuation on the downstream wetland or water ecological system. When the evaluation result shows that the water transfer operation of a certain path causes unacceptable negative impact on the ecological stability of the intermediate node, such as breaking the ecological minimum flow maintenance, causing short-term habitat flow rate sudden change or affecting the reproduction cycle of aquatic organisms, the path is excluded from the allocatable options to protect the ecological red line from being broken. After completing the ecological impact range screening, the system enters the scheduling sequence determination link. The basis for the sequence sorting is the marginal substitution ability of the water-saving quota. On this basis, the system carries out scheduling economic evaluation on the target river basin served by each candidate allocation path. Through the horizontal comparison of the unit water-saving cost and the unit water transfer cost in each target region, it is identified whether the resource benefit brought by the water-saving behavior is better than that of the inter-basin water transfer operation under the same resource consumption condition. If the unit benefit of water-saving behavior is higher, the water demand is preferentially met through the water-saving quota allocation. In the sorting process, the system introduces the scheduling efficiency index. The water-saving cost, water transfer cost, transmission energy consumption, scheduling response time and other parameters are comprehensively normalized to form a scheduling priority scoring system, and the resource flow path and node-level water quantity allocation sequence are determined accordingly.

[0044] The scheduling scheme execution includes a feedback learning link, which is used to establish a closed-loop adaptive mechanism of the water-saving scheduling system. Specifically, after the implementation of the scheduling scheme, the system collects and records the actual water transfer amount, transmission efficiency, water amount deviation value of the node, and actual water use response in the target area of each water transfer path in real time. The actual water transfer amount refers to the total amount of complete water quantity delivery from the source node to the target node, the compliance error refers to the difference between the actual water amount and the predetermined allocation amount, and the regional water use response data includes the change of water resource supply and demand gap, the improvement degree of ecological flow, the change of agricultural irrigation coverage, and the resident water pressure index before and after water transfer in the target area. The system archives the above feedback data and maps and labels the water-saving amount, path selection, scheduling period, and allocation rule used in this scheduling with the feedback data, and then inputs them into the historical behavior library to form a labeled scheduling compliance sample set. The sample library has a three-dimensional information structure of scheduling task, execution result, and regional feedback, which can be used to compare and predict the error and scheduling behavior deviation. In the next round of water-saving amount evaluation, the historical behavior library will be used as the adaptive calibration basis. The system compares the execution deviation under similar scheduling conditions, corrects the use boundary of water-saving amount, the selection range of allocation path, and the regional allocation proportion, and updates the value weight of water-saving amount and the priority sorting logic of resource allocation according to the above, so that the system can continuously correct the evaluation accuracy of water-saving efficiency and the scheduling efficiency in multiple rounds of operation.

[0045] The accompanying drawings are incorporated in and constitute a part of this specification. Figure 3, the method for calculating flow attenuation in the allocation path, regional carrying threshold and water quality compatibility comprises the following operations: the water saving quota generated by the water saving exchange is taken as a deployable resource unit, the system carries out loss evaluation and compatibility screening operations according to the target area and optional deployment path pointed by the water saving quota, in terms of path loss evaluation, the system extracts dynamic parameters including evaporation loss, leakage loss, mid-node diversion behavior, pressure control influence and other key links by accessing real-time operation monitoring records and historical water transfer feedback data of each node along the line, and divides the intensity changes of each influencing factor in different time periods in stages, realizes segmented identification and continuous tracking of actual water loss of the deployment path, and then calculates the effective reachable water quantity under the current path structure and operation condition, dynamically corrects the original water saving quota, so as to obtain the upper limit of the allocated water quantity closer to the realistic executability; in terms of regional carrying threshold determination, the system takes the final target area of the deployment water body as the core, retrieves its ecological function zoning information, historical maximum water transfer operation record, ecological environment fluctuation tolerance and ecological red line index, combines its ecological sensitivity in different seasons and different climate states, sets the maximum deployable water quantity threshold of the area, and limits the batch size, scheduling frequency and water transfer duration of the imported water quantity, so as to ensure that the import process will not destroy the original hydrological balance or cause ecological system stress response; in terms of water quality compatibility, the system takes the water quality indexes of the source water body and the target water receiving area as the basis, covers the basic physicochemical parameters including pH value, dissolved oxygen, conductivity, nitrogen and phosphorus pollutant concentration and organic matter content, carries out multi-level checking combined with the purpose classification of the target area (such as drinking water, irrigation, industrial cooling, etc.), introduces the environmental carrying capacity evaluation indexes of the water receiving area such as water self-purification capacity, water quality control facility operation load, water environment function level, etc., and carries out multi-level water quality adaptability comparison and analysis, and screens out the deployment paths with pollution risk, function conflict or overload risk.

[0046] Aiming at the problems of dynamic loss and ecological constraints in the process of water-saving quota dispatching, a dynamic correction mechanism of water-saving quota and ecological threshold calculation based on multi-source data integration is proposed, which includes: the system integrates multi-source data such as meteorological factors, water supply network operation state and water use behavior fluctuation to realize real-time sensing of water quantity changes in the allocation path of water-saving quota, in which the meteorological factors include temperature, wind speed, humidity and other factors affecting evaporation and transpiration, the water supply network state covers pipe material, supply and distribution pressure and slope structure, and the water use behavior fluctuation is dynamically monitored through the historical water taking behavior and water use response curve of terminal node users, and the system corrects the loss of water-saving quota in each path according to such information; At the same time, combined with regional ecological and hydrological data such as ecological function zoning information, downstream ecological response rate and upstream water fluctuation state, the loadable water quantity of ecological nodes is dynamically calculated to form the ecological dispatching boundary in the allocation path. The process constructs the dispatching capacity judgment logic with the dynamic loss and ecological response comprehensive function as the core, and the specific formula is:

[0047]

[0048] Where, is the available ecological allocation water quantity at time t and node s, α(s,t) is the allocation value of the initial water-saving quota, ε w (t) is the meteorological driven evaporation loss coefficient, which is fitted combined with multi-factor meteorological conditions, γ r (t,s) is the water leakage loss rate of path s, which is calculated by considering pipe network characteristics, slope and operating pressure, δ c (t) is the downstream ecological compensation response coefficient, which is used to describe the sensitivity of the ecological system to flow changes, Φ(t,s) is the time variation function of upstream node inflow, which represents the fluctuation rate, which is used to capture the immediate impact of water source stability on downstream ecological threshold, Λ(t,s) is the ecological function area intensity factor, which is set according to the ecological sensitivity level of the basin, and is used to adjust the dispatching weight of the node, and the function as a whole dynamically evaluates the linkage effect among water loss, compensation and ecological response in the allocation path through time integration. The core innovation of this formula is to introduce This derivative term, for the first time, introduces upstream water source instability into the dispatching capacity judgment mechanism, breaking the limitation of traditional methods that only rely on static or linear loss coefficient for dispatching correction, and through the self-defined composite adjustment term The dynamic correction of water-saving quota and the optimization of dispatching response are realized, and Λ(t,s) is used as the ecological sensitivity enhancement factor to make the dispatching scheme produce constraint or optimization effect in the ecological sensitive area.

[0049] The adaptability check aims to ensure the compatibility of water saving amount in actual allocation process and maximize the benefit of resource allocation. Specifically, it includes joint analysis of real-time water demand type and use priority of target node. The system calls the water structure composition, user category identification and registered use plan of target node in the dispatching period, identifies the water type in the current period of the node, including drinking water, farmland irrigation, industrial cooling, ecological water supplement and other functional water, and gives priority label to each type of use based on national and local relevant water standards. Drinking water and ecological water supplement are given the highest priority, and irrigation and industrial use are given secondary order according to seasonal timeliness and value return level. The system forms a real-time use priority matrix by analyzing the water shortage and replaceability of each use in the allocation period. Then, combined with the source water quality attribute pointed by the water saving amount and the water quality change prediction data in the water transmission process, the system makes multi-level use adaptation judgment on the allocation water quantity. According to the core indicators of water quality including microbial content, heavy metal concentration, total dissolved solids, conductivity, nitrogen and phosphorus content, hardness value, etc., the system respectively checks the water quality safety boundary required by each use, ensures that the water quality of drinking water use meets the drinking water standard, the water quality of agricultural irrigation use matches the water quality index absorbed by crops, and the water quality of industrial use considers the equipment corrosion and reuse possibility. The water quality allocation request that does not meet the corresponding standard is limited or converted to use flow direction, and high-quality water sources are preferentially allocated to high-value use nodes, so as to realize the directional allocation mechanism of water saving amount based on use value, improve the resource allocation efficiency and water quality adaptability of the whole dispatching scheme, and avoid the waste of dispatching resources or the risk of water pollution caused by incompatible use.

[0050] For the ecological nodes with high ecological sensitivity or vulnerability in the scheduling path, the system introduces a simulation prediction mechanism before formal deployment to evaluate the ecological impact of large flow deployment operation in advance. The prediction mechanism is constructed based on the combination of historical ecological monitoring data of the node, hydrological process model and water impact response model, simulates the impact on regional water structure under different deployment flow, duration and water quality characteristics conditions, including water stratification stability, disturbance degree of flow velocity change on aquatic species habitat environment, benthic habitat coverage, wetland connectivity and proximity of ecological red line value, etc. Ecological parameters identify whether there is an ecological threshold breakthrough risk or nonlinear ecological response. If the prediction result shows that the deployment behavior has a significant disturbance on the ecological carrying capacity of the node region or exceeds the safety boundary, the system will generate an emergency deployment adjustment scheme, including water flow reduction, water deployment in batches, scheduling time window delay, backup path switching or scheduling suspension, etc. Response strategies are used to trigger fast switching and safety redundancy mechanism in the execution phase; In the actual deployment process, the system synchronously enables the water saving quota dynamic feedback module, which monitors the execution error of each deployment path and node in real time. The execution error includes the deviation of the actual arrival value and the planned value of the water flow, the deviation of the water quality index and the real-time response data of the node ecological state. The system compares the above feedback data with the current deployment strategy. When the deviation exceeds the preset tolerance threshold or the ecological response index abnormally fluctuates, the feedback module starts the scheduling correction logic, re-evaluates the next round of scheduling path, adjusts the node to match the feasible channel, adjusts the node to adjust the admission quota or deployment rhythm, and realizes the real-time allocation correction of water saving quota.

[0051] After the implementation of the allocation scheme, the system carries out whole-process traceability recording operation on all participating nodes involved in the current dispatching process, specifically including: based on the executed dispatching scheme, the starting node, target node, and transfer node of each allocation path are numbered and managed, the water quantity dispatching time, dispatching time, actual flow path, and water quantity allocation proportion of each node are recorded, at the same time, real-time data collected by online monitoring equipment in the water delivery process are accessed, the actual arrival water quantity of each node on each path and the deviation information of the original allocation plan water quantity are obtained, and combined with the water quality online detection module collected water body index data, the ecological monitoring index system set before allocation is contrasted, including flow disturbance intensity, wetland water level fluctuation, habitat stability parameter, water ecological species response parameter, etc., the ecological system change characteristics caused by allocation behavior are extracted, the ecological impact record is formed, the allocation process information, actual execution situation, and ecological response change of each node are encoded and archived by time stamp and space label, and stored in the allocation compliance database, to construct the allocation compliance archives with node as unit, dispatching period as window, water quantity flow direction and ecological impact as core elements, which can be used for subsequent allocation performance evaluation, water right credit rating, ecological compensation payment, and dispatching compliance audit, has the characteristics of behavior traceability, result verifiability, and data callability, and provides whole-process information support and decision basis for cross-basin water resource fine management and long-term monitoring of water ecological system.

[0052] Embodiment 1:

[0053] In combination with the accompanying Figure 4 In this embodiment, A basin is located in a plain area in the middle of Hebei Province. Farmer Zhang has been operating a winter wheat-summer corn one-year-two-crop irrigation planting structure for a long time. The historical average annual irrigation water quantity of the irrigation area is 6200 cubic meters per mu. The continuous five-year water use record shows that the water use fluctuates little in May and September each year. In the 2023 irrigation season, Zhang responded to the local water price mechanism reform, actively invested in the installation of a drip irrigation system, and reduced the irrigation water demand by adjusting the planting density. According to the analysis of the water use data of Zhang from 2021 to 2023, under the condition of similar meteorological background and unchanged planting structure, the actual water use quantity is reduced to 5300 cubic meters per mu. The system records that this water use behavior continuously triggers a reduction threshold of more than 12% in the spring and autumn irrigation of 2023, and after comparing with the water use trajectory of 11 households in the same village, it is confirmed that this behavior is inconsistent with the regional average water use trend, which is a typical water-saving initiative behavior. Through the water use consistency scoring model, the score is 87 / 100, which is classified as a water right-confirmed water-saving behavior. It is calculated that the farmer saves 900 cubic meters of water in the current year. The system marks the water-saving quantity as “A-2023-WL-Z-0003” water-saving certificate in combination with the water supply structure of the sub-basin where Zhang's land is located, the intensity of groundwater overexploitation, the ecological sensitivity level determination, and the administrative control record, and enters the water-saving quantity right-confirmation database.

[0054] Subsequently, the system queries the B basin's current third quarter urban life and industrial area water shortage evaluation report, which shows that the industrial expansion caused a regional water shortage of 2.4 million cubic meters during July-September 2023, belonging to the moderate water transfer warning level. Due to the protection of the water source within the red line, further exploitation of groundwater is not allowed in this region, so it needs to be supplemented by external water. The system calculates the unit water transfer cost of A basin to B basin as 0.84 yuan / cubic meter, while the investment required to improve water efficiency in B region is 1.06 yuan / cubic meter, and the ecological compensation coefficient is low, only 0.12. Based on this information, the system uses the water-saving value conversion coefficient 0.91 to convert Zhang's 900 cubic meters of water-saving into the equivalent resource value of B basin, 819 cubic meters, and includes it in the cross-basin water-saving quota trading platform, obtaining the corresponding quota price of about 747 yuan.

[0055] After completing the water-saving quota right and transaction, the system determines that industrial water has the highest priority based on the water structure of B basin during the dispatch window period, and needs to complete the first batch of water allocation before July 15. The system analyzes the four available water transfer paths from A basin to B basin, path 1 is 37 kilometers long and has been neglected for a long time, with a water loss rate of 18%; path 2 passes through a storage transfer pool but has a slow response; path 3 is a newly built medium-pressure pipeline line with a water loss rate of less than 5% and a fast response speed; path 4 crosses the ecological red line of the three-level irrigation area and cannot be used. The system selects path 3 as the dispatch path based on the water loss estimation model, dispatch time window, and path carrying capacity judgment, with a maximum allocation of 1200 cubic meters, meeting the full allocation requirement of Zhang's water-saving quota.

[0056] In the final dispatch scheme generation, the system combines path 3 with the current surface water storage of A basin and the water plant supply plan to determine the dispatch start time as July 10 and the expected completion date as July 13. The system allocates 819 cubic meters of Zhang's water-saving quota, with a dispatch direction of A→B east industrial area and a dispatch ratio of 1:1 corresponding to Zhang's transaction quota. Zhang is listed as a level A compliance user in the water allocation plan, and the dispatch order is advanced. The system synchronously introduces an execution feedback module, configuring 3 water quantity monitoring nodes and 2 ecological water quality sampling points for dispatch quality verification.

[0057] Finally, after the dispatch is completed on July 13, the actual water quantity is 807 cubic meters, with a deviation of 1.46%. The water quality indicators are qualified throughout the process, and the industrial area feedback shows that the production water satisfaction rate has increased by 11.2%. The system writes this data back to Zhang's user behavior compliance file and updates his next period water-saving quota credit level. At the same time, this dispatch scheme is evaluated as a typical case with efficient path, ecological compatibility, and significant water use benefits, and is recommended as a template to the platform algorithm model learning sample, guiding the optimization of water-saving dispatch behavior in similar basins.

[0058] In the process of water-saving behavior identification, the system sets the behavior trigger threshold according to the water consumption change trajectory of Zhang in the two irrigation seasons after the drip irrigation reconstruction in the previous year. The average monthly water demand for wheat and corn planting in this area is 325 cubic meters per mu. Under the premise that there is no significant abnormality in meteorological conditions (temperature deviation not more than ±1.2℃, precipitation deviation less than ±10%), the actual irrigation water quantity of Zhang in the two consecutive periods is reduced to 278 and 272 cubic meters per mu respectively, with an average reduction of 15.7%, which exceeds the default trigger threshold of 10% set by the system. At the same time, compared with the irrigation data of 22 surrounding households, the average reduction of the region is only 4.8%, indicating that Zhang's water-saving behavior has obvious individual initiative. Therefore, the system marks Zhang's water-saving behavior as a typical sample with strong water-saving intention, and generates a digital behavior certificate number "DS-BV-A2023-00012" based on the behavior occurrence time, crop type, equipment reconstruction content, water quantity change curve and meteorological data. The certificate embeds the original water consumption behavior data hash digest and authentication timestamp, and is bound with Zhang's 2023 water-saving quota of 900 cubic meters, which becomes the basis for subsequent participation in water-saving transactions and dispatching priority sorting.

[0059] In 2024, B basin entered a new round of industrial expansion period, the system identified that the net water gap of B basin expanded to 3.2 million cubic meters, among which the stage water pressure in mid-July was 0.92 million cubic meters, which needed to be guaranteed through water transfer and unconventional water sources. The system called Zhang's water-saving quota generated in 2023 but not yet dispatched, and included it in the dispatching path screening module. In addition to path 3 used last time, the newly built path 5 (using segmented sealed high-pressure pipeline, total length 29 kilometers) has lower energy consumption and faster hydraulic response, but path 5 passes through the degraded wetland ecological protection pilot area in the north of D county. The system calls the ecological impact range parameter model to simulate and analyze the ecological disturbance intensity caused by path 5 in the July dispatching window, and finds that the water level fluctuation caused by large flow dispatching in the wetland area is ±35 centimeters, which has exceeded the allowed threshold of water level change (±20 centimeters) in the protection area. The wetland is in the root system recovery period of aquatic vegetation, which is extremely sensitive to flow fluctuation. Finally, the system determines that path 5 does not meet the ecological impact tolerance requirement and is excluded, leaving only path 3 as the optional scheme.

[0060] In terms of scheduling sequence ranking, the system updates the water saving amount transaction list and water transfer path economic data of three alternative basins A, C and E. The unit cost of water saving in basin A is 0.43 yuan per cubic meter, the unit cost of water transfer is 0.86 yuan per cubic meter, and the marginal substitution benefit is 0.50. Due to the need to extract groundwater for irrigation, the unit cost of water saving in basin C is as high as 0.71 yuan per cubic meter, the cost of water transfer is 1.05 yuan per cubic meter, and the marginal benefit is only 0.34. Although the water transfer cost of basin E is low, the proportion of unverifiable behavior in water saving data is high, and the compliance rating is medium to low. Therefore, the system prioritizes the water saving amount of Zhang in basin A for transfer, with a high ranking, and sets the scheduling direction as A→B. The system allocates a total of 400 cubic meters of Zhang's remaining water saving amount in 2023, accounting for 3.2% of the total amount of this round of scheduling, and the allocation order is the second. The expected water transfer completion time is July 14, 10:00.

[0061] During the scheduling execution process, the system synchronously enables the compliance feedback module, sets up two monitoring points in the middle of path 3 and the B industrial area water inlet, records the actual water inflow and the planned value deviation, and finally measures the water inflow of Zhang as 392 cubic meters, with an error rate of 2.0%. The water quality detection value meets the industrial cooling standard. The feedback data of B area shows that the equipment downtime rate decreases from 13.5% to 4.2% after water transfer, and the ecological monitoring data shows that the water level of the wetland protection area remains within ±10 centimeters without abnormal fluctuations. The system inputs the execution error, scheduling response time, water quality parameters and target area feedback indicators into the historical behavior library, updates the "DS-BV-A2023-00012" voucher status to partial compliance, and adds 1.3 compliance credit points to Zhang's water saving record in the scheduling priority assessment model. According to the execution results of this round, the system synchronously corrects the water loss correction parameter of A→B path from 5.2% to 4.6%, and increases the water level fluctuation sensitivity weight in the wetland area risk level model to 1.4, enhancing the sensitivity of subsequent ecological path screening.

[0062] Example 2

[0063] Combined with the Figure 5 Taking the second quarter of 2024 as an example, the system selects 1200 cubic meters of water saving amount traded by Zhang as the allocation resource in this round, and the scheduling direction is still A basin→B basin west industrial area, but the target node is changed from the original main water supply plant to the outlet water supplement section of the newly used water reclamation plant in the west, so it is necessary to recalculate the actual available water quantity of the allocation path.

[0064] During the calculation process, the system calls the relevant transaction information of the water-saving quota "DS-BV-A2023-00012" bound by Zhang, and allocates 1200 cubic meters of allocation value to the basic flow plan of path 3, then starts the path loss identification mechanism, analyzes the total length of path 3 about 34.7 kilometers, a total of 8 nodes, including two old concrete open channel sections and six medium pressure pipeline sections along the line, by backtracking the operation log along the line for nearly 6 months, it is found that the 3rd node and the 6th node have perennial operation abnormalities such as large average water pressure fluctuation and unstable water speed, combined with the records of the node embedded monitor, the monthly average loss amount is 4.6% and 3.1% respectively, superimposed with evaporation loss, in-river seepage and other factors, the system identifies the loss source by stage rule and decomposes the water loss of each section into three types of loss factors: hydraulic attenuation, structural aging loss and meteorological factor influence. After comprehensive correction, the system calculates the dynamic effective delivery rate of the path as 91.3%, that is, among the 1200 cubic meters allocated by Zhang, only 1095.6 cubic meters can reach the target node under the condition of no distortion.

[0065] After water quantity correction, the system synchronously calls the ecological function partition information of the target area of B basin, and finds that the section where the south of Xi industrial zone is located belongs to the II-level ecological buffer zone. According to the "regional ecological dispatching standard", the water transfer in this area should not exceed 72 hours continuously and should not exceed 85% of the node carrying threshold each time. After comparing the historical water transfer data by the system, it is confirmed that the maximum carrying capacity of the target node in the past 18 months is 1450 cubic meters / 3 days, so the water quantity of 1095.6 cubic meters in this round of dispatching is within the safe online range, but it still needs to be dispatched in two batches with an interval of not less than 36 hours. At the same time, the system generates a dispatching window from June 16 to June 20, plans to dispatch 550 cubic meters and 545.6 cubic meters in batches, and sets a water transfer suspension judgment point to ensure that the carrying rhythm meets the ecological recovery period.

[0066] In terms of water quality compatibility review, the system determines that Zhang's water-saving behavior comes from the surface irrigation canal system based on the properties of the source water-saving water body. The historical water quality is weakly alkaline, medium hardness, and the total dissolved solids (TDS) is about 480 mg / L. The standard for the recycled water pipe network in the target area is TDS < 550 mg / L, conductivity < 1200 μs / cm, and NH3-N < 1.5 mg / L. The system further compares the predicted water quality changes at each node of the path and finds that there is a slight risk of total nitrogen exceeding the standard at the 4th node (predicted value is 1.7 mg / L), but the proportion of the end-of-line flow is only 15%. The system sets the water quality buffer adjustment algorithm to dilute and guide the mixing of the water body before it is introduced and sets up a warning sampling point. In addition, the target area is used for industrial cooling and replenishment, and the tolerance standards for water pH, hardness, and chloride ions are wide. The overall water quality compatibility evaluation score is 89 / 100, which passes the review threshold. The system finally determines that the current allocation scheme meets the implementation conditions in terms of water quantity, ecological carrying capacity, and water quality matching.

[0067] To further improve the allocation accuracy and ecological adaptability, the system officially introduced a dynamic loss and ecological response comprehensive function mechanism in the third quarter of 2024. It fully integrates meteorological changes, water distribution pipe network operation status, and water-saving behavior fluctuations to calculate the real-time bearable water quantity at key nodes in the allocation path and provide high-precision support for the final dispatching path selection and node quota formulation.

[0068] The target of this round of water allocation is still the last 430 cubic meters of Zhang's water-saving quota. However, since the introduction path involves the southwestern wet area of the B basin, which has high ecological sensitivity, the system needs to evaluate the ecological allocation upper limit of node s in the region during the dispatching period t ∈ [0, 72] hours before dispatching. There are 7 control nodes along the allocation path, with node s being the core introduction node. The system first initializes the input variables, including:

[0069] α(s, t) = 430 / 72 ≈ 5.97 (m 3 / h), which is the initial allocation flow after spreading the water-saving quota;

[0070] ε w (t): Based on the actual temperature of 34.5°C, wind speed of 3.2 m / s, and humidity of 41% in July, the meteorological evaporation loss coefficient is calculated to be about 0.13, with a floating range of [0.08, 0.18];

[0071] γ r (t, s): The path segment s corresponds to an old open canal segment with unstable operation pressure, material is mortar concrete, and slope is 2.1‰. The system estimates that the leakage loss rate is about 0.07, with a value range of [0.02, 0.12];

[0072] δ c(t): Targeted area ecological compensation response coefficient derived from wetland plant restoration data, the system identifies that the species in this area is highly sensitive to flow fluctuations, the response coefficient is set to 0.65, and the normal range is [0.3, 0.8];

[0073] Φ(t,s): The upstream node's 3-hour inflow record is 22.5, 25.6, 19.8, 21.3m 3 / h, the corresponding derivative (flow rate change) is estimated to be The fluctuation intensity is in the upper middle level;

[0074] Λ(t,s): The system extracts the III-level ecological buffer zone to which this node belongs from the ecological zoning map, and assigns a value of 0.78, with a general range of [0.5, 1.0], and the higher the level, the closer the value to 1.

[0075] Substitute into the calculation formula:

[0076]

[0077] To evaluate the upper limit, the system takes the 3-hour average fluctuation rate as 0.4m 3 / h 2 Substitute, calculate the internal adjustment factor:

[0078] 1-0.13-0.07+0.65·0.4=1-0.2+0.26=1.06

[0079] Because there is a small amplitude increase, the system sets the upper limit of the adjustment factor to 1 to ensure ecological safety, so the expression is simplified to:

[0080]

[0081] The final calculation result shows that although Zhang's water saving quota is 430 cubic meters, considering meteorological loss, seepage, ecological sensitivity and inflow fluctuation, etc., this node is only allowed to allocate about 335 cubic meters of water in this round of dispatching, and the system will reserve the remaining 95 cubic meters to the next cycle or allocate it to other non-sensitive areas in the B basin, and adjust the allocation batch to complete two-stage water injection within 60 hours, the front 220m 3 , and the back 115m 3 , to match the plant root absorption curve and reduce the impact.

[0082] Further into the use adaptation, ecological prediction and prevention and control, and feedback and traceability links in the implementation phase. This round of dispatching is classified as a limited water injection behavior in the III-level ecological buffer zone, so it must consider the water use structure of the node being dispatched, the ecological system carrying capacity boundary, and the traceability of the entire dispatching process.

[0083] The system starts the adaptability checking mechanism, and the target node (number B-SW-04) in the southwest area of B basin real-time water demand is used for use disassembly. The daily water structure of this node includes industrial cooling water supplement (accounting for 55%), ecological irrigation (35%) and life water supply reserve (10%), among which the ecological irrigation is in the local wetland edge plant transplanting period, and the water quality pH and nitrogen and phosphorus concentration are more sensitive. The system sets the priority rules as follows: I level is direct drinking water or ecological restoration, II level is industrial cooling or agricultural irrigation, and III level is recycled water supplement. Combined with the planned use of the node and the attribute of the incoming water source, Zhang's incoming water body is the water saving source of the surface irrigation canal, the water quality is weak alkaline (pH 7.8), total nitrogen 0.9mg / L, TDS 490mg / L, among which the water quality meets the II level water standard but is difficult to meet the I level standard. The system compares the target use demand with the source water index, and removes the part allocated to the ecological irrigation area, and the allocation ratio is as follows: 55% flows to the industrial cooling water port (about 184m 3 ), 45% enters the recycling pool for reprocessing, the system locks the drinking water interface in the original configuration, ensures the priority of high value use, and avoids the risk of water quality misallocation.

[0084] In order to prevent sudden ecological risk, the system starts the simulation prediction mechanism for the incoming node B-SW-04, and executes rapid ecological disturbance simulation within 48 hours before incoming, inputs historical water level sensitive curve, sediment disturbance index and vegetation stress response parameters, and simulation shows that if more than 180m 3 of water is imported at one time, it will cause the over-limit of shallow water accumulation within the radius of 250m around the node, and flush the root zone of newly planted vegetation. The system generates emergency dispatch adjustment scheme accordingly, and suggests that the dispatch plan is adjusted from 2 batches to 3 batches: 120m 3 , 105m 3 , 110m 3 , respectively, every 24 hours, and sets the vegetation root zone physiological response monitor in the process, detects if the humidity index exceeds the threshold value 0.85, the system will pause the next batch of water injection, or trigger the standby dispatch to switch to the adjacent central node B-SW-03.

[0085] During the dispatch execution process, the system starts the dynamic feedback module of water saving amount, deploys 3 flow monitoring points, 2 water quality sensing units and 1 ecological sensor group along the line, and records the incoming water amount, flow rate change and plant humidity response in real time. After the dispatch is completed, the system statistics the actual arrival water amount as 335.7m 3, the estimated error is less than 2%; the water quality monitoring throughout the process is not over-standard nitrogen and phosphorus, the ecological sensor feedback humidity index fluctuation is between 0.72-0.81, and the pause condition is not triggered. The system writes this execution data into the allocation fulfillment module, completes the whole process of traceability record: Zhang's water-saving quota number "DS-BV-A2023-00012" is marked as complete fulfillment, and a complete fulfillment archive is formed, including five types of data such as path number, allocation ratio, execution error, use adaptation result and ecological response curve, which is archived into the fulfillment history data pool and used as the basis for subsequent credit, ecological assessment and scheduling priority.

[0086] The above shows and describes the basic principles, main features and advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above embodiments, and the above embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for inter-basin water saving quantity transaction and dispatch optimization, characterized in that The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device.

2. The method of claim 1, wherein The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device.

3. The method of claim 1, wherein The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. 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The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving behavior identification device. The application relates to a water-saving behavior identification method and a water-saving 4. The method of claim 3, wherein The water-saving quota allocation path screening process includes setting an ecological impact range parameter, and when a certain allocation path causes negative impact on an ecological node in the middle, the path is excluded; the determination of the scheduling order is based on the marginal substitution capacity of the water-saving quota, and the resource flow direction of the scheduling efficiency is determined by comparing and prioritizing the unit water-saving cost and the unit water diversion cost of different basins.

5. The method of claim 4, wherein The scheduling scheme execution includes a feedback learning link, which inputs the actual water diversion amount, the implementation error and the regional water use response data in the execution process into the historical behavior library for correcting the next round of water-saving quota evaluation and scheduling priority strategy.

6. The method of claim 1, wherein The method for calculating the flow attenuation, regional carrying threshold and water quality compatibility in the allocation path includes: Obtain the water-saving quota as the allocation resource, and in the allocation process, for each allocation path, combine the operation records and historical feedback data of each node along the transmission line to identify and track the actual loss source on the path in stages and dynamically correct the effective reachable amount of the water-saving quota; Based on the ecological function zoning of the target allocation area, the historical operation extreme value and the ecological protection requirements, the water quantity corresponding to the allocation path is subjected to batch and continuity constraints; according to the water quality indicators, use categories and water environment carrying capacity of each node, multi-level adaptive checking comparison is performed according to the water body characteristics of different sources and target areas, and the allocation scheme that causes water pollution or functional conflict is excluded.

7. The method of claim 6, wherein The loss correction of the allocation path includes collecting real-time weather data and water transmission pipe network working condition information, and synchronously counting dynamic evaporation, leakage and node water consumption fluctuation into the loss judgment; The setting of the carrying threshold is based on the ecological function zoning, and the dynamic evaluation of the downstream ecological compensation response speed and the upstream water source fluctuation of the basin is introduced.

8. The method of claim 7, wherein The adaptive checking includes multi-level use adaptation of the allocation water quantity according to the real-time water demand type and use priority of the target node, matching the water quality safety boundary of drinking water, irrigation and industrial different function water, and preferentially allocating high value use.

9. The method of claim 8, wherein For the ecological node with high risk, a simulation prediction mechanism is introduced before allocation to evaluate the influence of large flow allocation on the regional water body structure and ecological carrying capacity in advance, and an emergency allocation adjustment scheme is generated; a dynamic feedback module of the water-saving quota is set during the allocation execution process to collect execution errors and node response information in real time, and the next round of allocation path and node quota allocation is adjusted according to the feedback.

10. The method of claim 9, wherein After the implementation of the allocation scheme is completed, the water flow direction, actual arrived water quantity and ecological impact index of all participating nodes are recorded throughout the process to form an allocation implementation file.

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