49 results about "Reservoir capacity" patented technology

The invention relates to a buried hill gas storage effective gas storage space evaluation method, and belongs to the technical field of oil-gas exploration. The method comprises the following specific steps: acquiring fracture development parameters; determining the type of a storage space; reservoir logging response characteristics are determined; extracting buried hill cracks; establishing a bedrock geologic model and a bedrock buried hill discrete fracture model of the target area; and importing the results into a gas storage simulation model in the form of data flow, extracting effective gas storage spaces of a substrate and a crack of the buried hill gas storage, and determining a final buried hill building effective gas storage space. Through research on the method for calculating the reservoir space of the buried hill oil and gas reservoir rebuilt gas storage, the problem of invalid reservoir space calculation is deducted, the calculation accuracy is improved, and theoretical support is provided for calculation of the buried hill reservoir building capacity and later injection and production well position deployment.

The application discloses a kind of arid region reservoir water and sand prediction and coordinated regulation potential evaluation method and system, belong to water resources, silt treatment and reservoir optimization scheduling technical field.The technical problems of traditional model prediction accuracy insufficient caused by arid region hydrology data scarcity, water and sand prediction process is fragmented and reservoir desilting and silt reduction and water storage benefit difficult to be synergistically optimized, its gist is that: long short-term memory network is used to predict future runoff sequence by fusing attention mechanism, and the sediment concentration is calculated by combining the water and sand relationship formula;By setting the critical sediment concentration threshold, the high sediment concentration period is identified and the available water for dredging is calculated;At the same time, the flood resource potential is evaluated by combining reservoir capacity and water demand constraints;Finally, the coordinated scheduling scheme is generated by comparing the two potentials.The application realizes the integrated accurate prediction of water and sand process in arid region and the simultaneous quantitative evaluation of regulation potential, and provides intelligent decision support for multi-objective optimization scheduling of reservoir.

This invention discloses an intelligent scheduling method for reservoir water supply safety based on deep reinforcement learning, comprising: 1. Constructing a reservoir scheduling environment model and acquiring historical hydrological data and engineering constraints of the reservoir; 2. Establishing an agent based on a deep Q-network, defining a state space, action space, and a composite reward function; wherein the composite reward function includes a water supply guarantee reward, a water level control reward, and a water replenishment reward; 3. Training the agent using an experience replay mechanism and a target network separation method, and updating the network parameters by minimizing the loss function; 4. Outputting the optimal scheduling scheme through the trained agent. This invention can significantly improve water supply reliability while ensuring reservoir water level safety, thereby providing a reliable guarantee for reservoir water supply safety.

This invention relates to the fields of reservoir scheduling, flood control and disaster reduction, and hydrological forecasting, and particularly to a method for calculating reservoir rainfall carrying capacity based on a dynamic runoff coefficient. The method includes the following steps: collecting data including the target reservoir's catchment area, characteristic water level, and water level-capacity relationship curves; establishing a dynamic equation for rainfall-runoff coefficient based on reservoir storage using the initial water level, characteristic water level, and storage capacity relationship curves; collecting and analyzing historical flood data for the target reservoir to generate parameter statistics tables for each flood event; establishing a dynamic equation for rainfall-runoff coefficient based on underlying surface conditions based on the parameter statistics tables for each flood event; and solving the dynamic equations based on reservoir storage and underlying surface conditions simultaneously. This invention relies on real-time water level and real-time rainfall to dynamically calculate reservoir rainfall carrying capacity, thus improving the accuracy of reservoir rainfall carrying capacity calculation.

The invention discloses a cascade reservoir joint compensation scheduling method considering flood sources and reservoir capacity levels, and belongs to the field of reservoir joint flood control scheduling. In order to solve the problems that a traditional scheduling strategy is poor in adaptability and a reservoir impounding role is fuzzy, the method is implemented through the following steps that the range of cascade reservoirs included in scheduling is determined, and engineering characteristic data such as flood control water levels and flood control high water levels are collected; calculating the amount of flood needing to be retained and stored based on the flood forecasting process of the downstream flood control point; a control reservoir and a matching reservoir are divided according to the hydraulic topological relation, the impounding capacity is distributed by combining the flood volume proportion of each reservoir and the remaining flood control reservoir capacity proportion, full-reservoir impounding distribution is completed through secondary distribution and recursion, the dispatching effect is checked, and the flow regulation and control factors are dynamically adjusted. The method is simple, practical, reasonable, reliable and capable of quickly adapting to different water regimes and work conditions, accurately positioning the reservoir retaining role, improving the overall flood retaining benefit of the cascade reservoir group, conforming to actual dispatching characteristics, being easy to popularize and providing scientific support for real-time dispatching decision of a reservoir operation management department.

A well network deployment method for increasing the storage capacity of water-flooded high-permeability gas storage facilities, belonging to the field of oil reservoir gas storage construction technology, includes the following steps: S1, employing oil and gas reservoir fine description technology; S2, employing oil and gas reservoir engineering technology; S3, employing gas storage dynamic analysis technology; S4, establishing a comprehensive geological model, and combining steps S2 and S3 to clarify the direction of seepage dominance and delineate seepage zones in oil and gas areas. This invention, under conditions of high well network control and severe water intrusion and gas channeling, can significantly increase the storage capacity of water-flooded areas, solve the common problem of uneven injection-production displacement in sandstone gas storage facilities, and alleviate the contradiction of large differences in displacement effects between favorable and unfavorable areas during cyclic injection-production. This invention can be applied to the expansion of gas storage facilities that have been renovated due to significant seepage dominance or strong planar heterogeneity.

This invention provides a single reservoir scheduling method and device based on adaptive grid and micro-step simulation, relating to the field of flood control scheduling technology in water conservancy engineering. By using micro-step simulation, the integral error of traditional long-step calculation is overcome, making the simulation results closer to the actual hydraulic processes of the reservoir. Based on the simulation results, the effective reservoir capacity range is dynamically locked, and a search grid is adaptively constructed in conjunction with the inflow intensity, significantly compressing the state space while ensuring accuracy and solving the curse of dimensionality. Through physically driven grid density calculation, the difference in water volume between adjacent discrete states is ensured to be less than the reservoir's single-step regulation capacity, eliminating "grid deadlock" at its root. Dual capacity constraint verification is introduced into the dynamic programming to prevent the mathematically optimal solution from failing due to insufficient discharge capacity. Multiple engineering constraints can be flexibly incorporated, maximizing the peak reduction rate while ensuring safety, achieving synergistic optimization of safety and efficiency, and significantly improving the flood control scheduling efficiency of the reservoir.

This invention relates to the field of emergency hazard mitigation technology in water conservancy projects, and in particular to a method for controlled release and hazard mitigation of landslide-dammed lakes based on erosion benchmark protection. The method includes: calculating the allowable breach height of the landslide-dammed lake based on the dam length, dam volume, and reservoir capacity corresponding to the protection elevation; determining the erosion benchmark protection elevation based on the allowable breach height; calculating the cross-sectional dimensions of the spillway based on the determined maximum breach flood peak flow; and laying a temporary spillway based on the erosion benchmark protection elevation and the cross-sectional dimensions of the spillway. This invention achieves safe and controllable release of water from landslide-dammed lakes, improves the safety and efficiency of emergency hazard mitigation, effectively avoids downstream flood disaster risks, and is applicable to various landslide-dammed lake emergency response scenarios.

The application provides a method for determining a scheduling mode of reservoir flood control storage capacity released in stages at the end of flood season, and relates to the technical field of reservoir scheduling. The method comprises the following steps: collecting and arranging basic data, including hydrological and meteorological data, information of flood protection objects downstream, and data of reservoir scheduling parameters; determining a release time of reservoir flood control storage capacity based on multiple factor conditions; determining a release discrimination index of reservoir flood control storage capacity according to water level characteristics of a flood control station; carrying out risk analysis and risk atlas drawing of reservoir flood control storage capacity release; and determining a recommended flood control storage capacity release scheduling mode according to the flood control risk atlas. The application determines the release time of reservoir flood control storage capacity and the corresponding discrimination index by comprehensively considering multiple factor conditions, and draws a downstream flood control risk atlas on the basis of flood regulation calculation, and finally determines the recommended flood control storage capacity release scheduling mode in stages, which is of great significance for flood resource utilization at the end of flood season, improvement of reservoir storage guarantee rate, guarantee of downstream flood control safety and water safety.

This invention discloses a method for joint allocation and optimization of multiple water sources in underground reservoirs, specifically relating to the field of water resource allocation technology. The method includes basic parameter acquisition and spatial coordinate alignment, grid cell dual-accessibility attribute labeling, grid-based reservoir capacity effectiveness classification and twin mapping construction, full-cycle supply and demand parameter collection and time-period segmentation, and time-period supply and demand matching and allocation scheme generation. This invention unifies the spatial benchmark of multi-source parameters through cross-data source spatial coordinate matching and alignment, achieving precise spatial correspondence between grid-level hydrogeological and engineering node parameters. It links the spatial matching of single grid cells with recharge and extraction nodes to aquifer parameters for accessibility labeling, classifies reservoir capacity effectiveness based on dual thresholds, constructs a reservoir capacity mapping with dual constraints, segments the entire cycle into equal-length time periods for matching supply and demand parameters, completes time-period supply and demand matching and reservoir capacity iterative updates, and achieves temporal linkage between recharge and extraction, accurately matching the spatiotemporal distribution of multi-source water supply and irrigation water demand.

The application discloses a kind of low permeability reservoir underground gas storage multi-cycle injection-production condition under the prediction method of effective reservoir capacity boundary dynamic evolution, and the application is based on injection-production intensity driving seepage parameter self-adaptive evolution under the condition of low permeability reservoir underground gas storage multi-cycle strong injection and strong production, and the effective reservoir capacity boundary is dynamically predicted, to solve the systematic overestimation problem caused by parameter static, threshold effect neglect and connectivity loss in the effective reservoir capacity boundary prediction of low permeability reservoir underground gas storage under the condition of multi-cycle strong injection and strong production. Realize: the effective reservoir capacity boundary of injection stage and production stage is predicted respectively;Seepage parameter self-adaptive evolution with cycle and injection-production system intensity, not dependent on field testing / monitoring data;Through threshold-conductivity-connectivity accessibility triple criterion, the effective reservoir capacity boundary meeting engineering definition is obtained.

This invention discloses a method for calculating the reservoir capacity and iteratively optimizing the dam height of debris flow dams based on point cloud and TIN models, belonging to the field of debris flow disaster prevention and control engineering technology. First, original ground point cloud data of the dam site area is acquired and preprocessed. TIN models of the original gully and the post-dam siltation surface are constructed separately. The design reservoir capacity is calculated using the triangular prism volume integral method, and the siltation line can be automatically generated and the siltation visualization results are output. Simultaneously, with accurate reservoir capacity as the core indicator, a verification mechanism between the reservoir capacity and the required reservoir capacity is established. The dam height is iteratively optimized by adjusting the elevation of the dam crest centerline until the reservoir capacity meets the requirements. This invention achieves rapid and high-precision calculation of the design reservoir capacity, eliminating reliance on manual operation. It also constructs a standardized reservoir capacity-dam height iterative process, achieving precise matching between dam height and reservoir capacity, balancing engineering disaster control effectiveness and economy. The results are compatible with general engineering formats and applicable to complex gully terrain, providing reliable technical support for the precise design of dams.

The present application belongs to the technical field of oil and gas exploration, and relates to a method and system for predicting favorable targets of superimposed gas reservoirs based on source-reservoir configuration relationship. The present application obtains a reservoir thickness contour map and an effective reservoir thickness contour map; obtains a source-reservoir configuration coefficient contour map according to the excess pressure of a hydrocarbon source rock, the median pressure of a reservoir, and the vertical distance between the hydrocarbon source rock and the reservoir; and obtains a storage energy coefficient contour map using the effective thickness of the reservoir, the gas saturation, and the porosity of the reservoir. The favorable area of the dense reservoir under the condition of low-permeability-dense superimposed gas reservoirs is predicted according to the reservoir thickness contour map, the effective reservoir thickness contour map, the source-reservoir configuration coefficient contour map, and the storage energy coefficient contour map. The present application can comprehensively evaluate the formation conditions and the reservoir capacity of superimposed gas reservoirs in different regions by integrating the information of the above four contour maps, and can accurately screen the favorable area of the dense reservoir under the condition of low-permeability-dense superimposed gas reservoirs.

The application discloses a pumped storage power station and cross-regional conventional hydropower joint operation optimization method and model, comprising constructing and participating in the market by taking the joint operator as an independent settlement unit; establishing a target function which maximizes the sum of the day-ahead income and real-time income of the pumped storage power station and the day-ahead income and real-time income of the conventional hydropower minus the pumped storage cost in the scene probability; introducing pumped storage quantity reporting constraints, conventional hydropower quantity reporting constraints which fuse the discrete switching characteristics and minimum must-release power constraints of the conventional hydropower, pumped storage operation continuity constraints and reservoir capacity balance constraints; executing differentiated collaborative reporting strategies according to the price scene, and realizing the maximization of the overall income by optimizing the quantity reporting curve of each subject in the day-ahead market through the joint operation optimization model; and the application solves the technical problems of the existing pumped storage and conventional hydropower independent operation or simple joint scheduling, such as the lack of cooperation, the mutual occupation of the income space and the unexecutable optimization results under the discretization constraints.

The application discloses a kind of quantitative evaluation methods of associated hydropower station hydraulic correlation degree.The method includes the following steps: determining associated hydropower station hydraulic correlation index, and calculating associated hydropower station hydraulic correlation index value;According to the weight coefficient of dynamically distributing associated hydropower station hydraulic correlation index after division associated hydropower station type;Calculate the comprehensive correlation degree of associated hydropower station;Based on the regulation reservoir capacity ratio index and installed capacity of associated hydropower station, data processing is carried out on the comprehensive correlation degree of associated hydropower station to obtain the comprehensive correlation degree of associated hydropower station after data enhancement, and the comprehensive correlation degree of associated hydropower station after data enhancement is divided into correlation grade by using kernel density estimation method and natural breakpoint method, to realize the quantitative evaluation of associated hydropower station hydraulic correlation degree.The application first proposes the comprehensive correlation degree obtaining method of associated hydropower station, breaks through the limitation of traditional single index, and further provides core technical support for watershed collaborative scheduling.

This invention provides an intelligent inversion method for inflow based on multi-source error constraint fusion, belonging to the field of hydrological forecasting technology. The method includes: constructing physical constraints based on long-sequence water level observation data, measured outflow sequences, and reservoir capacity-water level curves; constructing a composite optimization function including a reservoir capacity time-varying error compensation term, inflow continuity regularization constraints, and a water level observation data assimilation module; deriving the analytical inversion solution of inflow based on the Lagrange multiplier method; and automatically optimizing key parameters such as constraint weights and smoothing coefficients using intelligent optimization methods such as grid search and cooperative search algorithms to perform adaptive high-precision inversion under different hydrological scenarios. This invention, by dynamically adjusting the error weight coefficients, directly generates physically consistent inflow sequences without relying on the prior assumptions of traditional smoothing filters, significantly improving the performance of negative value rate control, water balance, and flood peak characteristic preservation.

The present application relates to the technical field of gas reservoir development and efficient operation of gas storage, and particularly relates to a multi-cycle injection-production storage capacity dynamic prediction method for water-invasion gas reservoir type gas storage. The method comprises: obtaining injection-production experimental data of each cycle based on multi-cycle injection-production experiments; determining the phase permeability hysteresis coefficient, stress sensitivity coefficient, water invasion coefficient and water recession coefficient corresponding to each cycle based on the injection-production experimental data of each cycle; constructing a water invasion-seepage-pressure dynamic coupling model based on the phase permeability hysteresis coefficient, stress sensitivity coefficient, water invasion coefficient and water recession coefficient corresponding to each cycle; and predicting the storage capacity of the water-invasion gas reservoir type gas storage based on the water invasion-seepage-pressure dynamic coupling model. The present application solves the problems of storage capacity prediction deviation, insufficient experimental reproducibility and missing coupling model caused by dynamic interference of water invasion, stress sensitivity effect and hysteresis effect under water invasion conditions.

This invention provides a refined method, system, and storage medium for the scheduling of sediment discharge from multiple orifices in a large reservoir. It relates to the fields of reservoir sediment scheduling and multi-dimensional coupled water and sediment numerical simulation. The method includes: determining the initiation conditions of inflow sediment peaks; constructing a one-dimensional river network water and sediment mathematical model considering the sediment peak transport process; determining the water and sediment boundary conditions near the dam; constructing a three-dimensional refined water and sediment mathematical model considering strongly irregular river channel boundaries and multiple orifice discharge scenarios; simulating the sediment discharge effect under different orifice opening and closing conditions; and selecting the orifice opening and closing scheme with the maximum sediment discharge capacity. This invention utilizes one-dimensional-three-dimensional coupled water and sediment numerical simulation technology, combined with GPU parallel acceleration and ALE dynamic mesh technology, to achieve refined simulation of the sediment discharge effect from multiple orifices. This provides a scientific basis for the scheduling of sediment discharge from large reservoirs, effectively reducing reservoir sedimentation, delaying reservoir capacity decay, and ensuring the long-term effective operation of the reservoir's diverse functions.

A computer-implemented method includes training an artificial intelligence / machine learning (AI / ML) algorithm to generate a reservoir model representative of a storage reservoir and generating the reservoir model. a computer containing the trained reservoir model receives a set of real-time reservoir data generated at the storage reservoir, the set of real-time reservoir data being representative of measured reservoir operations and analyzes the real-time reservoir data using the trained reservoir model. The computer generates at least one recommended alteration to reservoir operations based on an output of the reservoir model.

This invention relates to the field of water conservancy and hydropower engineering scheduling, specifically to a multi-objective optimization scheduling method for reservoirs and related products. The method uses the planned output sequence as the decision variable, constructs a monotonic reservoir capacity-water level mapping, back-calculates the power generation flow rate for each time period, and verifies the net head. It combines inflow, direct water intake within the reservoir, and reservoir losses to perform water balance and back-calculation of water wastage. Then, based on the closed reservoir capacity and total outflow, it back-calculates the actual available power generation, water supply shortage, and insufficient ecological flow, and iteratively optimizes candidate scheduling schemes accordingly. After iteration, the candidate optimal scheme is verified using the same calculation method. If the verification passes, an executable scheduling scheme is output; if the verification fails, corresponding verification dissatisfaction information is output.

The application relates to a reservoir real-time scheduling sand peak transport time calculation method, which comprises the following steps: a beta coefficient is obtained by fitting calculation according to the sand peak transport time of measured data and the transport time of reservoir water flow particles; the relationship between the water depths h1 and h2 of the reservoir tail and the dam front under different reservoir inflow or scheduling is deduced; the relationship between the water level and the reservoir capacity is deduced; the dam front water level, the reservoir inflow and outflow are substituted into the sand peak transport time calculation formula under the reservoir real-time scheduling, so that the time of sand peak transport from the reservoir tail to the dam front can be quickly calculated. The application closely combines the reservoir real-time scheduling, deduces the change of the flow velocity along the sand peak in the reservoir, finally obtains the sand peak transport formula suitable for the reservoir and having a certain mechanism, and combines the reservoir inflow and outflow conditions and the reservoir scheduling, so that the time of the sand peak transport from the reservoir tail to the dam front can be quickly and conveniently predicted and estimated, the dam gate is timely opened for sand discharge, the working efficiency and the result precision can be greatly improved, and the sand scheduling of the reservoir is effectively supported.

This invention relates to a reservoir flood control peak shaving scheduling method, system, equipment, and medium based on time-series dynamic target water level and analytical POA optimization, belonging to the field of reservoir flood control scheduling technology. The method includes: obtaining the start and end times of flood events; identifying and dividing the flood peak and valley generation interval sequence within the start and end times; constructing a piecewise linearly changing time-series dynamic target water level process line based on the interval sequence and performing storage compensation calculations to generate an initial reservoir capacity sequence; under the constraint of the boundary reservoir capacity of adjacent time periods, locally linearizing the reservoir capacity relationship within the boundary reservoir capacity, then gradually transforming the objective function into a quadratic function, and solving for the derivative of the quadratic function to obtain the optimal reservoir capacity for the current time period; iteratively solving for the optimal reservoir capacity for each time period and updating the reservoir capacity sequence until convergence, outputting a reservoir scheduling scheme generated from the optimized reservoir capacity sequence. This invention improves the flood control efficiency and emergency response capability of reservoirs in dealing with complex multi-peak floods.

The application discloses a method, device and equipment for correcting water level-storage capacity relationship based on reservoir siltation, which comprises the following steps: obtaining initial storage capacity values corresponding to each water level layer of a reservoir; obtaining running state change data of each flow level of each water level layer of the reservoir within a period of time; calculating a relative siltation parameter of the reservoir according to a proportional relationship between the running state change data and initial running state data; calculating a siltation storage capacity according to the initial storage capacity values and the relative siltation parameter of the reservoir; and correcting actual storage capacity values of each water level layer by using the siltation storage capacity. The application completes siltation calculation and water level-storage capacity relationship correction by fully utilizing initial storage capacity data, daily running data and water level data of the reservoir, without complex external terrain measurement and data measurement at a specific time or scene, and the calculation process is simple. The calculated value is a proportional value based on an initial value, conforms to an existing economic dispatching system of a hydropower station, and has a low water level-storage capacity relationship correction cost.

The application discloses a kind of short-term peak shaving scheduling coordination optimization methods of cascade hydropower station group, and the application relates to the technical field of hydropower scheduling, based on the correlation curve of the power generation of each hydropower unit and water consumption rate is constructed by cloud historical operation data, the optimal operation interval is locked by curve analysis, the dual optimization of unit efficiency and water consumption economy is realized;According to the real-time power generation demand of power grid, combined with the current power state of unit and the storage capacity condition, the unit starting strategy of water consumption rate priority is adopted, and the power difference is intelligently distributed by introducing the curve slope inverse proportion normalization algorithm, to ensure that the water resource consumption is minimized while meeting the load demand, the dynamic fluctuation curve of storage capacity is constructed in real time during scheduling process, the safety threshold monitoring mechanism is set, the deviation of actual water output and theoretical value of unit and abnormal fluctuation of reservoir capacity are double early warning, form the closed-loop control system of prediction, optimization, monitoring and alarm, effectively improve the peak shaving response speed and operation safety of cascade hydropower station group.

This invention discloses a method for determining the geometric and temporal characteristic parameters of a landslide dam breach based on overtopping failure. The method includes collecting basic parameters and determining the reservoir capacity characteristic coefficient; determining the final breach morphology parameters; calculating the water depth in front of the dam corresponding to the peak flow rate based on the actual discharge volume at the end of the breach and its corresponding depth, the discharge volume at the peak flow rate, and the reservoir capacity characteristic coefficient; determining the breach bottom width at the peak flow rate by combining empirical coefficients with the final breach bottom width; calculating the vertical breach depth at the peak flow rate based on the sediment transport balance principle, the final breach bottom width, and the trapezoidal similarity principle; and solving for the duration of the rapid development stage of the breach based on the water balance equation and the peak flow calculation formula. This invention proposes a method for determining breach development parameters, including the duration of the rapid development stage reaching the peak flow rate, the breach morphology at the peak, and the total breach duration of this stage, enabling scientific prediction of the discharge flow process during a landslide dam overtopping failure.

This invention discloses a method for calculating the dynamic hydraulic replacement cycle of a reservoir based on an inverse integral algorithm. The method includes: responding to a hydraulic replacement cycle calculation request, determining a second time interval matching a first time interval; obtaining the daily average inflow of the target reservoir within the second time interval, forming a daily average inflow time series; forming a daily average reservoir capacity time series based on the daily average inlet water level of the target reservoir within the first time interval, and the relationship curve data between the measured inlet water level and reservoir capacity; and using the daily average inflow time series and the daily average reservoir capacity time series, searching for preceding related days corresponding to each day within the first time interval using an inverse integral algorithm, and generating the daily hydraulic replacement cycle of the target reservoir within the first time interval. This invention enables the accurate construction of the dynamic water replacement process under unsteady runoff conditions, improving the accuracy and robustness of hydraulic condition assessment methods.

This invention proposes a reservoir group interconnection and scheduling system and method based on head-capacity complementarity, relating to the fields of water conservancy engineering and water resource optimization scheduling technology. It addresses the shortcomings of existing technologies, which primarily rely on simple pipeline layouts for water allocation and the construction of joint reservoir scheduling projects. These methods result in high costs, reliance on human experience for scheduling decisions, low accuracy, significant resource waste, and an inability to optimize scheduling in real time. This invention, through an optimized pipeline network structure and intelligent control system, achieves automatic, bidirectional, and efficient complementary scheduling of water resources between reservoirs, improving the overall utilization efficiency and safety of regional water resources. It reduces reliance on human experience, lowers engineering costs, and provides a faster response time. Utilizing the potential energy of high-head reservoirs, it directly replaces the water lifting energy consumption of low-head reservoirs through a reverse allocation mode, generating significant economic benefits and realizing intelligent bidirectional complementary scheduling.

This invention provides a method and system for calculating farmland runoff storage capacity in the Chaohu Lake Basin based on AI-based runoff-generator coupling simulation. It relates to the fields of hydrological and water resources simulation and engineering scheduling. The method includes: acquiring underlying surface and hydrological data of farmland and multi-level ditch-pond and wetland storage systems in the Chaohu Lake Basin; constructing a runoff-generator coupling model constrained by both AI algorithms and hydrophysical mechanisms to characterize the runoff process from farmland to ditches and wetlands grid by grid; inputting real-time soil moisture, water level, and flow monitoring data into the runoff-generator coupling model to dynamically simulate the runoff process after heavy rainfall hourly, obtaining a non-constant runoff curve reflecting the peak runoff and the runoff process; and dynamically identifying multiple feature control points with precise spatiotemporal coordinates from the non-constant runoff curve. This invention enables refined simulation of the runoff process in the polder area and reasonable and effective allocation of storage capacity.