7161 results about "Water level" patented technology

The invention discloses a multi-point ditch flow monitoring method, and particularly relates to the field of branch ditch flow monitoring, which is used for solving the problem of complex branch ditch flow monitoring and optimization, and comprises the following steps of: constructing a branch ditch topological connection relation matrix, generating a flow characteristic curve in combination with flow and water level time sequence data, and marking interference points; generating an interference incidence matrix by utilizing two-channel interaction analysis, extracting upstream and downstream flow offset and disturbance propagation characteristics, judging an interference dominant mode according to a difference degree, and respectively calculating a flow offset compensation matrix and a disturbance propagation correction matrix; the recursive optimization model realizes segmented correction and reduces error residual errors, combines spatial-temporal feature clustering to identify abrupt change sections and generate a high-risk area key monitoring list, extracts refined data based on a high-frequency acquisition strategy to analyze abnormal causes, generates a dynamic correction result by using a prediction model, and updates a traffic balance data set. The multi-mode interference is accurately corrected, the flow distribution is optimized, and the monitoring precision and the system stability are improved.

The invention provides a drainage basin digital twinning construction method and system based on multi-source data fusion. The method is applied to the technical field of drainage basin digital twinning construction, and comprises the following steps: acquiring water level monitoring data, surface flood routing path data, weather forecast rainfall data and terrain slope change data; rainfall and topographic slope data are fused to generate a runoff distribution relation, and a high-risk area is identified in combination with a water level sudden change amplitude. A digital twinning preliminary framework is established, and related characteristic parameters are generated by utilizing reverse feedback of a flood path and water level data. And inputting meteorological data, constructing a twinborn model based on the boundary condition of the catchment area, and simulating flood direction abnormity and flooding early warning signals. And according to the early warning space-time distribution and the terrain elevation data, generating emergency schemes such as flood dividing gate scheduling and flood storage and detention area starting, and realizing risk hierarchical management and control. According to the technical scheme provided by the invention, the flood inundation prediction precision and the emergency response efficiency are improved, and precise decision support is provided for flood control of a drainage basin.

The invention relates to the technical field of environment monitoring, in particular to an underground water pollution source traceability identification method and system, and the method comprises the following steps: S1, collecting the flow velocity, flow direction and water level change data of underground water in a polluted region in real time; s2, constructing a preliminary underground water flow model; s3, simulating a migration path of pollutants in underground water, and predicting a potential pollution source position; s4, processing the collected underground water flow velocity and pollutant diffusion path data, and removing abnormal data interference; s5, generating a spatial distribution map of the potential pollution source in combination with a geographic information system; and S6, verifying pollutant components and concentration distribution thereof, and confirming the accuracy of a traceability result. According to the invention, by combining a multi-pollutant traceability algorithm, an underground water flow model and a geographic information system technology, a pollutant migration path is accurately simulated and a pollution source spatial distribution map is generated, so that the precision and reliability of underground water pollution source traceability are greatly improved.

The invention relates to the technical field of digital twinning, in particular to a high-density urban ponding evolution and early warning method based on digital twinning. The method comprises the following steps: real-time ponding depth, real-time river water level, real-time meteorological conditions and real-time drainage pipe network water level conditions corresponding to a city are collected in real time through ponding depth, river water level, meteorological monitoring and drainage pipe network sensors installed in the city, digital twinborn construction is carried out, and an urban inland inundation digital twinborn model is generated; obtaining drainage pipe network distribution and carrying out drainage grid division to generate an urban drainage grid model; acquiring a historical ponding event rule, and performing ponding area prediction analysis and ponding evolution coupling analysis to generate an urban ponding evolution distribution field; performing ponding space-time evolution analysis and ponding early warning processing on the urban ponding evolution distribution field so as to execute corresponding urban ponding emergency response work. According to the invention, accurate ponding evolution prediction and effective early warning can be provided.

The invention relates to a real-time river water level monitoring and early warning method and system based on deep learning. The method comprises the following steps: acquiring a target watershed remote sensing image and real-time hydrological data of multiple monitoring points; performing water flow direction topology analysis on the remote sensing image of the target watershed, and constructing a water flow topology network; performing basin structure dynamic change feature analysis on the target basin remote sensing image to generate basin structure dynamic change data; carrying out topology situation evolution fitting on the water flow topology network based on the basin structure dynamic change data to obtain a dynamic topology evolution network; performing multi-scale time sequence trend evolution analysis on the multi-monitoring-point real-time hydrological data to generate water flow time sequence evolution characteristics; and evolution characteristic space position mapping is performed on the dynamic topology evolution network based on water flow time sequence evolution characteristics, and a three-dimensional hydrological evolution model is constructed. According to the invention, timely and accurate river water level monitoring and early warning are realized.

The invention provides an intelligent management method for natural resource engineering data, and relates to the technical field of data processing, and the method comprises the steps: inputting a time-space coupling model into real-time weather forecast data, simulating water distribution schemes under different rainfall scenes, automatically recognizing a river reach position of which the ecological flow is lower than a design threshold value, and carrying out the calculation of the river reach position. In combination with a historical water replenishing strategy case library, generating a multi-objective optimization scheduling scheme including a water replenishing time sequence, a water replenishing path and a water replenishing amount; three monitoring points are arranged at a downstream section of an ecological protection area, a flood control section and a canal head of an irrigation area in a drainage basin, and ecological flow, flood control section water level and canal water level data are monitored in real time respectively; and dynamically correcting the water supplementing time sequence, the water supplementing path and the water supplementing amount in the multi-objective optimization scheduling scheme to obtain a corrected scheduling scheme. According to the method, refinement and toughness of drainage basin water resource management can be improved.

The invention belongs to the technical field of road deformation monitoring, and discloses a road slope deformation monitoring system and method, and the system comprises a fixed point monitoring mechanism which monitors the displacement, strain, underground water level and inclination parameters of a slope in real time at key points and key positions of the road slope; the route planning module plans the flight route of the unmanned aerial vehicle; the cruise monitoring mechanism is used for monitoring the side slope in all directions; the weather data acquisition module is used for acquiring local weather data; the three-dimensional laser scanner data analysis module is used for identifying abnormal conditions on the side slope; the image analysis module is used for identifying abnormal conditions on the slope; the comprehensive evaluation module is used for comprehensively evaluating the stability of the slope by utilizing a comprehensive evaluation model; and the alarm module comprises an alarm. According to the invention, the fixed-point monitoring mechanism and the cruise monitoring mechanism are combined to monitor the slope in all directions, the comprehensive evaluation module fuses data of various monitoring means, and the comprehensive evaluation model is utilized to comprehensively evaluate the slope stability.

The invention relates to the technical field of water quality and water level monitoring, and discloses a water quality and water level monitoring method for a water conservancy project, which comprises the following steps: S1, arranging a multi-parameter water quality and water level monitoring sensor at a key position of the water conservancy project; s2, performing real-time processing on the data acquired by the multiple sensors based on a data fusion algorithm, wherein the data fusion algorithm is based on a Kalman filtering model; s3, acquiring external data through an environment sensor, and dynamically adjusting a water level and a water quality monitoring threshold value based on environment change; s4, predicting the water level and the water quality by using a deep learning algorithm based on LSTM (long short-term memory network); and S5, if the monitoring data exceed the dynamic threshold value, automatically triggering an early warning mechanism. By arranging the multi-parameter water quality sensor and the water level sensor at the key positions of the water conservancy project, the water quality and the water level can be comprehensively monitored, the coverage range and the precision of the monitoring system are greatly improved, and the complex monitoring requirements of multi-source pollution can be effectively met.

The invention relates to a hydropower station safety comprehensive management system based on a digital twinborn scene, which designs a hydropower station data resource coding system, establishes a hydropower engineering digital twinborn base, integrates all related geospatial data, basic data, monitoring data and business management data of a hydropower station, and constructs the hydropower station digital twinborn scene. Predicting displacement and deformation conditions of a building structure of the hydropower station and a change trend of important facility and equipment state indexes of the hydropower station, and predicting and pre-judging safety risks therein; the reservoir flow of the hydropower station, the upstream and downstream river section water level, the flow change and the power generation output and the power generation capacity of the hydropower station are forecasted or predicted, corresponding plans are provided for flood early warning or meteorological disaster early warning or water level over-limit early warning, and key links of the plans are simulated in combination with a simulation engine; and performing simulation calculation on different power generation and reservoir scheduling strategies to obtain an optimal scheduling scheme. According to the invention, the intelligent management of hydropower station engineering safety, scheduling safety and power generation safety is realized.

The invention provides a control node locating protecting method of undercutting channel segment water level lowering amplitude. The method comprises the steps that a lateral erosion zone and a deep erosion zone are divided; a target channel section is subjected to meshing, a plane two-dimension water flow mathematic model is established, parameter calibration and verification are carried out; a protection project is generalized to the plane two-dimension water flow mathematic model, the arranging zone and the width of the protecting project are determined; local gradient amplification and upstream water level amplification corresponding to each working condition are obtained, mesh sequences are analyzed respectively; key nodes or other nodes which have obvious influence are selected, for lateral erosion nodes, a hidden closure dam and a beach protection part are arranged on a river branch or a bottomland, and for deep erosion nodes, a bottom protecting band or a hidden closure dam are placed in a main groove. According to the method, nodes are divided into the lateral erosion nodes and the deep erosion nodes, protection part difference of the nodes in different types is provided, by comparing the efficiency of a local channel segment arranging protecting project, the positions of the nodes are accurately located, and the optimum efficiency of the protecting project is guaranteed powerfully.

The invention relates to the technical field of hydrological monitoring, in particular to a multi-satellite collaborative hydrological monitoring system. The method comprises the following steps that a water level height measurement module obtains radar pulse recovery time delay data through a height measurement satellite and calculates the water level height, abnormal points are removed to generate river water level data, a water remote sensing module collects river water images through a remote sensing satellite to extract water boundary features, water area change data are deduced, and the water level height measurement module calculates the water level height. The meteorological wind shear analysis module obtains river channel meteorological data through a meteorological satellite, microwave scattering measurement and wind speed inversion are carried out, wind-induced shear stress parameters are generated, and the flow estimation module carries out section dynamic analysis and estimates the water flow in combination with river channel water level and water area data. And the flow correction module corrects the river water flow based on the wind-induced shear stress parameter and carries out real-time monitoring, and data are synchronously uploaded to the control terminal, so that comprehensive dynamic monitoring of the hydrological state of the river is realized. According to the invention, a more efficient multi-satellite collaborative hydrological monitoring system is realized.

The invention relates to the technical field of environment evaluation, in particular to a comprehensive evaluation method and system for a mine geological environment. The method comprises the following steps that mine ore content data, underground water level data, soil acidity and alkalinity data and mine geological meteorological condition data are obtained and subjected to time sequence synchronization processing, and corresponding ore content data, underground water level data, soil acidity and alkalinity data and mine geological meteorological condition data in the same time sequence range are obtained; mine geologic structure exploration data are obtained, three-dimensional space structure modeling and environment risk factor monitoring of all sites are carried out, meanwhile, environment risk comprehensive evaluation analysis and environment risk management analysis are carried out on a three-dimensional space model of mine geologic structure distribution, and mine geologic environment risk management decision suggestions are generated. And executing a corresponding mine geological environment risk level management decision treatment plan. According to the invention, comprehensive dynamic monitoring of the geological environment of the mine can be realized on different time scales and spatial position dimensions.

The invention provides an underground water dynamic evolution prediction method, and belongs to the technical field of underground water prediction based on deep learning. Hydrological parameters and geographic position data of monitoring points are collected, and a regional hydrogeological input tensor is constructed; then establishing an initial finite element model to carry out space extrapolation and flow field completion on underground water level distribution; based on an initial finite element model structure, designing a global optimization algorithm based on target decomposition, carrying out real-time structure optimization on the finite element model, then simulating underground water evolution of a non-monitoring area through a finite element numerical solution, and generating multi-node physical consistency hydrological time series data after resolution is improved; and inputting the generated hydrological time series data into a designed perceptual water level prediction model, and outputting underground water level prediction results at multiple moments and multiple positions in the future and corresponding underground water level thermodynamic diagrams. According to the method, more accurate, continuous and interpretable high-precision prediction of the underground water system is realized, and reliable support is provided for scientific management of underground water resources.

The invention discloses a plain water network area runoff simulation method which comprises the following steps: acquiring and preprocessing multi-source data to obtain a time-space consistency hydrological data set; based on the time-space consistency hydrological data set, obtaining polder area water level data and exchange flow data by adopting an enhanced polder system dynamic model; carrying out runoff production calculation in the plain area by adopting an improved XAJ model; constructing a multi-scale river network topological structure, and executing multi-directional flow state identification and prediction of deep space-time fusion; and constructing a time-varying structure adaptive BP neural network model to realize runoff simulation of the plain water network area. According to the method, the technical problems of reverse flow phenomenon identification in a plain water network area, polder area water exchange threshold effect simulation, distribution node dynamic distribution coefficient optimization, temporary moving pump station influence correction and the like can be effectively solved.

The invention provides a water conservancy data acquisition supervision method and system based on big data analysis. The method comprises the following steps: firstly, obtaining dam body surface temperature field data, reservoir water level time sequence monitoring data and a dam body three-dimensional structure, and carrying out environmental radiation interference elimination processing on the temperature field data; secondly, extracting temperature fluctuation amplitude time sequence characteristics and water level change rate in the corrected temperature field data, and constructing a matrix reflecting correlation strength of the temperature fluctuation amplitude time sequence characteristics and the water level change rate through dynamic correlation analysis; and identifying temperature fluctuation abnormal points by using the matrix, and generating a seepage correlation map in combination with the water level change rate. And dividing seepage state categories according to the water level change rate, and generating a leakage risk probability distribution diagram by combining periodic trend prediction. And finally, fusing the graph with a dam body three-dimensional structure to generate positioning supervision information with a seepage abnormal identifier. The technical scheme provided by the invention can improve the efficiency and accuracy of water conservancy data acquisition supervision.

A porous media grouting test system and method taking temperature effects into consideration. The system comprises a porous media formation simulation model (1), a grouting system (2), a water level adjustment system, a formation temperature control system and a data analysis system, wherein the porous media formation simulation model (1) is used for simulating a porous media formation; the water level adjustment system and the formation temperature control system are used for simulating the conditions of different water saturation levels and different water temperatures and ground temperatures; and the data analysis system is used for comparing different time-series data collected by sensors such as a temperature sensor and a pressure sensor with data such as temperature data and pressure data that is obtained by means of coupled solving of a heat transfer equation and a momentum equation, so as to verify and analyze a grouting diffusion path. Free simulation of different water saturation levels is realized by means of a water level adjustment system, and simulation of different ground temperatures is realized by means of a formation temperature control system, thereby realizing the research on grouting diffusion under different water levels and different water temperatures and ground temperatures.

The invention relates to the technical field of underground drainage pipeline monitoring and hidden danger analysis, and provides an underground drainage pipeline hidden danger data analysis method based on big data, which comprises the following steps: acquiring data such as flow, water level, pressure and pipeline structure by using a multi-source sensor to form an original monitoring data set; preprocessing the data, extracting time domain, frequency domain and spatial topological features, and constructing a multi-dimensional feature vector; and inputting the feature vectors into a pre-trained hidden danger prediction model, and outputting hidden danger types and position coordinates. And constructing a spatio-temporal data analysis model based on the hidden danger position, generating a spatio-temporal correlation feature matrix, and performing dynamic risk assessment to obtain hidden danger development trend parameters. And the hidden danger information is mapped to a geographic information system, a three-dimensional visual analysis result is generated, and a graded early warning instruction is transmitted to a drainage pipe network operation and maintenance management system through a communication interface. The operation and maintenance management efficiency of the drainage pipeline can be improved, the hidden danger checking cost is reduced, and the safety and reliability of the drainage system are enhanced.

The invention relates to the technical field of data analysis, in particular to an intelligent hydrological data analysis method and system, and the method comprises the following steps: collecting water level, flow velocity and precipitation data, calculating the change rate of adjacent moments, marking hydrological parameter abrupt change points, carrying out the statistics of time intervals, predicting the duration of extreme events, and obtaining the distribution characteristics of the hydrological abrupt change points. According to the method, by analyzing the time interval and the duration time of the data points, the distribution characteristics of hydrological abrupt change can be mastered in the early stage, response can be made in advance, the propagation sequence and the diffusion rate of the abrupt change points in different river reaches can be analyzed, and accurate division of the influence range and the risk level of hydrological events is enhanced; effective management of hydrological event space risks is achieved, understanding of hydrological key influence factors is deepened by screening key variables and evaluating the evolution relation of the variables along with time, accuracy of short-term and long-term hydrological risk prediction is enhanced, and a scientific basis is provided for dynamic early warning of hydrological abnormal events.

The invention relates to the technical field of water level surveying devices, and discloses a hydrogeological multi-layer underground water level surveying device and a surveying method.The hydrogeological multi-layer underground water level surveying device comprises a support and a water sampling barrel, the support is provided with a winding mechanism, and the winding mechanism is used for adjusting the sampling height of the water sampling barrel; the upper part of one side of the water sample sampling barrel is communicated with a liquid inlet pipe, and the bottom of the water sample sampling barrel is fixedly connected with a balancing weight. In the sampling process, large-particle impurities in water are blocked through the filter screen, the impact force of water flow can be converted into the rotating force of the blades, the rotating shaft and the scraping rod, the function of automatically cleaning the impurities in the sampling process is achieved, and the rope winding condition caused by uncontrollable winding position is prevented through the adjusting mechanism; the dustproof mechanism prevents dust and stones from falling into the hydrological hole to affect sampling of a water sample in the surveying process, and the highest water level in the hydrological hole can be accurately known through the water level monitoring mechanism.

The invention relates to the technical field of geotechnical engineering digitization, in particular to a BIM (Building Information Modeling)-based three-dimensional geotechnical engineering investigation information model construction method. The construction method comprises the following steps: acquiring multidimensional geotechnical engineering investigation data, acquiring geotechnical engineering investigation data from multiple sources in real time, including geological drilling position coordinates, soil sample attributes, underground water level dynamic values and geological structure maps, and executing data synchronization operation in the acquisition process to ensure timestamp consistency. According to the method, the technical bottleneck of static physical process in traditional modeling is fundamentally broken through the synergistic effect of a multi-physics field coupled rock and soil information generation mechanism and the dynamic response architecture of the BIM framework.

The invention discloses a water level monitoring and management method based on multi-source information fusion, and relates to the technical field of water level monitoring and management. Comprising the following steps: acquiring a water level and water level related data by adopting a sensor, and acquiring surface feature information and meteorological data through GIS data; performing data cleaning and standardization on the collected data; a convolutional neural network is adopted to analyze infrared cloud picture data obtained by satellites to predict precipitation, a weighted average method is adopted to carry out multi-source information fusion, and water level prediction is carried out through a hydrological model; and performing real-time water level monitoring and water level management decision according to accurate water level data obtained by data fusion. Through the above steps, the system can provide a more comprehensive view angle for water level management by fusing multi-source information, and can more accurately predict the water level change trend, thereby optimizing the water resource management strategy and flood control measures.

The invention relates to a pier damage early warning analysis method under the action of flood, and solves the technical problems of high disaster recognition cost, low bridge damage recognition precision, untimely early warning and alarming and the like based on monitoring equipment in the existing concrete bridge flood-disaster-resistant technology. According to the method, by means of an established plastic damage simulation model, expensive sensors do not need to be arranged on a bridge structure, only basic information of the bridge structure and flood information such as the flow speed, the water level and the scouring depth are obtained, and damage and failure analysis of the bridge pier structure under the action of different influence factors by the flood action can be studied; structural damage state qualitative analysis and modal integrity damage index quantitative analysis are combined to determine bridge pier structure damage grades and damage failure judgment criteria, and early warning values corresponding to different damage grades of a bridge pier are inverted, so that accurate damage identification and rapid grading early warning of the bridge pier structure under the flood effect are realized. The flood disaster resistance of the bridge structure is improved, safe operation of the bridge is guaranteed, and the service life of the bridge is prolonged.

The invention provides a lake ecological water level calculation method, device and system and a storage medium, and relates to the technical field of water resource regulation and control. The method comprises the following steps: obtaining the water turbidity of a target lake and the biomass of all submerged plants existing in the target lake; the water depth required by growth is calculated; dividing the target lake into habitat units; calculating the actual water depth of each habitat unit; calculating the plant coverage by using the water depth required for growth and the actual water depth; and obtaining an ecological water level range and an annual water level regulation and control range based on the plant coverage and taking the ranges as lake ecological water level results. By constructing the growth-illumination model and the underwater illumination prediction model of the submerged plants, the monthly water level accurate regulation and control based on biological requirements are realized, and by subdividing habitat units and analyzing ecological requirements, the growth conditions of the plants can be optimized, the water quality and biological diversity of a lake ecosystem can be improved, and the water quality and the biological diversity of the lake ecosystem can be improved. And the scientificity and systematicness of lake management are enhanced.

The invention relates to the technical field of coupling simulation, in particular to a river and underground water coupling simulation parameter generation method and system. The method comprises the following steps: collecting remote sensing and ground sensing monitoring data, and generating a multi-source space-time initial data set through time mark calibration, space resampling and signal-to-noise ratio weighted fusion; extracting features between the water level of the river and the water level of the underground water based on the data set, constructing a river-underground water space-time topological structure and identifying an interaction mode, and forming a space-time coupling feature map through significance screening and periodic enhancement; performing parameter inversion by adopting a hydrodynamic equation, and generating a physical inversion parameter set in combination with sensitivity analysis and local optimization; a parallelization hydrological simulation framework is constructed, error-driven optimization is executed, and dynamic optimization parameters are obtained; river and underground water exchange simulation is executed, and finally, coupling simulation parameter set updating is achieved through sliding window deviation evaluation and incremental parameter correction. Therefore, the precision and operability of a coupling simulation result are improved.

The invention discloses a reservoir bank slope deformation monitoring and early warning processing method based on InSAR data, and relates to the technical field of reservoir bank slope deformation monitoring, and the method specifically comprises the following steps: obtaining slope deformation characteristic information influenced by sudden drop of a water level in real time under the condition that the water level of a reservoir is determined to drop sharply in a short time, and carrying out the analysis after obtaining, respectively generating a water level sudden drop deformation response coefficient and an instantaneous instability trend index; constructing an instantaneous instability risk assessment model for the generated water level sudden drop deformation response coefficient and the instantaneous instability trend index, and generating a slope instantaneous instability assessment coefficient; and performing evaluation analysis based on the slope instantaneous instability evaluation coefficient, and evaluating the slope instantaneous instability risk under the condition that the water level of the reservoir drastically drops within a short time. According to the method, the problem that the instantaneous instability risk of the side slope cannot be evaluated under the condition that the water level of the reservoir drops sharply within a short time in the existing InSAR monitoring technology is solved, and dynamic monitoring and early warning with high timeliness and accurate quantification are realized.

The invention provides an underground water source water supply safety assessment method and system, and relates to the technical field of water supply safety assessment. The method comprises the steps of obtaining a permeability distribution diagram, dividing grids and analyzing direction changes, constructing an edge set to extract a closed form to generate a partition layer, setting measuring points to collect water level data, evaluating a change consistency screening path, matching a boundary to judge a crossing condition, marking a sudden change position, recording an interference path and establishing a recognition list. According to the method, by comparing the consistency of the water level direction in unit time and the response fluctuation, the path line segment with the hydraulic coherence characteristic is identified, the depicting ability of the actual underground water flowing path in the non-uniform supply environment is improved, the path trend sudden change and boundary overlapping position is analyzed, the response identification of the structure interference action area is enhanced, and the accuracy of the structure interference action area is improved. A key section with water supply interruption or supply abnormity is positioned, and the response capability of actual hydrological and geological changes and the spatial fineness of evaluation and judgment are improved.

The invention relates to the technical field of hydrological monitoring, and discloses a river flow monitoring method and system fusing multi-source data, and the method comprises the steps: collecting river flow data and river water level data through employing a high-precision sensor group, and collecting river image data through employing an unmanned plane; filtering the river flow data and the river water level data by adopting a Kalman filtering method to obtain filtered river flow data and filtered river water level data; performing edge detection on the riverway image data by adopting a Canny edge detection method to obtain riverway boundary information; on the basis of the riverway boundary information, a cubic spline interpolation method is adopted for interpolation, a smooth first boundary line and a smooth second boundary line are obtained, and the actual flow of the riverway is calculated on the basis of the filtered riverway water level data and the riverway flow velocity data; judging whether the actual flow of the riverway is greater than a riverway flow preset value, and if yes, sending alarm information; the actual flow of the river channel is calculated by fusing the multi-source data, and the accuracy of monitoring the flow of the river channel is improved.

The invention discloses a reinforcement learning-based intelligent flood discharge scheduling method for a small reservoir. The method comprises the following steps of S1, forming a complete reservoir data set; s2, constructing an environment state vector required by reinforcement learning based on the reservoir data set; s3, generating an initial flood discharge scheduling strategy; s4, establishing an improved reinforcement learning model based on the environment state vector and the initial flood discharge scheduling strategy; s5, updating the strategy network in the improved reinforcement learning model to obtain an optimal flood discharge decision scheme; s6, gate operation is carried out according to the optimal flood discharge decision scheme, and the water level change of the small reservoir, the safety state of the downstream drainage basin and the ecological demand satisfaction degree after execution are monitored; and S7, inputting the feedback information into the improved reinforcement learning model again, and performing iterative updating and strategy correction on the improved reinforcement learning model in combination with the reservoir data set and the environment state vector. According to the invention, the efficiency and reliability of flood discharge scheduling of the small reservoir are obviously improved.

The invention relates to the technical field of side slope deformation prediction, and discloses a side slope three-dimensional deformation prediction method, which comprises the following steps of: 1, carrying out InSAR three-dimensional time sequence deformation inversion to generate three-dimensional time sequence deformation of a side slope high-coherence point; 2, decomposing the three-dimensional time sequence deformation by using a grey wolf optimization algorithm and a variational mode decomposition model to obtain a trend term, a periodic term and a residual error; 3, establishing a deep learning network prediction model considering the environmental impact factors of the region where the slope is located; and step 4, generating a slope time sequence deformation prediction value. The method comprises the following steps: resolving a three-dimensional deformation sequence by using a synthetic aperture radar time sequence image; constructing a variational mode signal decomposition model based on a grey wolf optimization algorithm; and establishing a deep learning network prediction model considering the environmental impact factors. By means of the method, the difficult problem of the hydropower station dam area slope three-dimensional real-time deformation prediction technology can be solved, environmental physical factors such as the reservoir water level, the gradient and the direction are fully considered, and rapid, real-time and accurate three-dimensional deformation prediction of the slope can be achieved.

The invention discloses a UE5-based dynamic simulation method for digital twin flood inundation of small and medium-sized watersheds. The method comprises the following steps: 1, constructing a two-dimensional hydrodynamic numerical model; step 2, creating a flood inundation simulation UE5 plug-in project; step 3, creating a flood role class; 4, constructing a method for drawing triangular mesh primitives of the flood model; 5, constructing a flood hydrological feature and flood flow state rendering method; and 6, realizing a dynamic simulation process of digital twinborn flood submerging. According to the invention, dynamic rendering and high-fidelity visualization of an ultra-large data volume flood model in a small and medium-sized basin digital twinning three-dimensional scene are realized, and multi-dimensional flood inundation numerical simulation results of water level, water depth, flow velocity, flow direction and the like and complex flood flow states of backflow, convergent flow, bifurcated flow, overflat flow, turbulent flow and the like are expressed; the authenticity and accuracy of flood inundation simulation are improved, and the flood risk assessment and flood control plan decision support capability of small and medium-sized drainage basins can be enhanced.