302 results about "Water dynamics" patented technology

The invention discloses an urban inland inundation situation deduction method based on fusion of mechanism knowledge and deep learning, and the method comprises the steps: collecting data, such as weather, terrain and historical disaster situations, and constructing a standardized database in combination with an inland inundation production and convergence mechanism; constructing an urban inland inundation numerical twinborn model, and optimizing hyper-parameters to improve prediction precision by adopting finite element calculation and a multi-scale coupling method based on hydrological and hydrodynamic models; constructing a causal association network by using the numerical twinborn data, and identifying a core affected area; designing a situation deduction algorithm of a space-time diagram neural network, capturing rainfall waterlogging dynamic characteristics, and realizing advanced early warning and accurate deduction; based on the waterlogging intensity and the exposure and vulnerability of the disaster-bearing body, a risk assessment system is constructed, the disaster diffusion trend and the disaster risk are analyzed, and support is provided for flood prevention decision and emergency management.

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 relates to the technical field of error correction, in particular to a water conservancy facility environment interference error correction method and device based on multi-dimensional data. The method comprises the following steps: collecting historical monitoring logs of water conservancy facilities, carrying out environmental disturbance event identification and multi-scale disturbance relevance mining, and constructing an environmental disturbance space-time relevance map; monitoring surrounding environment water monitoring parameters of the water conservancy facility, performing sequential response trend change analysis and dynamic response characteristic modeling, and constructing a facility environment personalized change response portrait; identifying a plurality of water body position monitoring data according to the surrounding environment water body monitoring parameters, and constructing a hydrodynamic full-field sensing graph; and performing nonlinear correlation analysis based on the hydrodynamic full-field perception graph and the personalized change response portrait of the facility environment, and constructing a digital twinborn model of the water conservancy facility under the water flowing condition. According to the invention, through dynamic error trend analysis and correction, the monitoring precision and monitoring stability of the water conservancy facility are improved.

The invention discloses a reservoir real-time scheduling simulation system based on a deep learning algorithm, and belongs to the technical field of intelligent water conservancy and artificial intelligence. Aiming at the problems of low prediction precision, poor multi-target coordination capability, weak coping uncertainty and the like of a traditional scheduling system, the system is designed to acquire hydrological, meteorological, water quality and engineering safety data through a multi-source data acquisition unit, and a multi-dimensional feature tensor is generated after preprocessing and fusion; the dispatching center server adopts an STGCN-LSTM mixed model to achieve high-precision prediction and uncertainty quantification of the water inflow process in the future 7-30 days, a reservoir hydrodynamic model and an MO-PPO algorithm are combined to complete multi-scene simulation and multi-target optimization decision, and an AF-DT mechanism dynamically adjusts the dispatching rule priority. According to the system, a sensing-decision-execution-feedback closed loop is constructed, the scheduling adaptive capacity and robustness are improved, the synergistic interaction of flood control, water supply, power generation and ecological protection is realized, and the system is suitable for real-time intelligent scheduling of large and medium reservoirs.

The invention provides a digital twin water conservancy hyper-fusion method for coupling multi-source data and an all-in-one machine, and relates to the technical field of intelligent water conservancy. By constructing a unified water conservancy spatio-temporal data link protocol, efficient fusion of multi-source heterogeneous data of hydrology, meteorology, engineering operation and the like is realized, and the problem of water conservancy system data islands is solved; a coupling distributed hydrological model and a hydrodynamic model are established, and real-time accurate simulation of the watershed hydrological process and the river channel hydrodynamic process is achieved; a multi-target dynamic weight reinforcement learning algorithm is adopted to optimize a water conservancy scheduling scheme, model parameters are dynamically corrected in real time through a time sequence error regression analysis model, and closed-loop adaptive optimization is achieved; according to the method, closed-loop cooperation of water conservancy data fusion, real-time accurate simulation, intelligent scheduling optimization and dynamic parameter self-correction is realized, and the real-time performance and accuracy of water conservancy intelligent decision making are remarkably improved.

The invention provides an optical complex water body suspended sediment monitoring method based on man-machine cooperation, and belongs to the technical field of remote sensing water environment monitoring. The method comprises the following steps: acquiring a multispectral remote sensing image of a target area, preprocessing the multispectral remote sensing image, and performing space-time fusion to obtain a spectral data set with high space-time resolution; carrying out manual labeling on the spectrum data set, constructing a suspended sediment concentration classification data set, and carrying out synthesis expansion on a minority class of samples to generate an equalization training set; training a suspended sediment concentration inversion model by using the equalized training set to obtain an initial suspended sediment concentration predicted value, and dynamically optimizing the spectral feature weight and the classification boundary of the suspended sediment concentration inversion model based on expert knowledge; and locally correcting the initial suspended sediment concentration predicted value and diffusing the initial suspended sediment concentration predicted value to a global range based on a hydrodynamic law and a space consistency constraint to obtain a global suspended sediment concentration predicted value. The method combines remote sensing image analysis, machine learning and expert knowledge to realize high-precision inversion of SSC.

The invention discloses a microplastic transport simulation and risk identification method based on multi-factor coupling, which comprises the following steps: by coupling a hydrodynamic model and a microplastic transport model, comprehensively considering multiple environmental factors such as tide, water level, runoff, wind speed, wind direction and the like, constructing a wave flow coupling microplastic migration and diffusion model suitable for complex hydrodynamic conditions of a Pearl River estuary; the model is calibrated and verified through measured data, and the precision of the model is evaluated by using indexes such as a Nash efficiency coefficient and a root-mean-square error; in combination with the simulation result and the spatial distribution characteristics of the typical sensitive area, representative sections and stations are selected, and annual-scale micro-plastic concentration change analysis is carried out; and further introducing an ecological risk index to carry out regional ecological risk grade identification, and determining a micro-plastic high-risk area and influence main control factors. The method has high regional adaptability and expansibility, and scientific support and technical reference can be provided for prevention and control of microplastic pollution of estuary and coastal water.

The invention discloses a three-dimensional visual management system and method for groundwater resources, and relates to the field of groundwater resource management and pollution control, and the system comprises a groundwater data obtaining module which is used for obtaining groundwater dynamic monitoring data of a target area in real time; the underground water environment digital twinborn model construction module is used for constructing an underground water environment digital twinborn model based on the underground water dynamic monitoring data; the underground water change and pollution control simulation module is used for carrying out numerical simulation on underground water resource and pollutant migration based on the underground water environment digital twinborn model, carrying out pollution control area division and formulating a corresponding underground water remediation scheme; and the decision support and knowledge management module is used for integrating groundwater dynamic monitoring data, the groundwater environment digital twinborn model, the divided pollution control area and the corresponding groundwater remediation scheme, and realizing data storage, three-dimensional display, data evaluation and user interaction. According to the invention, efficient management and pollution control of underground water resources can be realized.

The invention provides a highway tunnel decision-making maintenance system and a maintenance method thereof. The method comprises the steps of obtaining tunnel static and dynamic data and tunnel surrounding geological environment data; according to the geological environment data, carrying out geological risk analysis by adopting a geological statistical simulation algorithm and a time sequence decomposition algorithm to obtain a safety risk assessment result of the tunnel structure influenced by geological factors and an underground water dynamic change trend prediction result; according to the geological risk analysis result, fusing the tunnel technical condition data by adopting a heterogeneous integration model of a dynamic Bayesian network and an extreme gradient boosting tree, predicting the tunnel technical condition, and generating maintenance decision parameters; optimizing the maintenance decision parameters by adopting a cuckoo search algorithm so as to minimize the maintenance cost under the influence of the geological risk; and outputting decision results including the total maintenance cost distribution based on the geological risk, the technical condition improvement expectation, the rock stratum stability safety factor prediction value and the underground water seepage risk early warning level.

The invention discloses a water environment monitoring system and method based on big data analysis, and the system comprises a data collection and processing module which is responsible for collecting and processing original data related to a water environment, and transmits the processed data to a water flow and pollutant diffusion modeling module; and the water flow and pollutant diffusion modeling module is responsible for constructing a hydrodynamic model by utilizing a CFD simulation method based on the processed data, and predicting a pollutant diffusion trend through a convection-diffusion equation. According to the invention, the data analysis and prediction module deeply excavates potential information in acquired data and simulation results through a K-means clustering algorithm and an LSTM algorithm, and realizes accurate prediction of pollutant diffusion and water quality change time series. And the early warning and emergency response module can discover potential water quality pollution events in advance based on the prediction results and the real-time monitoring data, and give out early warning in time, so that the quick response capability of coping with the water quality pollution events is enhanced.

The invention discloses a tuna pond culture strategy optimization method and system based on meteorological influence analysis, and the method comprises the steps: collecting regional meteorological data and pond culture monitoring data, and constructing a multi-modal pond ecological feature vector; establishing a weather-water body dynamic coupling model by using a space-time diagram neural network, and generating water body situation response prediction information; a breeding regulation and control strategy is made based on the prediction information, and strategy self-adaptive optimization is achieved through real-time monitoring data; evaluating the anti-disaster capability of the tuna after the meteorological influence is finished, screening high-quality germplasm resources by combining genetic analysis, and generating an anti-disaster breeding scheme. According to the method, full-chain optimization from meteorological early warning to culture regulation and control to genetic breeding is achieved, and the climate toughness and economic benefits of tuna pond culture are comprehensively improved.

The invention provides a tidal flat evolution prediction method and system based on a hybrid model, and relates to the field of dynamic geomorphology and artificial intelligence cross technology, and the method comprises the steps: constructing a tidal flat erosion and deposition evolution database under different scenes of a target coastal zone; constructing a landform prediction model through an artificial intelligence algorithm based on the database, and taking hydrodynamic characteristic data as input and seabed erosion and deposition variation as output; hybrid simulation is executed based on the physical mechanism model and the landform prediction model, and long-duration evolution prediction is realized by updating terrain boundary conditions through loop iteration; and the configuration service application module is used for receiving user input parameters through the interactive interface and outputting a visual result. According to the method, traditional hydrodynamic force-sediment-landform coupling calculation is decoupled into a physical mechanism and AI coordinated chain process, the calculation complexity is remarkably reduced, offline rapid calculation business of tidal flat evolution is achieved, and real-time technical support is provided for coastal zone planning and disaster prevention decision making.

The invention relates to a peak shaving power station downstream non-safe navigable water area identification method and system and a medium, and the method comprises the steps: building a peak shaving power station downstream river channel one-dimensional and two-dimensional coupling hydrodynamic mathematical model; determining a combination mode of a proposed condition and a water flow boundary condition of a typical peak regulation process of the downstream of the hydropower station; simulating and calculating downstream on-way hydrodynamic conditions of the power station under different peak shaving processes; calculating a downstream non-safe navigation index of the peak regulation power station; and identifying the downstream non-safe navigable water area of the peak shaving power station. According to the method, on one hand, the change condition of downstream hydrodynamic force of the peak regulation power station can be analyzed, on the other hand, the influence condition of the peak regulation process on downstream navigation conditions can be recognized, non-safe navigation water areas of the peak regulation power station in different discharge flow processes can be judged, and a research basis is provided for hub power generation and navigation scheduling of mountain rivers.

The invention discloses a water environment treatment method and platform based on a water environment mathematical model and artificial intelligence, and belongs to the technical field of water environment treatment, and the method comprises the following steps: S1, obtaining water quality data including water depth, water level, flow velocity, flow direction, temperature, salinity, dissolved oxygen, pH value, chemical oxygen demand, ammonia nitrogen, total phosphorus and turbidity; s2, constructing a water environment mathematical model and an artificial intelligence model; the method specifically comprises the following steps: constructing a water environment mathematical model by using water quality data; the water environment mathematical model is used for simulating a hydrodynamic process and spatial and temporal distribution of water quality parameters; the method comprises the following steps: firstly, selecting a basic artificial intelligence model, then carrying out training learning on the artificial intelligence model by using water quality data, and finally obtaining a trained artificial intelligence model; s3, analyzing a water environment by using the artificial intelligence model to obtain spatial and temporal distribution characteristics and dominant factors of water quality parameters; and S4, making a water environment treatment scheme according to the spatial and temporal distribution characteristics of the water quality parameters and the dominant factors.

The invention discloses a canal system gate scheduling optimization method based on distributed model predictive control and a one-dimensional hydrodynamic model, and the method comprises the steps: collecting the hydrodynamic data, irrigation demands and canal system characteristics of a canal system, and taking the data as basic data; on the basis of the basic data, various disturbance conditions of the canal system are simulated, and corresponding hydrodynamic response data are obtained; constructing a one-dimensional hydrodynamic model based on the Saint-Venant equation; based on the one-dimensional hydrodynamic model and the hydrodynamic response data, constructing a distributed model prediction control architecture, and predicting the hydrodynamic data of the canal system; based on the prediction result, taking the minimum water level deviation and the minimum control cost as objective functions, and performing dynamic scheduling on the canal system; and performing feedback updating on a dynamic scheduling result of the channel system based on a dynamic rolling optimization mechanism. The method is suitable for multi-channel pool distributed water flow regulation and control, and particularly has important application value in efficient utilization of water resources in an irrigation area, flood scheduling and irrigation canal system optimization management.

The invention discloses a dynamic topology mapping and GPU heterogeneous flood coupling model real-time early warning method, and solves the problems of inflexible coupling of a one-dimensional model and a two-dimensional model, low calculation efficiency, poor dynamic response capability and the like in traditional flood simulation. A dynamic topology mapping mechanism is introduced to respond to emergencies such as dike burst and overflow in real time, the calculation efficiency is remarkably improved by utilizing a GPU heterogeneous parallel architecture, rapid and accurate simulation of the whole process of flood formation, evolution and submerging is achieved, reliable technical support is provided for flood control dispatching and emergency decision making, and the method is suitable for large-scale popularization and application. The method comprises the following steps: constructing a two-dimensional hydrodynamic model based on an unstructured grid, establishing a dynamic topology mapping mechanism and realizing GPU parallel numerical calculation; a two-dimensional model lateral connection coupling mechanism is constructed, dam overtopping flow is calculated in real time, and breach flow dynamic calculation of an improved DAMBRK method is carried out; multi-target parameter calibration, multi-dimensional model verification and one-two-dimensional model GPU collaborative parallel computing are realized.

The invention provides a dynamic simulation method and system for synchronous grouting of a shield tunnel under the action of dynamic water, and relates to the technical field of tunnel and underground engineering, and the method comprises the following steps: obtaining a shield tail gap geometric parameter, a stratum characteristic parameter, an underground water dynamic parameter, an initial slurry physical property parameter and a shield propulsion parameter of a to-be-constructed area; establishing a geometric model according to the shield tail gap geometric parameters and the shield propulsion parameters; setting dynamic boundary conditions and physical parameters according to the geometric model, the stratum characteristic parameters, the underground water dynamic parameters, the initial slurry physical parameters and the shield propulsion parameters to obtain a computational domain and a dynamic grid rule; performing simulation according to the computational domain and the dynamic grid rule to obtain slurry distribution data; obtaining an evaluation result according to the slurry distribution data; and performing parameter optimization according to an evaluation result to obtain optimized slurry physical property parameters. According to the method, the influence of flowing water on the slurry diffusion process is accurately quantified by constructing comparative simulation under the flowing water condition and the non-flowing water condition.

The invention relates to the field of water engineering, and discloses a method for installing and positioning a prefabricated part under a complex hydrological condition, which comprises the following steps of: arranging a sensor network on the surface of the part, and establishing an initial reconstruction model of strain-hydrodynamic load mapping based on finite element analysis; acquiring sensor strain data in real time, and synchronously acquiring component pose information of an external positioning system; real-time hydrodynamic disturbance is calculated through the initial model, and sensor health diagnosis is carried out in combination with a dynamic threshold value method; the extended Kalman filter fuses the pose and disturbance data, and model parameters are updated online to generate a calibration model; and on the basis of calibration model output and state estimation, a feedforward-feedback composite control instruction is generated to drive an execution mechanism to adjust the pose. Through an online calibration model and a composite control architecture, and in combination with optimal distribution of a redundant execution mechanism, real-time offset of hydrodynamic disturbance and millimeter-level pose regulation are realized, and the technical bottlenecks of low precision and poor adaptability of a traditional method are broken through.

The invention relates to the technical field of bamboo forest ecological environment monitoring, in particular to a bamboo forest ecological environment collaborative observation method based on multi-source Internet of Things sensing, and the method comprises the steps: synchronously collecting a multi-source collaborative observation parameter set of a bamboo forest slope through an Internet of Things sensor network, and then constructing a point-surface scale fusion bamboo forest moisture dynamic model; correcting evapotranspiration point cluster data by using a random forest gradient lifting algorithm to generate terrain weighted evapotranspiration, aggregating runoff data according to terrain weight to obtain a total amount of runoff sub-regions, then executing dynamic water balance constraint calculation, optimizing infiltration capacity in combination with a variation assimilation algorithm, redistributing infiltration capacity space proportion according to soil hydraulic conductivity when a residual error exceeds a threshold value, and calculating the total amount of the runoff sub-regions. Finally, according to the residual space distribution thermodynamic diagram, the evapotranspiration point cluster is migrated to the micro-topography representative area, and observation network adaptive optimization is achieved, the problems that in the prior art, the data scale is disjointed, the observation precision is insufficient, and the network is difficult to adapt to change are solved, and the bamboo forest ecological observation precision and reliability are improved.

According to the ship ballast water dynamic adjustment method, device and equipment and the storage medium, the water level data set, the attitude data set and the water pressure data set are obtained through the sensor, then whether the ship is in the balance state or not is determined according to the water level data set and the attitude data set, and when the ship is in the non-balance state, the ship ballast water dynamic adjustment is performed. If yes, determining a water volume adjustment scheme through a ballast water allocation optimization model; and then, according to the water volume adjustment scheme, a water pump operation instruction and a valve opening and closing instruction are generated, so that the ship recovers the balance state. According to the invention, the response time of ballast water regulation can be obviously shortened, and the flexibility and operation efficiency of the system are improved; the intelligent central control unit can be utilized to realize automatic operation, human intervention is reduced, and the operation precision is improved; and a ballast water allocation scheme can be flexibly adjusted to cope with the change of the ship state in real time.

The invention discloses a wave-current combined simulation system and method in a low-pressure environment, and relates to the technical field of underwater vehicle hydrodynamic model tests. The defects that in the prior art, sealing and strength are difficult to guarantee in a low-air-pressure environment, and accurate flow velocity and shear gradient control of a multi-layer flow channel cannot be achieved are overcome. According to the technical scheme, the device comprises a low-pressure pool, a plurality of layers of layered water inlet galleries, a plurality of layers of layered water outlet galleries, a rectifying wall, a rectifying baffle, a flow guide grid, a wave absorbing bank, an in-cabin rocking plate type wave maker, a plurality of bottom flow making pump flow making systems, an electric butterfly valve, a high-voltage frequency conversion cabinet, a three-phase asynchronous motor, a gear box, an impeller shaft system and the like. All the devices work cooperatively, and accurate coupling simulation of a multi-layer flow field and high sea condition waves under low air pressure is achieved. The device is suitable for wave-current combined hydrodynamic characteristic simulation and test research of deep-sea navigation bodies and ocean engineering equipment in a low-pressure environment.

The invention relates to a shallow water dynamic process simulation method based on a local time step length, and the method comprises the steps: dividing a target region into a plurality of grids based on a shallow water dynamic process model, the target region comprising an ocean region and a land region adjacent to the ocean region; at least dividing the plurality of grids into a first grid set and a second grid set; determining a first time step length corresponding to the first grid set according to the first grid set; determining a second time step length corresponding to the second grid set according to the second grid set; determining a first simulation result of the shallow water dynamic process according to the first time step length and the second time step length; wherein the first grid set comprises a plurality of first grids, and the second grid set comprises a plurality of second grids; the first time step length is larger than the second time step length. The efficiency of the shallow water dynamic process simulation method is improved by respectively determining appropriate local time steps according to the precision requirements of different grid sets.

The invention discloses a reservoir ecological flow configuration method based on multi-section water transfer and multi-target fish collaborative protection, which comprises the following steps: S1, determining a hydrological sensitive area and an ecological sensitive area based on water transfer influence constraint and fish resource distribution data, superposing the hydrological sensitive area and the ecological sensitive area to construct a habitat evaluation model, determining a typical fish key habitat, and constructing a reservoir ecological flow configuration model; determining a target spawning site; s2, integrating the two-dimensional hydrodynamic model and the fish habitat model, calculating habitat hydraulic power demands and flow pulse demands of different fishes in the spawning period, constructing an ecological water demand process in the spawning period, and calculating basic hydrological demands of ecological base flow for supplementing a non-spawning period; and S3, carrying out ecological water demand coupling on a plurality of spawning sites with overlapped spawning periods, and determining a reservoir ecological flow collaborative configuration scheme. According to the method, on the basis of the particularity of multi-section water transfer disturbance and multi-target collaborative protection of a water source area of western-line engineering, the ecological water demand of typical fishes is researched, and a reservoir ecological flow configuration scheme is determined.

The invention discloses a device for simulating influence of ditch cleaning ice cover evolution on hydrodynamic parameters and an application method thereof, and relates to the technical field of ice water dynamics and hydraulic engineering experiments. The device comprises a low-level water tank, a high-level water tank, a centrifugal pump, a flow valve, a water tank, a steady-flow perforated plate, a ditch cleaning ice cover simulation device, a first water level control grid plate, a second water level control grid plate and a flow field measurement system. According to the invention, three key parameters of ditch cleaning length, ice cover submerging water depth and roughness of the bottom of the ice cover are independently regulated and controlled, and non-contact high-precision measurement is carried out by means of a PIV technology, so that systematic and refined research on hydrodynamic parameters of an ice cover ditch cleaning area is realized. According to the method, researchers can safely and systematically research the influence of a single variable on the ice cover ditch cleaning water power at low cost, and the fundamental bottleneck of traditional field measurement in the research is solved.

The invention discloses a flood process runoff monitoring method coupled with satellite remote sensing and hydrodynamics. The flood process runoff monitoring method comprises the following steps that unmanned aerial vehicle complete river topography measurement is carried out; river upstream and downstream section hydraulic parameters are obtained; constructing a digital river channel section; batch extraction of satellite remote sensing water surface width; flow calculation parameters are obtained based on the digital river section and the water surface width data; performing remote sensing inversion on the roughness of the complete riverway; and section flow monitoring and historical data inversion. A section of complete river channel is determined as a basic research unit, flow calculation precision is remarkably improved through multi-section synchronous monitoring in combination with river channel slope and roughness change dynamically captured in real time, the flowing process of water flow in the complete river channel is finely described, and the flow calculation precision is improved. The method provides long-sequence and high-reliability flow data for parameter calibration and result verification of a hydrological model, is particularly suitable for describing the flow condition when flood comes, and enables the flow condition to be closer to reality.

The invention discloses a steady-state boundary convection-dispersion model parameter acquisition method based on a variable separation method, and the method comprises the steps: constructing a convection-dispersion mathematical model under a one-dimensional finite-scale steady-state boundary condition, and carrying out the dimensionless processing of an original mathematical model through a dimensionless factor; secondly, analyzing and solving the new mathematical model after nondimensionalization by adopting a separation variable method, systematically deriving an analytical solution expression of a one-dimensional steady-state boundary convection-dispersion model in combination with a groundwater dynamic theory and a solute transport mechanism, and constructing a standard curve capable of reflecting different permeability parameters and solute transport related parameters; an indoor one-dimensional convection-dispersion test is carried out, water level and solute concentration measured data at different observation points are obtained, and permeability parameters and solute transport related parameters of a test medium are efficiently obtained through wiring. According to the method, the accuracy and adaptability of the convection-dispersion model in the aspect of parameter identification under the limited scale condition are enhanced; and operation is simple, parameter identification quantity is large, and precision is high.

The invention discloses a high-precision amphibious vehicle water motion simulation platform construction method and system, and relates to the technical field of vehicle simulation, and the method comprises the steps: obtaining the propulsion system configuration and parameters of an amphibious vehicle, and calculating a thrust database through the computational fluid mechanics principle; based on rigid body and fluid dynamics theories, a water dynamics model and an environment disturbance model are established. A high-precision water dynamics simulation program code is compiled and optimized, and an amphibious vehicle water motion simulation platform is developed in combination with an unreal engine. Based on the method, a high-precision amphibious vehicle water dynamics simulation platform can be established.

The invention provides a historical flood inundation dynamic reconstruction method and system based on deep learning, and relates to the technical field of flood simulation, and the method comprises the steps: obtaining a standardized historical flood data set; positioning P terrain cavity deficiency; matching and multiplexing P adaptive filling models in a terrain filling model library according to the P missing feature vectors; carrying out multi-thread parallelization of P terrain cavity deletion; adopting the P corrected terrain structures to carry out pixel-level replacement of P terrain cavity missing to obtain corrected DEM data; and after a two-dimensional hydrodynamic model is constructed based on the corrected DEM data, a hydrodynamic boundary control set is set to drive the two-dimensional hydrodynamic model to execute flood simulation, and a historical flood dynamic evolution process is output. According to the flood simulation method and device, the technical problem that the flood dynamic reconstruction accuracy is affected due to the fact that the flood simulation accuracy is limited due to the fact that topographic data are incomplete and the simulation generalization ability in different areas is insufficient in the prior art is solved, and the flood simulation accuracy is improved.

The invention provides an intelligent lake and reservoir water quality forecasting method and system based on physical constraint guidance and a medium. The method comprises the following steps: constructing and verifying a hydrodynamic water quality mechanism model; constructing a deep learning water quality intelligent model: preprocessing the historical hydrological water quality monitoring data to obtain a Transform-based deep learning water quality intelligent model and an input data set; constructing a physical constraint loss function based on a simulation result of the hydrodynamic water quality mechanism model subjected to calibration verification; using an input data set as a training set, taking minimization of a total loss function as a target, training the deep learning water quality intelligent model, and using the trained model for lake and reservoir water quality forecasting. According to the method, the physical mechanism is deeply embedded into the training process of the data-driven model in a differential constraint form, so that the prediction result strictly follows the physical law of pollutant migration and transformation while conforming to observation data, and the problem that the prediction result of a pure data-driven model violates physical common knowledge is effectively solved.

The invention discloses a flood inundation range dynamic simulation method and system based on multi-source data fusion. The method comprises the following steps: S1, collecting multi-source original data of a to-be-simulated target drainage basin; s2, extracting an initial submerging range grid according to the multi-source original data; s3, according to the initial submerging range grid, generating a river channel-beach area coupled section terrain file; s4, obtaining the dynamic water level process of each downstream section according to the section topographic file and the weather forecast rainfall field; and S5, obtaining a dynamic simulation result of the flood inundation range according to the dynamic water level process. According to the invention, through continuous driving of the distributed hydrological model and the one-dimensional hydrodynamic model, full-chain simulation from rainfall forecast to submerging dynamic state is realized, so that the submerging range can be updated in real time along with meteorological conditions and riverway water levels.