3185 results about "Stream flow" patented technology

The invention discloses a river flow missing data reconstruction method, which comprises the following steps of S1, constructing a river network topological structure, and quantifying hydraulic correlation; s2, spatio-temporal feature fusion and multi-source information extraction; s3, performing multi-task cooperative flow reconstruction and confidence coefficient prediction; s4, dynamic weighting and result correction of meteorological factors; and S5, performing anomaly detection and model dynamic updating. According to the method, a river flow missing data reconstruction method is set, the steps are mutually fused and used, and topology-aware space-time diagram convolution is performed: a river network topology structure is encoded into a weighted adjacency matrix for the first time, space correlation features are extracted through a diagram convolution network, and the problem that a traditional method ignores hydraulic connection is solved; a multi-task collaborative learning mechanism: synchronously outputting a flow reconstruction value and confidence, combining topological smooth constraints, and realizing reconstruction reliability quantification while ensuring precision; and meteorological dynamic weighted correction: dynamically adjusting the node weight based on the real-time rainfall intensity, and accurately adapting to the nonlinear response of the water flow in the heavy rainfall period.

The invention discloses a reservoir water regimen analysis method and system based on artificial intelligence, and the method comprises the steps: collecting original signals from multi-source monitoring indexes, such as water level, flow, rainfall and water quality, carrying out the standardized conversion through employing distributed calculation nodes, and forming a unified multi-source data set; based on this, using a feature extraction network to fuse upstream rainfall and reservoir flow, extracting space-time correlation features, and determining a short-term water level change trend; historical water quality abnormal data are integrated through a sequence prediction network, a time sequence is modeled, and potential pollution risks are judged; when the risk exceeds a threshold value, dynamically adjusting the weight of the prediction model, and generating an optimized water regimen simulation scene; finally, resource scheduling logic is fused, multi-scene risks are evaluated, and an optimization management strategy is output. Through deep fusion of spatial-temporal feature extraction and dynamic prediction, accurate water regimen prediction and flood control water supply decision support are realized, and the water resource management efficiency and the pollution prevention and control capability are improved.

The invention relates to the technical field of intelligent water affair and urban water supply system informatization, in particular to a water supply pipe network hydraulic model calibration and leakage locating method and system, and the method comprises the steps: obtaining the pressure and flow data of a plurality of monitoring points in a pipe network in real time; taking the model as a boundary condition to drive a hydraulic model to carry out real-time simulation, and calculating a theoretical value; calculating a residual error between a theoretical value and an actual value of the monitoring point; judging a triggering model calibration event or a leakage suspicion event based on a residual error abnormal mode; if calibration is triggered, inverting and updating global parameters of the model through an optimization algorithm to realize self-calibration; if leakage is triggered, a suspected area is determined by combining pressure space distribution analysis, and a leakage pipe section is accurately positioned through analog simulation and correlation analysis. Through closed-loop feedback of real-time data and the model, the model can adapt to changes of a pipe network system, dynamic self-calibration of the water supply pipe network hydraulic model is achieved, and the problem of precision attenuation of a traditional static model is solved.

The invention relates to the technical field of water conservancy management, and discloses a water conservancy dynamic decision-making method and system based on digital twinning and multi-source heterogeneous data, and the method comprises the steps: carrying out the real-time information capturing of a target water conservancy system, and generating a system operation information scheduling matrix based on a grid geographic model and a time dislocation mark; performing hierarchical slicing on the system operation information scheduling matrix according to a multi-scale time window to form a multi-channel flow framework of regional hydrological dynamic behaviors; analyzing the evolution trends of the water level, the flow and the water quality by using a multi-channel flowing framework and a dynamic fusion analysis operator; dividing a river reach, a reservoir and a regulation and control facility corresponding to the potential risk event as candidate scheduling areas; and based on the local risk coupling network, dynamically optimizing a scheduling strategy, a pump gate operation sequence and a data acquisition frequency, and generating a real-time scheduling and emergency response scheme of the candidate region. The method has the advantage of improving flood early warning accuracy and water supply scheduling efficiency.

The invention discloses a hydraulic engineering construction operation parameter optimization and data management method and system. The method comprises the steps of 1, multi-source data access and vectorization; step 2, time sequence feature extraction and multi-modal fusion; step 3, identifying interpretable influence factors; 4, performing multi-task dynamic anomaly prediction; 5, risk weighted fusion and uncertainty quantification are carried out; 6, carrying out digital twinborn simulation verification; step 7, governance strategy optimization and security auditing; and step 8, feedback acquisition and model adaptive updating. The method has the advantages that multi-modal unified representation is constructed by fusing structured data such as water level and flow with unstructured information such as meteorological images and operation and maintenance logs, time sequence feature extraction is carried out in combination with the space-time diagram neural network, the dynamic sensing and prediction capability of the complex hydrological process is remarkably improved, and the method is suitable for being popularized and applied. According to the invention, the conversion from static threshold alarm to multi-task and prospective abnormal early warning is realized, and the adaptability of the system to multiple scenes is enhanced.

The invention relates to the technical field of water supply pipeline detection, and discloses an underground water supply pipeline health grade evaluation and risk prediction method, which comprises the following steps: sensor arrangement: arranging a flow sensor, a pressure sensor and a sonic sensor at key positions of an underground water supply pipeline; and data acquisition: acquiring signals of the sensor in real time through a data acquisition module, wherein the signals comprise flow, pressure and sound wave signals. Preprocessing the data: carrying out preprocessing such as denoising and normalization on the collected signals; and multi-source data fusion: inputting flow, pressure and sound wave signals into a deep neural network model, and performing feature extraction and fusion analysis. And health level assessment: assessing the health level of the pipeline based on the output result of the deep neural network model. And risk prediction: predicting abnormal working conditions possibly occurring in the future and risk levels of the abnormal working conditions by analyzing the current pipeline state and historical data. And abnormal positioning: accurately positioning an abnormal position in combination with the propagation time of the sensor signal and a positioning model of the deep neural network.

The invention relates to the technical field of water supply pipe network monitoring and computers, and discloses a precise water leakage positioning method and system based on water supply pipe network leakage monitoring, and the method comprises the steps: obtaining pipe network time sequence data and a topological structure, and constructing a structured model; performing multi-source data cross validation according to the model, and determining a deviation source node; historical data of the deviation source node are extracted for simulation, and a confirmation result of the leakage event is obtained; analyzing the space-time gradient change of the upstream pipeline flow, and accurately positioning the coordinates of the water leakage point; the water leakage point coordinate enhancement model is fed back, consistency verification is carried out, and accurate coordinates are obtained; and integrating physical details of the pipe network to generate a final positioning result. By establishing a set of intelligent analysis closed loop from data fusion positioning to feedback verification, the problem of insufficient water leakage point positioning accuracy in the prior art is solved.

The invention discloses a method for evaluating the influence of reservoir-water transfer project combined regulation on downstream ecological flow. The method comprises the following steps: step 1, collecting data of a research area; 2, constructing a water transfer project water source area natural water circulation model WEP-NHA; step 3, constructing a natural-social binary water circulation coupling model WEP-HA; 4, simulating the runoff of the water source area by using a WEP-HA model; 5, the system analyzes the change degree of the key control section water quantity and the ecological flow guarantee rate of the water source area under the condition that the reservoir and the water transfer project are overlapped. According to the method, system simulation of disturbance response of a complex system in a water source area can be achieved, the comprehensive influence of a complex water conservancy project system on water resources and the ecological environment is effectively revealed, high adaptability and predictability are achieved, the problem of regulation and storage effect simulation of a reservoir without data or with little data is effectively solved, and the method is suitable for popularization and application. And decision support is provided for scientifically formulating the water transfer scale and guaranteeing the ecological flow.

The invention discloses a source network, plant, river and lake integrated model simulation method and device, a medium and equipment in the technical field of regional water environment pollution treatment. The method comprises the following steps: inputting a boundary condition and an initial condition of a first model into a pre-constructed surface runoff production and convergence model of a target area, and outputting a flow rate of surface runoff and a water quality index time sequence; inputting the boundary condition and the initial condition of the second model into a pre-constructed pipe network model of a target area, and outputting a flow and water quality index time sequence of key nodes in a pipe network system; and inputting the boundary condition and the initial condition of the third model into a pre-constructed riverway and lake grid model of a target area, and simulating the river and lake hydrodynamics and water quality change process of the target area. According to the invention, coupling simulation of surface runoff, pipe networks, rivers and lakes is realized, and a propagation path and an influence mechanism of pollutants are comprehensively reflected; and high precision and reliability of the model are ensured through parameter calibration.

The invention provides an irrigation district reservoir and canal system water resource joint optimization scheduling method and device based on partition decoupling, and the method comprises the steps: obtaining the topological information of a target irrigation district reservoir and canal system, carrying out the irrigation division, and determining the water supply and demand of a future time period; based on the topological information, aggregating and generalizing each reservoir and channel in the irrigation area reservoir and channel system into a plurality of aggregated reservoirs and aggregated channel systems according to a coupling relationship, and dividing the target irrigation area reservoir and channel system into a plurality of subareas; channel water distribution flow feasible regions of different types of aggregation channel systems are deduced step by step from bottom to top from the last-stage channel; a double-layer water resource joint optimization scheduling model is established, the upper layer takes the maximum sum of the ratio of the water supply amount to the water demand amount of each subarea as the optimization target, and the lower layer takes the shortest water delivery time and the minimum water delivery loss of each subarea as the optimization target; the model is solved, the optimal water supply amount of each partition and the flow of the reservoir and the channel of each partition are obtained, and a scheduling optimization scheme is obtained. The method can maximize the water-saving benefit of the irrigated area.

The invention discloses an integrated intelligent management and control method and system for underground water pumping and injection based on the Internet of Things, and the method comprises the steps: carrying out the geological investigation of a target region, constructing a three-dimensional geological model, and planning the layout of a pumping and injection well group and a sensor network according to the three-dimensional geological model; deploying a monitoring network and collecting data based on the layout scheme, and fusing a three-dimensional geologic model to construct a polluted site digital twinborn body; groundwater situation data are extracted through the digital twinborn body, a pollutant migration path and a water level dynamic state are predicted by using an LSTM model, and pollution scene simulation information corrected by geologic features is output; by taking the simulation information as input and coupling geological parameters as constraints, generating a pumping and injection well group cooperative control strategy set by adopting a BLMFO double-layer multi-objective optimization algorithm; and finally, a control instruction is executed, the real-time situation is monitored in the repairing process, strategy change suggestions including the flow adjustment amplitude, the agent optimization scheme and equipment operation parameter correction are judged and pushed, the repairing efficiency is improved, and the method adapts to the complex geological environment.

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 discloses a hydrological flow monitoring method and a hydrological flow monitoring system based on a dynamic topology adaptive technology. The hydrological flow monitoring method comprises the following steps: performing hydrological flow monitoring in real time by adopting a trained online flow measurement model; the method comprises the following steps: firstly, acquiring actually measured hydrological element data in the same period of an online flow measurement data sequence, and establishing a river section hydrological element information base; then based on edge computing gateway equipment, flow velocity analysis is carried out by adopting a dynamic topology adaptive technology, parameter calibration is carried out on an online flow measurement model, and the average flow of a test section is calculated; performing comparative measurement analysis and precision evaluation on the flow online monitoring result based on the edge computing gateway equipment; and finally, outputting the finally trained online flow measurement model. According to the method, the applicability of the online flow measurement equipment under different hydraulic conditions and water flow characteristics can be further explored, and a key technical support is provided for application of flood control early warning and other aging sensitive scenes and construction of a cloud-side-end collaborative distributed hydrological monitoring network.

The invention discloses an intelligent early warning method and system for snow-melting flood. The method comprises the following steps: constructing digital twin integrating snow-melting confluence and hydrological hydrodynamic force; collecting multi-source monitoring information, and forming driving data through quality control and spatio-temporal interpolation; driving data are input into digital twinning, and model parameters and states are updated through data assimilation; simulating snow-melting runoff, water level and flow to obtain snow-melting flood probability prediction; the method comprises the following steps of: solving a river reservoir gate pump scheduling scheme by using a multi-objective evolutionary algorithm by taking reservoir outlet flow, gate opening and pump station starting and stopping as decision variables, calculating a water level, flow and a submerging range in digital twinning, and selecting a target scheme according to an evaluation rule to generate a scheduling instruction and graded early warning information; monitoring data is collected during scheduling execution and compared with probability prediction, and when the deviation exceeds a threshold value, data assimilation and scheduling scheme updating are triggered. According to the invention, the snow-melting flood forecasting precision and flood control scheduling collaboration are improved.

The invention discloses an intelligent underground drainage pipe network management method and system, and relates to the field of drainage pipe network management, and the method comprises the steps: obtaining the real-time liquid level and real-time flow of an upstream monitoring point of a target pipe section; dividing the monitoring data into water rising time period data and water recession time period data; two-way resistance characteristic analysis is conducted on the liquid level-flow model, resistance release characteristics and resistance recovery characteristics are recognized, and the resistance release characteristics are that when the liquid level at the water rising time period or the water rising and recession junction reaches a first threshold value, the flow is sharply increased, and the liquid level is stagnated in rising amplitude or suddenly changed in falling; the resistance recovery characteristic is that the liquid level rebounds and rises when the flow is reduced to a second threshold value in the water recession period; when the two types of features are detected at the same time, it is preliminarily judged that soft intermittent blockage abnormity exists in the target pipe section; and generating a flexible dredging management work order based on a judgment result, and updating an asset state mark in a pipe network operation and maintenance database. The method solves the problem that it is difficult to timely and accurately identify the soft intermittent blockage abnormity and carry out linkage operation and maintenance disposal.

The invention provides a hydrological forecasting method and system based on an adaptive correction chain, and relates to the field of data processing, and the method comprises the steps: generating a first reservoir inflow forecasting result according to a rainfall deviation traceability-dynamic correction chain and rainfall observation data; multi-dimensional features of the current scene are determined, and a second reservoir inflow forecasting result is generated according to the historical similar sample matching-rule application chain and the multi-dimensional features of the current scene; according to the confluence and production knowledge-threshold constraint chain, the underlying surface condition, the rainfall spatial distribution and the basin state, a third reservoir inflow forecasting result is generated; and determining the dynamic weights of the first reservoir inflow forecasting result, the second reservoir inflow forecasting result and the third reservoir inflow forecasting result, and generating a final reservoir inflow forecasting result, thereby improving the accuracy of the reservoir inflow forecasting result.

The invention provides a reservoir pressure salinity scheduling method based on a physical information neural network (PINN). The reservoir pressure salinity scheduling method comprises the following steps: Step 1, salinity prediction based on a physical information neural network (PINN) model; the method comprises the following steps: in a PINN model framework, embedding a physical law of salinity conservation into a multi-layer perceptron (MLP) artificial neural network for training so as to carry out salinity prediction; step 2, establishing an estuary water-salt model based on a three-dimensional ocean numerical FVCOM model; step 3, carrying out upstream reservoir salty water pressing and light water supplementing emergency scheduling based on salinity forecast; comprising the following steps: Step3.1, establishing a multi-objective function; and Step3.2, solving a scheduling model. According to the method, the salinity momentum conservation constraint can be considered, the salinity prediction accuracy under the influence of different upstream flows and downstream tidal ranges can be improved, and the emergency scheduling of the reservoir for the salt tide invasion of the estuary drinking water source can be carried out in combination with the scheduling model, so that the water supply safety is ensured.

The invention provides a pressure difference bypass device for a water distributing and collecting device of a variable-flow liquid cooling system, and relates to the field of variable-flow liquid cooling systems, the pressure difference bypass device comprises a main water inlet collecting pipe, a water distributing device main body, a main input pipe and a connecting pipe, the main water inlet collecting pipe is communicated with the water segregator main body through the connecting pipe, and the main input pipe is connected with the main water inlet collecting pipe. On the basis of real-time data of the pressure difference detector and the backflow flow speed detector, the central control unit dynamically adjusts the opening degree of the intelligent flow speed adjusting valve through a PID algorithm, so that the flow of a main loop is accurately matched with the requirements of branches, and redundant energy consumption of a traditional constant flow system is eliminated. And a system health degree evaluation model is constructed, when the branch flow is lower than a preset safety threshold value, the stabilized pressure pump is triggered to be shut down for protection, and the cavitation risk is avoided.

The invention relates to a reservoir dispatching management method and system based on digital twinning, and the method comprises the following steps: carrying out the real-time parameter collection of a target reservoir, and obtaining a reservoir characteristic parameter matrix; performing three-dimensional space modeling based on the reservoir characteristic parameter matrix and the reservoir hydrogeological environment in the target reservoir to obtain a reservoir digital twinborn model; performing drainage basin rainfall-runoff dynamic response analysis on the reservoir digital twin model to obtain a drainage basin hydrological response characteristic curve group; performing prospective water balance calculation on the watershed hydrological response characteristic curve group to obtain a multi-period reservoir flow prediction sequence; and formulating an optimal scheduling instruction set of the target reservoir based on the multi-period reservoir inflow prediction sequence, and regulating and controlling a reservoir gate control system in the target reservoir based on the optimal scheduling instruction set. And the method is difficult to adapt to hydro meteorological conditions and multi-target scheduling requirements which change in real time.

The invention relates to a safety protection method based on dynamic monitoring of circulating flow of heat source equipment. The method comprises the following steps: collecting pipeline pressure data, circulating water flow data and circulating water temperature data in a circulating pipeline of heat source equipment through a multi-source sensor; inputting the circulation pipeline data into a preset heat source equipment state model to perform working condition evaluation so as to generate an equipment working condition report; performing fault feature extraction on the equipment working condition report, and identifying an abnormal operation mode according to the extracted fault features; in response to the identified abnormal operation mode, determining a fault type matched with the abnormal operation mode according to a preset fault type library; and based on the determined fault type, generating a corresponding control instruction by using a preset risk-instruction mapping rule. According to the invention, real-time monitoring of the operation state of the heat source equipment, automatic identification of abnormal modes and active safety protection control are realized.

This invention relates to the field of hydraulic engineering, and more particularly to a method for safety assessment and optimization design of large-flow aqueduct structures. The method includes: collecting displacement, strain, and temperature monitoring sequences based on a triple probe, completing grouping, coordinate and time registration, and establishing a monitoring baseline; constructing a spatial model including support nonlinearity and fluid-structure boundary conditions, applying loading conditions, and obtaining response predictions; aligning monitoring and prediction in time and location, performing hierarchical Bayesian filtering inversion, and obtaining parameter posteriors and structural health; under the integration of in-service monitoring and accelerated degradation characteristics, using multi-task learning to generate material evolution and lifespan intervals, and automatically generating and simulating optimization schemes under reliability and maintainability constraints. This application forms a closed loop from assessment to design, effectively enhancing data comparability, traceability of uncertain information, and adaptability of the scheme to engineering projects.

The invention provides a detection method and system for an automatic drain valve, and relates to the technical field of equipment testing. The method comprises the following steps: collecting working data of a drain valve to be detected; determining a flow peak change trend and a drainage efficiency attenuation degree based on flow data of continuous multiple drainage records, and generating an impurity deposition index; generating an impurity stripping index based on the instantaneous change rate of the flow velocity data and the variable quantity of the flow data, and determining a first impurity deposition degree in combination with an impurity deposition index; determining a vibration anomaly factor and an acoustic anomaly factor based on the vibration data and the acoustic data, and determining an impurity anomaly score in combination with the first impurity deposition degree; determining the working intensity based on the vibration data, the pressure data and the liquid level data, obtaining the drainage frequency of the drainage valve to be detected after last maintenance, and determining the fault probability based on the working intensity, the drainage frequency and the impurity anomaly score; and predicting the fault condition of the to-be-detected drain valve based on the fault probability. The fault detection accuracy is improved.

The invention discloses a reservoir desilting method and device using fixed jet flow, and relates to the technical field of water conservancy and hydropower engineering desilting. According to the method, the flow speed, pressure, mud layer thickness and gradient parameters of water around a nozzle are collected in real time; calculating a jet flow angle compensation coefficient, and identifying a nozzle direction stable state; on the basis of a nozzle set with stable direction, a nozzle group is constructed and a time sequence differential control table is established by combining a topological relation between nodes and disturbance propagation characteristics, so that ordered migration of turbulent flow disturbance is realized; sediment concentration, flow velocity and flow data are collected in a flow guide plate and a sediment discharge port area, and a desilting efficiency index is calculated and used for evaluating sediment transportation continuity and flow guide performance; and a comprehensive operation optimization coefficient is generated through a multivariable adaptive weighted fusion algorithm, and the system automatically executes adaptive regulation or sends out a manual intervention prompt. According to the method, self-monitoring, self-correction and global optimization of the fixed jet system can be achieved, and the reservoir dredging efficiency and the operation stability are remarkably improved.

The invention discloses a cascade reservoir flood control water level combined application scheduling method and scheduling system, and relates to the technical field of cascade reservoir scheduling, and the method comprises the following steps: dividing into a plurality of sub-regions according to an administrative region, determining a sub-reservoir corresponding to each sub-region, and collecting the rainfall and historical flood discharge data; analyzing the water storage capacity of each sub-region at the moment corresponding to the historical data to form a training data set; constructing a flood season flood discharge prediction model, and obtaining the target flood discharge flowing into the sub-reservoir by using the prediction model; analyzing the water level change in the flood season according to the target flood discharge amount, and judging whether scheduling is needed; and if scheduling is needed, determining a drainage flow combination of each sub-reservoir, setting a constraint condition, and performing optimization through a multi-target genetic algorithm to obtain an optimal drainage flow scheme meeting constraints. According to the scheme, the scientificity, the accuracy and the intelligent level of combined dispatching of the cascade reservoirs are remarkably improved.

The invention relates to the technical field of water resource management, in particular to a flow hydrograph simulation method based on coupling of a Xinanjiang model and a depression, and the method comprises the steps: obtaining the geographic space data and meteorological data of a target drainage basin; the geospatial data at least comprises a digital elevation model, land utilization data and soil type data; and carrying out sub-drainage-basin division on the target drainage basin based on the digital elevation model, identifying depressions in the digital elevation model by adopting an improved priority flood algorithm, and constructing a spatial topological relation of the depressions. According to the method, the hydrological characteristics of the depression are fused into the Xinanjiang model, the regulation and storage function of the depression group on the drainage basin runoff is quantified, the hydrological simulation precision of the depression dominant drainage basin is remarkably improved, and by improving the depression recognition algorithm, pre-construction of the slope confluence time matrix based on the cells and rapid judgment of the depression merging mechanism, the stability of the depression confluence time matrix is improved. The calculation speed of the distributed hydrological model is greatly improved, and the efficiency requirement of the real-time hydrological model can be met.

The invention provides a river sediment physical habitat evolution identification method, device and system and a medium. The method comprises the following steps: acquiring a multi-temporal remote sensing image and hydrological data (flow Q, water level Zw and slope S), screening and other hydrological condition image pairs; extracting a water surface range, and calculating the average width B of the main groove; deducing the average water depth h by using a Manning formula, and calculating the riverbed elevation zbed by combining the Zw; the difference value delta zbed of zbed in different periods is calculated, and the substrate state is judged according to the difference value delta zbed and a threshold value epsilon; and performing segment processing along the center line to output a spatial distribution result. On-site measurement is not needed by relying on conventional data, and consumption is reduced; water level interference is eliminated through equal hydrological condition matching, and comparability is ensured; water depth inversion and differential analysis directly reflect scour deposition and quantitatively reveal rules; long-distance automatic processing improves space-time coverage capability and precision, and provides a basis for river regulation, ecological restoration and drainage basin management.

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 provides an efficiency prediction method and system for a rural sewage resourceful treatment system. According to the method, the fluctuation amplitude and the duration are extracted through a flow fluctuation waveform and a retention duration deviation value, and a flow interference identifier is generated; triggering segmented deformation of the adjusting tank based on the fluctuation amplitude, adjusting the volume of the tank body according to the pressure gradient to dynamically compensate the flow fluctuation, and generating a volume compensation signal in combination with the retention duration difference and the fluctuation duration; the retention time length deviation is matched with a pollutant concentration time sequence, an aeration and precipitation equipment efficiency early warning track is generated based on correlation between the concentration change rate in the lag time period and a volume compensation signal, and a critical failure node is calibrated through a track trend turning point; and if the node is located in the preset discharge time period, updating the regulating reservoir deformation pressure gradient threshold value, synchronizing the dynamic compensation instruction, and executing the instruction to complete closed-loop correction. The closed-loop optimization of the treatment efficiency of the sewage system is realized.

The invention discloses a distributed hydrological model parameter two-stage calibration method based on remote sensing data and actually measured flow. The method comprises the following steps: collecting and preprocessing basic data required for constructing a distributed hydrological model, and remote sensing data and actually measured flow data for calibrating model parameters; constructing a distributed hydrological model, determining hydrological parameters needing to be calibrated in the model, and setting a value range of each parameter; performing grid-by-grid parameter calibration by utilizing remote sensing data to obtain model parameters with spatial heterogeneity characteristics; performing optimization adjustment on grid-by-grid model parameters based on remote sensing data calibration by utilizing actually measured flow data; and finally selecting a parameter combination with the optimal simulation precision as a finally determined model parameter for researching the drainage basin. Spatial distribution information of remote sensing data and time sequence precision of actually measured flow data are fused, and a multi-target calibration scheme considering parameter spatial heterogeneity and calibration result reliability is constructed.

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.