103 results about "Rainfall runoff" patented technology

The invention relates to the technical field of urban drainage and waterlogging prevention, in particular to an urban real-time drainage scheduling method and system based on deep reinforcement learning. The method comprises the steps of constructing a dual-target reward function and constraint conditions for minimizing the total amount of surface waterlogging and the overflow frequency of a combined system discharge port, performing rainfall runoff simulation by adopting a hydrodynamic mechanism model and combining basic data of a target area, and establishing a multi-agent model based on deep reinforcement learning. The method comprises the following steps: constructing interactive coupling of decision actions and simulated environment states, obtaining updated environment states and drainage scheduling reward values through the coupling, driving a multi-agent model to generate a strategy network, predicting and generating drainage waterlogging prevention engineering actions based on real-time rainstorm information, and dynamically updating the actions by utilizing the periodically generated strategy network. According to the method, it is ensured that multi-objective optimization decision is rapidly achieved within response time, the waterlogging relieving effect is achieved, urban rainfall flood toughness is enhanced, and the real-time requirement is met.

The present invention relates to urban rainfall runoff pollution prediction in urban water systems, and provides an urban rainfall runoff pollution prediction method based on integrated rolling decomposition method and deep learning algorithm. A rolling decomposition method is firstly used to decompose rainfall runoff sequence data into different sub-sequences; then decomposition is sequentially performed on added data, and future data is excluded, to prevent information leakage; a recurrent neural network is used to model and predict the sub-sequences; and finally, predicted results of the sub-sequences are summed to obtain the predicted result of rainfall runoff pollution.

The invention discloses a drainage basin nitrogen and phosphorus pollution prediction method based on rainfall runoff migration, and relates to the technical field of water quality pollution prediction, and the method comprises the steps: accurately obtaining land utilization and water body distribution through a remote sensing technology, carrying out the space division of a pollution source through combining a nitrogen and phosphorus load coefficient, and constructing a rainfall runoff model. The runoff volume and time and space distribution under different rainfall events are reflected, and the spatial dynamic change of pollutants is captured through a hydrodynamic model, in combination with a convection diffusion equation and by introducing a conversion model of nitrogen and phosphorus in various forms. By integrating remote sensing data, rainfall runoff simulation, hydrodynamic force and nitrogen and phosphorus form transformation, the space-time migration and transformation process of nitrogen and phosphorus pollution in a drainage basin is described, so that the coupling relation between pollution source distribution and runoff power is revealed, the conveying and diffusion rule of pollutants in a river network is dynamically reflected, and the drainage effect is improved. And refining to transformation evolution of different nitrogen and phosphorus forms, and generating intuitive concentration distribution and thermodynamic diagrams through spatial interpolation.

The invention discloses a drainage basin rainfall runoff prediction method and system based on a bidirectional long short-term memory network and multi-source data fusion, and relates to the technical field of drainage basin rainfall runoff prediction, and the method comprises the steps: collecting the multi-source data of a drainage basin, and carrying out the preprocessing; constructing a drainage basin rainfall runoff prediction model according to the preprocessed data; the model is trained, and a water balance constraint term is introduced into MSE loss for model optimization; performing model dynamic weight transfer learning of the data scarcity drainage basin, pre-training the model on similar drainage basin data, and obtaining an optimal drainage basin rainfall runoff prediction model through field adaptive fine adjustment of model parameters; and acquiring real-time data, and inputting the real-time data into the optimal drainage basin rainfall runoff prediction model to obtain a prediction result. Compared with one-way LSTM, errors in flood peak prediction are reduced through BiLSTM-ATT, it is guaranteed that a prediction result conforms to a hydrological law through a water balance constraint term, and cross-basin rapid deployment is supported through a transfer learning module.

The invention discloses a flood disaster scene-oriented urban power distribution network toughness evaluation method and system, and belongs to the technical field of power distribution network toughness evaluation, and the method comprises the steps: obtaining rainfall data, land utilization data, elevation data and the like, and inputting the data into a waterlogging simulation module; the waterlogging simulation module simulates rainfall runoff production and runoff convergence to generate ponding distribution; the disaster judgment module obtains the fault probability of the power distribution equipment and the line in combination with the power distribution equipment and line disaster fault model, and generates a system disaster scene under the flood disaster; the load reduction optimization module constructs a power distribution system load reduction optimization model, and takes the minimization of the total load reduction amount of the power distribution system as a target; and the system toughness evaluation module measures the overall toughness of the power distribution system in the flood disaster scene. According to the method, the overall toughness level is quantitatively evaluated based on the system load reduction amount, the node load importance degree and the ponding condition are combined to recognize the weak links of the system, reference is provided for differential reinforcement and operation and maintenance strategies, and subsequent waterlogging prevention planning and operation and maintenance management are guided.

The invention provides a power grid equipment large-range progressive real-time flood forecasting method based on a three-water-source Xinanjiang model, which abandons a basin homogenization hypothesis of a traditional lumped model, divides a target basin into subunits with spatial uniqueness and topological connectivity through a Thiessen polygon method, and accurately matches underlying surface spatial differentiation features; according to the method, the limitation of single parameter calibration is broken through, an NSGA-I I multi-objective optimization algorithm is adopted to be combined with historical flood data, a parameter optimization system containing multiple indexes such as a flood peak flow error and a peak present time error is constructed, a Pareto optimal solution set is generated, a parameter knowledge base is constructed in a classified mode, and the problem of poor parameter adaptability is solved; a geographically weighted regression method is used for fusing satellite remote sensing, ground rainfall station and hydrometric station data, a dynamic correction mechanism is established, model input is updated every 30 minutes, and the rainfall runoff calculation temporal-spatial resolution is remarkably improved; after subunit outlet flow riverway convergence calculation is completed based on a Muskingum method, power grid equipment space distribution and vulnerability threshold values are innovatively associated.

The invention relates to the technical field of data processing, and discloses a rainfall runoff pollution early warning system and method.The system comprises a sample analysis module, a pollutant model construction module, a water quality prediction module, an early warning signal generation module and a pollution control module; carrying out physicochemical property analysis on the pavement sediment sample and the rainfall runoff sample of the service area to obtain pollutant concentration data and pollutant composition data; constructing a pollutant migration and transformation model based on dynamic changes of pollutants in the pollutant concentration data and the pollutant composition data in the runoff process; hydrology and hydrodynamic force of the service area are predicted based on the pollutant migration and transformation model, and runoff water quality change trends under different rainfall scenes are obtained; when the water quality prediction index in the flow water quality change trend exceeds a pollution early warning threshold value, a pollution early warning signal is generated; the pollution early warning signal is pushed to a management terminal, and a corresponding runoff pollution control measure is triggered; the rainfall runoff pollution early warning method can improve the accuracy of rainfall runoff pollution early warning.

The invention relates to an urban non-point source pollution identification method and system based on rainfall events. The method comprises the following steps: step S100, decomposing rainfall data of a continuous time sequence into independent rainfall events and snowfall events; step S200, dividing grid units, and performing runoff calculation in each unit so as to obtain runoff information of spatial distribution; wherein the rainfall event runoff is estimated by adopting a runoff curve hydrological model method; calculating snow melting runoff by adopting a temperature index snow melting model; s300, estimating the average event concentration of the rainfall event by adopting an accumulation and scouring formula, and estimating the average event concentration of the snow melting event by using average observation values in different land utilization types; and step S400, realizing refined identification and accurate estimation of urban non-point source pollution load by integrating urban functional area characteristics, surface runoff simulation and event average concentration simulation of pollutants. The method is suitable for estimating the rainfall runoff pollution load in a large-scale region with relatively limited water quality monitoring data.

The invention provides a watershed flood early warning system and method based on hydrological model and mobile application coupling, and belongs to the field of watershed flood early warning. In the system, a communication and data transmission module collects data for hydrological model simulation in a watershed area; the model simulation module simulates hydrological data of rainfall runoff in a watershed area in real time by using a hydrological model based on the collected data, and transmits a simulation result to the flood risk forecasting module through the communication and data transmission module; the flood risk forecasting module generates a flood risk map based on the received simulation result and transmits the flood risk map to the communication and data transmission module; and the mobile application display module receives real-time early warning information generated by the communication and data transmission module based on the flood risk map, and displays the real-time early warning information to a user. The watershed flood is simulated in real time through the hydrological model, the flood forecasting and early warning information is sent to people in a watershed flood submerging range through the mobile application, and the accuracy and timeliness of watershed flood early warning can be improved.

The invention relates to the technical field of rainfall runoff simulation, and discloses a BIM-GIS (Building Information Modeling-Geographic Information System) coupling-based rainfall runoff dynamic simulation method, which comprises the following steps of: planning a simulation process based on input parameters and environmental conditions, determining required BIM data (including building geometric data) and GIS data (including terrain elevation data), and determining different scene types; then generating a dynamic simulation process set, determining an execution sequence, and generating a coupling parameter setting list and a data fusion scheme list of each scene; and finally associating the elements to generate an overall scheme. In addition, the invention also relates to the contents of dynamic simulation boundary determination, data subset extraction, scene type subdivision, simulation process updating, data fusion rule and database establishment and maintenance and the like. The method integrates the technical advantages of BIM and GIS, can adapt to different scenes, realizes data dynamic updating and efficient processing, improves the accuracy and reliability of rainwater runoff dynamic simulation, and can be used in the related field of urban rainwater management.

The invention provides a sediment concentration prediction method and system based on a freeze-thaw coupling physical constraint model, and relates to the technical field of sediment concentration prediction, and the method comprises the steps: obtaining hydrological data, meteorological data and various original data of soil and vegetation, and carrying out the preprocessing; constructing a benchmark sediment concentration physical model based on the multiple kinds of preprocessed original data, and constructing an input feature vector; inputting the input feature vector into a sediment concentration prediction ANN model, and outputting to obtain the sediment concentration; wherein in the training process of the sediment concentration prediction ANN model, reference sediment prediction and sediment mass conservation constraint of the physical model are introduced into an ANN model loss function, the loss function is enhanced by adopting a freeze-thaw weighting strategy, and the sediment concentration prediction ANN model in which the physical model and the ANN model are deeply fused is obtained. According to the invention, the stability and accuracy of prediction during extreme rainfall, runoff surge or frequent freezing and thawing are improved.

The invention discloses a grid runoff forecasting method based on a space-time diagram convolutional network, and particularly relates to the technical field of runoff forecasting. The method comprises the following steps: firstly, performing grid division on a target drainage basin based on a landform and hydrological response unit, and constructing a space map structure; combining historical rainfall, runoff and remote sensing meteorological data to construct a space-time input feature sequence; extracting a spatial dependency relationship by using a graph convolutional network, extracting a time evolution feature by combining a long-short term memory network, and generating a node representation fused with the spatial-temporal feature; outputting a runoff prediction result of multiple time steps through a full-connection neural network; for a heavy rainfall event, input characteristics and a space structure can be updated in real time, dynamic completion and local graph structure reconstruction of missing data are realized, and finally a gridding runoff distribution graph in a future time period is generated. The method has high precision, high timeliness and high adaptability, and is suitable for runoff intelligent prediction in complex terrains and sudden heavy rainfall scenes.

The invention discloses a rainy day overflow pollution analysis and calculation method for a flood drainage pump station, and relates to the field of environmental science. According to the scheme, the method comprises the steps that the target pump station under each pump station type in multiple pump station types is determined based on the incidence relation between the forebay water quality of at least one target pump station and different rainfall types in the historical time period; on the basis of underlying surface interpretation of a catchment area of the target pump station under each pump station type in the different rainfall types, the pollution load of rainfall runoff of the target pump station under each pump station type in the different rainfall types is determined; based on the rainfall runoff pollution load of the target pump station under each pump station type in different rainfall types, the living source pollution load of the target pump station under each pump station type in different rainfall types, and the total pollution load of the target pump station under each pump station type in different rainfall types, the pollution load of the target pump station under each pump station type in different rainfall types is calculated; and determining the proportion of various overflow pollution sources of the target pump station under each pump station type in different rainfall types.

The invention discloses a flood forecasting method and system considering similarity and a multi-dimensional classification system, and the method comprises the steps: obtaining the historical rainfall and runoff observation data of a drainage basin, and building a historical sample library and a test period of a similarity flood forecasting model; analyzing the influence time lag of early rainfall and runoff on the forecast section runoff; constructing rainfall-runoff combined similarity indexes, establishing a multi-dimensional classification system, and dividing runoff change modes according to a three-dimensional classification system; a similarity flood forecasting model is constructed, the model is trained for different runoff change modes, and model optimal parameters and forecasting schemes of all the runoff change modes are obtained; and integrating various types of models, constructing a flood forecasting model for automatically identifying a runoff change mode, automatically matching rainfall-runoff similarity of optimal parameters of the model and a multi-dimensional classification system, and generating hourly runoff forecasting in the future 72 hours through rolling forecasting. According to the method, the flood forecasting precision and robustness under the complex hydrological condition are improved.

The invention relates to the technical field of hydrology, and discloses a construction method of a watershed instantaneous unit line model based on a hydraulic energy complementation equation, a construction device of the watershed instantaneous unit line model based on the hydraulic energy complementation equation, a watershed instantaneous unit line determination method, a watershed instantaneous unit line determination device, electronic equipment and a computer readable storage medium. The method comprises the steps of obtaining sample rainfall runoff data of a sample drainage basin, constructing a basic model of a drainage basin instantaneous unit line model based on a hydraulic energy complementation equation, substituting the sample rainfall runoff data into the basic model, solving the basic model, performing parameter calibration by taking a precision index Nash efficiency coefficient as a target function, and obtaining a drainage basin instantaneous unit line model. And determining model parameters by maximizing the objective function, and substituting the model parameters into the basic model to obtain a watershed instantaneous unit line model based on the hydraulic energy complementation equation. The application range of the construction method of the instantaneous unit line is widened, and the accuracy of the construction result is improved.

The invention relates to the technical field of risk assessment, and discloses a small watershed disaster risk assessment system and method based on artificial intelligence, and the method comprises the following steps: synchronously obtaining real-time monitoring data such as rainfall, water level, soil moisture content and the like, associating equipment position information, verifying the water level change and rainfall-runoff relationship based on the fluid mechanics principle, and determining the risk of the small watershed disaster risk. Packaging and transmitting after abnormal values are filtered, integrating distributed node data, predicting the risk probability of disasters such as mountain torrents and landslides by using a lightweight model, aggregating edge node model parameters through federated learning, detecting and predicting reduction in precision in real time, triggering early warning, aggregating degradation signals, and quickly adjusting the model parameters by using physical constraint element learning. According to the invention, through an end-edge-cloud collaborative architecture and a physical constraint meta-learning mechanism, the real-time performance and accuracy of small watershed disaster risk assessment are improved, a modular architecture has lightweight deployment and cross-watershed expansion capabilities, and decision support of continuous evolution is provided for intelligent water conservancy projects.

The invention provides an intelligent watershed flood prediction method and system based on a multi-modal large model, and relates to the technical field of hydrology and water resources, and the method comprises the steps: S1, obtaining multi-modal original data from a meteorological radar, satellite remote sensing, a soil humidity sensor, hydrological station monitoring equipment and a terrain and land utilization database, and respectively performing signal denoising, spatial interpolation, dimension standardization and timestamp synchronization on the original data. According to the drainage basin flood intelligent prediction method and system based on the multi-modal large model, unified modeling of multi-modal information such as rainfall, runoff, soil water content and terrain is realized through deep fusion of multi-source heterogeneous data and large model structure design. The constructed time sequence processing subnet and the spatial feature extraction subnet are specially optimized for time sequence dependence and spatial topological relation respectively, the high dependence of a traditional physical model on data quality and boundary conditions is overcome, and the defects of a pure data driving model in the aspects of complex nonlinear relation and generalization ability are overcome.

The invention discloses a debris flow runoff threshold probability forecasting system construction method and a small watershed debris flow early warning method. The invention provides a debris flow runoff threshold probability forecasting system construction method for overcoming the defects of an existing dichotomy forecasting logic monitoring technology. According to the method, rainfall is regarded as a disaster clue, dimensionless single-width flow q * is regarded as a core variable, and a mapping relation among terrain parameters, q * and proportionality coefficients is established according to a model; the topographic parameters represent the influence of the topographic features on the disaster threshold in local and global meanings; the proportionality coefficient represents a q * induced soil position point starting proportion through a curve shape; and extracting a threshold corresponding probability from key parameter cumulative frequency analysis by using fitting generated data. According to the technical scheme, a complete rainfall runoff confluence input conduction model is established to be connected into a system construction core link, and a median particle size dynamic valuing method is adopted in the optimization scheme. The invention adopts a monitoring system threshold setting technical concept opposite to the prior art, is more scientific and rigorous, and has higher utilization value.

This invention provides a multi-model fusion method, device, electronic device, and system for debris flow early warning. The method includes: collecting geographical and geological data, real-time rainfall, runoff, and auxiliary monitoring data; fusing a shallow flow numerical model, a moving least squares machine learning model, and a generalized regression neural network model, and obtaining a comprehensive runoff prediction through weighted least squares calculation; constructing critical runoff indicators based on the safety requirements of disaster-bearing bodies such as roadbeds, retaining walls, and culverts, and inversely calculating critical rainfall thresholds, then making differentiated adjustments based on the average gradient of the gully; generating a debris flow early warning report by comparing real-time predictions with thresholds, achieving final graded and zoned early warning for the warning area. This invention improves the accuracy and engineering relevance of early warnings by integrating physical mechanisms and data patterns, achieving refined early warning from "whether it will occur" to "when, where, and what the impact will be," while reducing the error of a single model and adapting to different terrains and disaster-bearing bodies along highways.

The invention discloses an urban flood simulation method based on virtual pool network and SWMM coupling, and the method comprises the steps: taking each sub catchment region of a research region as an independent water storage unit, and constructing a corresponding virtual pool; adjacent pools are connected through triangular weirs to form a virtual pool network reflecting the evolution of surface accumulated water; for a sub catchment area containing an inspection well, bidirectional water exchange between a virtual pool and a pipe network is established by using a transverse weir, so that overflow of the pipe network can be supplemented to the earth surface, and accumulated water on the earth surface can also be discharged into the pipe network. The surface runoff firstly enters the corresponding virtual pools and then is exchanged between the virtual pools or between the virtual pools and the pipe network through the weir structure, so that the whole process simulation of rainfall runoff-surface ponding-pipe network drainage is realized. According to the method, the precision, the efficiency and the realizability are coordinated and unified, the bottleneck that high precision and high efficiency are difficult to consider in an existing urban flood simulation technology is broken through, and the method has remarkable engineering practical value and wide popularization prospects.

The invention discloses an urban rainfall runoff calculation method based on drainage node downstream tracking. The method comprises the following steps: step 1, obtaining drainage pipe network data of a research area; 2, analyzing the flow direction of the drainage pipe network; step 3, dividing sub catchment areas and setting runoff production parameters; 4, generalizing drainage pipe network data; step 5, node generalization marking; 6, new outlet nodes of the sub catchment areas are determined; step 7, calculating confluence delay; and step 8, calculating runoff production of the sub catchment areas. According to the method, on the basis of a drainage node downstream tracking mode, the accuracy of runoff production calculation of the sub catchment areas is improved, the defect that a traditional method can change a catchment path and a spatial pattern is overcome, the accuracy of urban rainfall runoff calculation is improved, and powerful support is provided for urban flood control and disaster reduction.

The invention discloses a large-span hyperbolic roof landscape drainage design method and system, and the method comprises the following steps: 1, simulating the real conditions of the slope of a basic site and the rainfall runoff based on a BIM model and according to the rainfall runoff stress principle through a circulation algorithm, and carrying out the visual analysis; 2, performing rule summarization and extraction on simulation and visual analysis results to obtain main flowing and converging routes of rainwater and variation differentiation of unit rainwater flow and flow velocity; and 3, designing a landscape drainage system of the large-span hyperbolic roof according to result characteristics of GH and BIM technical analysis. The invention relates to the technical field of constructional engineering, and can solve the problem of drainage defects of a traditional large-span hyperbolic roof landscape drainage design.

The invention discloses a method for judging a backflow time period of a gate in a plain tidal river network. The method comprises the following steps: acquiring water gate upstream and downstream long-series observation water level, drainage basin rainfall and wind field data; astronomical tide and rainfall runoff decoupling is carried out on the downstream section water level, dynamic deformation characteristic parameters are extracted and corrected, and a downstream water level forecasting curve set is obtained; physically decomposing the observation water level of the upstream shallow lake, extracting the average water level and the wind-generated water level deviation, and calculating an upstream forecast curve set in combination with rainfall; combining the forecast curve set to construct a predicted water level difference sequence set; extracting a prediction error quantile based on a pre-constructed error condition distribution library, and performing lower bound calibration and minimum extraction on the difference sequence to obtain a partial safety fusion water level difference sequence; a backflow risk period is identified based on the fused sequence and a decision threshold. According to the method, time consumption of complex numerical solution is avoided, and timeliness and robustness of advanced early warning in the backflow risk time period are improved.

The application discloses a kind of based on solidified soil rainfall-runoff combined simulation erosion system, it is related to rainfall-runoff simulation technical field, runoff water supply device is located at one end of runoff tank, and runoff water supply device can supply water to runoff tank, runoff water supply device is equipped with water inlet at the end away from runoff tank, runoff tank is equipped with water outlet at the end away from runoff water supply device, water inlet is equipped with flow stabilizing element, and flow stabilizing element can inhibit the initial disturbance of water flow, monitoring device is used to monitor the parameter in runoff tank and erosion process, runoff water supply device and runoff tank are all inclined to be arranged, and the height of the side where water inlet is located is higher than the height of the side where water outlet is located, runoff water supply device and runoff tank are all located on mobile adjustment device, and mobile adjustment device can drive runoff water supply device and runoff tank to move, and adjust the inclination angle of runoff water supply device and runoff tank.The application can avoid destroying natural runoff generation stability, realize simulating thin layer runoff erosion surface soil.

The application provides a source-sink landscape-based soil heavy metal remediation method and system, and relates to the field of ecological environment; the method generates target region small watershed space data by analyzing digital elevation model through GIS; on the other hand, the source-sink landscape type of the target region is determined according to satellite images and remote sensing images, and the pollution source intensity is determined by combining rainfall runoff and soil environment sampling monitoring to establish a source-sink landscape geographic information database; soil heavy metal monitoring and spatial evaluation are carried out by selecting typical landscape types, and a self-regression model is established by spatial autocorrelation analysis of soil heavy metal spatial distribution information and source-sink landscape types, and the best scheme of landscape space optimization is proposed based on the model; based on the optimal scheme, the landscape space pattern most conducive to the soil heavy metal self-repairing process is obtained; finally, physical, chemical and biological treatments are further carried out for different landscape types, and the source-sink landscape-based soil heavy metal remediation application is completed.

The invention discloses a gate pump real-time control method for regulating and controlling urban flood. The method comprises the following steps: S1, collecting urban river data; s2, constructing an urban hydrological model, and simulating an urban rainfall-runoff forming process according to detailed space division and different surface runoff characteristics; s3, constructing a river network hydrodynamic model, and simulating a river network system by considering hydraulic conditions of pump stations, gates, weir flows and reservoir and lake facilities; s4, the hydrological model describing the urban surface runoff and confluence process and the hydrodynamic model describing the water flow evolution process in the urban river network are coupled through the section node water exchange process to construct a hydrological and hydrodynamic coupling model; s5, compiling a water engineering real-time control rule based on the warning water level and ecological water level data of the river channel; s6, inputting the real-time control rule of the water engineering into the hydrological and hydrodynamic coupling model, evaluating the performance of the method through a rainstorm event, and quantitatively analyzing the response of flood to the real-time control of the water engineering; according to the invention, accurate regulation and control of the river network and effective relief of flood are realized.

This invention provides a method and device for simulating the relationship between urban rainfall and runoff based on a sensitivity function. The method comprises: Step 1: determining the area of ​​different underlying surface types in a catchment area and generalizing the runoff paths; Step 2: constructing a runoff calculation formula for the catchment area. This method considers the impervious area ratio and spatial distribution characteristics of the catchment area in the calculation, providing support for rainfall-runoff calculations under different urban development scales or sponge construction scales.

The invention relates to a small watershed multi-element cooperative monitoring method, device and equipment and a medium. The method comprises the following steps: acquiring satellite remote sensing data, unmanned aerial vehicle observation data and ground observation data of a target drainage basin; preprocessing the satellite remote sensing data, the unmanned aerial vehicle observation data and the ground observation data to obtain multi-element observation parameters; carrying out basin live inversion according to the multi-element observation parameters to obtain land utilization grids, water body boundary-area data, runoff data and sediment data; and according to the land utilization grid, the water body boundary-area data, the runoff data and the sediment data, constructing a rainfall-runoff-sediment-water quality chain response relationship, and obtaining drainage basin multi-element scale coordination time sequence data, an element influence map and land utilization influence evaluation. By adopting the method, multi-element data space-time cooperative monitoring can be realized, and the full-chain demand of small-watershed ecological hydrological management is supported.

The invention relates to a rainfall runoff pollution multi-dimensional data dynamic interpolation method based on a self-attention mechanism and physical constraints, and relates to a missing data interpolation method based on artificial intelligence. Comprising the steps of basic data collection, data preprocessing, missing data review, feature engineering, SAITS model construction, reconstruction and mask filling joint training strategy, optimal interpolation result output, and verification of the reliability of an interpolation result based on physical constraints and statistical parameters. According to the method, the problem that the spatial-temporal heterogeneity is difficult to consider in the existing rainfall related data interpolation by using simple mean interpolation or singly using a spatial position is solved, and meanwhile, an accurate interpolation mode is provided for the interpolation of rainfall events and corresponding runoff pollution missing data; the distribution of rainfall events and corresponding pollution data in time and space ranges is natural, and the credibility of an interpolation result is ensured.

The invention discloses a watershed runoff evolution trend prediction method based on multi-source data fusion, and relates to the technical field of hydrology and water resource prediction, and the method comprises the steps: obtaining historical hydrometeorological data, dividing rainfall runoff events, calculating the soil water absorption amount in unit time through water balance, and fitting wet and dry water absorption paths to construct a hysteretic loop; clustering the hysteretic loop set to extract a representative hysteretic loop family; and matching the most similar hysteretic loop during prediction, inputting the data into a reinforcement learning model to output a path advancing position, determining the corresponding soil water absorption amount, and calculating the predicted runoff volume in combination with meteorological data. By quantifying the nonlinear hysteretic characteristic of the soil water absorption behavior, the problem that the runoff prediction precision is low due to the fact that a traditional model ignores the water absorption capacity difference in the dry and wet process is solved.