576 results about "River section" patented technology

The invention relates to the technical field of energy efficiency management, in particular to a water conservancy sensing system based on edge computing. The system comprises the following modules: a riverway edge sensing module, a water conservancy characteristic analysis module, a sediment migration simulation module and a deposition scouring early warning module. Constructing a river channel water conservancy sensing network; performing real-time water conservancy monitoring data acquisition according to the river channel water conservancy sensing network to obtain river channel water conservancy sensing data; performing three-dimensional flow field model processing on the river channel water conservancy sensing data to obtain a three-dimensional sediment flow field network model; carrying out particle flow field simulation on the three-dimensional sediment flow field network model to generate sediment migration space-time distribution data; and according to the sediment migration space-time distribution data, carrying out siltation and scour area identification, and uploading the siltation and scour area data to a cloud platform through an edge computing node to carry out abnormal event alarm so as to obtain river section monitoring data. According to the invention, real-time, accurate and intelligent monitoring and early warning of the sediment deposition and scouring process of the river channel are realized.

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

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

The invention provides a river section water quality prediction method based on a combined machine learning model, and the method comprises the steps: building river monitoring section long-time sequence water quality big data, standardizing and supplementing water quality index data, preparing a water quality index data set and a water quality evaluation data set, and selecting and processing water quality big data features. Developing a water quality prediction model based on a combined machine learning algorithm, evaluating the performance of the water quality prediction model, and testing the generalization ability of the water quality prediction model. The correlation of river section historical data in a time sequence is fully utilized, the model not only improves the accuracy and real-time performance of water quality prediction, but also enhances the response capability to sudden water quality events, the monitoring and early warning cost is remarkably reduced, the efficiency and scientificity of water environment management are improved, and the method is suitable for popularization and application. The self-learning capability and the high-frequency data processing capability of the system ensure timely updating and long-term effectiveness of a prediction result, and provide solid technical support for water pollution prevention and control and water quality management.

The invention provides a river pollutant traceability method and a river pollutant traceability system. The method comprises the following steps: constructing a potential pollution source feature fingerprint database fused with an LSTM time sequence feature extraction model, carrying out abnormal water quality fingerprint identification on a monitored river reach, if identification is abnormal, collecting an upstream water sample, detecting to obtain a water quality fingerprint, comparing the water quality fingerprint with the abnormal water quality fingerprint, determining a target river reach according to a comparison result, and determining the target river reach according to the comparison result. The method comprises the following steps: sampling all enterprises of a target river reach in real time, comparing detection result data with detection result data of an abnormal water sample, determining potential pollution sources according to a comparison result, determining high-matching candidate sources from the potential pollution sources by utilizing an LSTM (Long Short Term Memory) time sequence feature extraction model, carrying out space transition verification on the high-matching candidate sources, and carrying out space transition verification on the high-matching candidate sources. And determining the pollution source according to the verification result. According to the method, the accuracy, efficiency and result reliability of tracing the river pollutants can be effectively improved, and the scenes of multi-source pollution, intermittent emission and the like of complex rivers can be effectively handled.

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

The invention relates to the technical field of river section measurement, in particular to a river measurement data preprocessing method based on artificial intelligence. The method comprises the following steps: obtaining river section measuring point data, and carrying out measuring point density evaluation on the river section measuring point data based on different scales and section elevation changes so as to obtain high-density measuring point data; performing section thalweg point and turning point identification based on adjacent measuring point slope change on the high-density measuring point data, and performing measuring point thinning processing of retaining thalweg points and turning points so as to obtain a retaining measuring point data set; according to the preset section line and the reserved measuring point data set, the measuring points exceeding the preset measuring point deviation distance threshold value are automatically detected and calibrated, coordinate reconstruction and position correction are conducted on the measuring points deviating from the preset section line, and therefore calibrated measuring point data are obtained. The problems of uneven data, missed measurement and deviation in traditional measurement can be effectively solved, and river channel measurement data are more accurate and complete.

The invention discloses a wind, light and water resource element simulation method and device for optimizing key parameters of a confluence mode. The method comprises the following steps: acquiring a river network database and gridded hydrotopographic data, and interpolating the gridded hydrotopographic data to a refined confluence grid with a target resolution to obtain interpolated elevation data; according to the altitude data, the flow direction data and the cumulative flow after interpolation, determining vector data of a river network center line and a water collection area boundary, segmenting the river network according to the Strahler river level, and determining river reach of different Strahler levels; inputting the vector data of the central line of the river network and the boundary of the water collecting area into a pre-established river network confluence model, and simulating by adopting different Manning coefficients for river reaches with different Strahler levels to obtain simulated flow; and through a dynamic dimension search algorithm, the Manning coefficients of the river reaches with different Strahler levels are optimized respectively, so that the objective function is minimum.

The invention discloses a channel flow evolution method and system based on a physical mechanism collaborative deep learning algorithm, and relates to the technical field of channel flow evolution, and the method comprises the steps: carrying out the data collection and preprocessing; carrying out feature extraction and constructing an evolution model; deducing a hydrological physical model through simultaneous operation of a Muskinggen tank storage curve equation and a river reach water balance equation; the section flow of each river reach is predicted through the hydrological physical model and the evolution model; and through the prediction result of the index evaluation model in each river reach, carrying out collaborative optimization intelligent evolution of each river reach through the evaluation result. The method guides the establishment of the constrained deep learning neural network model through a hydrological physical mechanism, organically fuses the hydrological physical model and the deep learning algorithm model, comprehensively applies the physical model and the mathematical model to better solve the hydrological problem of a complex system, gives full play to the respective advantages, and improves the reliability of the system. The method is suitable for flow simulation prediction of various river channels, operation is easy and convenient, training is fast, and results are reliable.

The invention relates to a method, device and product for monitoring river flow in real time, and the method comprises the steps: obtaining tower footing video data of a target river reach which comprises a target section and a pier buoy; inputting the tower footing video data into a water level and flow velocity identification model, and obtaining the water level elevation and the surface flow velocity of at least part of the cross section in the target section through the water level and flow velocity identification model; inputting the water surface elevation into a three-dimensional digital river channel model to obtain a section water passing area of a corresponding cross section; and obtaining the cross section flow of the target cross section according to the cross section water passing area and the surface flow velocity. According to the embodiment of the invention, automatic flow estimation based on the tower footing video can be realized, the manual measurement cost is reduced, the spatial-temporal resolution of flow monitoring is improved, and the method can be used for large-range river monitoring, especially in areas lacking hydrometric stations, and can provide data support for drainage basin water resource management and flood prevention early warning.

The invention provides a river channel dredging operation method, system and equipment and a storage medium, and relates to the technical field of engineering. The method comprises the following steps: acquiring geographical, meteorological and hydrological and silt data of a to-be-dredged river reach and upstream and downstream river reaches, and constructing a full-basin hydrodynamics-silt mathematical model; then, a preliminary dredging scheme is prepared according to operation river reach data, the preliminary dredging scheme is input into the mathematical model for dredging simulation, and the dredging effect and the influence on the downstream river reach are evaluated; and finally, the preliminary scheme is corrected according to the evaluation result, a target dredging operation scheme is obtained, and dredging is carried out. Through the method, the dredging effect and the environmental influence can be more accurately controlled.

The invention discloses a quantitative source tracing method for river and lake water pollution in combination with a knowledge graph and machine learning. The invention relates to the technical field of water quality pollution traceability, and the method comprises the steps: collecting and processing target river section data, constructing a hydrodynamic force-water quality model, and obtaining river downstream pollutant diffusion characteristics and target section concentration time sequence characteristics under different discharge situations of each discharge port based on the discharge port position of a target river section through a unit pulse response test; the method comprises the following steps: constructing a source intensity-time-concentration relation knowledge graph, randomly extracting a sample set from the graph, training the sample set by adopting a machine learning method, learning a nonlinear mapping relation between a downstream section concentration time sequence and multi-outlet source intensity, carrying out dynamic inversion of a river pollutant diffusion process, and realizing rapid positioning and contribution quantification of a pollution source. And finally, generating probability distribution of pollution source positions by adopting a Monte Carlo sampling method to assist in improving the traceability judgment priority, thereby improving the accuracy and response speed of river water quality pollution traceability.

The invention discloses an automatic data processing method and device for a flat beach river channel and a medium. The automatic data processing method for the flat beach river channel comprises the following steps: acquiring historical observation data of a target section in a target river reach; for each historical observation frequency, determining the beach lip position of the target section at the historical observation frequency by using the observation point where the lowest point elevation is located and the riverbed elevations of the plurality of observation points at the historical observation frequency; based on the riverbed elevation of the beach lip position of the target section at the historical observation times, determining the flat beach water level of the target section at the historical observation times; and determining the actual flat beach water level of the target section according to the flat beach water levels of the target section at the plurality of historical observation times. The flat beach water level identification efficiency and accuracy can be improved.

The invention relates to an intelligent regulation and control system for multi-phase conversion of water quality of a gate-controlled river reach, in particular to the field of water treatment, and realizes accurate dynamic perception of the multi-phase conversion process of the water quality of the gate-controlled river reach by constructing a high-fidelity digital twinborn body and fusing a real-time data assimilation technology; by means of a time-space diagram neural network agent model based on an attention mechanism, the system can predict a complex time-space pattern of pollutant concentration field and phase evolution under different regulation and control strategies in an ultra-fast manner; on the basis, a multi-agent reinforcement learning algorithm is adopted to automatically generate a globally optimal gate group coordinated regulation scheme, and multiple targets of water quality improvement, ecological protection, engineering operation and the like are effectively coordinated; and finally, a theoretical strategy is reliably converted into a physical action through rolling optimization and a closed-loop execution mechanism, and adaptive adjustment can be performed according to environmental feedback, so that the emergency response speed of sudden water pollution events, the scientificity of regulation and control decision and the intelligent level of water quality management of the whole river network are comprehensively improved.

The invention belongs to the field of water resources and water ecological protection, and aims to provide a water resource collaborative configuration reservoir ecological flow checking and scheduling method, so as to scientifically and reasonably check the ecological flow target, realize coordinated management of reservoir water supply, ecological protection and agricultural irrigation, and effectively improve the comprehensive utilization efficiency of the water resources. According to the technical scheme, the method comprises the steps of 1, analyzing and determining a downstream influence river reach of a reservoir project, investigating the distribution condition of ecological protection objects in the downstream influence river reach, and further analyzing ecological protection requirements; 2, calculating ecological flow targets step by step according to ecological protection requirements of various protection objects in the reservoir project influence river reach; 3, carrying out multi-functional reservoir water resource collaborative configuration, and comprehensively determining a reservoir ecological flow target; and 4, optimal scheduling of the ecological flow of the multifunctional reservoir. On the basis of the water resource collaborative configuration result of the multifunctional reservoir, the ecological flow scheduling rule of the multifunctional reservoir is perfected by formulating a coordination degree mechanism of ecological, living, industrial, agricultural and other industries.

The invention discloses a DEM-based reservoir flood control dispatching temporary submerging area rapid generation method and device, and relates to the field of hydraulic and hydro-power engineering temporary submerging area definition. The method comprises the following steps: dividing a river channel higher than a reservoir inundation area into a plurality of units by obtaining or generating a reservoir reach DEM, a river channel section line, a normal water storage level inundation area range and water return meters under different working conditions; calculating the water level of each unit grid by adopting an inverse distance weighting method in an interpolation manner, and comparing with the DEM elevation to determine the grid meeting the condition; and merging the units after boundary tracking and smoothing, and erasing a normal water storage level submerging area to obtain a temporary submerging area. The method solves the problems that an existing method is long in time consumption and insufficient in precision, gives consideration to efficiency and precision, and provides reliable support for flood control dispatching decision making, submerging loss evaluation and the like.

The invention relates to the technical field of pollution tracing, in particular to an underground water pollution tracing method and system based on sewage pipeline data, and the method comprises the steps: obtaining the water flow and mineral dissolution content of a monitoring well; acquiring all suspected downstream monitoring wells of each monitoring well; analyzing the fluctuation similarity of the water flow and combining with the mineral dissolution content to obtain a plurality of monitoring wells contained in each underground river reach; the intersection condition of the underground river reach is analyzed to obtain a plurality of tide suspected communication points and a plurality of marked wells thereof; the high water flow date of each marked well of each tide suspected communication point is obtained; judging the independence of the trend of the mineral dissolution content to obtain a plurality of tidal well channels and communicated river reaches thereof; and connecting an underground river section for pollution tracing. The invention aims to solve the influence of unclear upstream and downstream of an underground river and well channels existing between different underground river reaches on traceability, and realizes accurate groundwater pollution traceability.

The invention relates to the technical field of flood early warning, and discloses a drainage basin flood early warning method based on regional data, which comprises the following steps: acquiring rainfall duration of a set region, and calculating a riverbed convergence rate of the set region as an auxiliary function to be fused into a preset BP neural network so as to construct a river reach runoff risk early warning model and output a river reach runoff risk level; the sediment inflow mode and the sediment content of a set area are obtained, the potential sediment risk of the river reach is determined, and the water and sediment risk of the river reach is further determined in combination with the rainfall and the sediment content; and taking actually monitored rainfall and forecast rainfall as driving data, obtaining a predicted water level through the distributed hydrological model, and issuing early warning in the set area in combination with the river reach water and sediment risk. According to the method, the river reach runoff risk early warning model is constructed, the sediment risk level identification mode is determined in combination with the sediment inflow mode, the sediment content and the actual rainfall, the water and sediment disaster risk assessment early warning method considering the sediment effect is provided, and the effectiveness and reliability of flood disaster prevention and control are improved.

The invention relates to a river section water level multi-source satellite collaborative remote sensing monitoring method and system, and belongs to the field of river section water level remote sensing monitoring. The method comprises the following steps: classifying sections based on section morphological characteristics and gradient characteristics; based on the section water levels monitored by the satellites with different types of sections and different spatial resolutions, an error correction model for monitoring different types of section water levels by the satellites with different spatial resolutions is constructed; and on the basis of a water level error correction model for monitoring different types of sections by satellites with different spatial resolutions, and monitoring different types of sections and different time phase section water levels by satellites with different spatial resolutions, obtaining a multi-source satellite collaborative monitoring time sequence water level data set of different types of sections, namely finishing section water level multi-source satellite collaborative remote sensing monitoring. According to the method, the sections are classified, then the water levels of different types of sections are monitored through multi-source satellite cooperative remote sensing, and the requirement for high-frequency monitoring of river reach water level monitoring is met.

The invention discloses a medium and long term flood forecasting method, device, equipment, medium and product, and relates to the technical field of hydrological forecasting. The method comprises the following steps: firstly, extracting a plurality of sample data from river flow time series data and climate factor time series data, then constructing a Transform model, and carrying out model training by using the plurality of sample data to obtain an intra-segment maximum river flow prediction model; and finally, importing the maximum river flow and the plurality of climate factor values of the target river section in the most recent medium-and-long-term unit periods into a prediction model to obtain a maximum river flow prediction value of the target river section in the next future medium-and-long-term unit period, and taking the maximum river flow prediction value as a medium-and-long-term flood prediction result. The long-distance dependence in the time sequence data can be processed and recognized, the problem that a traditional hydrological prediction model is difficult to cover is solved, and then the precision of medium-and-long-term flood prediction is improved.

The present invention belongs to the ecological field and provides a reservoir ecological regulation method that meets the requirements of fish spawning occurrence and fish egg density, including: obtaining the natural reproduction characteristic information and habitat information of fish species that produce drifting eggs in the regulated target river section, and determining the regulated target fish species; obtaining the first key habitat information required when the spawning occurrence probability of all fish species that produce drifting eggs and the regulated target fish species is not less than a first preset threshold; obtaining the second key habitat information required when the fish egg density of all fish species that produce drifting eggs and the regulated target fish species is not less than a second preset threshold; determining a reservoir ecological regulation plan according to the first key habitat information and the second key habitat information of the river section; and carrying out reservoir ecological regulation according to the reservoir ecological regulation plan. Through the above technical solution, the adverse impact of reservoir regulation operation on the spawning of fish species that produce drifting eggs can be alleviated, which is beneficial to promoting the restoration of fish resources and the protection of biodiversity.

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 belongs to the technical field of hydraulic engineering, and provides a river section form measurement method and system, a storage medium and electronic equipment, and the method comprises the steps: collecting and processing data needed for measuring a river section form; extracting a waterline and a center line from data required for measuring the river section form; calculating a relative stability index of the section based on the center line and the waterline, and identifying a stable river reach in the river channel through the relative stability index of the section; dividing the stable river reach into a curved river reach and a straight river reach; giving elevation values to the waterline of the curved river reach and the waterline of the straight river reach by using data required for measuring the shape of the cross section of the river to obtain waterline elevation values; and measuring the river section form based on the waterline elevation value. According to the method, any section form of the river channel can be effectively constructed, the space-time limitation of measurement is broken, basic data support is provided for runoff monitoring, and an important basis is provided for large-scale flood process monitoring and water resource management decision.

The invention relates to the technical field of non-point source pollution decision, and discloses a non-point source pollution simulation method and a non-point source pollution intelligent interaction method based on an agent, and the simulation method comprises the steps: extracting land and river attribute data of a target region, and constructing a nitrogen emission coefficient database; associating the land attribute type with a nitrogen emission coefficient library, calculating the plot emission amount through a reference area correction model nitrogen emission coefficient, converting the plot emission amount into emission amount grid data, and generating a nitrogen emission distribution map; converting the emission raster data into point data, calculating each pollution point and a river reach influence area, and constructing a river directed graph network; calculating a river reach absorption coefficient by adopting an exponential decay model, and calculating a pollution load transmission quantity and a river reach absorption quantity step by step along a river digraph network topology through breadth-first search by combining the river reach absorption coefficient based on the digraph network; the total consumption amount of the influence river reach of each pollution point is accumulated, the net discharge load distribution diagram and the consumption amount distribution diagram are generated, the calculation process is high in real-time performance, and the method is suitable for various application scenes.

The invention discloses a method for evaluating the stability of a river ecosystem based on the proportion of generalization species and specialized species. The invention relates to the technical field of river ecosystem stability evaluation, and solves the problem that an existing evaluation method is insufficient in sensitivity to dynamic response of river system stability. The method comprises the following steps: respectively setting sampling points at different river reaches according to actual conditions of a river, collecting benthic microorganism samples on gravels, sand and bottom mud of a target river reach, and measuring environmental indexes of each sampling point; performing high-throughput sequencing on benthic microorganism samples, and identifying generalization species and specialization species by combining the Levins ecological niche width; the method comprises the following steps: identifying and quantifying generalization species and specialized species of benthic microorganisms, determining a threshold relationship between the proportion of the generalization species and the specialized species and the river ecosystem stability, and constructing a river ecosystem stability evaluation system based on the proportion of the generalization species and the specialized species. The stability evaluation of the water ecosystem is realized; and the basin comprehensive management and the ecosystem construction are promoted.

The invention relates to the technical field of Internet and environment monitoring, in particular to an Internet-based river water quality remote monitoring system, which comprises a water quality data acquisition module, a pollution detection module, a water quality grading module and a mobile terminal early warning module, the water quality data acquisition module is used for acquiring water quality parameters and water quality pollution parameters of each river section and storing water quality parameter data and water quality pollution parameter data; the pollution detection module is used for calculating a water quality pollution index of each river section; the water quality pollution level of each river section is determined; the early warning module is used for generating river interval water quality early warning signals; the water quality grading module is used for calculating a water quality health index of each river section; the mobile terminal early warning module is used for displaying the segmented linear river graph by using the water quality pollution grade data and the water quality health grade data corresponding to each river interval in different colors; and a corresponding river interval alarm is given.

The invention relates to the field of water conservancy and hydropower engineering construction land acquisition and physical index investigation, in particular to a method and a system for quickly generating a mountainous area riverway type reservoir inundation area based on a high-precision DEM (Digital Elevation Model), and aims to solve the problems of poor reservoir inundation area generation precision, long time consumption and large personal error in the prior art. The method comprises the following steps: acquiring or generating a reservoir reach DEM, a river section line and a water return meter, and preprocessing; expanding section lines to divide river channel units; calculating a grid water level based on inverse distance weighting interpolation, and comparing the grid water level with DEM elevation to determine a submerged area grid; and generating a closed surface domain through boundary tracking and smoothing processing, and combining to obtain a whole submerged region. The method gives consideration to efficiency and precision, supports second-level dynamic generation of multiple schemes, improves analysis precision and efficiency, is suitable for mountainous river type reservoirs, and provides data support for scheme comparison and selection and object investigation.

The invention relates to the technical field of river channel model construction, and provides a river channel model generation method and system and a medium, and the method comprises the steps: obtaining a remote sensing image and satellite height measurement data of a target river channel, extracting a river channel thalweg line based on the image, extracting feature points from a waterline, and giving an elevation value in combination with the height measurement data; dividing the river channel into independent interpolation areas on the left side and the right side by taking the thalweg as a boundary, and setting a direction attenuation coefficient and a distance attenuation coefficient according to the characteristics of the river reach; generating direction control points along the thalweg according to the minimum width of the dry-season river channel, calculating the local direction angle of each river section, and combining the direction angle, direction attenuation and distance attenuation coefficients to construct a weighting function; spatial interpolation is carried out on the feature points on the left side and the right side through the function, double-side digital elevation models are generated respectively, finally, a complete river channel model is obtained through splicing, and refined expression of the river channel terrain is achieved. According to the method, the precision and physical rationality of complex river channel terrain modeling can be improved.

The invention discloses a small watershed flood risk early warning method, which comprises the steps of constructing a digital watershed bottom plate based on watershed DEM data, and obtaining a flow direction grid, a flow grid, a river reach watershed range and a river reach data set; trying and determining a rainstorm formula of the area where the drainage basin is located; performing 1-5km space rainfall grid interpolation based on the integrated rainfall station to obtain a small watershed unit, a river reach watershed range and peripheral rainfall grids; calculating the surface average rainfall in different time periods; calculating an early-stage rainfall capacity and an early-stage rainfall index based on the grid mode; extracting an early rainfall index of the river reach basin according to the small basin unit and the river reach basin range; calculating rainfall recurrence periods of the small watershed units and the river reach; flood risk early warning is carried out on the small watershed unit; carrying out risk early warning on the river flood; flood risk early warning is carried out on the flood control object; the problem that large-scale application and popularization are not facilitated due to lack of hydrological data of most small watersheds is solved.

The invention discloses a river flow remote sensing inversion method based on a local water area, and belongs to the technical field of environment remote sensing and hydrological observation, and the method comprises the following steps: S1, obtaining a flow monitoring section position, an actually measured flow and a remote sensing image of a region of a target river; s2, determining a plurality of research areas; s3, converting the vector file and performing cloud removal processing; s4, generating a binary water surface distribution diagram; s5, obtaining historical maximum riverway boundary vector data; s6, constructing a water surface area data set; s7, forming a paired sample set; s8, constructing a river section flow inversion model, and performing training and verification; s9, outputting a river flow inversion result based on the river section flow inversion model; only the local water area of the river channel needs to be monitored, the monitoring cost is reduced, meanwhile, the dependence of a traditional remote sensing technology on the width of a large river can be broken through, the small and medium-sized river channel flow inversion problem is effectively solved, and the applicability of the remote sensing means in narrow river sections and complex terrain areas is remarkably expanded.