434 results about "Fluvial" 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 river organic carbon flux inversion method based on multi-source data and related equipment. The method comprises the following steps: acquiring multi-source data of a river basin range in a target research area; obtaining a normalized difference index based on remote sensing image conversion; river parameters of the target research area are obtained based on the normalized difference water body indexes and multi-source data processing, and river runoff is obtained through conversion of a hydraulic geometrical relationship; on the basis of the remote sensing image, the normalized difference chlorophyll index and the normalized difference turbidity index, the particle organic carbon concentration is obtained through inversion by means of a first inversion model; based on the population number and the rainfall capacity, a second inversion model is used for inversion to obtain the concentration of dissolved organic carbon; and converting the river runoff, the particle organic carbon concentration and the dissolved organic carbon concentration to obtain the river organic carbon flux. The method can significantly improve the accuracy and reliability of monitoring on a high-dynamic river, accurately realizes the inversion of the organic carbon flux of the river, and can be widely applied to the technical field of data processing.

The invention discloses a river sediment scouring and silting simulation method, and belongs to the technical field of hydraulic engineering and hydrological simulation. In order to solve the problem that it is difficult to accurately simulate the river sediment erosion and deposition evolution trend in the prior art, the method comprises the steps that on the basis of actually measured topographic data and channel chart data of a target river reach, a water-sediment coupling mathematical model is constructed by adopting a non-uniform sediment unbalance sediment transportation theory, and the model interacts with a water power module and a wave module in real time through an MCT coupler; actually measuring a flood and water and sediment series data calibration verification model; and obtaining future water and sediment process data predicted by a plurality of climate modes, inputting the future water and sediment process data into the verified model, dividing river reaches according to the characteristics such as riverbed gradient and river channel curvature, and calculating the erosion and deposition amount of each sub-river reach in the future 50 years. The method can simulate water flow and sediment movement of rivers, reservoirs and lakes, can be applied to the fields of riverway regulation planning, flood control and disaster reduction decision making, reasonable development and utilization of water resources and the like, and provides important data support and scientific basis for construction and management of water conservancy projects.

The invention discloses a lightweight optical flow neural network method for river velocity measurement, and the method comprises the steps: collecting a dynamic monitoring image of a water area surface flow field, calculating an approximate optical flow field through combining with a DeepFlow optical flow algorithm, and generating an optical flow label; an improved lightweight ConvFFN-Flow optical flow estimation model is built, and the model comprises a feature extraction module, a 4D related structure body module, a GRU optical flow residual error iteration module and an up-sampling module; by introducing a ConvFFN module, the model parameter scale and the calculation amount are reduced, and the optical flow prediction precision is kept; and based on pixel coordinates of front and rear frames of images of the optical flow field data, obtaining corresponding positions in a real three-dimensional space, calculating an actual displacement amount, and deducing to obtain a real flow velocity vector size and a flow direction of the water body surface. The method still has stable and high-precision optical flow estimation capability when being used for processing scenes such as fine river water surface texture and complex flow state change, and meanwhile, the calculation overhead and the storage demand are remarkably reduced.

The invention provides a reservoir area landslide susceptibility evaluation method considering reservoir water level change factors. The method comprises the following steps: preparing data; constructing a model; introducing an adjustment coefficient; probability calculation and loss function definition; optimizing parameters; carrying out regularization processing; and outputting a result. The invention mainly considers the influence of reservoir water level change on reservoir area landslide susceptibility evaluation, provides a reservoir area landslide dynamic susceptibility evaluation method considering reservoir water level change, and mainly solves the following problems: a traditional landslide susceptibility evaluation technology is mainly oriented to administrative division, and the method mainly aims at evaluating the reservoir area landslide susceptibility, so that the reservoir area landslide dynamic susceptibility evaluation method can be used for evaluating the reservoir area landslide susceptibility. A river distance is introduced as an important influence factor of reservoir area landslide susceptibility evaluation.

The invention relates to the technical field of data processing, in particular to a river pollution monitoring management method fused with environmental information perception. According to the method, monitoring points are classified according to information collected in a non-rainfall period, and a plurality of monitoring point clusters are obtained. In the target rainfall period, the rainfall influence degree of the monitoring points is determined by analyzing pollutant concentration data changes before and after analysis and rainfall information, and then the target monitoring points needing data correction are screened out. A time correction method is adopted, reference time periods are selected in the non-rainfall time periods, the reference weight of each reference time period is determined by analyzing the time sequence position of the reference time periods and the rainfall influence degree of the latest rainfall time period, and then time correction is conducted; and further performing space correction by using other monitoring points in the monitoring point cluster obtained by classification to finally obtain corrected pollutant concentration data. According to the method, the influence of rainfall on pollutant concentration data is eliminated, and the data reference is increased while the data coherence is ensured.

The invention discloses a surface water storage amount monitoring method and system based on space-air-ground water multi-source collaboration, and relates to the technical field of water resource investigation, and the method comprises the steps: obtaining multi-source collaboration collection data of a target water body, and generating a multi-source data set of a unified space-time reference; carrying out automatic extraction and change detection on a surface water area range by using a water body index method and deep learning to obtain a water area boundary; taking a water area boundary as a spatial constraint, extracting ashore terrain and underwater terrain data, and inputting the ashore terrain and underwater terrain data into a deep learning fusion model based on an encoder-decoder structure to generate a water-land integrated digital elevation model; and according to the water body types, based on the model, respectively adopting corresponding deep learning models to carry out storage volume monitoring, and calculating the water storage volumes and dynamic changes of different water body types. Efficient fusion and intelligent processing of multi-source data are achieved, the precision and efficiency of surface water storage capacity monitoring are remarkably improved, and the method is suitable for refined dynamic monitoring of various water bodies such as rivers, reservoirs and ponds.

The invention relates to the technical field of water pollution diffusion prediction, and particularly provides a sewage pollution diffusion prediction method and system, and the method comprises the steps: obtaining river bed topographic feature information, real-time hydrological data and sewage discharge information of a river basin; the river basin is divided into a plurality of river reaches according to the river bed topographic feature information, and then local hydrodynamic parameters corresponding to the river reaches are obtained according to the river bed topographic feature information and the real-time hydrological data; for each river reach, acquiring sediment dynamic characteristics according to the river bed topographic feature information and the local hydrodynamic parameters, and then determining sediment adsorption parameters and sediment release parameters according to the sediment dynamic characteristics; according to the sediment adsorption parameters, the sediment release parameters, the real-time hydrological data and the sewage discharge information, pollution diffusion prediction is carried out to obtain a diffusion prediction result; the method can effectively solve the problem of inaccurate prediction caused by the fact that sediment adsorption parameters and sediment release parameters cannot dynamically reflect hydrological condition changes.

The invention discloses a multi-dimensional diagnosis method for river ecological degradation degree, and particularly relates to the technical field of river ecological degradation analysis. Obtaining multiple types of ecological parameters of the target river reach, and constructing a physical and chemical coupling parameter set, a biocenosis response factor set, a structure instability index set and an ecological function coupling parameter set; performing wavelet transform and principal component merging on the parameter set to form a multi-dimensional ecological feature tensor; extracting a main disturbance feature subspace by adopting high-order singular value decomposition to obtain a disturbance feature vector set; constructing a nonlinear degradation function based on an ecological stress response mechanism, outputting an ecological degradation risk value, identifying an ecological degradation weak region coordinate set, and generating a spatial degradation trend chart and an intervention priority suggestion path; the river ecological degradation degree can be comprehensively and accurately revealed, the scientificity and interpretability of diagnosis and the pertinence of treatment are improved, and the method has remarkable application value.

The invention discloses a Beidou-based multi-dimensional adaptive atmospheric river detection method and system, and belongs to the field of atmospheric sciences, and the method comprises the steps: obtaining original meteorological data; based on the original meteorological data, comprehensive water vapor transportation is obtained through calculation, the comprehensive water vapor transportation is judged through a Gaussian kernel density smooth threshold value and a fixed threshold value, and a preliminary atmospheric river is obtained; geometric features of the preliminary atmospheric river are calculated through a three-way axis search mechanism; and based on the geometrical characteristics of the preliminary atmospheric river, removing a non-atmospheric river by combining relative vorticity with comprehensive water vapor transportation to obtain a final atmospheric river. The Beidou satellite is used for providing high-precision time service, real-time positioning and short message communication services, time synchronism and space accuracy of meteorological data are ensured, atmospheric river axis smoothness and length calculation accuracy are optimized through a three-way axis search mechanism, relative vortex and comprehensive water vapor transmission, and the atmospheric river axis smoothness and length calculation accuracy are improved. Therefore, the atmospheric river recognition reliability is remarkably improved.

The invention relates to the technical field of river ice disaster prevention, and discloses a river freeze-up state prediction method under a multi-flow condition, which comprises the following steps: calculating the flat beach flow at the early stage of river freeze-up; calculating the river sealing volume at the early stage of riverway freezing; obtaining the cooling intensity of the river channel in the cooling process; after correlation analysis is carried out on the accumulated negative air temperature in the time period from the flow to the river closure, the flat beach flow, the river closure flow and the cooling intensity, an accumulated negative air temperature prediction model in the time period from the flow to the river closure is established, a nonlinear least square method is adopted for solving, an optimal fitting coefficient is obtained, and an optimal accumulated negative air temperature prediction model is generated; the accumulated negative air temperature of the current year is obtained, the accumulated negative air temperature is predicted, and the riverway freezing-up state of the current year is obtained through comparison; according to the method, the accumulated negative temperature of the frozen river channel can be accurately obtained by establishing the nonlinear relation between the factors such as the river channel condition (flat beach flow), the sealed river flow and the cooling intensity and the accumulated negative temperature, so that the frozen state of the river reach is accurately judged.

The invention relates to the technical field of intelligent control, and discloses a river flow simulation method and system applied to a full-automatic sediment monitoring system.The method comprises the steps that before sediment conditions are detected, according to multi-dimensional collection information corresponding to a to-be-analyzed river water sample, the to-be-analyzed river water sample is analyzed; further combining with a river flow simulation model which is trained to converge in advance to generate a flow control parameter corresponding to the existing river water sample so as to simulate the river water flow condition when the to-be-analyzed river water sample is collected; after the river water flowing condition is simulated when the river water sample to be analyzed is collected, the sediment is detected through the detection unit. Therefore, the river flow condition can be accurately simulated when the sediment content is tested, and the testing accuracy of the sediment content is improved while the testing efficiency of the sediment content is improved.

The invention provides a suspended sediment concentration inversion method capable of resisting particle size interference, which comprises the following steps of: standardizing the original acoustic echo intensity of each observation grid to obtain the standardized volume back scattering intensity; establishing a sonar equation considering the sound wave attenuation of the sediment particles, and performing explicit processing on the sonar equation considering the sound wave attenuation of the sediment particles to obtain an explicit inversion model which resists particle size interference and considers the on-way change of the sediment particle size; and performing model parameter calibration on the explicit inversion model, and performing suspended sediment concentration inversion on the river observation section based on the suspended sediment concentration inversion value of each observation grid. According to the method, the dependence of ADCP inversion of the suspended sediment concentration on suspended sediment particle size distribution is effectively eliminated, and the stability and accuracy of suspended sediment concentration inversion are improved. The particle size interference resistant explicit method can realize continuous and real-time suspended sediment concentration monitoring, and is suitable for various water environments such as rivers, lakes, reservoirs and the like.

The invention relates to the technical field of river ice condition early warning, and discloses an ice plug prediction method based on fusion of a physical model and machine learning, and the method comprises the steps: obtaining and preprocessing the monitoring data of a to-be-predicted river reach; carrying out parallel calculation on a physical risk index based on a physical mechanism and a machine learning prediction probability based on data driving; performing weighted fusion on the index and the probability to obtain a basic risk index; then, performing multi-stage correction on the basic risk index based on the critical jamming condition and the river channel curvature to obtain a final risk index; and finally, determining and outputting an ice plug risk grade according to a preset threshold value. The mechanism definition of a physical model is combined with the ability of a machine learning model to capture a complex nonlinear relationship. By introducing critical jamming condition correction and river channel geometric feature reinforcement, the reliability of the prediction method under extreme working conditions is ensured, the applicability and prediction precision of the model to different river channel conditions are enhanced, and the comprehensive accuracy of a prediction result is improved.

The invention relates to a mountain river flood dynamic rehearsal method, device and equipment based on big data fusion and a medium. The method comprises the following steps: acquiring a multi-source fusion data set of a target mountain river; based on the multi-source fusion data set, recognizing the flood type of the target mountain river in combination with a preset threshold rule to obtain the flood type and cause parameters; according to the flood type and the cause parameter, calculating a design flood peak flow value of each node in the target mountain river; according to each design flood peak flow value, performing section-by-section trial calculation through an energy equation to obtain a design flood surface line; and performing dynamic simulation processing on the flood routing process of the target mountain river based on the designed flood water surface line, and generating a flood routing dynamic simulation report of the target mountain river. The method can accurately adapt to the characteristics of diverse causes and complex propagation process of flood in a mountain river, and remarkably improves the refinement degree and reliability of flood rehearsal.

The invention discloses a cold region water and sediment function connectivity quantification method. The method comprises the following steps of S1, obtaining basic raster data of a research region and performing preprocessing; s2, determining sources and catchment conditions of rivers in the drainage basin, and performing catchment and sediment transport unit identification on a GEE platform; s3, a D-Infinity (DINF) algorithm is applied to determine the flow direction of watershed water flow, an upslope drainage threshold value is defined, and the contribution area of the unit is obtained based on iterative calculation of the flow direction of watershed water flow and the upslope drainage threshold value; s4, writing the weighting factor of each unit and calculating the component factor of each unit; s5, calculating an uphill component and a downhill component of each catchment and sediment transport unit, and sequentially performing iteration and quantitative calculation in combination with the S3 to obtain high-resolution cold region water and sediment function connectivity raster data of the whole drainage basin; the method breaks through the current situation that the method is not suitable for large-area cold region drainage basin calculation, can analyze the response of thermal erosion to the scale of the cold region drainage basin, can also clarify the complex cold region water and sediment cascade process, and is of great significance to cold region ecological protection and landscape evolution research.

Conventional estimation model generating apparatuses are required to be able to estimate information on a flow rate of a target river. An estimation model generating apparatus 101 includes: a basin data acquiring unit 142 that acquires basin data of a basin of a river of interest from an image containing the basin; a candidate model acquiring unit 143 that acquires one or more candidate models for estimating information on a flow rate of the river based on the basin data; a verifying unit 145 that verifies validity of at least one candidate model out of the one or more candidate models using verification data; an estimation model acquiring unit 147 that acquires one candidate model out of the one or more candidate models as an estimation model based on a verification result; and a model accumulating unit 149 that accumulates the acquired estimation mode. Accordingly, it is possible to estimate information on a flow rate of a target river.

The invention relates to the technical field of water ecological environment remote sensing monitoring, in particular to a river total nitrogen concentration remote sensing estimation method based on multi-source data fusion, and the method comprises the following steps: S1, obtaining and processing total nitrogen measured data, and unifying time and a coordinate reference system; s2, processing the Landsat 8 / 9 image, and extracting water body reflectivity and remote sensing indexes; s3, ERA5-Land meteorological data are acquired, and derivation indexes are calculated; s4, DEM elevation data are extracted; s5, fusing the multi-source data to generate a table type data set; s6, screening sensitive indexes based on SHAP and correlation; s7, constructing and evaluating an inversion model; s8, extracting an MNDWI water body mask; s9, generating a feature stack and inverting and outputting a total nitrogen concentration diagram; according to the method, through fusion of multi-source data, construction of a high-precision inversion model and a cloud platform automatic processing flow, high-temporal-spatial-resolution, stable and reproducible remote sensing estimation of the total nitrogen concentration of the river is realized, and the monitoring efficiency and the application value are effectively improved.

The invention discloses a river water quality inversion and health evaluation method and system based on satellite remote sensing, terminal equipment and a medium, and relates to the technical field of environment remote sensing monitoring. The method comprises the following steps: acquiring a time-space matched multispectral remote sensing image and ground actually measured water quality parameter data set of a research area; preprocessing the image and extracting a water body area image; constructing a data sample set based on the water body area image and the water quality parameter data set; establishing a plurality of inversion models for each water quality parameter, and selecting an optimal inversion model through performance verification; and calculating a comprehensive health index and a health level of the river in the water body area through objective weight determination. According to the method, the problems of low monitoring efficiency, insufficient inversion precision and high evaluation subjectivity in the prior art are solved, efficient and accurate inversion and objective health evaluation of large-range river water quality are realized, and decision support is provided for environment management.

The invention relates to a small river habitat restoration effect evaluation method, and aims at solving the problems of habitat damage, habitat fragmentation and the like caused by hydroelectric development to formulate restoration targets of restoring river connectivity, guaranteeing ecological base flow and constructing a stable river ecosystem. The method comprises the following steps: firstly, monitoring a river, then monitoring fish resources and an ecological environment, carrying out special investigation on ecological restoration measures, and finally, constructing an evaluation index system from the dimensions of river connectivity, habitat quality, biodiversity, ecological bearing capacity and the like based on monitoring data. Scientific quantitative evaluation is realized, support is provided for engineering optimization, and river ecological protection and restoration technology development can be promoted.

The invention discloses a space remote sensing image analysis method for detecting surface water and underground water exchange in a river region based on surface temperature, and belongs to the field of remote sensing detection surface temperature anomaly analysis. According to the method, background field construction is carried out on pixels in a space by combining single-scene high-resolution surface temperature data and land cover classification data, and temperature thermal anomaly of a river main stream is extracted by adopting an adjacent pixel temperature anomaly analysis method, namely, the temperature thermal anomaly of the river main stream is extracted by analyzing subtle change of surface temperature in a remote sensing image; and identifying abnormal pixels which are obviously different from the temperature characteristics of the surrounding area. The abnormal pixels often correspond to areas where surface water and underground water exchange is active, such as permeable zones, spring water exposure points and the like. The method can be applied to drainage basin water resource management and ecological protection, and the conversion path and intensity between surface water and underground water can be deduced by further analyzing and processing the abnormal pixels extracted by the method and combining background information such as geology and hydrology.

The invention discloses a river water level inversion method taking altimeter footprint heterogeneity into consideration. The method comprises the following steps: acquiring an observation waveform of an SAR altimeter; space geometric parameters are calculated through footprint gridding and observation geometric modeling; constructing a water distribution scene based on the water mask and the river network, and classifying the water into a main river channel, a flood area and an adjacent isolated water body; electromagnetic scattering numerical integration is carried out based on the differentiated surface roughness parameters, and a simulated echo waveform is generated; waveform retracking and parameter inversion are realized through coarse grid search and local optimization solution; calculating an absolute water level and carrying out geophysical correction; performing multi-index quality control based on the interpretation rate of the analog waveform and the residual whitening degree; and finally outputting a water level product. According to the method, the defects of insufficient inversion precision and robustness of an existing method in a complex earth surface mixed scene are overcome, and the accuracy, reliability and physical interpretability of inland river water level monitoring are remarkably improved.

The invention relates to the technical field of water ecology toughness evaluation, and discloses a water ecology toughness quantitative evaluation method and device aiming at northern river characteristics, and the method comprises the steps: building a multi-dimensional mapping of a water ecology toughness evaluation dimension and a model based on a DPSIR model; constructing a three-level evaluation index system based on multi-dimensional mapping, and determining the comprehensive weight of each index; and obtaining the actual value of each index of the target river, and carrying out quantitative evaluation on the water ecology toughness of the target river based on a water ecology toughness evaluation grading standard and the comprehensive weight of each index. According to the method, a causal chain is completely described by means of a DPSIR model, typical characteristics such as flow seasonal fluctuation, freezing and ablation alternation and human interference superposition of northern seasonal rivers are comprehensively considered, research is carried out from multiple dimensions, and the ecological current situation, the recovery process and the action mechanism of drainage basin water are mastered based on a three-level evaluation index system; fragile links and key factors in the water ecological system are identified, and quantitative evaluation is carried out on the water ecological toughness.

The invention discloses a landslide catastrophe simulation and multi-parameter early warning method coupling river erosion and progressive deformation. The method comprises the steps that a rock-soil domain and a fluid domain in a model are discretized into particle sets respectively, bidirectional coupling calculation is conducted, and real-time interactive updating of the erosion rate, the pore water pressure, rock-soil deformation and the boundary form is achieved; based on the stress, strain, displacement and damage field variables obtained through calculation, multi-parameter criterion indexes of the point scale, the surface scale and the body scale are calculated in real time; and carrying out normalization and direction unification on the multi-scale criterion indexes, constructing a joint risk index through weighted fusion, and carrying out landslide early warning grade judgment according to the joint risk index. According to the method, bidirectional strong coupling numerical simulation of the whole process of river erosion, underground water seepage, rock-soil progressive deformation and large slippage is achieved for the first time, a multi-scale fusion early warning index system is constructed, and the accuracy and reliability of glide catastrophe prediction and risk early warning in the complex environment are remarkably improved.

The embodiment of the invention provides a BIM (Building Information Modeling) generation method and device for a bend revetment, equipment and a medium, and relates to the technical field of artificial intelligence. The method comprises the following steps: collecting geological data and water flow data of a river curve; analyzing the geological data and the water flow data based on a pre-constructed bank protection type analysis model to obtain a bank protection type corresponding to the river curve; based on the revetment type, the geological data and the water flow data, calculating to obtain a revetment inclination angle corresponding to the revetment type; obtaining target material information corresponding to the revetment type; and inputting the revetment type, the geological data, the revetment inclination angle and the target material information to a pre-trained BIM generation model to obtain a revetment BIM model corresponding to the river curve. According to the method, the geometric accuracy and the parameter accuracy of the bank protection BIM model are remarkably improved, the design modeling period is greatly shortened, and the construction efficiency of the bank protection BIM model is improved.

The application discloses a kind of RCBAM model construction methods of river flow remote sensing inversion, which comprises the following steps:1) collecting remote sensing image data;2) high-precision DEM production;3) river center line acquisition;4) river width and slope acquisition;5) river section shape extraction;6) flow area calculation;7) river flow estimation.The application obtains the section shape of river channel based on high-precision digital elevation model DEM, combines the instantaneous water surface information obtained from remote sensing image, dynamically calculates the river section area, effectively solves the problem that the flow area in the traditional BAM flow model relies on empirical formula to obtain, realizes the river flow estimation considering the shape characteristics of river channel, and can realize efficient and accurate river flow remote sensing inversion.

The invention discloses a complex riverway geologic modeling method based on automatic pickup of multiple object source directions, and belongs to the technical field of oil-gas exploration and development, and the method comprises the following steps: S1, obtaining the plane and longitudinal distribution characteristics of a riverway; s2, establishing a three-dimensional space distribution model of the river channel body in different periods, and processing boundary data of the river channel in different periods; s3, calling azimuth angle data to establish a sand body distribution model in the river channel in different periods; s4, single well reservoir types are divided, and reservoir type distribution models in the river channels in different periods are established; and S5, discretizing the porosity curve of the single well, calling azimuth angle data to establish porosity models under different reservoir types, and establishing permeability models under different reservoir types. According to the built river channel sand body and physical property parameter model, the situation that reservoir physical property distribution is controlled by river flow direction variability material sources is truly represented, the method is suitable for scenes with large work areas and complex river channel distribution, and modeling timeliness and accuracy can be improved.

The invention provides a multi-temporal-spatial-scale river sediment tracing method, and relates to the field of geomorphology and river dynamics. According to the method, light release light (OLS) samples of terraces and floodplains and zircon sand samples of corresponding layers are collected on the sections of a source (branch) and a sink (main stream), and different age sequences are divided in combination with contemporary zircon sand samples of a tender beach; the contribution rate of a source to a sink is directly calculated by using a zircon age spectrum matrix, and a quality contribution rate algorithm is optimized in combination with a zircon mass percentage. According to the method, contemporary and historical multi-time-scale sediment traceability is realized, the traditional fitting simulation process is simplified, the calculation efficiency and accuracy are improved, and the method is suitable for sediment source analysis in areas poor in data.

The application discloses a kind of lake total phosphorus concentration spatio-temporal evolution and driving factor identification method, and the application relates to water environment monitoring technical field, constructs water body, sediment and in and out lake river multi-medium linkage analysis system, carries out multi-scale spatio-temporal evolution analysis and multi-path mechanism quantization, realizes the accurate identification of scene main control driving factor, and the standardization analysis process is formed by verification solidification, the application has the advantages that by constructing water body, sediment and in and out lake river multi-medium linkage full-dimensional analysis system, simultaneously integrate multi-source spatio-temporal data covering full lake area function partition, complete hydrological year cycle, carry out the coupling analysis of multiple time scales and multiple spatial dimensions, break through the industry common defects that the evolution law of total phosphorus concentration is not comprehensive, data is insufficiently representative, and the whole chain variation characteristics cannot be clarified, caused by the fact that the prior art only focuses on single medium of water body, uses scattered point position low-frequency monitoring data.

The application discloses a kind of partition classification hierarchical river ecological water demand target calculation method, the method includes the following steps: step 1, collecting research area data;Step 2, the river of research area is partitioned;Step 3, the river of research area is classified;Step 4, determine ecological protection object;Step 5, ecological water demand target hierarchical calculation.The method is disclosed in the application by considering the difference of river natural conditions and human development and utilization, the river of research area is scientifically partitioned and classified, and the ecological protection object of river is reasonably determined, the hierarchical system of ecological water demand including minimum ecological flow and suitable ecological flow is proposed, the water demand of river ecological environment and economic and social development is effectively considered, the real situation of river is objectively reflected, is helpful to the implementation of ecological water demand, provides technical support for river ecological water demand management and guarantee.