266 results about "Urban water" patented technology

The invention relates to the technical field of water treatment intelligent control, in particular to an AI-based intelligent urban water purification and sewage treatment process optimization system and method, and the method comprises the steps: obtaining related sensor data information, and monitoring and recording the change of key data in real time; establishing a water quality change prediction model by using a multiple linear regression model, wherein the water quality change prediction model predicts the water quality change according to the key data change acquired in real time; the dynamic agent AI model adjusts the dosage, and the water treatment chemical / biological reaction kinetics AI model predicts the pollutant degradation condition; a local lightweight AI model optimizer and a multi-target genetic algorithm are combined with energy consumption, medicament cost, processing efficiency and carbon emission to obtain an optimal control model; the optimal control model optimizes the operation parameters of the sewage treatment process according to the pollutant degradation condition. According to the method, the operation parameters of the sewage treatment process are optimized through the optimal control model, the energy consumption, the agent cost and the carbon emission are reduced, and the treatment efficiency is improved.

The present invention relates to the field of water affair monitoring and early warning, and provides a smart urban water affair early warning system and method integrating the Internet of Things and the Internet, for solving the problems of existing urban water affair systems. The present invention comprises a sensing layer, a communication layer, a data layer and a decision-making layer. The sensing layer constructs, on the basis of the Internet of Things technology, an integrated sky-ground water conservancy Internet of Things sensing system covering water sources, pipeline tunnels, water plants, and river collection points, to collect multi-source data. The communication layer is used for sending to the data layer a large amount of multi-source data collected by the sensing layer. The data layer constructs, on the basis of the large amount of collected multi-source data, an urban water affair hydrological database, including a foundation database, a hydrological database, an engineering database, a water quality database, a management database and a remote sensing database. The decision-making layer is used for performing analysis and decision-making on the large number of multi-source data collected by the sensing layer, performing water quality prediction on all the collection points on the basis of each type of database, and when prediction results exceed a threshold, integrating a BIM platform and a GIS platform to display an alarm.

The invention discloses an urban water body pollution traceability system based on multi-source sensing data fusion, and the system comprises a data acquisition module which is used for deploying a multi-source water quality sensor to collect initial multi-source water body data, and carrying out the time-space unified alignment processing, and obtaining the time-space aligned multi-source time-space water body data; the pollution factor tracing module is used for constructing a pollution event deconstructor and a factor tracing reasoning engine based on a water network topological graph neural network on the basis of multi-source space-time water body data, and outputting pollution component vectors through pollution component decomposition driven by the pollution event deconstructor; inputting the pollution component vector into a tracing reason inference engine to carry out tracing reason space-time correlation to obtain a tracing reason pollution fusion map; and the traceability decision module is used for performing inversion through a reverse traceability algorithm based on the traceability pollution fusion map, calculating the probability that each upstream area is a pollution source, mapping the probability that each upstream area is the pollution source to a GIS platform, obtaining a pollution traceability confidence distribution map, and realizing accurate traceability of the urban water pollution source.

The invention discloses an urban ecological unit scale water conservation function evolution simulation system, relates to the technical field of ecological hydrological simulation, and is technically characterized in that the system combines an InVEST model, a water balance method, a geographic detector and a Moran index to construct a multi-source data fused water conservation evaluation method. According to the system, key factors are obtained through remote sensing data and geostatistical data, a mapping model between water yield and actually measured runoff depth is established based on a regression fitting relation, and a spatial heterogeneity analysis and factor interaction detection mechanism is introduced, so that time sequence dynamic simulation and spatial pattern recognition of a water conservation function are realized. The system can be widely applied to the fields of urban water resource regulation and control, ecological space planning, hydrological safety evaluation and the like.

The invention relates to the technical field of water resource scheduling, and provides an urban inland river system intelligent resource scheduling management system and method based on dynamic data collaboration, and the method comprises the following steps: S1, collecting river hydrological data, water quality indexes, urban water demands and water transfer facility state data in real time, and carrying out the time-space alignment and abnormal value filtering; s2, a hydrodynamic force-water quality coupling model of multiple water sources is established, a multi-objective optimization model is established in combination with constraint conditions of ecological base flow and an engineering upper limit, and the multiple water sources include but not limited to river water, underground water, reservoir water, reclaimed water, rainwater and desalinated seawater; and S3, carrying out global dynamic optimization on the water transfer proportion and the water transfer facility parameters by adopting a model algorithm, and minimizing the water transfer cost and the ecological influence. By quantifying the maximum flow upper limit and the ecological base flow threshold value of each water source and optimizing the water transfer proportion and facility parameters, the water resource utilization efficiency is improved, and it is guaranteed that the water transfer cost and the ecological influence are balanced in the urban river water dispatching process.

The invention relates to the technical field of water affair pipe network operation and maintenance, in particular to an intelligent analysis processing and decision support method for mass data of an intelligent water affair integrated platform based on a GIS (Geographic Information System) and the Internet of Things. According to the method, GIS topology and data of the internet of things are fused, the problems that the estimation deviation of the influence range of traditional pipe explosion is large, and the valve closing instruction lacks accuracy are solved, and the valve closing effectiveness is verified. The pipe explosion emergency response efficiency is improved, the water resource waste is reduced, the water supply stability is guaranteed, and the method is suitable for urban water refinement management.

The invention discloses a non-point source pollution and waterlogging collaborative four-pre management and control system based on short temporary rainfall forecast, which relates to the technical field of urban water environment management and comprises a short temporary rainfall forecast module, a non-point source pollution control module, a waterlogging management module, a four-pre management and control platform, an intelligent decision support system, a real-time monitoring and feedback system and a water ecological management module. By integrating meteorological monitoring, hydrological monitoring and environment monitoring data, high-precision short and temporary rainfall forecast is realized by using a machine learning algorithm, the operation strategies of the intelligent catch basin and the initial rain storage pond are dynamically adjusted to control non-point source pollution, and meanwhile, the waterlogging risk is predicted and preventive measures are taken in combination with real-time hydrological data. According to the technology, integrated management of forecasting, early warning, rehearsal and plans is achieved through a four-pre-management and control platform, an intelligent decision support system, a real-time monitoring and feedback system and a water ecological management module under the sponge city design concept are used in an auxiliary mode, and the efficiency and effect of urban water environment management are comprehensively improved.

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 factory network river-lake integrated scheduling method and system based on a butterfly optimization algorithm, and solves the problems that resource scheduling is not systematic and the optimization effect is poor in urban water environment management. The method comprises the following steps: firstly, collecting and sorting data information such as a rain sewage pipe network, pump gate characteristics and a water system in a research area, constructing one-dimensional and two-dimensional hydrodynamic models, and simulating dynamic behaviors of a drainage system; on the basis, a meta-heuristic butterfly optimization algorithm is adopted to construct an optimization scheduling model, and an optimization scheme conforming to a scheduling target is generated through the steps of population initialization, fitness calculation, iterative search of an optimal solution and the like. In the optimization process, scheduling parameters are adjusted in combination with real-time monitoring data, and the effectiveness and practicability of the scheme are ensured.

The invention discloses a multi-dimensional drainage port overflow risk assessment system and assessment method, and belongs to the technical field of drainage port overflow risk assessment systems, and the system integrates ground monitoring and satellite remote sensing multi-source data, and collects related information of a drainage port in an omnibearing manner. The ground monitoring data provides accurate local hydrology, water quality and drainage facility operation state information, the satellite remote sensing data realizes large-range monitoring, the advantages of the ground monitoring data and the satellite remote sensing data are complementary, the data are fused through a weighted average method and a Kalman filtering method, the data accuracy and reliability are improved, and the weighted average method distributes weights according to data characteristics for preliminary fusion, so that the accuracy and reliability of the data are improved. The Kalman filtering method adapts to data dynamic change, such as water level data fusion according to a state equation and an observation equation optimization result, combines the advantages of ground high-precision monitoring and satellite wide-range coverage, accurately reflects water level change, quantifies the overflow risk of a drainage port, and provides effective support for urban water fine supervision.

The invention provides an urban water network drainage joint scheduling method and system, and relates to the technical field of urban flood control and drainage, and the method comprises the steps: carrying out the fusion processing of multi-source monitoring data, and obtaining a feature vector; inputting the feature vector into a runoff prediction model for runoff prediction to obtain a comprehensive runoff prediction result; based on the comprehensive runoff prediction result, pipe network water flow and surface accumulated water simulation is conducted through a drainage hydraulic model, and a target simulation result is obtained; performing waterlogging risk assessment based on the target simulation result and the monitoring data to obtain a waterlogging risk level; selecting a corresponding scheduling generation mode based on the weather forecast data, the monitoring data and the waterlogging risk level; and determining a corresponding scheduling strategy based on the selected scheduling generation mode and the waterlogging risk level. According to the urban water network drainage joint scheduling method and system provided by the invention, accurate prediction simulation and scientific scheduling are realized, and the drainage efficiency is further improved.

The invention relates to the technical field of remote sensing spectrums, in particular to an urban black and odorous water body recognition method and system based on remote sensing spectrums. The method comprises the following steps: acquiring infrared spectrum and visible spectrum data based on a remote sensing satellite or an unmanned aerial vehicle, processing the data, eliminating noise and abnormal values in the data, and extracting spectral features to obtain a spectral feature data set; according to the invention, through infrared and visible spectrum data collected by a remote sensing satellite or an unmanned aerial vehicle and through combination with urban water body data of a geographic information system, the dimension and quality of the data are improved, so that monitoring of the urban black and odorous water body is not limited to surface coverage, and sensitivity of data analysis can be accurately regulated and controlled by dynamically adjusting a spectrum band weight; the method has the advantages that the method adapts to variable environmental conditions, recognition precision of various polluted water bodies is improved, continuity and accuracy of long-term monitoring are guaranteed by continuously updating and optimizing the processing flow, and urban water quality management and decision-making processes are effectively supported.

The invention belongs to the technical field of water resource monitoring, and particularly relates to an urban water environment quality evaluation and assessment method based on an automatic monitoring network, which comprises a water quality monitoring module, a parameter preprocessing module, a comprehensive quality calculation module, a water quality analysis module, a long-acting management module and a closed-loop optimization module. According to the method, parameter weights are dynamically distributed through ecological influence, evaluation deviation caused by traditional fixed weights is avoided, and the scientificity of water quality index calculation is improved; a monitoring-analysis-management and control-optimization whole process is closed-loop, and a long-acting management cycle is formed by combining hierarchical management and control such as III-class limited rectification, IV / V-class production halt management and quarterly strategy updating; a multi-level monitoring network architecture is adopted, real-time monitoring data, seasonal factors and public feedback are integrated, and data comprehensiveness and credibility are enhanced; a pollution hotspot map is matched through five-level water quality labels, a pollution source is quickly positioned, and differentiated treatment decisions are assisted.

The invention discloses an urban scale rainfall absorption and vegetation configuration collaborative optimization evaluation method, which belongs to the field of urban rainfall flood management optimization, and comprises the steps of performing integration and rainfall event identification on basic data of an urban region; physical mechanism inference is carried out by constructing multiple physical gating such as energy consistency, wet surface dissipation and geometric radiation sensitivity, and underlying surface hydrological response characteristics are obtained; constructing and solving a robust optimization model in combination with the underlying surface hydrological response characteristics and a preset planning target, and determining an optimal vegetation configuration scheme; and carrying out back substitution on the optimal vegetation configuration scheme to carry out closed-loop check and effect evaluation. According to the method, the hydrological response characteristics of the urban underlying surface can be accurately quantified, the vegetation configuration scheme with the definite achievement probability and the controllable risk is formulated under the uncertain condition, and the scientificity and the reliability of urban water resource toughness planning are improved.

The invention discloses a variable weight-based urban water supply deep learning prediction method and system, and the method comprises the steps: obtaining the historical data of an urban water plant, and carrying out the data preprocessing, and obtaining the preprocessed historical data of the urban water plant; performing sample weight calculation based on time according to the preprocessed urban water plant historical data to obtain an urban water plant historical data sample weight value; based on a long-short-term memory neural network, urban water plant historical data sample weight values are introduced, and a long-short-term memory network model based on variable weights is constructed; and performing water supply prediction on the preprocessed historical data of the urban water plant based on a variable-weight long-short-term memory network model to obtain an urban water supply prediction result. According to the embodiment of the invention, the prediction precision of the water supply demand in the peak period can be improved, so that the prediction precision of the peak water demand can meet the actual scheduling demand. The method can be widely applied to the technical field of urban water supply and drainage prediction.

The invention discloses an urban multi-water-source joint scheduling method based on a discrete scene set and a robustness decision, and the method comprises the steps: researching the characteristics of multiple uncertainty factors of urban multi-source water supply, and generating a multiple uncertainty scheduling scene set through a Latin hypercube sampling method; constructing a water supply city regulation and storage reservoir and external water source joint scheduling model and a water receiving unit internal optimization scheduling model; and constructing a robustness decision-making-based urban annual multi-water-source combined scheduling model. A multi-uncertainty scene set and a robustness measurement method based on an expected benefit index are utilized, the minimization of the annual water level fluctuation risk and the urban water shortage risk of a regulation and storage reservoir is taken as a scheduling target, an urban multi-water-source combined scheduling model based on a robustness decision is constructed, the rationality and the applicability of the robustness scheduling model are verified, and the urban multi-water-source combined scheduling model is established. And analyzing a robust decision scheduling result under an uncertain condition.

The invention provides a smart city water supply pipe network emergency supervision Internet of Things large model system and method, and relates to the field of city water pipe monitoring, and the system comprises a government supervision management platform, a government supervision sensing network platform, a government supervision object platform, a water affair company sensing network platform, and a smart water affair equipment object platform. The government supervision and management platform is configured to determine time sequence flow corresponding to the multiple water pipe node groups based on water flow characteristics of the multiple water pipe nodes in the water supply network; based on the time sequence flow, determining water and soil loss coefficients corresponding to the one or more target areas; based on the water and soil loss coefficient, temporary control parameters are generated through a parameter generation model; and on the basis of the temporary control parameters, the valve opening degrees of the corresponding valves in the one or more target areas are controlled. The system can determine the control parameters of the adjusting device according to the water and soil loss coefficient of the target area, and realizes informatization and intelligence of urban water pipe emergency monitoring.

The invention discloses an urban water supply pipe network leakage detector and a detection method, and relates to the field of municipal engineering. A leakage detector for an urban water supply pipe network comprises a circular sealing cover composed of two semicircular sealing covers, the circular sealing cover is arranged at a connector between every two water supply pipes in a sleeving mode, and the two semicircular sealing covers are detachably connected through fixing bolts; the semi-circular sealing plate is arranged in the semi-circular sealing cover and is used for blocking a joint between the two water supply pipelines when water leaks; by means of the emergency plugging function, water can be timely prevented from continuously leaking at the initial stage of water leakage at the pipeline connecting position, compared with a traditional mode that only detection is conducted without pretreatment, waste of water resources is greatly reduced, and the urban water saving concept and the efficient utilization requirement of the water resources are met.

The invention discloses a water quality comprehensive measurement method based on water quality-algae coupling analysis, and belongs to the field of environmental sciences, the method establishes a progressive water quality grading path by constructing AT (unit mass algae apparent turbidity) and ADI (typical algae dominance) double indexes and combining sensory (Tur), nutritive salt (TN, TP), organic matter (DO, CODmn) and algae response (Chla, AT, ADI) characteristics, and the water quality comprehensive measurement method based on the water quality-algae coupling analysis is realized. The water quality deterioration trend can be quickly identified. The method integrates water quality and algae response characteristics, breaks through the limitations that a traditional water quality evaluation standard neglects water quality deterioration and biological indexes, an evaluation method lacks pertinence and neglects an advanced monitoring technology and the like, and lays a theoretical foundation for water environment monitoring and evaluation system research. When the method is applied to urban water, rapid grading quantitative evaluation of comprehensive grade and deterioration trend of water quality can be realized, and accurate and efficient management of a water environment system is greatly promoted.

The invention relates to the field of water quality detection and analysis, in particular to a water quality detection method, device and equipment and a storage medium. The method comprises the following steps: performing multispectral remote sensing scanning on a to-be-detected urban water body to generate a standardized water body spectral image; performing mixed pixel component decomposition on the standardized water body spectral image, performing concentration spatial distribution calculation, and constructing a multi-pollutant concentration distribution diagram; a concentration diffusion rule is obtained based on pollutant motion vector estimation of the multi-pollutant concentration distribution diagram; collecting topographic surveying and mapping data of the urban water body, positioning and tracing potential pollution sources, and marking the positions of the potential pollution sources; and performing water pollution diffusion prediction calculation according to the concentration diffusion rule and the potential pollution source position, performing pollution risk comprehensive analysis, and generating a pollution risk analysis report. Through non-contact spectral image analysis, the water quality pollution concentration and distribution are accurately analyzed and calculated in real time.

The invention discloses a disaster avoidance place starting and path planning decision-making method considering an urban water affair system. The method comprises the steps of obtaining rainfall updating forecast data under a rainfall event in a target area; establishing a decision scene: establishing an urban inland inundation simulation model through the urban water affair data, inputting rainfall update forecast data into the urban inland inundation simulation model to generate a submerging scene, obtaining spatial and temporal distribution of evacuation demands of disaster victims in each building, and obtaining a function change condition of a road network; constructing a multi-stage update evacuation decision framework: considering the cost of disaster avoidance places and the transfer risk of disaster victims, constructing a dual-objective optimization mathematical model, and updating the solving result of the dual-objective optimization mathematical model; and carrying out path planning on the disaster victims needing to be transferred so as to obtain an optimal transfer path. According to the method, the cost of a disaster avoidance place and the transfer risk of disaster victims are balanced, the inherent error in rainfall forecasting is solved, and the decision is dynamically optimized in the process that rainfall information is gradually clear as time goes on.

The invention discloses a tunnel, bridge and culvert water level detection and alarm system and method based on deep learning, and the method comprises the following steps: S1, collecting an image and a capacitance water level signal at the lowest point of a tunnel or an easy water accumulation region, and generating standardized multi-source data; s2, inputting the image into a SegmentAnything model, extracting a water body mask, and calculating an image water level value in combination with scale mapping; s3, carrying out confidence weighted fusion on the image water level and the capacitance signal to obtain a fused water level value; s4, constructing a fused water level time sequence, constructing an SCI Net model, and outputting a predicted water level sequence; s5, generating an alarm label according to the fused water level and the prediction result; s6, LED display and acousto-optic response are controlled according to the alarm label, and an early warning prompt is started when a serious alarm is given; s7, capturing an image in an early warning or serious alarm state, and generating an alarm data packet; and S8, uploading to an urban water level monitoring platform through the Internet of Things module. According to the invention, intelligent identification and remote early warning of the ponding state of the tunnel bridge and culvert are realized.

The invention provides a method, a device and equipment for determining a toughness index of an urban water environment, and belongs to the technical field of urban toughness calculation. The method for determining the toughness index of the urban water environment comprises the following steps: determining risk levels corresponding to M time periods according to hydrological data of a target urban area in the M time periods; according to the water quality data of the target city region in the M time periods, obtaining respective water quality indexes of N predetermined risk grades; and determining the toughness index of the water environment of the target urban area according to the respective water quality indexes and hydrological indexes of the N predetermined risk grades. The toughness index of the water environment determined by the method provided by the invention is more accurate, and the practicability and operability are high.

The invention discloses an urban water collection capability evaluation system and method based on ecological data analysis, and relates to the technical field of urban water collection. Comprising the following steps: a soil information acquisition module divides a to-be-evaluated region into sub-regions, acquires soil feature information and calculates a soil water holding capacity index; and the water holding capacity analysis module is combined with the average vegetation coverage density and the soil permeability to correct the water holding capacity index of the soil. The evaporation potential analysis module is used for calculating the water evaporation capacity and generating an evaporation potential index based on the maximum bearing volume of the water body and the meteorological parameters. And the terrain factor analysis module corrects the evaluation coefficient and considers the ground average slope angle. And the catchment capability evaluation module dynamically adjusts a catchment capability evaluation threshold according to the average rainfall and the soil humidity, and finally generates an urban catchment capability evaluation result. The system improves the adaptability and effectiveness of urban catchment capacity evaluation.

The invention relates to the technical field of intelligent water affairs, in particular to a three-level combined processing method for urban water consumption prediction, which comprises the following steps: S1, data restoration: correcting abnormal values in an urban water consumption time sequence by using a dynamic threshold correction method based on multi-scale wavelet decomposition; s2, performing feature decoupling; and S3, performing prediction fusion. According to the method in the technical scheme, a dynamic threshold correction method based on multi-scale wavelet decomposition is adopted, signal hierarchical analysis is achieved through discrete wavelet transformation, a dynamic threshold mechanism is constructed in combination with MAD robust statistics, and abnormal points are effectively recognized and corrected; constructing a dynamic frequency band division joint model of variational mode decomposition and spectrum energy balance, proposing a dynamic frequency band recombination strategy guided by amplitude ranking, and performing energy balance division and inverse transformation reconstruction on VMD high-frequency sub-components through fast Fourier transform spectrum analysis; fine separation and multi-band phase synchronization of high-frequency abrupt change characteristics and periodic fluctuation are realized; and finally, constructing a long-short-term memory network to predict and reconstruct all sub-components.

The invention belongs to the technical field of water affair management, and relates to an urban water plant water supply balance automatic scheduling method and system. According to the method, the water pressure value of each monitoring point in the water supply network and the water consumption of the water metering unit are collected in real time, the water time sequence characteristics are extracted to identify the potential peak period, and the validity of the peak period is verified by combining the correlation between the water pressure and the water consumption; performing region division and water consumption aggregation based on peak period distribution and a pipe network topological structure, calculating water consumption deviation of adjacent regions, and when the deviation exceeds a historical synchronous fluctuation range, dynamically generating a target water supply pressure value and issuing a scheduling instruction; and evaluating the balance state of the water pressure and the water consumption between the areas after scheduling by executing the feedback data. According to the method, the problems of response lag and regional supply and demand imbalance in traditional scheduling are solved, accurate regulation and control of the water supply pressure and regional water consumption balance in the peak period are achieved, and the stability and the energy efficiency level of a water supply system are improved.

The invention provides a novel sponge city rainwater recycling system, and belongs to the technical field of urban rainwater management and resource utilization. According to the system, rainfall intensity, soil humidity, water quality, underground water level and other data are collected in real time through an intelligent integrated monitoring layer and uploaded to a central intelligent management system; the dynamic permeation adjusting layer utilizes a nanoscale intelligent permeation material and a self-adaptive permeation algorithm to adjust the permeation rate according to monitoring data and optimize surface runoff and groundwater supply; the intelligent water collection and pretreatment layer is combined with a deep learning water level prediction algorithm to realize efficient water collection and water quality pretreatment; the water quality purification and recycling layer adopts an advanced treatment technology to ensure that the effluent quality meets the urban water standard; and the intelligent water resource distribution and reuse layer dynamically optimizes a water resource distribution strategy through an ensemble learning and demand prediction algorithm to meet the demands of different water use departments. According to the system, efficient collection, purification and resource utilization of rainwater are achieved, and the intelligent level of urban water resource management is improved.

The invention discloses a dynamic simulation cooperative regulation and control method for an urban water system. Comprising the following steps of demand analysis and target setting, data collection and analysis, modeling and simulation, simulation analysis and verification, collaborative regulation and control strategy making, implementation and monitoring, and evaluation and improvement. In a demand analysis and target setting stage, key problems are identified through investigation and research, and water-saving, energy-saving and carbon emission reduction targets are set. In the data collection and analysis stage, data of water resources, energy consumption and carbon emission are collected, processed and analyzed. In the modeling and simulation stage, multi-agent modeling and system dynamics modeling are adopted, and an urban water system dynamic simulation platform is constructed. In the simulation analysis and verification stage, simulation models under different scenes are operated, the accuracy and reliability of the models are verified, the simulation models and regulation and control strategies are optimized, efficient utilization of urban water resources is achieved, energy consumption and carbon emission are reduced, and sustainable development of the urban ecological environment and social economy is promoted.

The invention relates to the technical field of urban life facility efficiency evaluation, and discloses an urban wading infrastructure efficiency evaluation method, device and equipment and a storage medium. The current data of each index of a to-be-evaluated urban wading infrastructure in a current stage and the prediction data of each index in a future planning stage are acquired; the two types of data are integrated to construct an index data set, and the states of the urban wading infrastructure in different stages are comprehensively reflected. According to the method, the index data set is subjected to two-dimensional division of the time dimension and the wading period dimension, a whole-process index system is constructed, all links and all stages of the urban wading infrastructure can be comprehensively covered, and the problem that in the prior art, the assessment dimension is single is solved. According to the method, the characteristic correlation factor is introduced into the DEA model objective function and the slack variable upper limit constraint is set, so that the complex relationship between the urban wading infrastructure indexes can be accurately quantified, the slack variable is prevented from being excessively amplified, and the accuracy of the evaluation result is improved.

The invention discloses a composite index-driven urban water body health measurement method, which belongs to the field of environmental sciences, and constructs a new index system comprising 12 composite indexes such as algae apparent turbidity, water body algae primary productivity, oxygen dynamic equilibrium index, multi-element spectrum blotting and the like; aiming at the complexity of the urban water body, the invention provides the urban water body health measurement method driven by the composite indexes by taking the composite indexes and the key water quality indexes as elements, taking the water body nutrition level, the water body cleanliness degree and the ecosystem elasticity as key dimensions and taking self-adaption and quick response as cores. According to the method, the limitations of water quality and biological index separation, evaluation and early warning separation, lack of pertinence of an index system, incapability of feeding back internal optimization, neglect of an advanced monitoring technology and the like of a traditional urban water environment evaluation method are broken through, and a theoretical foundation is laid for water ecology monitoring and evaluation system research; the method is applied to urban water to realize rapid grading quantitative evaluation of the water ecological health state.