11555 results about "Water resources" patented technology

The invention provides an intelligent ecological restoration system, method and device for a high and steep slope of a strip mine in an arid region. Comprising a data acquisition layer which realizes real-time acquisition of multi-dimensional environmental data through InSAR satellite remote sensing, a ground sensor network and unmanned aerial vehicle multispectral imaging; the transmission layer adopts LoRa and 5G hybrid networking; the platform layer is used for constructing a slope stability prediction and restoration scheme optimization platform based on a digital twinborn model and a deep learning algorithm; and the application layer is used for remotely controlling the repairing device through a mobile terminal and a Web terminal and monitoring the repairing progress in real time. The problems that a traditional restoration technology is poor in adaptability, low in vegetation survival rate, high in ecological restoration cost, insufficient in monitoring technology application, insufficient in monitoring feedback mechanism, insufficient in intelligence, long in ecological restoration period and the like are solved.

The invention relates to a high and cold wetland dynamic monitoring and health evaluation method and system based on multi-source remote sensing. The method comprises the following steps: step 1, data acquisition and preprocessing; step 2, multi-modal data feature extraction; step 3, performing multi-modal data fusion; step 4, dynamic monitoring; step 5, evaluating wetland health; according to the invention, the calculation method of the SAR polarization decomposition model and the optical wetland index is optimized due to the unique seasonal change and earth surface complexity of the high and cold wetland, a scientific basis is provided for the management of the wetland protection area, and the ecological restoration efficiency is improved; alpine region water resource management and ecological protection policy making are supported; and data support is provided for researching the wetland carbon sink function and the climate change influence.

The present invention relates to the technical field of land engineering, and relates to a water and soil resource comprehensive improvement method for loess hilly and gully region channels. The method comprises: (1) soil layer general survey: performing soil layer thickness survey and soil nutrition content measurement; (2) soil body reconstruction: on the basis of soil layer general survey data, selecting a soil body construction mode, and performing soil body profile reconstruction, soil body nutrition reconstruction and field parcel arrangement; and (3) constructing a water resource regulation and control system for the loess hilly and gully region channels. According to the present invention, investigation and survey are performed firstly, then treatment is performed, water and soil are treated simultaneously, and steps are coordinated, so that ecological treatment of the loess hilly and gully region channels is finally completed, and comprehensive improvement of water and soil resources is achieved. The present invention ensures mechanical cultivation of the region after the improvement, effectively increases the area of the irrigable land and the area of the non-irrigated land, effectively improves the farmland quality and the grain yield, and effectively reduces the soil erosion amount of the channels.

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 discloses a reservoir scheduling decision support system for multi-objective optimization, and relates to the technical field of hydraulic engineering scheduling. According to the system, comprehensive optimization of flood control, power generation and ecological targets is realized through cooperative work of the multi-source dynamic constraint analysis module, the collaborative optimization module, the scheduling module and the correction module. A dynamic constraint boundary table is generated by collecting meteorological, hydrological and ecological data in real time. And matching a multi-target coordination rule through a physical constraint double-depth network algorithm, generating a Pareto feasible solution set, and mapping the Pareto feasible solution set into a coordination strategy of flood discharge flow and power generation output. In combination with a hydraulic model, flood control and power generation weights are adjusted, an executable dispatching instruction is generated, it is ensured that the ecological flow reaches the standard, and the influence of a downstream submerged area is optimized. And correcting the dynamic constraint boundary table according to actual monitoring data, and continuously optimizing a scheduling decision. Accurate management and multi-objective optimization of reservoir dispatching are realized, and the utilization efficiency of water resources is improved.

The invention belongs to the technical field of hydrology and water resource intelligent management, and discloses an inter-basin water resource system cooperative scheduling and forward-reverse bidirectional coupling dynamic decision method and system, and the method comprises the steps: S1, constructing a multi-modal water conservancy infrastructure topological relation graph, and carrying out the bidirectional conduction optimization; s2, sensing hydrological gap risk situation and analyzing multi-source water supply potential coupling based on the multi-modal water conservancy infrastructure topological relation map and optimized bidirectional conduction; s3, based on hydrological gap risk situation and multi-source water supply potential coupling, generating an elastic grading water quantity distribution strategy and a cross-engineering replacement protocol; and S4, constructing and optimizing a positive-negative two-way rehearsal decision engine based on an elastic grading water distribution strategy and a cross-engineering replacement protocol. The technical problem that a traditional one-way scheduling model is difficult to deal with complex topological relations, sudden water shortage events and cross-administrative-region collaboration is solved.

The invention relates to the technical field of town sewage pipe network detection, and discloses a town sewage pipe network leakage detection system and method. The system comprises a data acquisition module which uses a multi-source sensor to acquire real-time operation data such as pipe network pressure, flow and the like; the feature extraction module extracts spatio-temporal features based on the multi-scale convolutional neural network, and generates a pipe network state feature matrix; the anomaly detection module inputs the feature matrix into a pre-training model and marks a potential leakage area; the optimization analysis module constructs a multi-constraint dynamic optimization model, and pipe network pressure parameters are optimized by using an adaptive particle swarm algorithm; the hierarchical execution module generates a global regulation and control sequence, dynamically matches local pressure parameters and adjusts the valve opening and the pump station power through a decision layer, a region coordination layer and an execution layer. The system and the method are accurate in detection and reasonable in regulation and control optimization, leakage risks can be effectively reduced, the operation management level of a pipe network is improved, and water resource waste and environmental pollution are reduced.

The invention discloses a concrete curing device for constructional engineering, and belongs to the technical field of constructional engineering. The device comprises the following modules: a data acquisition and sensing module for acquiring real-time parameters of the interior and surface of concrete through a temperature and humidity sensing network and a plurality of detection devices so as to support subsequent data analysis and decision; the internal temperature control execution module is used for controlling the internal temperature of the concrete through a snake-shaped cooling pipeline and precise flow regulation and maintaining the concrete within a proper curing temperature range; the surface curing execution module is used for continuously curing the concrete surface, and all-directional spraying of concrete surface curing moisture and cyclic utilization of water resources are achieved; the central control module is responsible for data analysis, maintenance decision optimization and execution instruction distribution, and intelligent control and remote monitoring of the maintenance process are achieved; and the performance evaluation module monitors the concrete strength development in real time, evaluates the maintenance effect, provides trend analysis and optimization suggestions, and provides a basis for continuous improvement of a maintenance decision.

The invention relates to the technical field of drainage basin water scheduling, and discloses a drainage basin water regulation and control optimization method based on ecological element changes. The method comprises the following steps: deploying a drainage basin monitoring system, and collecting ecological element real-time data such as a hydrological parameter sequence and a remote sensing image; after the data is cleaned and converted, hydrological trend features and spatial distribution features are extracted by adopting a feature learning model, and the hydrological trend features and the spatial distribution features are fused into unified ecological representation through a cross-modal alignment mechanism; inputting the unified ecological representation into a physically constrained neural network prediction model, and outputting a water regimen dynamic prediction value; and finally, based on the predicted value, a water resource regulation and control instruction is generated and executed by using a multi-objective decision algorithm so as to optimize the watershed water circulation process. According to the method, feature extraction comprehensiveness is improved through multi-source data fusion and cross-modal analysis, prediction reliability is enhanced in combination with physical constraints, reasonable allocation of water resources is achieved by means of multi-target decision, the ecological condition of a drainage basin can be improved, and the water utilization efficiency is improved.

The invention provides an underground water dynamic evolution prediction method, and belongs to the technical field of underground water prediction based on deep learning. Hydrological parameters and geographic position data of monitoring points are collected, and a regional hydrogeological input tensor is constructed; then establishing an initial finite element model to carry out space extrapolation and flow field completion on underground water level distribution; based on an initial finite element model structure, designing a global optimization algorithm based on target decomposition, carrying out real-time structure optimization on the finite element model, then simulating underground water evolution of a non-monitoring area through a finite element numerical solution, and generating multi-node physical consistency hydrological time series data after resolution is improved; and inputting the generated hydrological time series data into a designed perceptual water level prediction model, and outputting underground water level prediction results at multiple moments and multiple positions in the future and corresponding underground water level thermodynamic diagrams. According to the method, more accurate, continuous and interpretable high-precision prediction of the underground water system is realized, and reliable support is provided for scientific management of underground water resources.

The invention relates to the field of river and lake water quality monitoring, and discloses a river and lake remote sensing monitoring multi-source data fusion and analysis method, which comprises the following steps: firstly, collecting satellite remote sensing images, unmanned aerial vehicle aerial images and ground monitoring station data of a river and lake area, and preprocessing to form a feature data set; and then, constructing an image classification model based on a convolutional neural network (CNN), a water quality evaluation model based on a support vector machine (SVM) and a water quality prediction model based on time sequence analysis, and respectively classifying, evaluating and predicting water quality. And finally, by defining a multi-source data fusion algorithm, carrying out fusion analysis on a model output result, obtaining a comprehensive water quality evaluation result, and generating a river and lake remote sensing monitoring report. The advantages of multiple data sources are fully utilized, comprehensive, rapid and accurate monitoring of the water quality of rivers and lakes is achieved, powerful support is provided for environmental protection and water resource management, and the method has wide application prospects and important practical value.

The invention discloses a flexible load multi-target collaborative scheduling system and method, and relates to the technical field of collaborative optimization of power systems. The method is used for solving the problem of lack of accurate prediction and multi-target coordination of agricultural electricity and water utilization regulation and control. Firstly, based on meteorological data, soil moisture content and crop growth characteristics, an irrigation demand prediction model is constructed, irrigation water demand is predicted, and a water pump load power baseline is generated; then, a dynamic baseline constraint condition is generated in combination with historical behavior data and water pump start-stop logic; establishing a power grid side objective function, a user side objective function and a water affair side objective function, and introducing an underground water and carbon emission punishment mechanism; thirdly, dividing the power distribution network into sub-regions, adopting an alternating direction multiplier method to solve a region regulation and control strategy in parallel, coordinating water resource distribution conflicts through virtual interactive variables, and outputting a global scheduling instruction; and finally, collecting real-time response data and correcting the prediction model on line to realize closed-loop adaptive optimization.

The invention discloses a water flow intelligent monitoring system and method, and relates to the technical field of water flow intelligent monitoring, in combination with an actuator health degree evaluation and multi-target prediction control method, the characteristics of a valve and a water pump are finely described by arranging sensors and constructing a digital twinborn model; model predictive control or multi-agent reinforcement learning is adopted to dynamically generate a reliable and efficient control instruction; furthermore, through real-time closed-loop deviation detection and self-adaptive correction, delay, faults or communication abnormity of the actuator can be accurately dealt with; 4, quickly completing self-healing and fault-tolerant control by using a fault prediction and standby scheduling strategy to prevent failure diffusion; and 5, scenes such as rainfall flood, fire fighting and reclaimed water are incorporated into the same framework, and multi-scene coupled comprehensive water resource management is realized, so that water hammer impact and water leakage risks can be effectively reduced, and the safety of the water supply system under complex working conditions or equipment aging is remarkably improved.

The invention discloses a cascade reservoir optimization regulation and control method based on nitrogen and phosphorus circulation of a water body, and relates to the technical field of water resource management optimization. Multi-dimensional data of a gradient reservoir is collected, and a time-space aligned multi-modal data set is constructed; according to a biogeochemical process of nitrogen and phosphorus circulation, a physical equation of the nitrogen and phosphorus circulation is deduced, and a physical constraint loss item is designed and is subjected to weighted combination with data driving loss to form a mixed loss function. According to the method, the physical constraint neural network model is constructed, and the physical equation of nitrogen and phosphorus circulation is embedded into the neural network loss function, so that the strong fitting capability of the data driving model is utilized, and the model output is ensured to accord with the biogeochemical law through the physical constraint; the key parameters of the physical equation are calibrated through the Bayesian optimization algorithm, the prediction precision of the model on the nitrogen and phosphorus migration and transformation process is further improved, the dependence on big data is effectively reduced, and a reliable prediction result can still be provided especially under the condition that the temporal-spatial resolution of data is low.

The invention relates to the field of hydrology and water resource management and karst hydrodynamics, and discloses a karst basin coupling hydrology model prediction method, which comprises the following steps: S1, collecting and standardizing multi-source heterogeneous monitoring data of a karst basin; s2, constructing a hydrological model for dynamic coupling of surface runoff, fracture seepage and a pipeline network; s3, performing global optimization on the multi-dimensional hydrological parameters by adopting a hybrid intelligent optimization method; s4, performing iterative correction on the model based on a multi-level verification system; and S5, outputting a hydrological prediction result and generating disaster early warning information. By adopting a dynamic adjusting technology of karst area underground river and surface water flow network joint modeling, multi-karst water-containing medium characteristic analysis and integration of underground river and surface water system response characteristics, the problems that a traditional method cannot accurately predict underground water flow and flow velocity, and is difficult to deal with complexity of a karst water system, lack of data and the like are solved.

The invention discloses a digital twinborn-based irrigation area water distribution scheduling method and system, and relates to the technical field of water distribution scheduling, and the method comprises the steps: collecting data, and constructing a digital twinborn model; dynamically simulating water resources in an irrigation area by using a hydrological model simulation technology based on a digital twinborn model; performing irrigation demand prediction by using a machine learning algorithm according to a simulation result; optimizing a water distribution scheduling model according to a prediction result; performing real-time scheduling control according to the scheduling strategy; performing scheduling effect evaluation according to the scheduling control data; adjusting a scheduling strategy according to an evaluation result; and performing irrigation area water resource management and long-term optimization by using an irrigation area water distribution scheduling system based on digital twinning according to an adjustment result. According to the method, the limitation of static weight distribution of a traditional method is overcome, the accuracy and flexibility of water distribution scheduling are improved, the actual requirements of a complex irrigation area environment are met, the maintenance cost and the operation risk are reduced, and efficient and stable operation of an irrigation area water distribution system is guaranteed.

The invention provides a mine water disaster monitoring and early warning method and system based on multi-source heterogeneous data fusion, and the method comprises the steps: collecting multi-source data of a mining area, carrying out the time-space alignment of the multi-source data, and generating a data set, the multi-source data comprising remote sensing data; preprocessing the data, inputting the preprocessed data into a multi-modal fusion network, and extracting surface water body distribution, lithologic permeability, underground water level and structural fracture characteristics to obtain a three-dimensional hydrogeological static model; the hydrological numerical model based on physical driving is coupled with the static model, and the dynamic model is used for simulating the dynamic change of an underground water flow field and a pollutant diffusion path; based on the dynamic model updated in real time, multi-target collaborative evaluation is carried out to evaluate the mining area water resource, ecological and social collaborative effect; and calling an unmanned aerial vehicle to inspect a leakage position or a settlement position in the hydrogeological risk map based on a multi-target collaborative evaluation result. According to the method, the prediction accuracy is improved through the multi-source data.

The invention discloses an AI intelligent collaborative monitoring management system for a multi-index water volume system, and relates to the technical field of monitoring management, the collaborative monitoring management system comprises a data acquisition module, a water volume system analysis module, a collaborative monitoring module, an emergency early warning module, an early warning scheme module and a data visualization module, all the modules are connected through electric signals. According to the AI intelligent collaborative monitoring management system for the multi-index water volume system, abnormal changes in water quality, water volume and water ecological indexes are identified through anomaly detection, an early warning mechanism is triggered according to the detected anomaly, early warning information is sent to management personnel through various modes such as a visual interface, a short message and an email, and the management personnel can carry out early warning on the water quality, the water volume and the water ecological indexes. According to the invention, the time interval from the occurrence of the abnormity to the discovery of the abnormity is greatly shortened, and valuable response time is provided for managers, so that further deterioration of the abnormity is effectively restrained, and the safety and sustainable utilization of water resources are guaranteed.

A fuzzy cloud-based risk assessment method for reservoir operation schemes, including: collecting basic data of target reservoirs; constructing optimal operation model of conventional reservoirs to obtain model calculation results; acquiring change process of operation characteristics during whole operating period according to model calculation results, and constructing multi-level reservoir multi-dimensional risk assessment index system; dividing different risk level intervals according to multi-level reservoir multi-dimensional risk assessment index system; obtaining large number of sample data xij of reservoir risk index under corresponding working conditions by multiple parallel calculations to conduct risk assessment; calculating cloud digital features of different indexes by inverse cloud generator; and weighting indexes in index layer and criterion layer by Analytic Hierarchy Process to obtain multi-dimensional risk assessment results. In order to promote sustainable development and utilization of water resources and enhance level of reservoir risk management, scientific evaluation of reservoir risk is conducted by comprehensively considering various uncertainties.

The invention discloses a water level monitoring and management method based on multi-source information fusion, and relates to the technical field of water level monitoring and management. Comprising the following steps: acquiring a water level and water level related data by adopting a sensor, and acquiring surface feature information and meteorological data through GIS data; performing data cleaning and standardization on the collected data; a convolutional neural network is adopted to analyze infrared cloud picture data obtained by satellites to predict precipitation, a weighted average method is adopted to carry out multi-source information fusion, and water level prediction is carried out through a hydrological model; and performing real-time water level monitoring and water level management decision according to accurate water level data obtained by data fusion. Through the above steps, the system can provide a more comprehensive view angle for water level management by fusing multi-source information, and can more accurately predict the water level change trend, thereby optimizing the water resource management strategy and flood control measures.

The invention provides a lake ecological water level calculation method, device and system and a storage medium, and relates to the technical field of water resource regulation and control. The method comprises the following steps: obtaining the water turbidity of a target lake and the biomass of all submerged plants existing in the target lake; the water depth required by growth is calculated; dividing the target lake into habitat units; calculating the actual water depth of each habitat unit; calculating the plant coverage by using the water depth required for growth and the actual water depth; and obtaining an ecological water level range and an annual water level regulation and control range based on the plant coverage and taking the ranges as lake ecological water level results. By constructing the growth-illumination model and the underwater illumination prediction model of the submerged plants, the monthly water level accurate regulation and control based on biological requirements are realized, and by subdividing habitat units and analyzing ecological requirements, the growth conditions of the plants can be optimized, the water quality and biological diversity of a lake ecosystem can be improved, and the water quality and the biological diversity of the lake ecosystem can be improved. And the scientificity and systematicness of lake management are enhanced.

The invention relates to the field of intelligent agriculture, and discloses an intelligent drip irrigation control method, system and device and a storage medium, and the method comprises the following steps: data collection: obtaining soil humidity data, environmental meteorological data and crop growth state data of a target area through a plurality of sensors, and transmitting the data to a data processing module; the system comprises a data acquisition module used for acquiring soil humidity data, environmental meteorological data and crop growth state data and transmitting the acquired data to a data processing and storage module; the device comprises a machine case shell, and an intelligent control chip, a wireless communication module, an electromagnetic valve and a water flow meter are installed in the machine case shell. By integrating a sensor network, intelligent analysis and a real-time feedback mechanism, the water demand of crops is accurately calculated, irrigation is automatically adjusted, and water resource utilization is optimized; a personalized irrigation plan is made by combining a deep neural network and time sequence analysis, and the water requirements of crops in different growth stages are ensured.

The invention relates to the technical field of resource management, in particular to a seawall ecological protection-oriented vegetation water demand prediction method and system, and the method comprises the steps: collecting the environment monitoring data of a seawall region; establishing a salinity stress factor model based on the soil data, calculating a comprehensive salinity stress coefficient of the monitoring point, and performing multi-factor dynamic correction on the vegetation water demand to obtain a vegetation basic water demand; establishing a multi-dimensional time sequence model of a tidal cycle and a soil moisture supplement relationship considering geologic structure differences, and obtaining resource scheduling weights under different tidal stages and environmental conditions; according to the vegetation data, the underground data and the environmental data of the different seawall regions, based on a multi-region collaborative water resource allocation network, obtaining a deployment optimization scheme based on regional characteristic parameters; and generating a vegetation water demand prediction result and a graded resource scheduling scheme by integrating the vegetation basic water demand, the resource scheduling weight and the allocation optimization scheme, and performing irrigation.

The invention discloses an intelligent soil moisture content monitoring and precise irrigation linkage system, and relates to the technical field of irrigation. Key parameters such as moisture content, temperature, humidity and conductivity of soil are obtained in real time through a soil moisture content monitoring module, processed by a data acquisition and transmission module and transmitted to a control center; the control center carries out deep analysis and evaluation on the soil moisture condition through the edge computing gateway and the cloud decision controller, an accurate irrigation control instruction is generated, the irrigation control execution module carries out accurate regulation and control on irrigation equipment according to the instruction, and reasonable irrigation of a farmland is achieved. The system can comprehensively master the moisture condition of farmland soil, provides data support for precise irrigation, improves the precision and efficiency of irrigation, saves water resources, is intelligent and high in automation degree, can reduce manual intervention, reduces the labor cost, and improves the stability and reliability of irrigation at the same time.

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 saline-alkali soil dynamic precise irrigation method based on a water-salt-carbon flux coupling model, and relates to the technical field of saline-alkali soil improvement and precise irrigation, and the method comprises the following steps: dividing soil into a surface layer, a middle layer and a deep layer, building the coupling model based on a Darcy law, a convection-dispersion equation and a first-order dynamic model, and simulating a water-salt-carbon flux dynamic state; collecting data such as soil water content, conductivity and organic carbon content through a layered sensor network, and inputting the data into the model after cleaning and fusing; the irrigation time, the irrigation amount and the water quality are optimized through a genetic algorithm in combination with the crop growth period requirements; irrigation is executed through an intelligent valve and a variable frequency water pump, and model parameters are adjusted based on real-time monitoring feedback. According to the method, multi-element cooperative regulation and control of saline-alkali soil irrigation are achieved, the soil ecological process can be accurately simulated, the water resource utilization efficiency is improved, the soil environment is improved, and crop yield increase is promoted.

The invention relates to the technical field of environmental impact assessment, in particular to an intelligent environmental impact assessment method and system, and the method comprises the following steps: collecting environmental data including pollutant discharge, water resource consumption, air quality change and biodiversity, building an impact factor data set, and segmenting the data set to obtain an impact factor data set; and calling a kernel function type to carry out numerical prediction on pollutant emission. According to the method, by integrating data processing and machine learning technologies, the accuracy and efficiency of environmental impact assessment are improved, numerical prediction is performed on environmental data by using a kernel function and a support vector regression model, the adaptability and precision of a prediction model are enhanced, model parameters are optimized through automatic population generation and crossover mutation operation, and the accuracy and efficiency of environmental impact assessment are improved. The model can better learn and adapt in a complex data environment, sensitivity and response speed to environmental changes are further improved through dynamic clustering analysis and time sequence adjustment, and scientific support is provided for formulating timely and effective environmental protection measures.

The invention provides a water quality monitoring system model construction method and device based on edge calculation and computer equipment, and relates to the technical field of water quality monitoring. The invention aims to solve the problems of data processing delay and insufficient real-time performance in the traditional water quality monitoring technology. The method comprises the key steps that the collecting end is arranged at a key monitoring point of a water body to collect water quality parameters, the water quality parameters are sent to the edge end for real-time data processing, water quality prediction and anomaly detection are conducted in combination with the BP neural network and the support vector machine, and quick response to water quality changes is achieved. And meanwhile, deep learning and a support vector machine are combined, so that the prediction precision and the anomaly detection capability are improved. And the water quality condition is comprehensively evaluated through a comprehensive weighted index method, so that a manager can identify a pollution source more quickly and take effective countermeasures. The water quality monitoring efficiency and accuracy are improved, and solid technical support is provided for sustainable management of water resources.

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 photovoltaic field rainwater collection and intelligent distribution irrigation system, and relates to the water resource management and utilization technology, the photovoltaic field rainwater collection and intelligent distribution irrigation system comprises a photovoltaic panel body, and one side of the photovoltaic panel body is provided with a distribution irrigation mechanism. According to the application, the integrated sensor module, the control module and the execution module are arranged in the distribution irrigation mechanism, so that real-time monitoring and analysis of soil humidity, crop states and meteorological data are realized, and water is accurately distributed to the target area according to irrigation requirements of different areas. The drip irrigation unit, the spray irrigation unit and the micro-spray irrigation unit are utilized to meet irrigation requirements of different land parcels, and the problems that in the prior art, the irrigation mode is single, resource waste is serious, and the irrigation amount cannot be adjusted according to dynamic requirements are solved. According to the design, through intelligent control and partition management, accurate irrigation and efficient utilization of water resources are achieved.