44 results about "Water state" patented technology

The invention relates to the technical field of underground water state evaluation, and discloses an underground water level dynamic evaluation method based on multi-source data mapping and fluid model correction. The invention aims to solve the technical problems of insufficient underground water level monitoring precision and lack of space details caused by low spatial resolution of existing satellite gravity detection data and difficulty in accurately separating a deep underground water change signal from a land total water reserve signal. According to the method, through space-time reference unification of multi-source heterogeneous data, high-resolution surface texture features are utilized to guide a low-resolution gravitational field to carry out space downscaling reconstruction; surface water body and soil water reserve signals are removed layer by layer in combination with spectral characteristics and a thermal inertia principle; and introducing measured data to construct a spatial error correction curved surface of specific yield parameters, and identifying the underground water funnel by using an image connected domain analysis technology.

The invention relates to the technical field of disaster early warning, in particular to a mountain torrent disaster real-time monitoring and early warning method based on the Internet of Things and artificial intelligence, which comprises the following steps: acquiring a water level data identification rising point, marking an area number, retrieving rainfall nodes, judging synchronization, tracking a non-drainage path, extracting channel frequency and screening response nodes. And multi-section mountain torrent early warning information is obtained. According to the method, the continuous rising trend of the water level is extracted, the monitoring section with the continuous change characteristic is delimited, the response path between the water level and the rainfall is constructed by means of the multi-node space distribution relation, the interaction area is recognized and merged, and the water body retention section and the upstream water supplementing direction are calibrated by comparing the drainage state with the node behavior. The response continuity is analyzed through a broadcast channel and scheduling frequency, key nodes in the change process are screened, water level, rainfall and path information is organized through a time sequence, the multi-region hydrological response process is integrated, and staged recognition and risk pointing of the disaster process are promoted.

The invention provides a dam body monitoring method and system and electronic equipment, and the method can recognize the current state of each water outlet through a first image which comprises the real-time images of all water outlets, and then dynamically adjusts the monitoring strategy corresponding to each water outlet according to the current state of each water outlet, thereby improving the monitoring precision of each water outlet. Therefore, the interference of the drainage port in the drainage state on the monitoring data is eliminated. By adopting the technical scheme provided by the invention, the dynamic self-adaptive optimization of the monitoring strategy can be realized on the whole so as to flexibly eliminate the influence of the random drainage / flood discharge event on the monitoring point position of the dam body drainage port, and the accuracy and precision of dam body monitoring are improved.

The invention discloses a hydraulic structure concrete underwater repair robot based on heterogeneous dual-core cooperative control and an operation method. The system is mainly composed of an ROV carrier, an embedded dry chamber cabin, a vector propeller, a mechanical arm and a Pixhawk + PLC dual-core control system. The equipment adopts a hierarchical control framework: a motion control layer is based on Pixhawk flight control, realizes six-degree-of-freedom motion and attitude overturning, and accurately matches a complex-angle working plane; the operation control layer adopts an industrial PLC to control the dynamic sealing of the dry chamber cabin and the underwater operation surface, and a negative pressure dry environment is quickly established. A plurality of sensors and a manipulator are integrated in the cabin, visual accurate repair is carried out in a water-free state, and negative pressure evacuation is relieved after the repair is completed. The maneuverability of open source flight control and the logic reliability of the PLC are fused, the defects that a single controller is prone to overload and complex attitude alignment is difficult are overcome, and the high efficiency of deep water complex structure repairing and the system stability are guaranteed.

The invention relates to a water area drowning detection method based on multi-model cooperation and scene self-adaption, and belongs to the technical field of computer vision and safety monitoring. A human body target is quickly positioned through a YOLOv8-Nano model of an optimized anchor frame; a MediaPipe-Holistic model is used to extract key points, and a multi-dimensional feature map is generated; the motion trend vector is fused through the lightweight Transform, and the specific'micro-motion-sinking-static 'dynamic time sequence characteristics of drowning are accurately captured; swimming pool, lake and seaside scenes are identified through a scene adaptive attention module, key point weights are dynamically adjusted, low-confidence double-branch complementary reasoning is combined, finally, drowning state confidence is output through a full-connection neural network, and alarm is triggered. The technical problems that existing drowning detection is poor in scene adaptability, insufficient in dynamic feature capture, high in missing and false alarm rate and high in deployment threshold are solved.

This invention discloses a system and method for water replenishment and exchange through multi-gate coordinated control, comprising: a river channel; and a first control gate assembly and a second control gate assembly respectively disposed in the upstream and downstream sections of the river channel, and further comprising multiple channels disposed in the river channel and positioned between the first and second control gate assemblies. This invention utilizes natural tidal energy to replenish and exchange water in the inland river channel through multiple gates, while simultaneously and rationally coordinating the opening and closing of the upstream and downstream first and second control gate assemblies, thereby ensuring a long-term unidirectional flow state in the inland river channel, increasing water circulation, and ultimately improving the water quality of the inland river channel.

The invention relates to a grid scale wetland flooding state judgment method, device, medium and program, a linear relation model of subgrid underground water level and topographic index is constructed, the subgrid underground water level is 0 to represent a critical flooding state, the topographic index value at the moment is obtained based on the linear relation model, and the subgrid underground water level is calculated according to the topographic index value. The terrain index is used as a terrain index threshold value of sub-grid flooding; calculating a flooding area proportion for each grid based on the flooding state of the sub-grids; the grid is composed of a plurality of sub-grids; constructing a fitting model of the grid average groundwater level and the proportion of the flooding area; acquiring a wetland image and a grid average underground water level in the image; and obtaining the grid flooding area proportion of the wetland based on the fitting model. According to the method, the underground water level change and the subgrid terrain heterogeneity characteristics can be coupled on the grid scale, a new technical scheme for fine judgment of the wetland flooding state is achieved, and the defect of an existing hydrological model in the aspect of wetland flooding space expression ability is overcome.

The invention relates to a soda water quality optimization control method and system based on artificial intelligence. The method comprises the following steps: acquiring a multi-source data set of the combined cycle power system; a step of predicting the steam-water state index through a pre-trained dynamic prediction model by taking the multi-source data set as input to obtain a prediction result of the steam-water state; a mapping rule between the chemical agent and the steam-water state is input into the dynamic prediction model, and a corresponding agent scheme is generated; when the prediction result exceeds a set threshold value, the boiler discharge capacity is adjusted or chemicals are added according to the scheme, so that the steam-water state index is improved; and if the deviation of the regulated steam-water state index exceeds a preset deviation range, iteratively optimizing the medicament scheme according to the current prediction result, the steam-water state index and the mapping rule. And prediction and optimal regulation and control of the steam water quality can be realized under multi-factor interference under complex working conditions on the sea.

The application provides a shallow water self-adaptive navigation control system for a contactless trackless electric ship, and relates to the technical field of ship engineering, and comprises: an acquisition module, which is used for acquiring water depth information of a water area where the ship is located in real time; based on the water depth information, a preset shallow water threshold is used for judgment to obtain a shallow water state signal of whether the ship is in a shallow water navigation state; a measurement module, which is used for acquiring real-time measurement data of three depth measurement sensors arranged at a bow and two sides of the ship according to the shallow water state signal, and constructing a reference geometric structure according to the measurement data. The application realizes the dual protection of stable ship navigation posture and continuous contact power supply under shallow water conditions.

The invention relates to the field of intelligent water conservancy, in particular to an intelligent concealed conduit drainage coordinated control system based on water level adaptive regulation and control, which comprises a data acquisition module, a feature construction module, a space-time analysis module, a risk prediction module and a visualization module. Under the condition that the water level data is lack of measurement or incomplete, drainage state information in an incomplete sample can be fully excavated, a drainage operation state analysis model is gradually corrected and optimized, and the accuracy and stability of underground pipe drainage state analysis are effectively improved; the water level-drainage capacity dynamic response mapping model is constructed, the drainage state confidence coefficient and the potential drainage risk index are introduced to conduct self-adaptive correction on the mapping relation, under the condition that the drainage risk is increased or the state uncertainty is increased, the response strength of the drainage capacity is improved, and the drainage capacity is improved. Therefore, refined, coordinated and self-adaptive control of the concealed conduit drainage process is realized.

The present application belongs to the technical field of rock physics, and is especially a longitudinal wave velocity calculation method under a gas-water system. The method comprises the following steps: S1: obtaining longitudinal and transverse wave velocities of a sample under normal pressure and under a limit high pressure through experiments; S2: calculating a skeleton bulk modulus and a clay water relaxation time according to a sample XRD mineral analysis result; S3: converting the wave velocities into moduli; S4: calculating saturated volcanic lava longitudinal wave velocities considering frequency dispersion according to a Gurevich formula; S5: measuring a nuclear magnetic T2 spectrum of the sample under a saturated state; S6: calculating bulk moduli under different saturation degrees; and S7: converting to obtain longitudinal wave velocities under different saturation degrees. The present application explains the reason why the volcanic lava saturation degree-longitudinal wave velocity rule presents a "convex" shape from a mechanism, and effectively calculates volcanic lava longitudinal wave velocities under different saturation degrees.

The invention relates to the technical field of water disaster warning, in particular to a coal mine water disaster early warning system based on video recognition, which is characterized in that discretization results are constructed into a tag sequence arranged according to a time sequence, so that a Markov chain can describe a jump relation of water body change on the basis of a clear state sequence; therefore, different types of water body changes in the picture are expressed in a discretization label mode, the evolution path of the water body state in the time dimension has inference, a dynamic time warping mode is introduced in link node processing, water body diffusion trajectories in different time periods can be aligned when time scale difference exists, and the water body diffusion trajectories in different time periods can be aligned. The corresponding relation between the trend nodes is more rigorous, judgment errors caused by time migration are reduced, difference accumulation is conducted on the trend nodes and the mode nodes, the water state matching relation is output in a difference sequence screening mode, the deviation degree is presented in a quantitative mode, and therefore a stable deviation basis is provided for risk judgment.

The invention discloses a method for removing antibiotic resistance genes in bottom mud in situ, which comprises the following steps of: lowering the water level of a water body to expose the bottom mud out of the water surface, and keeping the time of exposing the bottom mud out of the water surface within 25 days; and recovering the flooding state, and keeping the sediment in the flooding state for more than 25 days. Compared with a conventional method, the method for removing the antibiotic resistance genes in the bottom mud in situ has the advantages that the growth states of different microorganisms and the content of organic matters in the bottom mud can be controlled by adjusting the water level of water around the bottom mud and controlling the exposure time and the exposure height, and then the antibiotic resistance genes in the bottom mud can be removed by adjusting the content of the microorganisms and the organic matters in the bottom mud. The sediment antibiotic resistance gene can be effectively removed under the condition of lower cost, and the sediment antibiotic resistance gene removal method has the advantages of simple process, low cost, good removal effect, good adaptability and the like, and has an important promotion effect on effectively improving the ecological environment of sediment.

The present application relates to an array electrode intelligent sensing system for tunnel gushing water monitoring and a method thereof. The system comprises a flexible sensing array implanted inside or on the surface of a tunnel lining structure, an intelligent acquisition node and a data analysis platform. The flexible sensing array is composed of multiple composite sensing units arranged in a predetermined topological structure, each unit integrating a main electrode for measuring resistivity / potential, a temperature sensor for measuring temperature and a flexible strain sensor for measuring deformation; the intelligent acquisition node connects the sensing array to synchronously acquire resistivity, temperature and strain data in multiple channels, and preliminarily processes and extracts features from the original data; the data analysis platform receives data from multiple nodes, and through a multi-parameter spatio-temporal fusion analysis model, realizes the collaborative intelligent analysis from "water-bearing state perception" to "structure deterioration evaluation" to "gushing water risk early warning". The present application realizes the fine, three-dimensional and real-time monitoring of the incubation process of tunnel water disasters.

The invention relates to the technical field of hydrogeological monitoring, in particular to a single-hole multi-horizon underground water monitoring system and method, and the system comprises a data collection module, a data processing module, a horizon recognition module, a state evaluation module and an early warning output module. Wherein the data acquisition module is used for acquiring underground water original monitoring data of a plurality of layers; the data processing module is used for filtering and normalizing the original monitoring data; the horizon identification module is used for identifying different horizons through threshold comparison and time sequence analysis and generating horizon identification data; the state evaluation module is used for evaluating the underground water state of each horizon; and the early warning output module is used for generating and outputting underground water early warning information. According to the invention, through multi-layer sensor arrangement, data fusion processing and grading early warning linkage, accurate identification and dynamic monitoring of single-hole multi-layer underground water are realized, and the accuracy and real-time performance of underground water state evaluation and risk early warning are significantly improved.

The present application relates to the technical field of numerical simulation of ecological hydrological process, and discloses a sand-distributed ecological hydrological two-way coupling modeling system, which comprises initialization and discretization, ecological growth calculation and source item generation, rhizosphere biochemical environment evolution and hydraulic constitutive correction and fluid transport solving modules, a finite difference grid is constructed in the system, and a root exudate release source item is calculated based on a current water state; exudate migration is simulated to reconstruct an effective dynamic viscosity of fluid and a dynamic contact angle of a sand particle surface; the soil unsaturated hydraulic conductivity and the matric potential are corrected according to the reconstructed parameters, a fluid transport control equation is solved to update the water distribution, and the state is fed back to the ecological module to form a closed loop. Through simulation of the rheological resistance and infiltration shielding effect induced by root exudate, the present application solves the problem that the traditional model ignores the dynamic evolution of the physical properties of the medium, and improves the physical authenticity of the simulation of the hydrological process in the arid region.

The invention provides a dynamic identification and restoration decision-making method for an underground water funnel area, and belongs to the technical field of water conservancy optimization based on deep learning. The method comprises the following steps: firstly, constructing a high-dimensional underground water state data set; then, establishing an underground water evolution numerical model by utilizing the data set, and realizing dynamic and accurate extraction of three-dimensional boundaries and key characteristic parameters of the funnel area; then through a deep learning prediction model cluster, on the premise of following a groundwater dynamic physical rule, high-fidelity and uncertainty quantitative rapid prediction is carried out on future head field changes; and finally, taking the prediction model as a decision-making deduction environment, and training an intelligent agent by using a deep reinforcement learning algorithm, so that the intelligent agent can autonomously learn and generate an optimal restoration management and control strategy considering restoration benefits, economic cost and sustainability. According to the invention, a closed-loop intelligent system capable of autonomously learning and continuously optimizing is formed, and a scientific, efficient and systematic brand-new solution is provided for management of underground water resources.

The invention provides a multi-frequency variable-amplitude dynamic compaction reinforcement construction method suitable for water-containing soft soil. The multi-frequency variable-amplitude dynamic compaction reinforcement construction method comprises the steps that a sensing network is arranged at a to-be-constructed position in advance, the to-be-constructed position is firstly subjected to preliminary compaction, in the process, strain fields of all sub-areas of the to-be-constructed position are monitored through the sensing network, and a strain field cloud picture is generated. And the soil body state of each sub-region is identified according to the strain field cloud picture. And the sub-areas in the tamping state are directly tamped again, and after the sub-areas in the stagnant water state are naturally converted into the tamping state, the sub-areas are tamped again. Based on the scheme, after preliminary tamping is completed, soil bodies in different states can be distinguished. And in the process that the area waiting for the stagnant water state is naturally converted into the ramming state, the other areas in the ramming state can be rammed again. Therefore, secondary ramming in a stagnant water state can be avoided; and the construction time can be shortened, and the construction efficiency is improved.

The present application relates to the field of aquaculture technology, and particularly relates to a precision hatching method and system for eyed eggs of Atlantic salmon. The method comprises the following steps: a real-time sensing step, in which hatching environment parameters and embryo visual information are synchronously collected; an intelligent analysis and decision step, in which an AI model is used to quantify key biomarkers from the visual information, and combined with environment data and accumulated temperature model, an individualized environment regulation strategy is generated through an optimization algorithm; a precision execution step, in which an execution mechanism is driven to adjust the water state according to the strategy; and the above steps constitute a closed loop and self-adaptive iteration. The system comprises a sensing module, an intelligent decision module and an execution control module. The present application builds a closed-loop intelligent control system with the real-time physiological state of the embryo as the feedback core, realizes dynamic, precise and self-adaptive regulation of the hatching process, and effectively improves the hatching synchronization rate, healthy fry rate and production controllability.

A system and method for early warning of falls into water by maintenance personnel in floating photovoltaic power plants is applicable to agricultural-photovoltaic complementary scenarios such as fishponds. Through waterproof safety equipment worn by maintenance personnel, the system achieves dual determination of the fall-in status. After triggering an early warning, a signal is transmitted via a dual-band communication module, and after validity verification by the base station, it is synchronized to the backend and rescue terminal. The system adopts a tiered response mechanism: the first-level response dispatches rescue forces within 300 meters of the fall-in point; if no confirmation is made within a short time, a second-level response is automatically triggered. The rescue terminal plans an obstacle avoidance path based on preset 3D data of the fishpond, prioritizing the avoidance of obstacles such as photovoltaic piles and deep water areas. On-site, specialized tools such as telescopic rescue poles and fluorescent waterproof lifebuoys are used to carry out targeted rescues based on the personnel's conscious state, and real-time feedback of rescue node information is provided. After the rescue is completed, vital sign checks and medical coordination are conducted, and a fully traceable summary report is generated. This invention shortens the rescue response time and improves scenario adaptability and process standardization.

The invention relates to the technical field of channel dredging, in particular to a sand-water efficient separation and drainage system based on in-cabin overflow adjustment, which comprises a sand loading cabin, the side wall of the sand loading cabin is provided with an intelligent overflow port array, and the positions of each row in the intelligent overflow port array are respectively located at different depths in the sand loading cabin. A sensing unit is further arranged in the sand loading cabin, and the system further comprises a control module which is used for obtaining the deposition states of different depths in the sand loading cabin according to sand-water state data and then independently controlling the opening degree of each row of overflow ports so as to drain water. The intelligent overflow port array is combined with the sensing unit to monitor sand-water state data in real time, so that the control module can accurately analyze deposition conditions at different depths, the opening degree of each overflow port is independently regulated and controlled, and layered drainage and efficient sand-water separation are achieved. The traditional separation time depending on natural sedimentation is greatly shortened, the sand-water separation efficiency is remarkably improved, and the problem of insufficient sand-water separation efficiency in the prior art is solved.

The application discloses a cloud and fog sheltered area flood disaster image reconstruction method based on precipitation prior and SAR constraint, and relates to the technical field of remote sensing image processing. Firstly, permanent water body information is extracted by using pre-disaster cloud-free optical images, and daily flood state prior is constructed by combining multi-temporal SAR images, precipitation data and terrain hydrological information. Then, according to the cloud sheltered area, flood state category and background stability, a partitioned differentiated optical reconstruction prior is constructed. Finally, a conditional diffusion model is adopted to reconstruct the disaster image of the cloud and fog sheltered area under the guidance of SAR flood space constraint, precipitation driving weight and flood state prior, while the real observation information of the non-cloud visible area is reserved. The application can reduce the flood information missing problem caused by cloud sheltering of traditional optical images, improve the spectral texture recovery capability of the newly added expansion area, shallow stagnant water area and water recession transition area under the cloud, and improve the continuity and reliability of flood disaster remote sensing monitoring.

The invention discloses a drowning detection method, which comprises the following steps: acquiring a current water surface image, and detecting and tracking a human body target in a current water area according to the current water surface image to obtain a plurality of tracking objects; performing prediction tracking and multi-frame human body posture analysis on each tracking object, judging whether a current human body has a drowning trend or not, and outputting a drowning state result; according to the type of the water area where the tracking object is located and the drowning state result, spatial position data collection and on-site early warning are carried out, and according to the spatial position data, optimal lifesaving equipment sending is carried out on a plurality of drowners.

The utility model belongs to cup cover technical field, concretely relates to the slide formula straight drinking cup cover of rotary seal. In view prior art push piece straight drinking cup cover realizes sealing through spring compression sealing ring, is difficult to take into account the shortage of reliable sealing and the operation of labor -saving, the utility model adopts the following technical scheme: the slide formula straight drinking cup cover of rotary seal includes: main lid, sets up water hole and through slot; Sliding assembly includes the slide piece above water hole and the sealing element below water hole, the sealing seat below sealing element and the rotating element on slide piece, and sealing seat and rotating element are threadedly connected, when sealing element is located just below water hole and sealing seat and rotating element are screwed, sealing element seals water hole and through slot, and sliding assembly is in sealed state, when the projection of sealing element and water hole on horizontal plane is staggered and sealing seat and rotating element are loosened, sealing element removes the sealing of water hole and through slot, and sliding assembly is in the water state. The utility model has the advantages of reliable sealing and easy operation.

The invention provides a dam water level detection device and method, relates to the field of dam water level monitoring, and aims to solve the problem that existing dam water level detection equipment is poor in detection element water contact state recognition precision, a traction rope is adopted as a traction rope to drive a detector to move along a pressure measuring pipe, and the pressure measuring pipe serves as a part of a closed conductive loop. After the detector moves to the bottom conductive tip to touch water, a conductive closed loop is formed, the water touch state is accurately and quickly identified, and after the detector is separated from the water, the detector is disconnected to identify the water leaving state, so that misjudgment caused by wetting of a sensing device is avoided, and the detection accuracy and precision are improved.

The application discloses a water resource information acquisition method based on remote sensing images and belongs to the technical field of image recognition, and specifically comprises the following steps: firstly, remote sensing image data of a target water area is acquired, and a dynamic substrate spectrum template library is constructed by collecting measured spectrum reflection curves of different substrate types in a water-free state; then, for each spatial position in the image, the exposed substrate type of the adjacent area is matched according to the geographic coordinates, the corresponding spectrum features are extracted from the template library as the basic reflection reference; then, a light propagation path separation model is established to simulate the process that sunlight penetrates through the water layer, is reflected by the substrate and returns to the sensor, and the substrate reflection contribution component is generated in combination with the basic reflection reference; finally, the contribution component is deducted from the spectral reflectance to obtain the pure water body optical response value, and according to the physical correlation model between the optical response value and the water body transparency, a water body transparency parameter distribution map of each spatial position of the target water area is output; the application realizes reliable remote sensing acquisition of the water body transparency of a shallow water area.

This invention provides a method and apparatus for real-time water turbidity control, applied to a real-time water turbidity control system, and relating to the field of water environment management technology. By using multiple autonomous inspection robots to collect water state data in real time, it solves the problems of low frequency and limited coverage of traditional manual inspections, enabling real-time capture of dynamic changes in turbidity. A central control platform generates a real-time turbidity heat map, dynamically allocating tasks and planning inspection paths covering high-turbidity areas using a contract network protocol, concentrating treatment resources on pollution hotspots. Based on historical and real-time data, it predicts turbidity change trends and uses an optimization algorithm to dynamically determine the minimum dosage of chemicals, avoiding waste from excessive dosage or treatment failure due to insufficient dosage. Based on the treatment effect, it updates model parameters, forming a closed-loop feedback control, realizing intelligent management and control of the entire process from "monitoring-prediction-decision-execution-optimization." This significantly improves the real-time performance, accuracy, and resource utilization rate of water turbidity treatment.

The invention discloses a discrete landslide surge test and whole-process wave amplitude prediction method based on speed equivalence. According to the method, a three-dimensional physical model is established according to Froude similarity criteria, and accurate control over the water entering speed of the slip mass is achieved through speed equivalence. The high-position landslide movement is divided into an initial state, a sliding-out state, a water entering state, a sliding-out stage and a sliding stage, and the speed of a slide body in each state is calculated by adopting a structural strain energy method, an improved Pankend classification method and an energy method. Through a multi-factor orthogonal test, the influence rule of the landslide sliding speed, the water entry volume and the initial water depth on the surge characteristics is systematically analyzed, and a surge whole-process prediction model system covering the initial wave amplitude, the propagation attenuation and the dam front climbing height is constructed based on test data. According to the invention, the problems of insufficient sliding speed control precision and lack of prediction model systematicness in the prior art are effectively solved, the test accuracy and prediction reliability are significantly improved, and important technical support is provided for risk assessment of landslide surge disasters in the reservoir area.

The invention relates to the technical field of hydraulic engineering quality acceptance, in particular to a hydraulic engineering quality acceptance data acquisition system based on the Internet of Things. Performing data acquisition on the arch dam in the initial state to obtain initial structure data; monitoring the surface temperature of the arch dam according to a sunlight irradiation rule to obtain temperature distribution data; dividing an arch dam temperature field area according to the initial structure data and the temperature distribution data; according to the waterless deformation data and the temperature distribution data of the arch dam temperature field areas, the deformation degree of each arch dam temperature field area under the influence of different temperature distributions is identified, and waterless deformation parameters are obtained; under the water state, the coupling temperature data, the water pressure load data and the structure data of the arch dam are collected, and water deformation data are obtained; according to the method, coupling temperature data, water pressure load data and water deformation data of an arch dam temperature field area are identified through an arch dam quality acceptance model, and quality judgment is carried out in combination with water-free deformation parameters.

The invention relates to the technical field of ecological hydrological process numerical simulation, and discloses a sand distributed ecological hydrological bidirectional coupling modeling system which comprises an initialization and discretization module, an ecological growth calculation and source item generation module, a rhizosphere biochemical environment evolution and hydraulic constitutive correction and fluid transportation solving module. Calculating a root secretion release source item based on the current moisture state; secreta migration is simulated to reconstruct the effective dynamic viscosity of fluid and the dynamic contact angle of the surface of sand grains; and the soil unsaturated hydraulic conductivity and matrix potential are corrected according to the reconstruction parameters, a fluid transport control equation is solved to update moisture distribution, and the state is fed back to the ecological module to form a closed loop. According to the method, by simulating the rheological retardation and infiltration shielding effect induced by root exudates, the problem that a traditional model ignores dynamic evolution of physical properties of a medium is solved, and the physical authenticity of hydrological process simulation in the arid region is improved.