172 results about "Drainage basin" patented technology

The application discloses a multi-period water supplement evaluation method based on big data simulation, and comprises the following steps: taking the Yangtze River estuary and the downstream basin as an object, establishing a hydrodynamic salinity diffusion numerical model, and training a physically constrained Fourier neural operator proxy model; dividing spatial grid nodes to construct a spatial topology connection graph; establishing data interaction relationship between nodes and updating parameters in real time through an improved spatial perception Mamba network; calculating uncertainty based on the salinity simulation results output by the proxy model, and dynamically feeding back and optimizing the Mamba network; reversely transmitting the optimized prediction results to dynamically update the constraint conditions of the proxy model; and determining an ecological water supplement position, time and water quantity scheme. The application realizes high-precision and high-frequency ecological water supplement decision support.

The present application belongs to the technical field of hydrological forecasting, and specifically relates to a multi-source adaptive transfer learning data-scarce watershed daily runoff prediction method, which comprises the following steps: selecting multiple source watersheds with long sequence observation data, independently training a basic prediction model based on a Transformer architecture by using historical hydrological and meteorological data of the source watersheds, and constructing a source watershed prior knowledge base containing diversified production and confluence mechanisms; adopting a parameter freezing and differential fine-tuning strategy, transferring the source watershed basic model to a data-scarce target watershed, fine-tuning the output layer by using limited measured daily runoff samples of the target watershed on the basis of keeping the parameters of the Transformer feature extraction layer fixed, and constructing multiple transfer branch models; establishing a dynamic attention module to realize real-time sensing of the evolution of meteorological environmental elements of the target watershed and self-adaptive calculation of the dynamic confidence weight of each transfer branch model at the current time; and based on the weight, weighting and integrating the preliminary prediction values of each branch model to obtain the final daily runoff prediction result of the target watershed.

This invention discloses a method and system for dynamic visual analysis of oxygen-consuming pollutants across multiple interfaces in watersheds. Addressing bottlenecks in large-scale rendering of complex watershed hydrology, such as GPU memory overflow, lack of cross-interface flux representation, and difficulty in perceiving prediction errors, this invention acquires a multi-source heterogeneous spatiotemporal sequence set of water quality data; constructs a topological directed acyclic graph (DAG) based on Strahler hierarchy in memory, and performs online hierarchical temporal aggregation algorithm in the GPU for dynamic LOD memory scheduling; generates a three-dimensional cross-medium particle streamline flux layer using Runge-Kutta numerical integration and pollution degradation constant constraints; and extracts the prediction variance field using a regularized multi-decoder scene representation network (RMDSRN), mapping it to the physical geometric roughness and fogging effects of the water surface mesh. This invention achieves hardware-level isomorphism between geographical laws and low-level memory scheduling, intuitively presenting hidden physical flux interactions and deep AI-predicted risks, significantly improving the scientific rigor and hardware / software efficiency of watershed management.

The application provides a dredging device for treating sewage in a river basin water environment, which comprises a mobile vehicle body, a suction pipe and a moving mechanism. The moving mechanism comprises a walking track, a rotating plate, a mounting plate, a containing box, a first electric push rod, a flexible sleeve, a second electric push rod, a sealing plate, a magnetorheological fluid, an electromagnetic coil and a main control unit. The mobile vehicle body moves on a shoal to perform dredging. If the shoal is relatively soft, the flexible sleeve is abutted against the top surface of the adjusting groove by the first electric push rod, the sealing plate is lifted by the second electric push rod, the magnetorheological fluid in the flexible sleeve is extruded, the magnetorheological fluid can push the flexible sleeve to deform outward, the top surface area of the flexible sleeve is increased, the electromagnetic coil is electrified, under the action of the magnetic field, the magnetorheological fluid becomes solid, the flexible sleeve can remain in a fixed form, finally, the flexible sleeve is transferred downward and contacts the shoal surface, the contact area is increased, the stability of the mobile vehicle body is ensured, the silt is sucked, and the water environment ecology is repaired.

This application relates to the field of optimized scheduling technology for cascade hydropower systems in river basins, and particularly to a multi-stage collaborative scheduling method and device for integrated hydropower, wind power, and solar power systems. The method includes: acquiring day-ahead and intraday forecast data of photovoltaic and wind turbine output; constructing a day-ahead collaborative optimization model with dual objectives of minimizing power generation water consumption rate and maximizing expected absorbable electricity; solving the day-ahead collaborative optimization model for multi-objective optimization to obtain the day-ahead unit output plan of the hydropower station; and then constructing an intraday rolling correction model with the single objective of minimizing wind and solar curtailment. The day-ahead unit output plan is used as the operating benchmark for the intraday stage. The day-ahead unit output plan is adjusted by solving the intraday rolling correction model to obtain the intraday unit output plan. Thus, through a multi-stage collaborative mechanism of day-ahead benchmark setting and intraday deviation correction, the problem that related technologies are limited to a single time scale and suffer from uneven solution set distribution and poor convergence when solving multi-objective problems, making it difficult to obtain accurate integrated hydropower, wind power, and solar power operation schemes, is solved.

This invention provides a peak-scale response analysis method based on nested sub-basin division. By constructing a nested sub-basin structure controlled by area thresholds, and based on a unified design storm conditions and hydrological model parameter system, the method calculates peak discharge under different scale conditions by only changing the sub-basin division scale. It also establishes a logarithmic decay function model between peak discharge and the number of sub-basin units, achieving a quantitative expression of peak-scale response. Furthermore, by comparing and analyzing the scale decay coefficients under different design frequencies, the method quantifies the sensitivity of peak discharge to changes in the division scale. This method forms a complete technical process from data acquisition, structure construction, control variable setting, model running to function modeling and sensitivity analysis. It features a clear logical closed loop, strong repeatability, and good generalization, and does not depend on specific hydrological model software or specific watershed conditions. Under the premise of meeting the unified storm input and nested division principles, it can be widely applied.

The application discloses a kind of fish suitable flow habitat spatio-temporal distribution calculation method and system, through basic data collection pre-processing, target fish life history and reservoir scheduling spatio-temporal matching, cascade reservoir dynamic backwater length calculation, habitat suitability determination of dehydration river section, spatial superposition between cascades, habitat time dimension accounting and spatio-temporal matrix construction, planning scheme compliance verification and the like steps, realize the spatio-temporal dynamic accurate delineation of the habitat of native fish suitable flow after cascade development.The application fully considers the water level fluctuation and backwater dynamic change of reservoir within a year, the differentiated habitat needs of different life history stages of target native fish, solves the industry pain points of traditional method such as insufficient accuracy, disconnection with protection target and lack of time dimension evaluation, and can provide scientific and accurate technical support for basin hydropower development layout optimization, ecological protection measure formulation and planning scheme environmental impact assessment comparison.

The present application belongs to the technical field of hydrological prediction and water resources management, and specifically relates to a prediction method and system based on multi-scale decomposition of runoff sequence and dynamic weight reconstruction. The method first constructs a physical hydrological model based on meteorological driving data and generates a runoff simulation sequence; the simulation sequence is subjected to multi-scale decomposition by using variational mode decomposition, the decomposition parameters are adaptively determined by particle swarm optimization, and a plurality of mode components are obtained; a long short-term memory network is constructed to establish a mapping relationship between the contribution weights of the mode components, and dynamic weights varying with time and normalized are output; the mode components are weighted and reconstructed according to the weights, so as to realize deviation correction of the simulated runoff of the physical hydrological model on different time scale structures. In the prediction stage, the same decomposition is performed on the future runoff simulation sequence, and the trained model is directly used to output the runoff prediction result. The present application converts the runoff prediction problem into a dynamic weight distribution problem of multi-scale structure components, improves the prediction precision and migration ability while maintaining physical interpretability, and is suitable for scenarios such as basin runoff prediction, flood simulation, water resources scheduling and the like.

This invention provides a simulation and pre-drilling method and system based on smart water conservancy. Through multi-source data integration and preprocessing, it fuses hydrological, geographical, and population data to output a standardized fusion dataset. Digital twin scenario construction, combined with the MARL algorithm, achieves bidirectional coupling between flood evolution and resident behavior. Dynamic simulation and pre-drilling drive bidirectional coupled simulation to predict flood inundation and disaster chain transmission. Strategy generation and optimization employ an improved NSGA-III algorithm to achieve multi-objective evacuation path optimization and generate resettlement plans. Specifically, it breaks through the limitations of traditional unidirectional simulation, achieving multi-objective dynamic optimization and improving the intelligence, precision, and fairness of flood disaster response. It can be widely applied to flood disaster prevention and control in various river basins and cities.

This invention discloses a GIS-based risk management system and method for pollutant migration in mining area watersheds, relating to the technical field of simulating pollutant migration patterns. It includes a 3D GIS functional module, a hydrodynamic-water quality model coupling module, and a mining watershed pollution risk management module. Based on watershed hydrology theory and pollutant migration and diffusion mechanisms, it fully considers the migration of pollutants in the storage area after rainfall via surface microrunoff. By studying the formation patterns of microrunoff, it simulates the watershed migration process of pollutants in the mining area under different rainfall intensities, thereby more accurately calculating pollutant migration and diffusion fluxes and managing the risk of pollutant migration in the watershed. Based on historical and real-time data and models, it uses a 3D model to display the spatial distribution patterns and development trends of pollutants, achieving accurate pollutant identification and source tracing. It can simulate pollution control measures in mining area watersheds, predict development trends, and provide early warnings for pollution events.

The application discloses a geological disaster multi-scale environment control factor identification system based on machine learning and relates to the technical field of geological disaster identification.The system comprises a multi-scale environment factor collection module, which acquires historical geological disaster data of a target region, extracts multi-scale environment characteristics of geological disasters and constructs a geological disaster-environment factor correlation characteristic set; a quantitative evaluation module, which establishes a geological disaster risk probability prediction model, quantitatively evaluates the marginal contribution degree of each environment factor at different spatial scales, identifies environment factors that dominate the development of geological disasters in the multi-scale of regions, river basins and slope surfaces and establishes a target region geological disaster risk probability surface and an environment factor contribution spatial distribution map; and a prevention and control module, which introduces a target region human activity intensity index and an ecological system state index, establishes an environment factor dynamic coupling risk propagation model, realizes real-time multi-scale risk transmission paths and generates a dynamic risk classification early warning atlas. The application improves the precision of geological disaster risk assessment.

The application provides a global intermittent runoff prediction method based on multi-expert hydrological attribute decoupling, comprising the following steps: S1, obtaining a standardized training sample tensor; S2, constructing a time series gated expert network; S3, outputting the trained time series gated expert network; S4, preprocessing hydro-meteorological time series data of a to-be-predicted basin to obtain an input tensor; S5, inputting the input tensor into the trained time series gated expert network; S6, obtaining enhanced feature representation; S7, inputting the enhanced feature representation into a gated hybrid expert module of the trained time series gated expert network; obtaining fusion features; S8, inputting the fusion features into a classifier of the trained time series gated expert network, and obtaining a final intermittent runoff duration category prediction result. The method achieves leading prediction accuracy on a global multi-basin data set, and provides clear physical mechanism attribution explanation through visualization of expert attention and routing weight.

This invention discloses a comprehensive evaluation method for land-based pollutants in watershed environments, relating to the field of watershed environmental pollution assessment technology. The method includes: constructing a dual-connectivity screening and discrimination mechanism based on confluence transportability and pollution permeability; using this mechanism to screen each watershed evaluation area in the evaluation area load inventory for hydrological connectivity and pollution connectivity to form effective inflow loads; establishing a reverse constraint relationship based on the effective inflow load and control section response information; deriving the actual contribution share of each watershed evaluation area through this reverse constraint relationship; and adaptively redistributing the effective inflow load to obtain a regional contribution load table. This invention improves the logical completeness of regional contribution characterization, enhances the pertinence and interpretability of contribution share decomposition, and provides a stable data foundation for subsequent lag compensation, overload migration identification, and pressure level classification.

The present application relates to the technical field of river dredging treatment, and relates to a river sludge treatment method based on dynamic simulation and optimized decision, obtains and processes historical and real-time multi-dimensional environmental data of a river to be treated and an influence area thereof, constructs a watershed process simulation system capable of simulating river water dynamics, sediment transport, pollutant migration and transformation and ecological response process, parameterizes definition of decision variables constituting a river treatment scheme, formal definition and setting of a multi-objective optimization problem, adopts a multi-objective optimization engine, embeds the watershed process simulation system as a core evaluation module into an optimization iteration loop, implements an optimized scheme, and continuously monitors environmental state changes during and after implementation, the present application can accurately predict long-term and short-term effects of different treatment schemes in terms of water dynamics, sediment, pollutant migration and transformation and ecological response, and solves the problem of sludge comprehensive treatment.

Embodiments of the present application disclose a reservoir over-standard flood inundation risk zoning method, device and equipment, by determining the reservoir siltation influence probability factor and the reservoir dam break influence probability factor under the siltation condition, the reservoir siltation influence probability factor and the reservoir dam break influence probability factor are used to calibrate the reservoir inundation comprehensive risk degree of siltation-dam break double influence probability under the over-standard flood condition, and the K-means clustering algorithm is used to cluster and analyze the reservoir inundation comprehensive risk degree of each grid calculation unit, and finally the flood risk grade is determined. The technical problem of low accuracy of prediction and zoning of flood inundation risk in the prior art for the reservoir area with high sediment concentration and weak dredging capacity is solved, and a scientific basis and certain technical support are provided for reservoir flood inundation risk assessment and disaster prevention and mitigation planning in high sediment concentration basin areas.

The present application provides a kind of debris flow early warning and adaptive protection system, it is related to disaster warning technical field, system includes: drainage basin stereoscopic monitoring network, for obtaining the multi-source monitoring data of monitoring area;Early warning and analysis platform, for early warning analysis according to the multi-source monitoring data, generates early warning level;Also for when the early warning level is action level, generate debris flow prediction scale parameter, and according to the debris flow prediction scale parameter and the operating state of the monitoring area, simulation is carried out, generates debris flow influence simulation parameter;Adaptive protection decision and execution subsystem, for generating and executing protection strategy according to protection plan base and the debris flow influence simulation parameter, wherein, the protection plan base is based on the construction of special research results.The present application can comprehensively collect the multi-dimensional monitoring information of debris flow prevention and control area, simulation result is accurate, also solves the pain point that present technical special research results are idle, protection decision lacks quantitative basis and is passive response.

The application relates to the technical field of water resource management and environmental governance, and discloses a river water conservancy dispatching and water pollution collaborative governance system based on digital twinning, which comprises a predictive digital twinning module, a right tokenization module and a futures transaction module.The predictive digital twinning module is used for predicting the available net water quantity, water environment capacity and water power potential value of a key node in one or more time units in the future of a river based on basin multi-source data; the right tokenization module is used for generating standardized tradable water right tokens, pollution right tokens and water power potential tokens; and the futures transaction module is used for providing a transaction platform for multiple stakeholders in the basin, and can carry out futures transactions on the water right tokens, pollution right tokens and water power potential tokens.Through digital twinning prediction, right tokenization and futures transaction, the application realizes dynamic market allocation of water rights and pollution rights, collaborates multiple target values such as reservoir power generation and downstream water supply, and enables the pollution cost to reflect the spatial environmental risk.

This invention discloses a multi-dimensional watershed similarity discrimination method based on geography, meteorology, and hydrology, relating to the fields of hydrological simulation and watershed management technology. By integrating a method for extracting underlying surface morphology features from multi-source data, combined with a meteorological time-series data feature selection method based on high-dimensional dynamic time distortion distance, and utilizing Sentinel-1 / 2 multi-source remote sensing images to invert flood hydrological process features, the method calculates the geographical morphological similarity, meteorological feature similarity, and hydrological process similarity between data-free and data-rich small watersheds. Weighted comprehensive similarity is then used to complete the small watershed similarity discrimination, achieving high-precision transfer of hydrological model parameters in data-free areas. This invention's method provides comprehensive underlying surface discrimination that closely aligns with hydrological mechanisms, effectively preserving dynamic meteorological and hydrological features and improving time-series classification accuracy. It directly matches flood processes through remote sensing inversion, avoiding misjudgments caused by traditional indirect inference. The process is standardized, adaptable to multiple scenarios, and suitable for hydrological simulation in data-free areas.

The application discloses a kind of rice irrigation area field dynamic hydrological process simulation method and system, method includes: the spatial correlation information base of rice field and ditch is constructed;With day as step simulation cycle, according to the dynamic adjustment effective field height of rice growth stage, based on field type and water level potential energy difference calculation lateral recharge or discharge;According to the exponential decay correction of plow pan saturated hydraulic conductivity of consecutive flooding days, calculate vertical infiltration amount;Overflow drainage, lateral discharge, vertical infiltration are updated into water balance equation field water depth;According to the topological network of confluence of field spatial position and elevation, consider the peak-shaving superposition of confluence time delay, obtain sub-basin export total runoff.It realizes the whole process fine simulation of field ridge water storage, field-ditch lateral interaction, plow pan nonlinear infiltration and distributed confluence, significantly improves the precision of rice irrigation area hydrological process simulation, provides scientific basis for irrigation water resources management.

The application provides a disaster risk assessment method based on a two-dimensional index of external flood and internal waterlogging composite events, and relates to the technical field of composite flood and waterlogging disaster risk assessment. The method comprises the following steps: acquiring basic geographic, underlying surface, hydro-meteorological and water conservancy engineering data of the external basin and urban area of a target region; constructing and verifying a basin-urban coupled hydrological model based on time-varying gain theory; extracting flood and waterlogging processes according to simulation results, setting a threshold to select a composite event, and fitting marginal distributions respectively; establishing a joint distribution based on a Copula function, and constructing a two-dimensional index of fusion intensity and cause indicators; determining an index threshold according to the urban flood control and drainage capacity, and calculating disaster risk based on a risk-exposure-fragility framework. The application can simultaneously measure the overall intensity of the composite event and the relative action of internal and external disaster-causing factors, and realizes quantitative and comparable assessment of regional risk.

This invention discloses a water pollution data monitoring method and system based on multi-objective analysis, belonging to the field of water pollution source tracing technology. The method includes: collecting a GIS map of the target watershed and time series data on rainfall, flow, and water quality; hydrologically segmenting the flow series according to the opening and closing status of dams to obtain surface runoff and baseflow components; constructing a two-dimensional water quality observation matrix, setting pulse and delay constraints in conjunction with rainfall and runoff components, and using a non-negative matrix factorization algorithm with ratio constraints for source analysis to obtain a source feature matrix and a source contribution time coefficient matrix; identifying pollution source emission attributes based on the ammonia nitrogen to total phosphorus ratio and the correlation between the source contribution coefficient and rainfall in the source feature matrix, and marking them on the GIS map. This invention integrates dam-controlled hydrological segmentation with matrix factorization based on physicochemical constraints to achieve refined source tracing, improving the accuracy and interpretability of pollution source identification.

This invention discloses a coupled simulation and prediction system for regional water and carbon cycle processes, relating to the field of watershed carbon cycle simulation. The system includes a data acquisition module that determines the watershed extent and identifies riverbank areas within a unified grid system. Simultaneously, vegetation type and soil organic carbon are mapped to riverbank grid cells, consistently expressing the spatial location of carbon sources in relation to hydrological watershed migration. This facilitates subsequent clarification of carbon source distribution. Based on a DEM (Digital Elevation Model), flow direction and confluence paths are constructed. Runoff in each grid is calculated under meteorological conditions and gradually converges into the river channel, establishing hydrodynamic transport paths with clear upstream and downstream relationships. This provides a physical carrier for carbon transport. Based on soil organic carbon and vegetation type in the riverbank grids, the system quantifies the differences in carbon supply capacity of different riverbank areas during regional water migration. Riverbank carbon sources are traced along the confluence paths. Spatial weights are constructed using distance attenuation and connectivity, mapping carbon sources to each grid cell. Carbon flux is then coupled with runoff to calculate and accumulate through gradual transport.

This invention discloses a method for monitoring long-term changes in primary productivity of rivers at a continental scale, belonging to the technical field of river ecosystem monitoring. The method involves determining the effective duration of daytime each day, forming a daily-scale meteorological and hydrological element time series, and selecting high-quality primary productivity data. The daily-scale meteorological and hydrological element time series and watershed attributes are fused to form daily input features, with high-quality primary productivity data used as output variables. A continental-scale river primary productivity simulation model is constructed and optimized. The trained simulation model outputs simulated river primary productivity values, generating daily-scale primary productivity time series data. The mean and annual mean of primary productivity are calculated, and the correlation between the annual time series and the annual mean is analyzed. This invention uses daily-scale meteorological and hydrological elements and constant watershed attributes as inputs, combined with a long short-term memory network deep learning algorithm, thus overcoming the strong dependence of traditional methods on minute- to hourly high-frequency dissolved oxygen monitoring data.

The application provides a water level prediction method and device for a water collection area of a pumped storage power station, and the method comprises the following steps: correcting rainfall prediction data to obtain rainfall input data; making a prediction based on the rainfall input data and basin water level characteristic parameters to obtain an initial water level prediction value; constructing a residual prediction model based on the residual between the measured monitoring water level value and the initial water level prediction value, determining boundary correction data of a monitoring blank period based on the initial water level prediction value of an effective monitoring period adjacent to the monitoring blank period and the residual prediction model; simulating the water level of the monitoring blank period based on the boundary correction data and the rainfall input data to obtain target water level data of the monitoring blank period; constructing a full-period continuous water level sequence based on the measured monitoring water level data and the target water level data of the monitoring blank period, making a water level prediction based on the full-period continuous water level sequence to obtain a water level prediction result; and making a water level warning according to the comparison result of the water level prediction result and a preset warning threshold.

The present application relates to a kind of surface water resource quantity calculation method based on runoff depth contour optimization, steps mainly include: runoff depth contour vector diagram is converted to TIN;Linear interpolation method converts TIN into grid data;Determine the runoff depth correction coefficient of each basin;Using correction coefficient, the runoff depth of all grids of each basin is corrected;The mosaic of corrected grid data is carried out;Using linear interpolation method, update runoff depth contour vector diagram and repeat the above steps;Then unit segmentation is carried out to complete grid data, and the unit water resource is summarized according to the need to obtain the required surface water resource quantity result.In addition, the present application also discloses an optimization method based on runoff depth contour.The present application can realize high-precision, high efficiency and automatic surface water resource quantity calculation.

The application discloses a mountain torrent disaster rainfall station optimization method based on grid coverage, belongs to the technical field of mountain torrent disaster research, and comprises the following steps: S1. extracting a grid related to an upstream of a mountain torrent disaster prevention object; S2. calculating a dynamic monitoring radius and a coverage area; S3. spatial intersection analysis; S4. calculating a coverage of the mountain torrent disaster prevention object and calculating a regional comprehensive coverage; and S5. rainfall station network layout optimization. The application solves the problems of insufficient coverage of an existing rainfall station network and failure to combine the characteristics of a basin, improves the scientificity of coverage evaluation, optimization efficiency and scheme economy, and is suitable for rainfall station network planning of a small-basin mountain torrent disaster prevention area.

This application discloses a method, system, equipment, and medium for deploying flood risk awareness and early warning stations in densely populated areas, relating to the fields of hydrological monitoring, flood disaster early warning, and disaster prevention and mitigation. The method includes: classifying stations in different river basins into first-class and second-class flood risk awareness and early warning stations; identifying a set of feasible deployment locations composed of road and bridge infrastructure; constructing a flood wave physical propagation model and calculating the flood propagation lag time between adjacent stations; using an interactive reinforcement learning algorithm incorporating a physical attention mechanism to calculate the physical sensitivity of flood propagation time to flood propagation lag time in real time; and determining the spatial deployment scheme for the second-class flood risk awareness and early warning stations from the set of feasible deployment locations. This application can solve problems such as early warning lag, spatial coverage blind spots, lack of systematic optimization, insufficient feasibility, and lack of an overall solution.

The invention discloses a water conservation evaluation system and method based on ecological protection engineering, and relates to the technical field of water conservation evaluation, the system comprises an information acquisition module, an analysis and calculation module, an evaluation module and a database, grid division is performed on a monitoring drainage basin to obtain drainage basin units, and monitoring moments are set; the rainfall, land utilization type, potential evapotranspiration and soil attribute information of each drainage basin unit are collected at each monitoring moment, the monitoring drainage basin is divided into a marked area and each ecological engineering area, the water conservation amount of each drainage basin unit is calculated according to monitored data for the marked area, and the water conservation amount of each ecological engineering protection area is calculated according to the monitored data for each ecological engineering protection area. According to the method, the influence of each ecological protection project on soil is analyzed, the water conservation amount of each drainage basin unit is calculated according to the analysis result, and the change characteristics of the water conservation amount are obtained through Sen + M-K trend analysis, so that the calculation accuracy and effectiveness of the monitoring drainage basin water conservation amount are guaranteed, the calculation cost is reduced, and the ecological protection project can be monitored for a long time.