47 results about "Catchment hydrology" patented technology

The invention provides a method for monitoring hydrology and water quality of a river basin under influence of water projects based on Internet of Things. According to the method, various fixed and flowing sensors are additionally mounted so as to obtain real-time hydrology and water quality data of important water areas, in combination with a video technology, monitoring on a spot environment is achieved, the monitoring information is transmitted through the Internet of Things, intelligent prediction for hydrology and water quality of the river basin is carried out through a neural network, and finally, critical applications, such as current situation assessment, tendency estimation, implementation effect estimation and extreme event handling, are achieved through an expert system. The method provided by the invention can provide real-time, reliable and complete hydrology and water quality information for the river basin under influence of water projects, and can achieve cross-regional and multi-machine type integrated remote protection for the river basin.

The invention discloses a flood forecasting scheme real-time optimization method based on machine learning. The flood forecasting scheme real-time optimization method comprises the following steps: 1)collection and processing of basin hydrological data; 2) rainfall and flood session division and association; 3) generation of a rainfall flood event sample set; 4) flood grading; 5) construction ofa flood forecasting scheme; 6) classifier training based on machine learning; and 7) forecasting scheme real-time optimization based on early rainfall. According to the flood forecasting scheme real-time optimization method, the sample set is divided into subsets on the basis of flood levels, and the flood forecasting schemes are compiled respectively and associated with the early rainfall processthrough a machine learning method, and optimization of the flood forecasting schemes during real-time forecasting is achieved, and the real-time flood forecasting precision of the drainage basin canbe effectively improved.

The invention relates to a geological disaster prediction and forecast technology, and aims to provide a rainfall threshold analysis method causing basin landslide risks. The method comprises the following steps: establishing a three-dimensional grid according to DEM topographic data and soil layer thickness data of a target watershed, and generating boundary conditions and initial conditions required by an RIRM hydrological model; calculating space-time changes of hydrological elements in the drainage basin and drainage basin slope stability reference indexes of any three-dimensional positionin the drainage basin; drawing a relation curve that the safety factor SF, the landslide volume and the landslide area respectively change along with time under the conditions of different rainfall durations and different rainfall intensities; analyzing the relationship between landslide deformation damage and rainfall to obtain rainfall thresholds causing basin landslide risks under different conditions. According to the method, natural basin geomorphic hydrological response characteristics are reserved, and prediction errors can be effectively reduced; drainage basin hydrology and slope stability analysis can be carried out simultaneously, the actual occurrence process of drainage basin landslide disasters is met, and the prediction result is more real and reliable.

The invention discloses an urban flood assessment method based on urban toughness and an urban watershed hydrological model. The method comprises the steps: acquiring satellite remote sensing data andurban meteorological data; calculating flood disaster occurrence areas, flood ponding areas and ponding depths of cities over the years; constructing an urban drainage basin hydrological framework model and an urban flood disaster response toughness framework model; calculating the toughness index of the city in response to flood disasters; carrying out contribution analysis on all elements of the city, and obtaining dimensions corresponding to the elements with the indexes lower than a first set value, wherein the lower the indexes of the elements are, the weaker the corresponding dimensionsare; calculating the drainage pressure and the ultimate drainage capacity of the urban drainage pipeline opening, and calculating the ponding risk of each area of the city; according to the water accumulation risk of each region of the city, obtaining the city region with the water accumulation risk greater than a second set value, wherein the higher the ponding risk is, the more easily the floodoccurs in the corresponding area; and evaluating the urban flood area and the urban weak dimension in the urban rainfall process.

The invention discloses a method for improving simulation precision of a high-altitude drainage basin hydrological process without data. The main purpose is to provide a method for improving simulation precision of a high-altitude drainage basin hydrological process without data. According to the method, a hydrological physical process, a neighboring area law and a vertical differentiation law are used as basic theory bases, and a parameter transfer relation is built for multiple groups of soil and water assessment tool (SWAT) parameters adjacent to a station mountain drainage basin in Xinjiang; based on the parameter transfer relation, a tool parameter set of a reference basin is converted into a tool parameter set of a target drainage basin, so that high-precision simulation of the high-altitude drainage basin hydrological process without data is achieved. The method is applicable to hydrological process simulation of medium and small rivers of a high-altitude region without data; after localization of tool parameters is achieved, the simulation precision of the drainage basin hydrological process without data can be improved, the method is beneficial to monitoring and early warning of a mountain torrent, and the risk of the mountain torrent disaster is reduced.

The invention provides a runoff calculation and prediction method based on a watershed hydrological model. The method comprises the steps: building a watershed hydrological model, and constructing a feature region basic watershed database; dividing hydrological response units according to different characteristic area basic drainage basin data; inputting localized model data, and carrying out related data simulation; determining model parameters of the watershed hydrological model; verifying the correctness of the watershed hydrological model; and inputting meteorological data in the watershed in a future climate scene into the watershed hydrological model, and predicting the river runoff in the hydrological response unit. According to the rainfall runoff and rainfall runoff prediction method, the whole runoff production and confluence process in the drainage basin is considered, the water flow movement process of the whole drainage basin is simulated by inputting climate data, drainage basin data and land utilization data of the drainage basin, and the rainfall runoff and rainfall runoff prediction method can be well applied to simulation of river runoff of the drainage basin and is fast in rainfall runoff calculation and program response.

The invention discloses a watershed hydrological model parameter dynamic estimation method based on a digital twinborn technology. Constructing digital twin bodies of the watershed based on the physical characteristic data of the watershed and observation data such as historical hydro meteorology; sensors are arranged in the drainage basin to achieve real-time monitoring of multiple feature elements of the drainage basin, and real-time tracking and information synchronization of digital twins of the drainage basin are achieved; according to historical and real-time synchronous drainage basin digital twins, state variables and parameters in the simulation model are estimated in a mode of synchronously combining a data assimilation method and an optimization algorithm, and finally dynamic estimation of parameters of the drainage basin hydrological model is achieved. According to the method, the real-time monitoring data of the drainage basin can be fully utilized, the dynamic change presented by the characteristic conditions of the drainage basin under the changing environment background can be accurately reflected, the targets of intelligent management, analogue simulation, automatic optimization, real-time updating and reasonable prediction are achieved, and the runoff simulation precision of the drainage basin under the changing environment can be improved.

The invention relates to a hydrological model parameter calibration method based on multiple hydrological variables, and the method comprises the following steps: S1, obtaining long-time series hydrometeorological data, remote sensing inversion soil humidity and evaporation capacity data in a watershed range, and taking one year as a minimum unit, dividing the data period into a plurality of different sub-periods according to the conditions of annual precipitation, annual runoff and drainage basin underlying surface; s2, aiming at each sub-period, on the basis of remote sensing inversion evaporation capacity data and soil humidity index SWI data, calibrating hydrological model parameters in two modes of joint calibration and step-by-step calibration; and S3, by taking the King-Gupta efficiency coefficient as an evaluation index, analyzing and evaluating the flow process simulation effect of the model parameters in each rate stator sub-period and the flow process simulation effect of the model parameters transferred to other sub-periods. According to the method, the uncertainty of the model parameters can be effectively reduced, the mobility of the model parameters in different time periods is improved, and the reliability of the watershed hydrological model in production practice can be improved.

The invention discloses an automatic calibration method for hydrological model parameters in a data area. The automatic calibration method comprises the following steps: step 1, selecting hydrologicalmodel parameters needing to be calibrated; and step 2, adopting an artificial intelligence genetic algorithm to automatically calibrate hydrological model parameters needing to be calibrated in a data area. The technical problems that in the prior art, a traditional trial and error method is adopted for determining parameters of a hydrological model of a watershed with data, that is, parameter values of the hydrological model are continuously adjusted manually to meet the requirement for simulation precision, and the method is subjective, low in work repeatability, low in efficiency, extremely high in complexity, not beneficial to application and popularization of the hydrological model and the like are solved.

The invention discloses a method for researching the split ratio and the sewage separation ratio and the evolution rule thereof of a bifurcated channel. The method comprises the following steps: surveying hydrological information of a drainage basin where the bifurcated channel is located; calculating the river flow of the drainage basin under different assurance rates; constructing a water environment mathematical model; analyzing a split ratio rule of the bifurcated channel; analyzing a sewage separation ratio rule of the bifurcated channel; and analyzing the evolution rule of the split ratio and the pollutant separation ratio of the bifurcated channel. The invention provides a research method for analyzing the splitting ratio and the sewage separation ratio and the evolution rule thereof of a bifurcated channel, aiming at the current situation that the current research on the sewage separation ratio, the splitting ratio and the sewage separation ratio evolution rule of the bifurcated channel is insufficient, and a scientific basis is provided for formulating environmental management policies such as flood control and drainage, ecological water supplementation, total pollutant amount control, water environment protection and water ecological restoration.

The invention discloses a small reservoir flood level forecasting method based on a two-dimensional-zero-dimensional coupling model. According to the current situation that hydrological data of a drainage basin where a small reservoir is located is deficient, the drainage basin where the reservoir is located is divided into two parts with the water surface boundary corresponding to the limited water level of the reservoir in the flood season as a dividing line, and the upstream land part adopts a two-dimensional hydrodynamic model to simulate the surface runoff process; the downstream reservoir area part adopts a zero-dimensional water conservation model to calculate the reservoir water level, the flow of the coupling edge of the two-dimensional hydrodynamic model is used as the inflow condition of the zero-dimensional water conservation model, the newly calculated reservoir water level is used as the control boundary of the next time step of the two-dimensional hydrodynamic model, and the two models are calculated in a rolling manner; therefore, the purpose of reservoir water level forecasting is achieved. According to the method, only two parameters which do not depend on historical hydrological data need to be considered, and a new technical solution can be provided for forecasting the water level of the small reservoir in a watershed lack of historical hydrological data.

The invention discloses a remote sensing-based riverway water volume estimation method. The method comprises the following steps of obtaining a drainage basin boundary; acquiring a drainage basin remote sensing data image; cutting the drainage basin remote sensing data image: cutting the remote sensing data image in the step S2 by using the drainage basin boundary obtained in the step S1 in ENVI software to obtain the remote sensing data image of the whole drainage basin; extracting a basin water surface area; obtaining basin water volume data; and establishing a watershed water surface annualrunoff relationship: drawing a watershed water surface area and watershed water volume curve of the corresponding year, performing fitting to obtain a watershed runoff estimation formula and a correlation coefficient, and obtaining a river water volume estimation result through the watershed runoff estimation formula. According to the method, the water volume change of the river can be timely andquickly obtained, the problems of insufficient basin hydrological data and the like can be effectively solved, the dependence on actual measurement data is reduced, and the method has relatively goodprecision and extrapolation applicability.

The invention relates to a short-term power generation output prediction method for a distributed small hydropower station, and the method comprises the steps: carrying out the basin hydrological law analysis according to the historical electric quantity information and rainfall information of the small hydropower station, employing a distributed frame structure, and employing a large-scale data mining calculation method, and building a rainfall and power station electric quantity incidence relation calibration parameter; predicting the electric quantity of the power station in the future three days by adopting a chaos time sequence method through a future drainage basin rainfall prediction sequence, performing day-by-day process decomposition on the daily electric quantity by utilizing a similarity machine learning discrimination method, and finally obtaining an output process prediction sequence of the small hydropower station in the future three days. Therefore, the internal relation between the rainfall and the electric quantity of the small hydropower station without water regimen forecasting is accurately described, the daily electric quantity process is decomposed by using a recurrent neural network and similar data mining, and the daily output process forecasting of the small hydropower station without water regimen forecasting is realized. And the planned output compilation method of the water-regimen-free forecasting power station is provided for refined small hydropower dispatching.

The invention discloses a watershed hydrological model error correction method and device based on distributed evaporation error compensation. The method comprises the following steps: establishing a subunit evaporation error compensation vector model according to a watershed outlet section simulation flow process and a watershed subunit evaporation process; establishing a surface evaporation error compensation vector and an error compensation matrix model according to the subunit evaporation error compensation vector model; establishing a surface evaporation error estimation model and determining an evaporation error correction mode of the subunits; and calculating evaporation errors of the subunits to obtain a corrected evaporation process of the subunits, inputting the corrected evaporation process into a flow function of the drainage basin outlet section, namely a drainage basin hydrological model, and obtaining a corrected flow process of the drainage basin outlet section. The hydrological model feedback information is fully utilized, the method is decoupled from the hydrological model during error inversion, the method is theoretically suitable for any distributed hydrological model, and the method provides a new technical means for solving the watershed hydrological model daily scale evaporation input item error correction problem.

The invention belongs to the technical field of hydrological analysis, and particularly relates to a runoff forecasting model construction method and device, electronic equipment and a medium. The method comprises the steps of obtaining a historical hydrological sequence of a target drainage basin and a target distribution function used for fitting a hydrological distribution condition of the target drainage basin; substituting the historical hydrological sequence into the target distribution function to obtain a first probability sequence; obtaining a probability prediction model, a second probability sequence and a prediction error sequence according to the first probability sequence; generating an error probability correlation function according to an error threshold sequence and the prediction error sequence; and according to the inverse function of the target distribution function, the probability prediction model and the error probability correlation function, generating a runoff prediction model for predicting the hydrological condition of the target drainage basin. According to the forecasting model construction method provided by the invention, through mutual cooperation of the target distribution function, the probability forecasting model and the error probability correlation function, the runoff forecasting model can have relatively high precision.

The invention discloses a data-free region hydrological parameter calibration method based on an adversarial neural network. The method comprises the following steps: collecting soil texture, vegetation coverage, land utilization rate, topographic data, runoff coefficient, annual total evaporation amount, gradient and gradient data; dividing the calibration region into calculation units within 30square kilometers or less; determining the underlying surface and meteorological correlation factors of each parameter of each calculation unit; adopting an adversarial neural network GAN to automatically calibrate the hydrological parameters of the watershed with the data to obtain the optimal hydrological parameters of each unit; training a unified parameter generator based on an adversarial neural network (GAN) by adopting the optimal hydrological parameters of all computing units in the area with data; determining hydrological parameters of the data-free region through the trained parameter generator. The technical problems that in the prior art, work repeatability and efficiency are low, complexity is extremely high, and application and popularization of a hydrological model are not utilized are solved.

The invention discloses a watershed hydrological similarity estimation method based on time series nuclear distance, comprising the following steps: S1. Obtaining hydrological observation data of the watershed to be studied; S2. Determining the precipitation process to be analyzed according to the hydrological observation data of the watershed to be studied and the analysis period of the hydrological response process; standardize the hydrological response time series of different analysis stations in the watershed to be studied to obtain the standardized sequence of the hydrological response process; S3. S4. Use the calculation method described in S3 to calculate the nuclear distance between the hydrological response processes of two different analysis stations, obtain the nuclear distance matrix D of the hydrological response process of different analysis stations in the watershed, and finally use the hierarchical clustering analysis method Analyze its hydrological similarities. The invention overcomes the disadvantage of high cost in the prior art, improves the utilization rate of the existing hydrological observation data, and reduces the estimation cost of the hydrological similarity of the existing watershed.