79 results about "Catchment hydrology" patented technology

The invention discloses a reservoir group-lake system flood control risk adaptive analysis method and system. The method comprises the following steps: acquiring a basin hydrological sequence and a pre-configured physical causal constraint matrix, and constructing a VineCopula joint distribution and initial Bayesian network conforming to physical topology according to the basin hydrological sequence and the pre-configured physical causal constraint matrix; risk sensitive weights of the sample points are calculated based on the Bayesian network, and weighted sampling density inclining towards the high-risk area is constructed; generating a self-adaptive scene set based on the density, solving an optimal scheduling scheme, feeding back a scheduling result to the Bayesian network to update parameters, carrying out closed-loop iteration of perception-sampling-scheduling-learning until risk assessment is converged, and determining a comprehensive flood control risk assessment result of the system based on the converged risk factor Bayesian network. According to the method, the problems of poor physical interpretability and scarcity of extreme risk samples of a traditional model are solved, and accurate capture and quantification of extreme risks of a complex flood control system are realized.

The invention provides a watershed artificial precipitation enhancement operation effect evaluation method based on hydrological simulation, and belongs to the technical field of artificial influence weather, and the method comprises the steps: obtaining first data and second data; based on the first data, settling a rainfall-runoff process, selecting a preset hydrological model to carry out a drainage basin hydrological batch simulation test, calibrating hydrological parameters, and constructing a drainage basin hydrological simulation forecast model; based on the second data, calculating the natural precipitation of the non-operation area and the operation precipitation of the operation area, and constructing a natural precipitation-operation precipitation data sequence; based on the natural precipitation-operation precipitation data sequence, inputting the natural precipitation into the watershed hydrological simulation forecasting model to obtain runoff before precipitation enhancement operation, and inputting the operation precipitation into the watershed hydrological simulation forecasting model to obtain runoff after precipitation enhancement operation; and based on the runoff before the rainfall enhancement operation and the runoff after the rainfall enhancement operation, carrying out quantitative evaluation on the artificial rainfall enhancement operation effect of the drainage basin. Scientific quantitative evaluation of the artificial precipitation enhancement operation effect of the watershed is realized.

The invention relates to a reservoir dispatching management method and system based on digital twinning, and the method comprises the following steps: carrying out the real-time parameter collection of a target reservoir, and obtaining a reservoir characteristic parameter matrix; performing three-dimensional space modeling based on the reservoir characteristic parameter matrix and the reservoir hydrogeological environment in the target reservoir to obtain a reservoir digital twinborn model; performing drainage basin rainfall-runoff dynamic response analysis on the reservoir digital twin model to obtain a drainage basin hydrological response characteristic curve group; performing prospective water balance calculation on the watershed hydrological response characteristic curve group to obtain a multi-period reservoir flow prediction sequence; and formulating an optimal scheduling instruction set of the target reservoir based on the multi-period reservoir inflow prediction sequence, and regulating and controlling a reservoir gate control system in the target reservoir based on the optimal scheduling instruction set. And the method is difficult to adapt to hydro meteorological conditions and multi-target scheduling requirements which change in real time.

The invention discloses a drainage basin hydrological prediction method based on digital twinning, and the method comprises the steps: obtaining multi-source heterogeneous data, carrying out the processing of the multi-source heterogeneous data, and obtaining a multi-source data set; constructing a multi-dimensional spatial feature set according to the multi-source data set; based on the multi-dimensional space feature set, a finite volume method is adopted to simulate a water circulation process, and a water circulation simulation result is obtained; obtaining an error value of the water circulation simulation result and actual observation data, and performing nonlinear relation mining on the multi-dimensional spatial feature set through a neural network algorithm based on the error value to obtain a data driving prediction result; fusing the water circulation simulation result and the data driving prediction result by adopting a weighted fusion algorithm to obtain a fused prediction result; and constructing a digital twinborn model according to the fusion prediction result, and predicting the hydrological state in real time based on the digital twinborn model. The method can provide more effective decision support for water resource management and flood control and disaster reduction.

The invention discloses a hydrological forecasting method based on multi-feature combination and a Transform model. The method comprises the following steps: acquiring measured data of a target watershed hydrological station, building a physical hydrological model, acquiring output data and derivative feature data of the physical hydrological model, and integrating to obtain basic hydrological data; creating enhanced hydrological physical features, and forming a multi-dimensional original feature pool; constructing a plurality of combination strategies based on the basic hydrological data and the multi-dimensional original feature pool; capturing a long-term dependency relationship of the hydrological time sequence by using an improved Transform model; and the model performance is improved through automatic hyper-parameter optimization. According to the method, the influence of different input feature combinations on the flood forecasting precision is highlighted, and effective technical support is provided for water resource management and flood control and disaster reduction.

The invention discloses a basin hydrological simulation method and system embedded with a canopy interception mechanism, and the method comprises the steps: embedding a revised Gash canopy interception model module in an SWAT model, dividing a rainfall event into a wetting stage, a saturation stage and a drying stage according to the parameters of rainfall, a leaf area index and a tree height, dynamically calculating the canopy interception amount and the interception evaporation amount, and carrying out the calculation of the canopy interception amount and the interception evaporation amount. The effective rainfall capacity is used for replacing original rainfall input in the SWAT model, the adjusting effect of the forest canopy on the rainfall process is reflected more truly, and the basin hydrological simulation precision is improved. According to the method, the response and simulation capability of the SWAT model to the hydrological process of the underlying surface of the forest is effectively improved, the dynamic response to effective rainfall and evaporation terms is enhanced, the method is suitable for watershed hydrological process modeling of various forest types, and the reliability of flood forecasting and water conservation evaluation is improved.

The invention discloses a space intelligent watershed hydrology and water quality multivariable prediction method based on quaternion time-frequency multi-scale, and the method comprises the steps: obtaining the hydrology and water quality data of a space-time heterogeneous watershed, and representing the space-time coupling characteristics of the interior of the watershed and cross-site; carrying out missing value restoration on the hydrology and water quality data; constructing a time domain-frequency domain composite feature tensor; sequentially mapping the constructed time domain-frequency domain composite feature tensor to a real part and a three-imaginary part of a quaternion to generate coupled quaternion feature representation; summarizing multi-head output through a quaternion fusion layer to obtain high-dimensional coupling feature representation; and inputting the high-dimensional coupling characteristics into a quaternion Transformer decoder, and after nonlinear mapping and channel-by-channel regression processing, outputting a hydrology and water quality multivariable predicted value in a future time period. The method can be quickly migrated to a new drainage basin or a monitoring station and maintain high-precision output, and provides a reliable and extensible intelligent decision basis for real-time water resource scheduling, pollution load management and control and ecological flow guarantee.

The invention relates to a flood and drought disaster risk assessment and deduction system and method based on slope multi-level regulation and storage, and belongs to the technical field of flood and drought disaster risk prevention and control and watershed hydrological regulation and control. The method comprises the following steps: acquiring multi-source data of a target drainage basin, performing water source refined analysis through coupling of water transfer coefficients (K1 and K2) based on a hierarchical synergistic effect of'upper closure-middle retention-lower dissipation 'of a slope, and calculating a controllable, effective and renewable water source amount; in combination with the regulation and storage capacity difference of each level, carrying out flood and drought disaster chain risk collaborative assessment, and outputting hierarchical risks and 0-10 level set risk indexes; a physical mechanism and data driving coupled scene deduction model is driven, and historical extreme event redisk and future climate scene prediction are completed; and after rendering by a visual engine, through hierarchical slope regulation and storage threshold comparison, outputting a regulation and storage measure layout optimization scheme. The system adopts a micro-service architecture and comprises a data management module, a multi-level regulation and storage collaborative analysis module, a water source analysis module, a risk evaluation module, a scene deduction module, a decision support module and a threshold comparison module. According to the method, high-resolution accurate positioning, low-error simulation and efficiency improvement of flood and drought disaster risks are realized, a decision closed loop from risk identification to optimization regulation is formed, and direct and quantitative technical support can be provided for flood and drought prevention and control engineering practice of drainage basins.

The invention discloses a basin sand reduction efficiency evaluation and regulation method based on a reservoir group topological structure, and belongs to the field of hydraulic engineering, and the method comprises the steps: S1, inputting basin hydrological data; s2, calculating accumulated runoff sediment transport and drawing a double-accumulation curve; s3, recognizing turning years of human activities on the water-sediment relationship through the double-accumulation curve mutation points, and dividing a natural period and a human influence period by combining the mutation points; s4, analyzing a water-sediment relationship, and calculating a drainage basin sediment reduction amount; s5, determining the topology type of the reservoir; s6, calculating an effective control drainage basin area; s7, establishing a relationship between the effective control basin area and the sand reduction rate; and S8, nonlinear regression equation modeling is carried out. The topology cutting effect theory is applied to reservoir group sand reduction efficiency evaluation, and the error problem of a traditional linear superposition model is solved; dynamic prediction of the long-term sand reduction cumulative effect of the cascade reservoir group under the watershed scale is realized; quantitative decision support is provided for newly-built reservoir site selection and built reservoir group optimization scheduling, and the river channel siltation treatment cost is reduced.

The application relates to the technical field of hydrology and water resources simulation, and discloses a SWAT watershed hydrology model task planning system, method and product, which comprises a knowledge graph construction module, an embedded index construction module, a query coding and two-stage retrieval module, a context construction module and a large language model task planning module. Through the complete planning process of knowledge graph modeling, vector index construction, two-stage retrieval, context generation and structured task output, the whole-process intelligentization from a user's natural language demand to SWAT watershed hydrology model executable task planning is realized, the SWAT file / parameter structure can be accurately matched, the professionalism, accuracy and executability of task planning are improved, and the problems of high operation threshold, large artificial workload, unstable and unexecutable output of a general large model of a traditional SWAT watershed hydrology model are solved.

The application discloses a large-scale basin deep learning flood forecasting method based on runoff lag information and relates to the technical field of hydrological simulation and flood forecasting of machine learning, and comprises the following steps: collecting basin hydrological observation site information data, basin characteristic data, basin historical hydrological data and meteorological forecasting characteristic data; dividing a large-scale basin into a plurality of sub-basins; preprocessing data, extracting runoff lag information obtained by using a convolutional neural network model, and constructing a runoff lag information database; adopting a deep learning long short-term memory model to couple the runoff lag information database, obtaining a plurality of sub-basin runoff lag information models; obtaining optimal runoff lag information parameters of the plurality of sub-basins according to a model precision evaluation index, obtaining an optimal hydrological forecasting model, and realizing accurate flood forecasting of the large-scale basin. The application makes up for the deficiency of flood forecasting under the condition of lack of hydrological data of a large-scale basin and has a strong application prospect in areas with little or no data.

The invention relates to the field of hydrological data analysis and model correction, in particular to a digital twin basin correction method based on non-stationary reservoir hydrology, which comprises the following steps: acquiring hydrological data of a basin in a predetermined season period to extract corresponding hydrological motion features; in combination with hydrological motion characteristics and the number of branch runoff paths, analyzing characteristic parameters representing hydrological connectivity stability of the watershed to divide hydrological fluctuation categories of the watershed; adaptively evaluating and correcting twinborn parameters of the drainage basin based on hydrological fluctuation categories; and determining a corresponding prediction deviation level based on the corrected prediction deviation value of the simulation prediction result and the actual result. According to the method, the adaptability and robustness of the digital twin basin model are improved while the accuracy of hydrological simulation and prediction is improved, and then the practicability and efficiency of engineering practical application are improved.

The application introduces a kind of aquatic organism protection threshold identification method based on four water coupling models, comprising: S1, constructing a watershed hydrological model, then inputting rainfall data, obtaining runoff output data;S2, constructing a river water power and water quality model, then inputting water quantity data, water level data and water quality concentration data, obtaining water quantity output data, flow velocity output data, water level output data, flow direction output data and water quality concentration output data;S3, determine the aquatic organism sampling point, and obtain the hydrology, hydrodynamic, water quality data of the corresponding aquatic organism sampling point through the watershed hydrological model and the river water power and water quality model;S4, extract the hydrology, hydrodynamic, water quality data matched with the aquatic organism sampling point from the model, construct a multi-factor coupling model based on random forest, and identify the aquatic organism protection threshold. Through the above design, the technical effect of solving the data matching in the aquatic organism protection threshold identification process is realized.

The application provides a hydrological simulation method and system based on one-way driving of a nested model in the Yellow River Basin, and belongs to the technical field of hydrological simulation; the method comprises the following steps: taking a SHUD model as a core layer for simulating the hydrological cycle of the basin, taking a MIKE hydrodynamic model as a river channel hydrodynamic simulation layer, coupling the two models to construct a nested model, and performing one-way driving based on a spatial nesting technology; a two-way data interface is constructed, data exchange between the SHUD model and the MIKE hydrodynamic model is realized, a data assimilation algorithm is introduced, historical observation data are used to calibrate the parameters of the nested model, and key parameters are optimized; and then, the hydrological process of the basin is simulated based on the optimized nested model. The application can realize high-precision simulation of the hydrological process of the basin, and further provides scientific guidance for water resource management in the Yellow River Basin.

The application discloses a kind of based on hydrological hydrodynamic coupling model's small and medium-sized reservoir scheduling optimization method, obtains the basic information of reservoir basin and carries out data processing;Set boundary condition, adopt SCS runoff generation model to carry out runoff generation calculation to reservoir basin grid;Based on two-dimensional N-S equation, model is constructed, two-dimensional hydrodynamic calculation is realized;And according to actual data, using different reservoir area calculation method, construct reservoir basin hydrological hydrodynamic coupling model;Carry out reservoir basin multi-source water resources allocation, for scheduling rule optimization boundary inflow condition and water demand upper limit;According to coupling model, in combination with the objective function of reservoir, constraint condition and water demand upper limit, scheduling rule is optimized, obtains optimal scheduling parameter and scheduling scheme.Optimal scheduling strategy of real-time and forecast period reservoir can be given, and the problem that real-time or forecast optimization scheduling simulation is difficult due to the lack of hydrological data in the basin where small and medium-sized reservoir is located is preferably overcome.

The invention relates to the technical field of watershed hydrological model parameter calibration, in particular to a hydrological model parameter calibration method for a watershed lacking hydrological data, which comprises the following steps: determining a watershed A lacking data and a watershed B controlled by an adjacent hydrological station (reference station) with data, and collecting hydrometeorological and underlying surface feature data of the two watersheds; calculating the design flood of the drainage basin A and the drainage basin B by using a rainstorm runoff survey algorithm; comparing the design flood calculated by the rainstorm runoff of the watershed B close to the data with the design flood calculated by the actually measured flow data, and determining a flood correction coefficient kappa for correcting the design flood calculated by the watershed A lacking the data by using the rainstorm runoff calculation algorithm; inputting the model parameters of the data-lacking watershed A and the design surface rainstorm into a hydrological model; simulating an outlet section flood; and comparing a simulation result with a corrected rainstorm runoff checking result, analyzing parameter sensitivity, and adjusting and optimizing model parameters. The method is suitable for parameter calibration of the data-lacking small-watershed mountain torrent forecasting model, and a new means is provided for flood control and disaster reduction.

The invention discloses a stage-by-stage dynamic flood control water level regulation and control method suitable for a hydropower station, and the method comprises the steps: obtaining watershed hydro meteorology, engineering operation and topographic geology multi-source basic data, and carrying out the Spark distributed cleaning, wavelet denoising and GAN missing value complementation preprocessing, thereby forming a standardized data set; an optimal flood season staging scheme is screened through coupling of qualitative analysis and a quantitative method; then, the safe pre-discharge amount and the effective pre-discharge time serve as sensitive factors, a flood control water level dynamic control model is built in combination with fuzzy mathematics and Copula joint distribution, and flood control water level process lines and regulation and control domain values of all flood season stages are generated; the safety of a regulation and control threshold value is verified through finite element simulation and a two-dimensional hydrodynamic model, a regulation and control scheme meeting flood control safety and efficient utilization of water resources is output, dynamic and accurate regulation and control of the flood control water level of the hydropower station are achieved, and the problems that in traditional static flood control water level dispatching, the contradiction between flood control and benefit making is prominent, the staging precision is low, and safety verification is insufficient are solved.

The application relates to a two-dimensional flood risk prediction method, device, electronic equipment, medium and product, which comprises the following steps: acquiring multi-modal data in a target river basin; obtaining simulated runoff results based on a plurality of hydrological models pre-established according to the multi-modal data in the target river basin, and establishing a hydrological-machine learning coupled model based on the simulated runoff results; simulating the river basin hydrological process under a future scenario through the hydrological-machine learning coupled model to obtain a river basin hydrological process simulation result under the future scenario, and extracting flood duration and flood volume characteristic values under a plurality of warming level time windows by using a preset optimal model based on the river basin hydrological process simulation result, obtaining a two-dimensional flood risk prediction result based on the flood duration and flood volume characteristic values under the plurality of warming level time windows, thereby solving the problems of low flood risk prediction accuracy and poor applicability in the related art, and improving the flood risk prediction accuracy and applicability.

The application discloses a kind of watershed hydrology water quality model generation progressive decoupling method, system, equipment and medium, the method is first in pre-constructed watershed hydrology water quality model (parent model) Positioning target area's most downstream sub catchment, then by dynamic topological tracking method, the sub catchment of upstream sub catchment that exists hydraulic connection with most downstream sub catchment is identified, and the topological correlation sub catchment set is obtained;Then the parameters of each sub catchment in the set are extracted, including model parameters, boundary conditions, initial conditions and parent model general configuration parameters;Finally, according to the extracted information, the sub model is constructed, and the consistency of the model results is verified;When the research requirement involves more fine scale, the above decoupling process is iteratively executed with the above sub model as a new parent model, until the final scale requirement is met.The application significantly improves the accuracy and efficiency of the spatial scale decoupling of the watershed hydrology water quality model, and is suitable for large-scale watershed fine management and research.

The invention relates to the technical field of watershed hydrological simulation, and discloses a hydrological model parameter calibration method and device, equipment, a medium and a product, and the method comprises the steps: obtaining the spatial distribution characteristics of a first model parameter; determining a reasonable value range of the first model parameter according to the actual value range and the theoretical value range of the first model parameter; determining a search interval of the first model parameters according to the reasonable value range and the spatial distribution characteristics; the first model parameter is calibrated according to the search interval and the calibration database by taking the first index optimization as the target to obtain a target hydrological model, the first index represents the simulation precision of the hydrological model through the predicted hydrological data and the actual hydrological data, the predicted hydrological data is the output value of the hydrological model, and the actual hydrological data is the output value of the hydrological model. The actual hydrological data is hydrological data corresponding to the hydrological model input in the calibration database. According to the method, the spatial difference and the physical consistency of the calibration parameters can be ensured, and the stability of the finally obtained target hydrological model is improved.

The present application relates to the technical field of hydrological simulation, and more particularly to a rainfall-runoff-concentration-evolution whole-process dynamic simulation system and method. The method comprises the following steps: obtaining basin topographic information and extracting basin boundaries; dividing grid cells according to the basin boundaries and setting river nodes using the grid cells; collecting rainfall data using a rain measurement radar; calculating runoff using the rainfall data; inputting the runoff into a pre-trained distributed concentration model for concentration analysis and recording the concentration flow; inputting the concentration flow and the river nodes into a river flood evolution model to perform river evolution simulation and generate river concentration data; determining the amount of water entering the main river according to the river concentration data; generating a flow time series according to the amount of water entering the main river; and predicting the flood peak flow based on the flow time series. The present application realizes accurate simulation of the hydrological process of a basin based on hydrological simulation technology, and improves the accuracy and timeliness of flood prediction and early warning.

The application discloses a basin hydrology simulation method and system based on multi-source remote sensing, relates to the technical field of data processing, and comprises the following steps: acquiring multi-source remote sensing data by interacting with a satellite remote sensing platform and a ground measurement station; constructing a basin simulation model comprising a physical simulation layer and a digital simulation layer by analyzing the digital elevation structure and physical elements of a target basin; performing simulation solving on the digital simulation layer of the basin simulation model, mapping to the physical simulation layer, and generating a water area simulation state; and performing optional display of the water area simulation state. The application solves the technical problems of strong dependence on ground measurement stations, insufficient spatial coverage, difficulty in fusing multi-source heterogeneous remote sensing data, and low accuracy and efficiency of hydrology control equation solving under complex terrain conditions in the prior art, and achieves the technical effects of improving the spatial resolution, model accuracy, calculation efficiency and multi-source data fusion capability of basin hydrology simulation.

The invention relates to a two-dimensional flood risk prediction method and device, electronic equipment, a medium and a product. The method comprises the following steps: acquiring multi-modal data in a target drainage basin; obtaining a simulation runoff result based on a plurality of pre-established hydrological models according to the multi-modal data in the target drainage basin, and establishing a hydrological-machine learning coupling model based on the simulation runoff result; the method comprises the following steps: simulating a basin hydrological process in a future scene through a hydrological-machine learning coupling model to obtain a basin hydrological process simulation result in the future scene, and extracting flood duration and flood volume characteristic values in a plurality of warming horizontal time windows by utilizing a preset optimal model based on the basin hydrological process simulation result; and obtaining a two-dimensional flood risk prediction result based on the flood duration and the flood volume characteristic values under the plurality of warming horizontal time windows, thereby solving the problems of low flood risk prediction accuracy and poor applicability in related technologies, and improving the flood risk prediction accuracy and applicability.

The invention relates to a watershed hydrological prediction method and system based on meteorological driving and causal reconstruction, and belongs to the technical field of watershed hydrological prediction. The method comprises the following steps: constructing a causal structure diagram between meteorological driving variables and between meteorological driving variables and rainfall to form an interpretable meteorological and rainfall causal diagram, explicitly converting a functional relationship in a sub-module into a series of structural equations by taking a traditional hydrological model as a construction basis, and uniformly embedding the structural equations into a causal model framework to form a meteorological and rainfall causal diagram; and a unified structural causal graph is constructed through a graph structure merging technology, and the whole process description of a causal path from external climate factors to drainage basin runoff and runoff response is realized. According to the method, a physical mechanism, statistical learning and causal reasoning are fused, the defect that a traditional model lacks explanatory ability and generalization ability when coping with non-stationary meteorological conditions is overcome, and a system modeling method with causal support is provided for flood forecasting, water resource management and extreme climate response simulation.

The application discloses a method for in-situ rapid acquisition of soil hydraulic parameters based on water infiltration process, adopts a brand-new derivation method, derives an analytical solution which can accurately describe one-dimensional water infiltration of homogeneous soil under constant water head boundary conditions based on Richards water flow control equation and Brooks-Corey model, first depicts the important infiltration characteristics that the saturation zone grows with time, and can more accurately simulate the soil water infiltration process. Based on the inverse process of the analytical solution, a parameter optimization estimation method is provided. The method only needs to measure the change data of cumulative infiltration and wetting zone length with time in the water infiltration process through a time domain reflectometer (TDR), and can rapidly acquire the soil hydraulic characteristics in-situ in a field. The calculation method is low in cost, stable in inversion process, avoids problems such as multiple solutions of parameters and non-convergence, and provides a powerful acquisition means for parameters required by large-area watershed hydrological simulation.

The invention provides a drainage basin hydrological toughness evaluation and regulation method based on a Budyko framework, and belongs to the technical field of hydrological water resource management and environment monitoring. Firstly, an improved Budyko framework and a standardized rainfall index (SPI) are adopted to carry out hydrological toughness analysis calculation and mutation analysis research on the Weihe river basin; then, the driving force influencing the hydrological toughness of the watershed and the regulation and control mechanism of the driving force are analyzed by adopting CCM-Geoderator; and finally, constructing a natural scene without human activities through a VIC model, and illuminating the influence of human climate change on hydrological toughness. The new hydrological toughness evaluation method provided by the invention can comprehensively explore the space-time evolution characteristics and driving force of the hydrological toughness in the Weihe River basin, and provides effective support for improving the ecological restorability of the basin and promoting sustainable development.

The invention provides a reservoir discharge flow continuous prediction method and device, and belongs to the field of basin hydrological simulation. The method comprises the steps of obtaining daily reservoir storage flow, total reservoir storage flow, water taking amount and timestamps corresponding to each day of a to-be-predicted time period, respectively normalizing the daily reservoir storage flow, the total reservoir storage flow of one month, six months, one year, two years and five years in the past, constructing a first input feature data set, and then inputting a reservoir water storage model to obtain a second input feature data set; obtaining a prediction result of the reservoir water storage and the reservoir water level at the beginning of each day; and constructing a second input feature data set after standardizing the reservoir inflow rates of the to-be-predicted time period every day and the first two days, the total reservoir inflow rates of the past one month, six months, one year, two years and five years, the water taking amount, the timestamps and an output result of the reservoir water storage model, and inputting the second input feature data set into the reservoir outflow model to obtain a reservoir outflow rate sequence of the to-be-predicted time period. The method obviously improves the accuracy of continuously predicting the reservoir outlet flow, and is suitable for the condition of lacking continuous water storage observation data.

This invention discloses a flood simulation method and system that couples the dynamic characteristics of the underlying surface and the river channel, relating to the fields of watershed hydrological simulation and disaster prevention and mitigation. The method includes: multi-source data acquisition and preprocessing; prediction of underlying surface evolution and hydrophysical parameterization; inversion of river channel dynamic roughness based on water-sediment coupling simulation and inverse Manning's formula; coupling the future runoff generation parameter field and dynamic roughness sequence to a distributed hydrological model for simulation; and quantitatively decoupling the contributions of underlying surface and river channel changes to flood characteristics through multi-scenario comparative experiments. This invention overcomes the shortcomings of existing technologies, such as the disconnect between underlying surface and river channel processes and the static nature of roughness parameters, achieving full-chain dynamic coupling simulation. It significantly improves the physical realism and prediction accuracy of flood simulation under complex environments, and is particularly suitable for data-scarce high-altitude watersheds.

The invention belongs to the technical field of water conservancy projects, and particularly relates to a data-free area runoff sediment transport simulation method and system based on an SWAT model. The method comprises the steps that a data-free small watershed is selected as a target watershed, and a system collects comprehensive geographic information data of the target watershed; based on a hydrological similarity principle, selecting data basins with similar hydrological attributes as reference basins; constructing, calibrating and verifying a reference basin SWAT hydrological model; and transplanting the verified model parameters to the target drainage basin to realize long-term sequence simulation of annual runoff volume and sediment transport volume of the target drainage basin. Compared with the prior art, the parameter transplantation method based on the SWAT model realizes runoff-sediment transport synchronous simulation under the condition of lack of actual measurement data, data requirements and calculation cost are reduced, and simulation results can provide scientific basis for regional water resource total amount analysis, drainage basin treatment measure evaluation and hydraulic engineering design; the method is of great significance in improving the scientific management capability and strategic planning level of water resources in areas without data.

A method for fusing actual evapotranspiration from multiple sources in a watershed considering the eco-hydrological effects of vegetation includes: 1. collecting target data; 2. setting an appropriate target spatiotemporal resolution, preprocessing the data, and calculating the saturated vapor pressure difference (VPD) based on the air temperature; 3. using sunlight-induced chlorophyll fluorescence data (SIF), saturated vapor pressure difference data (VPD), and surface net radiation data (R) to calculate the evapotranspiration from multiple sources in a watershed. n 4. Calculate evapotranspiration data that explicitly considers vegetation effects; 5. Calculate the variance of multi-source evapotranspiration data using a three-source matching method; 6. Utilize linear data fusion based on the variance of multi-source evapotranspiration data to generate a long series of raster basin evapotranspiration products. This method, through multi-source matching and data fusion techniques, integrates other evapotranspiration products, ensuring that the fused product fully accounts for vegetation effects while retaining the high-resolution advantages of established evapotranspiration products. This provides important and accurate data for basin hydrological and ecological research.