130 results about "Catchment hydrology" patented technology

The invention discloses a small watershed hydrological runoff and pollution load short-term prediction refinement method, which comprises the following steps of: constructing a modeling data set, constructing a small watershed foundation base model, segmenting hydrological response units according to land utilization types, crop planting structures and reservoir pond / wetland distribution data in a refinement manner respectively, and calculating the hydrological runoff and pollution load short-term prediction of the small watershed foundation base model. A small watershed foundation base model corresponding to the optimal segmentation scheme is screened out, and a small watershed depth base model is generated; constructing a reservoir pond / wetland simulation module; coupling the small-watershed depth base model and the reservoir pond / wetland simulation module to form a small-watershed hydrology and water quality early warning model, and optimizing the small-watershed hydrology and water quality early warning model; rolling to generate a hot start file for short-term prediction; constructing a future short-term weather enhancement forecasting model; the small watershed hydrology and water quality early warning model is driven to operate, the future water volume and load output are calculated in a rolling mode, and hydrology and water quality results are output; and calibrating and updating the small watershed hydrology and water quality early warning model. The precision and timeliness of hydrology and water quality prediction of the small watershed are remarkably improved.

A river-lake system ecological scheduling method coupled with basin hydrological response belongs to the field of reservoir ecological scheduling, and comprises the following steps: firstly, selecting a research area to represent a hydrological station, and drawing a basin hydrological evolution topological graph; secondly, constructing a watershed hydrological response model step by step, and simulating a response process of lake hydrological situation to upstream reservoir drainage; thirdly, putting forward an ecological evaluation index, and quantifying lake hydrological-ecological response; 4, constructing a multi-objective optimization scheduling model of the river-lake system; 5, optimizing the multi-objective optimization scheduling model of the river-lake system; and finally, based on a fuzzy optimization method, recommending an optimal reservoir scheduling rule conforming to decision preference. According to the method, the beneficial benefits such as power generation and water supply of the reservoir are guaranteed, the adverse effect of concentrated water storage of the upstream reservoir on the ecology of the downstream lake can be weakened to the maximum extent, the reservoir scheduling rule with the maximum comprehensive benefits is recommended, and scientific scheduling basis and decision support are provided for green development of a river-lake system.

The invention discloses a cold region SWAT model construction method considering a glacier melting process. A calculation method comprises the following steps: step 1, obtaining corrected rainfall data; corrected air temperature data are obtained; evapotranspiration correction data is obtained; actually measured runoff is obtained; 2, obtaining a plurality of sub-basin boundaries and spatial distribution of each sub-basin glacier; 3, calculating the glacier melting amount of each sub-drainage basin in the research time period by adopting a day-to-day factor method to obtain the day-by-day glacier melting amount of each sub-drainage basin; step 4, performing double-element parameter calibration based on the actually measured runoff data and the evapotranspiration correction data to obtain parameters suitable for the watershed hydrological process; and 5, calculating to obtain the relative contribution rate of the glacier melting process to runoff and evapotranspiration. The simulation precision of hydrological elements such as runoff of the cold region hydrological model is improved, and a scientific basis can be provided for sustainable utilization and planning of water resources of a local drainage basin.

The invention provides a freezing circle watershed hydrological prediction method and system based on multi-source data fusion, and relates to the technical field of hydrological monitoring and sediment monitoring, and the method comprises the steps: obtaining a vibration signal of the interaction of a water flow and a riverbed and meteorological data in a region, and carrying out the preprocessing; the preprocessed meteorological data and vibration signals are input into a multi-source data fusion model, sequential feature extraction is conducted on the meteorological data and the vibration signals through a multi-layer perceptron in the multi-source data fusion model, the extracted sequential features are fused through a gating circulation unit, and multi-source data fusion features are obtained; and carrying out empirical mode decomposition and Hilbert spectrum analysis on the preprocessed vibration signal to obtain a plurality of signal characteristics such as instantaneous frequency and instantaneous amplitude of the vibration signal, inputting the signal characteristics and the multi-source data fusion characteristics into a hydrological parameter prediction model, and outputting corresponding predicted values of the water flow velocity, the flow and the sediment transport capacity.

The invention provides a drainage basin mountain torrent debris flow physical process simulation method for risk early warning, which comprises specific research and development contents and corresponding problems and achieves the following purposes: constructing a drainage basin unit database, clarifying drainage basin and channel characteristics, and providing data support based on physical process refined simulation; and carrying out basin hydrological process simulation research on the basis of the SWAT distributed model for improving glacier melt water simulation. A mountain torrent and debris flow disaster whole-process coupling model is constructed, a dynamic data chain is used for connecting watershed hydrology and a channel water and sediment dynamic process, full-link simulation from rainfall to disaster modeling is achieved, a disaster forming mechanism is accurately revealed, a visualization system is integrated through the model, channel disaster dynamic evolution evaluation and risk zoning functions are provided, and the reliability of channel disaster dynamic evolution evaluation is improved. A forecasting system designed in an object-oriented development mode can be seamlessly accessed to a provincial early warning platform, and a systematic solution is provided for early warning of watershed or regional disasters.

The invention discloses a drainage basin hydrological multivariable prediction method based on a meta-learning TFT architecture, and relates to the technical field of hydrological prediction, and the method comprises the steps: collecting multivariable water quality data, external driving force data and static drainage basin attribute data of a plurality of hydrological observation stations; splicing and processing missing values, and dividing the missing values into a training set, a test set and a verification set which are arranged in time as input; the capture of the model on the long-term dependency relationship is enhanced by enhancing the gating circulation unit; capturing a multi-level dependency relationship in the time sequence by using a multi-scale image attention network; and integrating the meta-learning framework, fusing a plurality of subtasks, and outputting a predicted value. Model fusion enhanced meta learning and improved Temporal Fusion Transformer are combined, a multi-scale map attention network and a dynamic model fusion mechanism are fused, the defects of a hydrological prediction model in the aspects of capturing a long-term dependency relationship and generalization ability in a complex watershed environment are overcome, and the precision and reliability of multivariable hydrological prediction are improved.

The invention relates to the technical field of wetland ecological restoration, in particular to a beach wetland near-natural ecological restoration method based on a hydrological connectivity threshold value, which comprises the following steps of: firstly, collecting multi-source data such as river network boundary vector data and wetland topographic data of a drainage basin, and selecting a representative remote sensing image; analyzing a hydrological sequence change trend and water body information, and calculating a hydrological situation change degree; then constructing a hydrological and hydrodynamic model, and cooperatively observing space-time evolution of the wetland; the hydrological connectivity is quantified, and the evolution relation between the hydrological connectivity and the wetland is analyzed; and finally, according to the response of wetland evolution to hydrological communication, identifying a hydrological communication threshold value, and proposing water system communication and ecological channel restoration suggestions. The method is scientific, reasonable and high in practicability, can effectively reveal the wetland evolution mechanism, provides an important reference basis for basin hydrological regulation and control and wetland ecological restoration under the influence of human activities, and has important application value in the field of wetland ecological restoration.

The invention relates to the technical field of hydrological assessment and environmental science, in particular to a watershed hydrological assessment method and system under climate change, and the method comprises the steps: collecting multi-source heterogeneous data, and generating fusion feature data and causal path data through multi-modal fusion; optimizing a watershed hydrological network structure based on reinforcement learning, performing runoff simulation by using an enhanced hydrological model, and generating optimized runoff prediction data; combining runoff prediction data and a run-length theory to extract drought characteristic data, and generating scene data for describing an extreme scene through a path constraint type generative adversarial network; and constructing a dynamic joint distribution model of the drought characteristics based on the scene data, and carrying out multi-scene risk assessment. According to the method, accurate modeling and risk quantification of drainage basin drought characteristics in a complex climate scene are realized, the precision and applicability of hydrological assessment are remarkably improved, and a scientific basis is provided for drainage basin water resource management.

The invention discloses a runoff change attribution nonlinear contribution identification method based on segmented hydrological simulation. The method comprises the following steps: dividing an annual runoff sequence into a natural period and a human activity influence period; selecting a watershed hydrological model, and respectively calibrating parameters of the watershed hydrological model in a natural period and a human activity influence period by using hydrometeorological data; analyzing the influence of climate change on runoff change; analyzing the influence of human activities on runoff changes; combining the influence of the climate change and the human activity on the runoff change, and analyzing the synergistic effect of the climate change and the human activity on the runoff change; and quantifying the contribution rate of climatic change, human activity and synergistic effect of the climatic change and the human activity to runoff change. According to the method, on the basis of runoff change attribution linear analysis, the synergistic effect of climatic changes and human activities is recognized in an emphasized manner, the recognition result can objectively reflect the nonlinear response of the hydrological process to environmental elements, and the method is effectively applied to the specific work of watershed water resource evaluation and management.

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 discloses a drainage basin seasonal runoff change prediction and attribution method and system and a medium, and the method comprises the steps: carrying out the seasonal division of a hydrological year based on the monthly scale rainfall, potential evapotranspiration and land water reserve change rules in a drainage basin; establishing a plurality of coupling models of the GCM and the ABCD so as to predict the runoff process of the drainage basin under the conditions that only future climate change scenes are considered and climate change and human activity influence scenes are considered at the same time; a seasonal-scale Buddyko model is considered, and the relative influence of seasonal-scale climate change and human activities on future runoff change is quantified. The method has a strong statistical basis, can objectively reflect the change rule of the watershed hydrologic runoff, can fully decouple the complex relationship between climate change and human activity and other factors on a seasonal time scale, and provides a new technology for the research of a water circulation process driving mechanism in a changing environment.

The invention provides an ecological hydrological process simulation method, device and equipment based on dynamic vegetation, and relates to the technical field of hydrological process simulation, and the method comprises the steps: obtaining long-sequence hydrological meteorological data and satellite remote sensing image data in a target watershed; interpreting and generating a surface average normalized vegetation index sequence corresponding to the target drainage basin based on satellite remote sensing image data; and through a pre-constructed watershed hydrological model, based on the long-sequence hydrometeorological data and the surface average normalized vegetation index sequence, simulating an ecological hydrological process of the target watershed under a dynamic vegetation condition so as to obtain an ecological hydrological process simulation result corresponding to the target watershed. According to the invention, accurate simulation of the ecological hydrological process under the dynamic vegetation condition can be realized.

The invention relates to a drainage basin hydrological forecasting method and system based on big data, and the method comprises the following steps: collecting drainage basin hydrological related data through a big data platform, transmitting the data to an edge calculation node of a data collection end in real time, and carrying out the preprocessing and feature extraction; forming a data set by the data after feature extraction, and dividing the data set into a test set and a verification set through space-time cross validation; respectively constructing and training a random forest model and a long short-term memory network model LSTM by using the training set to obtain a trained random forest model and a trained long short-term memory network model LSTM; fusing the trained random forest model and the long short-term memory network model LSTM by using a Stacking method to obtain a watershed hydrological prediction model, and evaluating and optimizing the watershed hydrological prediction model by using test set data; newly-collected data are processed by the edge computing nodes and then fused into the original data set, and basin hydrological data are predicted in real time through the optimized basin hydrological prediction model.

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 belongs to the technical field of watershed hydrological process simulation research, particularly relates to a distributed storage and hypersonic dynamic combination model construction method based on water and soil conservation measures, and solves the technical problems that an existing loess plateau region hydrological model is low in simulation precision and poor in applicability. Firstly, a research area is subdivided into a plurality of uniform grids through uniform grid division, and each grid represents different underlying surface features; the method comprises the following steps: carrying out an observation test on a typical field slope of a loess plateau to obtain observation data under different water and soil conservation measures, and determining a model parameter range in each grid under the water and soil conservation measures. According to the method, the rainfall-runoff process in each grid is linked with each other by combining a one-dimensional motion wave equation to form a complete distributed storage hyperdynamic combined model, the model structure can dynamically reflect runoff production mechanisms of different grid units, and the prediction capability of the model is improved.

The invention relates to a multi-target water storage scheduling method and system for a large reservoir group, and a storage medium. The method comprises the following steps: step 1, collecting watershed hydrological data; 2, determining an optimization target of combined water storage scheduling of the cascade reservoir group, and setting reservoir scheduling constraint conditions; further determining the priority of each scheduling target, and constructing a two-stage segmented optimization model framework; 3, introducing a partition-based large system aggregation-decomposition method, and optimizing by adopting a parameter-simulation-optimization method to obtain an initial Pareto frontier; 4, based on the initial Pareto frontier in the step 3, a parallel successive optimization algorithm is adopted to further improve a water storage strategy obtained through aggregation decomposition, and efficient utilization of water resources of all subareas is achieved. Optimized water storage management of the large reservoir group can be achieved, and the water storage efficiency of the large reservoir group is improved on the premise that the flood control standard of the original design is not lowered. And further utilization of limited water resources in each subarea in the drainage basin is promoted.

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 coupling model nitrogen and phosphorus simulation method based on agricultural seasonal decomposition characteristics, provides an agricultural seasonal decomposition model SDA, and simulates the total nitrogen flux and the total phosphorus flux of a drainage basin in combination with a hydrological model and a multivariate deep learning model. The method not only can follow a watershed hydrological cycle process, considers migration and transformation processes of nitrogen and phosphorus along with hydrological processes such as rainfall, infiltration and evaporation, has a solid hydrological physical process, but also can deeply excavate a complex relationship between nitrogen and phosphorus and factors influencing migration and transformation of the nitrogen and phosphorus, so that the method has a good application prospect. According to the method, the features in the time series data can be efficiently extracted and fused, the interpretability of machine learning can be improved, the data requirement and parameter uncertainty of a traditional hydrological model can be reduced, and therefore the accuracy and robustness of total nitrogen flux and total phosphorus flux prediction are improved.

The invention belongs to the field of hydraulic structure safety monitoring and predictive analysis, and particularly relates to a method for estimating abnormal seepage flow of a concrete faced rockfill dam based on parameter transplantation and overflow weir monitoring flow. The scientificity and the precision of seepage flow estimation are improved by combining an upstream watershed hydrological model and dam rear micro-region runoff and confluence simulation; the overflow weir is adopted to monitor flow data, and is combined with the actual reservoir water level change to construct a more reliable water level-seepage flow relationship. The method is suitable for dam seepage flow estimation under the normal working condition, abnormal seepage can be recognized and quantified, and the early warning capacity for the hidden danger of seepage is improved. Dependence of a traditional method on a large number of monitoring devices is avoided, engineering operation and maintenance cost is reduced, and stability and reliability of data are improved.

The invention provides a large-scale watershed hydrological modeling method based on variable grids, and belongs to the field of large-scale distributed hydrological modeling. The large-scale watershed hydrological modeling method comprises the following steps: firstly, determining the size of a watershed basic grid according to the spatial resolution of available basic data and the calculation time consumption of a distributed hydrological model under different resolutions; secondly, determining a grid level according to a rainfall level and a mountain torrent prevention and control level of a flood event; and finally, according to the grid levels of the different partitions, the basic grids are aggregated into coarse grids of different levels, and basin variable grid hydrological modeling is completed. The method is suitable for a large-scale watershed flood forecasting system, and can meet the timeliness demand of flood control decision while guaranteeing the refined modeling of a key area.

The invention discloses a small and medium-sized reservoir scheduling optimization method based on a hydrological and hydrodynamic coupling model. The method comprises the steps of obtaining basic data of a reservoir basin and performing data processing; setting boundary conditions, and adopting an SCS runoff production model to carry out runoff production calculation on the reservoir basin grids; a model is built based on a two-dimensional N-S equation, and two-dimensional hydrodynamic calculation is achieved; according to actual data, different reservoir region calculation methods are adopted, and a reservoir basin hydrological and hydrodynamic coupling model is constructed; carrying out reservoir basin multi-water-source water resource configuration, and optimizing boundary inflow conditions and a water demand upper limit for a scheduling rule; and according to the coupling model, in combination with a target function, a constraint condition and a water demand upper limit of the reservoir, optimizing a scheduling rule, and obtaining an optimal scheduling parameter and scheduling scheme. The method has the advantages that a real-time and forecast-period optimal reservoir scheduling strategy can be given, and the problem that real-time or forecast optimal scheduling simulation is difficult due to the fact that hydrological data of drainage basins where small and medium-sized reservoirs are located are deficient is well solved.

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 relates to the technical field of hydrological prediction and water resource management, in particular to a multi-time-scale runoff predictability measurement method and device, equipment and a medium, and the method comprises the steps: obtaining runoff time sequence data meeting a first preset processing condition; target classification processing is carried out on the runoff time sequence data to obtain a target classification result meeting a second preset processing condition, then the internal predictability and the implementation predictability of the runoff time sequence data are determined respectively, and the target correlation between the internal predictability and the implementation predictability is analyzed; and determining a multi-time scale runoff predictability measurement result of the runoff time sequence data. Therefore, the problems that only runoff forecasting can be carried out, the predictable degree of the runoff sequence cannot be systematically quantified, the prediction effect is difficult to form systematic intuitive understanding, the complexity and the regularity of a watershed hydrological system are difficult to comprehensively reveal, the predictability of a research object and the applicability and the reliability of a hydrological model are reduced and the like in related technologies are solved.

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 discloses an intelligent water conservancy algorithm development system and method based on artificial intelligence, and relates to the technical field of intelligent water conservancy, and the method comprises the steps: constructing a cross-reservoir federated learning network, initializing local model parameters of each node, building communication connection between an edge layer and a cloud end, and receiving hydrological sensor data and meteorological early warning information in real time; recognizing a flood event through a space-time convolutional network, generating a dynamic gradient mask to perform sparse processing on a local model parameter, and reserving a gradient parameter of which the event association degree is higher than a dynamic gradient mask threshold value; and converting the non-dominated solution into a dynamic scheduling strategy, and generating real-time operation instructions of flood discharge, generator set control and irrigation water distribution. According to the method, federated learning and a space-time attention mechanism are combined, and the space-time correlation characteristics of the cross-basin hydrological data are identified more accurately, so that the accuracy of flood prediction is improved.

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 present invention provides a large-scale watershed hydrological modeling method based on a variable grid, which belongs to the field of large-scale distributed hydrological modeling. The large-scale watershed hydrological modeling method is as follows: first, the size of the basin basic grid is determined based on the spatial resolution of the available basic data and weighing the calculation time of the distributed hydrological model at different resolutions; second, the grid level is determined according to the rainfall level of a flood event and the flash flood prevention level; finally, according to the grid level of different partitions, the basic grid is aggregated into coarse grids of different levels to complete the variable grid hydrological modeling of the watershed. The present invention is applicable to large-scale watershed flood forecasting systems, and can meet the timeliness requirements of flood control decisions while ensuring the refined modeling of key areas.