146 results about "Catchment area" patented technology

The invention discloses an urban inland inundation optimization transformation method and system based on a pipe network earth surface coupling hydrodynamic model, and the method comprises the steps: firstly generalizing a pipeline and a catch basin, constructing a pipe network confluence model according to a pipe network hydrodynamic method, then dividing a sub-catchment area according to a river network flood routing method, building an urban comprehensive drainage model through the sub-catchment area, and carrying out the optimization transformation of the urban inland inundation. Then establishing a surface runoff model by using a surface flood routing method and a Horton penetration method; according to the system, the function of accurately and efficiently simulating the urban inland inundation process is achieved, urban rainwater circulation is completely simulated, an urban drainage pipe network and a river channel model are integrated, and the interaction between an urban drainage system and a ground surface storage water body is truly simulated; and necessary support is provided for disaster situation rehearsal and rainwater engineering planning and layout, so that urban inland inundation points can be removed in advance, influences on production and life of people are avoided, and the method is suitable for being widely popularized and used.

The invention discloses a dynamic DEM spatial interpolation method which comprises the following steps: performing depression filling, flow direction analysis and confluence cumulant calculation on DEM data, and extracting a natural sub-basin unit by adopting a minimum catchment area threshold method; constructing a topographic feature matrix, performing refined second-level classification on the first-level drainage basin through an improved self-organizing mapping network, generating a hydrological response unit through boundary processing, and establishing a hydrological attribute library; fusing multi-source data, supplementing attribute interpolation such as underlying surface and rainfall, and constructing an interpolation auxiliary parameter system; a drainage basin is divided into regular grids as neurons, a dynamic neural network containing dynamic states and static attributes is constructed, and nonlinear mapping of DEM correction parameters is achieved through optimization of a dynamic activation function and a loss function. The method overcomes the defects that a traditional interpolation algorithm does not consider hydrological boundary constraints, a neural network model topological structure is fixed and the like, and the DEM interpolation precision and the hydrological simulation effect of the complex terrain area are improved.

The invention relates to the field of flood forecasting, and discloses a flood forecasting method and system, a storage medium and computing equipment, and the method comprises the steps: topological modeling: taking a river catchment area surrounded by a water diversion line and a catchment area outlet hydrometric station as nodes of a graph, constructing a connection relation of edges according to the actual flow direction of a river and the connection relation of branches, and carrying out the topological modeling; therefore, topological graph structure data adaptive to a hydrological mechanism is constructed; converting month number characteristics, generating a dynamic periodic timestamp vector, splicing the dynamic periodic timestamp vector with topological graph structure data, and inputting an attention neural network for training; the attention neural network architecture comprises two independent feature channels which are used for processing historical data and forecast data respectively, the network supports a variable modular architecture, and a flood forecast result can be output according to needs after a model is trained. According to the method, the flood prediction precision and interpretability are improved, and a high-precision and interpretable space-time joint flood prediction scheme is realized.

The invention discloses an urban rainstorm waterlogging rapid simulation method based on a deep convolutional neural network, relates to the field of urban waterlogging management, and solves the problem that the judgment of the urban waterlogging prevention capability is inaccurate due to the fact that the current urban waterlogging prevention capability is generally obtained according to the urban water supply and drainage capability and the historical peak rainfall condition. The method comprises the steps that a catchment area corresponding to a target city is set according to a city design drawing, and catchment grids corresponding to the catchment area are divided based on the catchment area; a height-area curve corresponding to the catchment area is constructed according to the catchment grid, and an overflow model corresponding to the catchment area is constructed based on the height-area curve and improved; the result is simulated and recognized through the improved overflow model, then the result is compared with a historical actual value, and the precision condition of the improved overflow model is judged; real-time rainfall data is obtained and imported into the improved overflow model, the simulated submerging conditions of different catchment grids in the target city are obtained, and accurate simulation of urban rainstorm waterlogging is achieved.

The invention discloses a rainstorm ground waterlogging prediction method, device, equipment and product, and relates to the technical field of urban waterlogging prediction.The rainstorm ground waterlogging prediction method comprises the steps that ephemeris and ground observation station data are obtained, the atmospheric moisture delay amount and the high-altitude water vapor conversion factor are calculated respectively, the historical water vapor content is calculated, and the future atmospheric precipitable water amount is predicted; rainfall time distribution data are obtained through rainstorm intensity decomposition; calculating the rainwater overflow amount of the catchment area in combination with the water discharge amount time distribution data of the urban drainage pipe network; and iterative calculation is carried out by using a digital elevation model grid to obtain the waterlogging depth, and waterlogging early warning information is sent out. By constraining the total rainfall amount, the rainfall amount can be effectively constrained by predicting the precipitable water amount based on the satellite ephemeris; the underground pipe network drainage is restrained, and a water flow condition in a pipe channel is simulated by adopting an SWMM model; and finally, the waterlogging accumulated water volume is calculated, constraint verification is carried out on each link of urban waterlogging, and relatively high precision and relatively long timeliness are ensured.

The invention discloses a watershed sediment connectivity evaluation method based on an MATLAB platform and considering relative surface roughness. The method comprises the following steps: acquiring digital elevation model (DEM) data of a target watershed; obtaining a digital elevation model DEMF after depression filling based on the DEM; calculating a flow direction matrix FD; calculating a catchment area A of a catchment area above each DEM cell, and extracting water system position vector data S; calculating a surface roughness factor RRF and a surface undulation factor SLF based on the DEMF, and generating a surface relative roughness factor RRSF; calculating a weighted confluence path length DISTW based on the FD and the RRSF; calculating a sediment'source 'component Dup and a sediment'sink' component Ddown based on A, S, DISTW and FD; and calculating a connectivity index RIC of the target drainage basin based on the Dup and the Ddown. According to the method, the influence of micro-topography evolution of the erosion-driven drainage basin on the sediment connectivity can be more comprehensively represented.

The invention provides a quantitative risk assessment method and system for an ice rock collapse-river blockage-dam break flood disaster chain. The method comprises the following steps: acquiring an ice rock collapse risk grade index by adopting a BP neural network improved by an Adam optimizer; if the ice rock collapse occurs, correcting and calculating an ice rock collapse movement path based on a D8 algorithm in combination with a rock-soil friction coefficient, correcting the volume in real time through an erosion-accumulation dynamic balance model, and constructing a river blocking risk grade index in combination with the river entering volume and speed; the stability of the dam body is evaluated through a dynamic catchment area model and a Sigmoid function, and the dam break risk is calculated in combination with the ratio of the volume to the area; and if the dam break disaster does not occur in the barrier dam, integrating the ice rock collapse risk grade, the river blocking risk grade and the dam break risk grade index, and evaluating the comprehensive risk of the disaster chain. According to the method, disaster prediction of each stage is realized through neural network improvement, path optimization analysis and variance tracking change, and comprehensive risks are evaluated through multi-element coupling.

The invention discloses an urban flood simulation and safety evaluation method, and belongs to the technical field of hydrological data processing and flood rehearsal. The method comprises the following steps: firstly, collecting DEM data of a to-be-processed range, performing projection depression filling preprocessing through ArcGIS software, calculating a flow direction and a flow rate, extracting a river network, and constructing a catchment area and a rainfall flood model; carrying out rainfall simulation and one-dimensional hydrodynamic force calculation by using SWMM software to obtain a river channel and node time sequence flow; then, the flow data are input into HEC-RAS software, two-dimensional hydrodynamic simulation is completed in combination with the terrain, and the flood inundation range and depth are obtained; finally, repeatedly simulating rainfall in different recurrence periods, and dividing flood risk areas according to indexes such as a water depth threshold value and a flooded area. According to the method, full-process automatic processing from rainfall input to flood routing is realized, the timeliness and precision of flood rehearsal are improved, and support is provided for disaster prevention and reduction decisions.

The invention relates to the technical field of urban area configuration, and particularly discloses a service area low-impact measure optimization method and equipment based on an SWMM model. According to the method, the rainfall flood management model of the target service area is constructed through the storm flood management model (SWMM), runoff response under the rainfall condition can be accurately simulated in combination with sub catchment area division and low-impact measure optimization, and compared with a traditional static design method, the low-impact measure design efficiency is remarkably improved, and the method has the advantages of being high in practicability and the like. Therefore, the waterlogging problem caused by the rainstorm in the urban service area is effectively relieved; according to the method, the efficiency coefficient is introduced as a quantitative index, iterative optimization is carried out through comparison with the preset threshold value, and it is ensured that the layout parameters of the low-influence measures can dynamically adapt to terrain, soil and rainfall characteristics of different service areas.

The invention provides a land suitability evaluation method for a placement area under a large height difference condition, and the method comprises the steps: obtaining topographic data and planning constraint elements of the placement area, recognizing topographic features based on an elevation threshold value, and screening an initial land unit through a first evaluation unit constructed by historical data and topographic parameters; decomposing the initial unit, identifying a high-risk area, and performing optimization adjustment by using a second evaluation unit when a risk exists to form a planning scheme; in implementation, the first evaluation unit is regularly corrected according to updated topographic data, and the remaining schemes are dynamically adjusted. The first evaluation unit and the second evaluation unit optimize a land use sequence through a dynamic programming algorithm, and the connection weight is determined by weighting calculation of factors such as gradient, geological stability, traffic accessibility, vegetation coverage and catchment area. According to the method, the scientificity and safety of site selection of the placement area of the large-height-difference area can be improved.

The invention relates to a subway station waterlogging risk rapid assessment method based on system water balance, and the method comprises the following steps: S1, dividing a research region through terrain analysis and pipe network partitioning, and taking a catchment region where a subway station is located as an independent system; s2, calculating system inflow Wr by utilizing the designed rainstorm intensity and the comprehensive runoff coefficient; s3, calculating the system displacement Wp based on the design standard of the research area pipe network; s4, calculating the water accumulation amount Wj of the system through a water balance equation; s5, calculating system capacity W0 by means of terrain elevation data and a GIS tool; and S6, judging whether a waterlogging risk exists in the research area or not by comparing calculation results of the system water accumulation amount Wj and the system capacity W0. According to the method, rapid assessment of the metro station waterlogging risk at the initial stage is realized, the data requirement of metro station waterlogging assessment is reduced, and the required cost and time are reduced.

The application discloses a flood simulation method based on urban infrastructure and a device thereof, and the method comprises the following steps: collecting street view images of a city, wherein the street view images comprise street view data collected from different urban infrastructures at different angles and different times; classifying and processing the street view data according to the types of the infrastructures, and extracting urban infrastructure data; fusing the infrastructure data and terrain data of the city to obtain fused terrain data of the city; dividing catchment areas of the city based on the fused terrain data and extracting water system data, and establishing a flood simulation model based on urban infrastructure according to the water system data, so that the influence of urban street networks, fence systems, buildings and other infrastructures on urban flood processes is fully considered, the simulation accuracy of a city rainstorm flood model is improved, and urban flood disasters are reduced.

The invention discloses a CDOM prediction method based on a multi-source driving factor and a related device, and relates to the technical field of water environment governance, and the method comprises the steps: carrying out the training based on an actually-measured CDOM concentration value and a remote sensing monitoring image corresponding to the time-space of the actually-measured CDOM concentration value, and obtaining a trained CDOM inversion model, according to CDOM data obtained through long-sequence remote sensing monitoring image inversion and long-sequence CDOM inversion data, a trained CDOM prediction model is obtained through training on the basis of the long-sequence CDOM inversion data and historical multi-source driving factors, and the CDOM prediction model can predict the target water body catchment area according to the multi-source driving factors of the target water body catchment area in the historical time period. And predicting and outputting CDOM prediction data of the target water catchment area in the prediction time period. According to the method, the LSTM model is utilized to learn the nonlinear coupling influence of the multi-element complex driving factors on the CDOM, so that the prediction of the CDOM under the influence of the multi-element complex driving factors can be accurately realized.

The utility model relates to a mine dump slope water guide device, and belongs to the field of mine drainage. The device comprises a hard permeable pipe (1), an HDPE (High-Density Polyethylene) water guide pipe (2), a cross four-way PVC (Polyvinyl Chloride) pipe (3), a T-shaped three-way PVC pipe (4) and a pipeline filter screen (5), the three hard permeable pipes (1) are arranged in the direction parallel to the top line of the step slope, two of the three hard permeable pipes (1) are arranged in parallel, the third hard permeable pipe (1) is arranged between the two hard permeable pipes (1) and connected with one hard permeable pipe (1) through a T-shaped three-way PVC pipe (4), and the other hard permeable pipe (1) and the HDPE water guide pipe (2) are connected through a cross-shaped four-way PVC pipe (3). The water guide device is buried below the water converging surface of the top surface of the step slope of the dump, so that rainwater can be quickly collected and discharged through a pipeline, the problems that the slope is scoured and eroded by slope surface flowing water for a long time are prevented or reduced, and then potential safety hazards such as secondary disasters caused by slope landslide are eliminated.

The application provides a method for determining inflow hydrograph of urban stormwater inlet, which is in line with actual urban runoff conditions and can effectively reduce the error of calculation results. The urban area is divided into multiple sub-regions according to the road network, and the net rainfall is discharged from the stormwater inlet, and the single stormwater inlet in the sub-region is calculated respectively; the urban surface runoff is calculated by using the comprehensive runoff coefficient method, and the runoff coefficient not greater than 1 is used to represent the runoff after the rainfall is intercepted and lost on the ground; for the rainfall in the small urban area, the ground water flow is in the form of slope flow and shallow concentrated flow; the catchment time is the sum of the two, the slope flow with a flow line not greater than 90m is calculated by using the Manning dynamics method to calculate the surface runoff flow time; after the slope flow stops flowing for 90m, the shallow concentrated flow with a water depth greater than 3cm appears at this time, and the stormwater inlet design flow inflow calculation formula is: Q = F * (P - S) / (T + 90) wherein Q is the stormwater inlet inflow, L / min; F is the average catchment area controlled by each stormwater inlet, m 2 .

The invention provides a method for quantitatively recovering an ancient landform of an upstream material source area based on geometric attributes of a downstream sedimentary body. According to the method, a modern lake basin or fan delta system with a typical source-sink coupling relation is selected, a digital elevation model and shallow water topographic data are obtained, and a source area and a sink area are divided; parameters such as gradient, catchment area and confluence main channel length are measured in the source area, and geometric attributes such as length, gradient and sedimentary body height difference of a top accumulation layer, a front accumulation layer and a bottom accumulation layer of the fan delta are measured in the confluence area; based on modern sample data, a quantitative relation model between the geometric attributes of the sedimentary body and the landform parameters of the source region is established by adopting a statistical regression method. And then geometric parameter measurement is performed on a target stratum sedimentary body, and the geometric parameter measurement is substituted into the model to recover the area, the thalweg and the gradient distribution of an antique source region. The method takes the geometric attribute of the sedimentary body as a core constraint, is low in dependence on high-quality seismic data, simple and convenient in parameter acquisition and high in result repeatability, and can be used for lake basin evolution and reconstruction, sand body prediction and oil-gas exploration.

The invention discloses an urban flood simulation method based on virtual pool network and SWMM coupling, and the method comprises the steps: taking each sub catchment region of a research region as an independent water storage unit, and constructing a corresponding virtual pool; adjacent pools are connected through triangular weirs to form a virtual pool network reflecting the evolution of surface accumulated water; for a sub catchment area containing an inspection well, bidirectional water exchange between a virtual pool and a pipe network is established by using a transverse weir, so that overflow of the pipe network can be supplemented to the earth surface, and accumulated water on the earth surface can also be discharged into the pipe network. The surface runoff firstly enters the corresponding virtual pools and then is exchanged between the virtual pools or between the virtual pools and the pipe network through the weir structure, so that the whole process simulation of rainfall runoff-surface ponding-pipe network drainage is realized. According to the method, the precision, the efficiency and the realizability are coordinated and unified, the bottleneck that high precision and high efficiency are difficult to consider in an existing urban flood simulation technology is broken through, and the method has remarkable engineering practical value and wide popularization prospects.

This application discloses a CDOM prediction method and related apparatus based on multiple driving factors, relating to the field of water environment management technology. The method includes: a trained CDOM inversion model obtained by training on measured CDOM concentration values ​​and remote sensing images corresponding to the measured CDOM concentration values ​​in time and space; long-sequence CDOM inversion data obtained from long-sequence remote sensing images; and a trained CDOM prediction model trained on the long-sequence CDOM inversion data and historical multiple driving factors. This CDOM prediction model can predict and output CDOM prediction data for the target water body's catchment area during the prediction period based on the multiple driving factors of the target water body's catchment area over historical periods. This application utilizes an LSTM model to learn the nonlinear coupling effect of multiple complex driving factors on CDOM, thus accurately predicting CDOM under the influence of multiple complex driving factors.

The invention belongs to the technical field of uranium ore geological exploration, and particularly relates to a sandstone uranium ore excretion structure authenticity discrimination method based on gravity gradient deep constraint, which comprises the following steps: step 1, deep fracture ridge extraction based on gravity data; 2, constructing a'deep part-earth surface 'structure projection buffer area; 3, removing a micro-landform catchment area based on a DEM (Digital Elevation Model); 4, extracting earth surface remote sensing abnormity; and step five, space coupling and excretion zone authenticity discrimination are carried out. According to the method, by constructing a deep fracture-earth surface projection buffer area model and combining with micro-landform analysis, earth surface non-structural ponding and salt accumulation interference is effectively eliminated, and an effective discharge zone with a deep root is accurately locked.

This invention relates to the fields of reservoir scheduling, flood control and disaster reduction, and hydrological forecasting, and particularly to a method for calculating reservoir rainfall carrying capacity based on a dynamic runoff coefficient. The method includes the following steps: collecting data including the target reservoir's catchment area, characteristic water level, and water level-capacity relationship curves; establishing a dynamic equation for rainfall-runoff coefficient based on reservoir storage using the initial water level, characteristic water level, and storage capacity relationship curves; collecting and analyzing historical flood data for the target reservoir to generate parameter statistics tables for each flood event; establishing a dynamic equation for rainfall-runoff coefficient based on underlying surface conditions based on the parameter statistics tables for each flood event; and solving the dynamic equations based on reservoir storage and underlying surface conditions simultaneously. This invention relies on real-time water level and real-time rainfall to dynamically calculate reservoir rainfall carrying capacity, thus improving the accuracy of reservoir rainfall carrying capacity calculation.

This invention provides a method for obtaining the location of hydrological stations based on a digital elevation model, belonging to the fields of hydrology, water resources, and geographic information technology. The method includes: generating an initial boundary centered on the hydrological stations through spatial distribution; extracting the river channel grid; obtaining the outlet points and their catchment areas; and performing spatial overlay analysis with the initial boundary. For incorrectly generated initial boundaries, the scope is expanded to generate extended boundaries. The catchment areas of the extended boundaries are then iteratively calculated to finally obtain the correct catchment areas and accurate coordinates of the hydrological stations. This invention solves the problem of insufficient spatial distribution information for hydrological stations and is of great significance for water resources information statistics.

This invention relates to the field of environmental anomaly early warning technology, and discloses an automatic early warning system for environmental anomalies in urban ecologically sensitive areas based on spatiotemporal data mining. The system includes: extracting intermediate center scalars; calculating rainfall concentration coefficients; generating bottleneck boundary retention and collapse coefficients; generating a dynamic adjacency matrix; outputting predicted future anomaly intensity values; generating cumulative anomaly energy; and outputting automatic early warning values ​​for the entire area. This invention constructs structural segments by spatially overlapping the catchment area of ​​the total urban ecologically sensitive area with riverside or boundary strip areas. It uses intermediate center scalars to identify topological bottleneck segments, employs a dynamic adjacency matrix to allow the propagation weights between structural segments to change in real time with the boundary hydraulic conditions, and integrates the bottleneck boundary retention and collapse coefficients into the gating mechanism of the spatiotemporal graph convolutional network to achieve adaptive adjustment of the model's time memory. It outputs standardized early warning values ​​for the entire area, adapting to practical application scenarios for environmental management in urban ecologically sensitive areas.

The utility model provides a self-adaptive underground water drainage control device, belongs to the technical field of underground water drainage, and aims to solve the problems that the drainage control device is lack and can effectively warn a water pump fault and the water level exceeds the standard. Comprising a water collecting area, wherein underground water permeates from the periphery and / or the bottom of the water collecting area; the floating body is located in the water collection area and ascends and descends along with the water level of the water collection area, the floating body comprises an upper floating body and a lower floating body which are connected into a whole through a water separation structure, a scale rod is arranged on the upper floating body, and a pull rope is connected to the lower floating body; the water suction pump is arranged in the water collection area and comprises a water drainage pipe and a switch box, the water drainage pipe is led out of the water collection area, the pull rope is connected with the switch box, and the two working states of starting and stopping of the water suction pump are switched according to the pulling force. The device can timely remind related personnel of drainage failure and water level exceeding a safety range, so that potential safety hazards caused by drainage failure are effectively avoided, and the safety of structures is guaranteed.

The present invention discloses a method for optimizing the layout of urban LID facilities based on SOBOL sensitivity analysis. The method is characterized by first establishing a SWMM model of the urban area under study, constructing a functional relationship between node overflow and LID scheme construction costs within the SWMM model, and then using the SOBOL method to conduct a global sensitivity analysis of the LID facility layout scale parameters for each sub-catchment area. Based on the results of the parameter sensitivity analysis, the LID facility layout area for the selected sensitive variables is adjusted and optimized. The Pareto optimal solution sets before and after parameter optimization are compared and analyzed to obtain a more optimal urban LID facility layout scheme. Compared to existing technologies, this method improves the reduction effect of node overflow by increasing the LID layout area in sensitive areas and reduces the LID layout area in insensitive areas to reduce scheme construction costs. Consequently, the present invention has higher computational efficiency and makes the LID spatial layout more rational.

The invention relates to a drainage system inflow and infiltration diagnosis method and device and electronic equipment, and belongs to the technical field of drainage system monitoring. The method comprises the following steps: according to water condition data of each catchment area, determining the flow of each category of inflow source in each catchment area and a first flow ratio of the flow of the inflow source of the category flowing into the whole drainage system at each collection moment, and obtaining a first flow ratio time sequence of each category of inflow source in each catchment area; based on a first system type and a first weather scene corresponding to the drainage system and a weight method, determining a weight time sequence corresponding to each first flow ratio time sequence; based on a scoring method, determining a scoring time sequence corresponding to each first flow ratio time sequence; determining the seepage score of each catchment area based on the weight time sequence and the score time sequence corresponding to each first flow ratio time sequence; and based on the seepage score, determining a key seepage region. Therefore, the accuracy of determining the key seepage area can be improved.

The present invention relates to the field of urban waterlogging control, and in particular to a method for predicting water accumulation in a sunken bridge based on downscaling and dynamic division of catchment areas. S10: Predicting rainfall in the sunken bridge area based on large-scale climate forecast factors in the sunken bridge area; S20: Dividing the sunken bridge area into a main catchment area and multiple secondary catchments, and obtaining elevation data for the main catchment area and each secondary catchment area; S30: Determining the risk rating of each secondary catchment area based on rainfall in the sunken bridge area, the elevation of the main catchment area, and the elevation data of each secondary catchment area; S40: Obtaining the amount of water flowing into the main catchment area from each secondary catchment area based on the risk rating of each secondary catchment area; S50: Obtaining the total amount of water accumulated in the main catchment area based on the amount of water flowing into the main catchment area from each secondary catchment area and the amount of water accumulated in the main catchment area itself. The present invention can accurately predict rainfall in the sunken bridge area, and at the same time, dividing the catchment area according to the risk rating can reduce computer computing load and improve prediction accuracy.

The invention discloses a bank filtration system and method based on an inclined water intake well. The bank filtering system is suitable for underground water taking in a karst landform area, and comprises a filtering layer comprising natural sediments and / or artificial enhancement media of a surface water bank; the first aquifer is formed by carrying out bank filtration on the surface water by the filter layer; optionally at least one second aquifer located spatially below the first aquifer; the inclined water taking well extends towards the filtering layer at the angle that the included angle between the shaft axis and the horizontal direction is larger than 0 degree and smaller than 90 degrees, and the water taking section of the water taking well penetrates through or extends into the recoverable water-rich section of the first water-containing layer from the bank filter and at least one optional second water-containing layer. The inclined water taking well is introduced, the horizontal projection length of the water taking well is increased, the water catchment area and the effective water inlet section are remarkably increased, and more bank filtered water from lateral infiltration of a surface water bank can be collected.

This system provides a simple prediction method for forecasting river water levels. [Solution] The water level prediction system predicts the future water level at a prediction point in a river and comprises: a rainfall acquisition unit 1 that acquires the future rainfall amount of the catchment area for the prediction point; a storage unit 2 that stores parameters of a first-order lag system that takes the rainfall amount as input and outputs the water level at the prediction point in the river; and a water level prediction unit 3 that takes the rainfall amount acquired by the rainfall acquisition unit 1 as input and calculates the predicted water level at the prediction point in the river from the first-order lag system using the parameters of the first-order lag system stored in the storage unit 2, wherein the time constant of the first-order lag system is set according to the water level at the prediction point in the river.

The invention relates to an urban drainage green measure vertical layout control optimization method, device and equipment and a medium, and the method comprises the steps: determining a plurality of layout evaluation indexes according to a to-be-laid green measure region, a waterlogging water accumulation amount, a green measure retention amount and to-be-drained urban population information through employing a GIS geographic analysis technology, determining a layout priority coefficient of each green measure type in each catchment area on the basis of a fuzzy comprehensive evaluation method according to the plurality of layout evaluation indexes and the weight corresponding to each layout evaluation index, and adopting a preset green measure vertical collaborative optimization algorithm to determine the layout priority coefficient of each green measure type in each catchment area according to the layout priority coefficient and the to-be-laid green measure parameters. And obtaining a Pareto optimal solution set of green measure total outflow and green measure layout total cost of all catchment areas in the city to be subjected to drainage management, and determining an optimal green measure layout scheme of the area to be subjected to green measure layout in each catchment area. The flood control efficiency of the urban drainage system can be remarkably improved.

The application provides a slope unit division and landslide susceptibility evaluation method, and belongs to the technical field of data processing, and specifically comprises the following steps: generating basic data required for slope unit division and susceptibility evaluation; identifying and skeletonizing the terrain boundary information of a study area based on the basic data; establishing a spatial connection relationship based on the terrain skeleton to form a closed initial catchment area; optimizing and integrating the initial catchment area in combination with terrain and hydrological constraints to obtain a final slope unit division result; extracting various evaluation factors required for landslide susceptibility evaluation based on the final slope unit, and constructing evaluation sample data; establishing a susceptibility evaluation model by using the evaluation sample, and training and optimizing the model parameters; and using the optimized susceptibility evaluation model to carry out prediction analysis on the slope units in the study area, and outputting the landslide susceptibility evaluation result. Through the scheme of the application, the evaluation efficiency, accuracy and adaptability are improved.